North East Nigeria – Emergency Survey

NIGERIA FINAL REPORT Nutrition in Emergency

NUTRITION AND FOOD SECURITY SURVEILLANCE : NORTH EAST NIGERIA – EMERGENCY SURVEY

NOVEMBER, 2016

Executive Summary

The Boko Haram conflict was declared to be a state of emergency at the beginning of 2012 by the government of Nigeria. In May 2013, the area under the state of emergency was extended to include all of Adamawa, Borno and Yobe states in Northeastern Nigeria. The insurgency and political violence has caused mass population displacement. According to the International Organization of Migration’s (IOM) October 2016 report, there were 1,392,927, 170,070 and 124,706 internally displaced persons (IDPs) in Borno, Adamawa and Yobe states respectively.

Conflict and resulting mass displacement often results in increased prevalence of acute malnutrition and mortality. The most recent state level estimates of global acute malnutrition are from the National Nutrition and Health Survey (July to September 2015) which found 10.9% (8.6, 13.7 95% CI) in Yobe, 11.5% (8.8, 14.9 95% CI) in Borno, and 7.1% (5.0, 10.1 95% CI) in Adamawa. These state level estimates excluded areas of Borno that were inaccessible due to security. Additionally, more recent data, collected since the declaration of the nutrition emergency in April 2016, suggest an increase in prevalence of acute malnutrition in some areas of N.E. Nigeria. Small scale SMART surveys conducted in the local government areas (LGAs) of Jere,Kaga,Konduga, and Monguno town between April and August 2016 documented prevalence of global acute malnutrition (GAM) ranging from 13.0-27.3%.

Additionally, screening data collected by NGOs and United Nations Children's Fund (UNICEF)- supported teams in Yobe and Borno states included assessments of IDPs with the proportion of children with global acute malnutrition [as identified by mid-upper arm circumference (MUAC) and/or oedema] reported to be over 80%. These initial assessments provide an indication of increasing levels of acute malnutrition. However, there remained many areas of the emergency states with no information to inform the ongoing response.

Given the severe situation suggested by the small-scale surveys and screening data, as well as increased access to newly liberated areas since the emergency declaration, surveys were organized with the primary objective of providing representative estimates for prevalence of acute malnutrition among children (by weight-for-height and MUAC), as well as mortality rate in N. E. Nigeria to inform the ongoing emergency response. Information on nutritional status of women, prevalence of common child health morbidities, access to health services and health status among children, infant feeding, and household water and sanitation were also collected as part of the surveys.

These surveys were carried out by the National Bureau of Statistics (NBS) in coordination with the National Population Commission (NPC), the Federal Ministry of Health (FMOH), and the Nigeria Nutrition in Emergency Working Group (NiEWG). Financial support was provided by the Government of Nigeria, United Nations Children’s Fund (UNICEF), and the United Nations Central Emergency Response Fund (CERF). Technical support was provided by the Centers for Disease Control and Prevention (CDC) and UNICEF through NBS.

Methods

We conducted cross-sectional household surveys using a two-stage cluster sampling design consistent with the SMART methodology. The survey area consisted of 65 LGAs within the three states of Adamawa, Borno and Yobe. The 65 LGAs were divided into 10 domains: 2 in Adamawa (North and South), 3 in Yobe (North, Central and South) and 5 in Borno state (North, South, Central, East, and MMC/Jere). Domains were created considering livelihood zones, geographic proximity and socio-cultural homogeneity.[1] Results are representative at the level of the II domain, groupings of LGAs.

Clusters were selected using probability proportional to size (PPS) sampling. The primary sampling unit (PSU) for Yobe and Adamawa domains were based on Enumeration Areas (EAs) from the 2006 census frame. Estimated populations for each EA are 2016 populations projected from the 2006 census. Given recent large scale population movement in Borno, an updated sampling frame was built using boundaries and population estimates from the September- October 2016 polio campaign microplan and September 13 IOM Displacement Tracking Matrix (DTM) report .[2]

Sample size was calculated to ensure adequate precision for estimates of global acute malnutrition (GAM) and crude mortality rate (CMR). A sample of 600 households, 30 clusters of 20 households, was selected per domain. Within selected clusters, all households were listed and selected using systematic random sampling. Enumerators received a five day training including a full standardization and field test.

Results

Data collection took place between October 17 and November 11, 2016. Two of the domains in Borno (North and East) were determined by state level actors to be inaccessible at the time of this survey. Within the eight domains, 13 of the originally selected clusters were either inaccessible or vacant at the time of data collection including: 2 in North Adamawa, 1 in South Adamawa, 3 in Central Borno, 2 in MMC/Jere, 2 in Central Yobe, 2 in Southern Yobe, and 1 in Northern Yobe. Inaccessible clusters in Central Borno were replaced with all reserve clusters selected a priori as per SMART guidelines.

Prevalence of GAM was 11.4% in Yobe, 11.3% in Borno, and 5.6% in Adamawa. Prevalence of GAM exceeded the WHO Crisis Classification threshold for “serious” (10%) in 5 domains: Central Borno, MMC/Jere, Northern Yobe, Central Yobe, and Southern Yobe. Prevalence of GAM was highest in Northern Yobe both as assessed by weight-for-height and/or odema (14.3%), and as assessed by MUAC (10.5%).

Both crude and under-five mortality rates were highest in Central Yobe, 0.63 (0.39-1.01 95% CI) and 2.06 (1.24-3.38 95% CI), respectively. The under-five mortality rate in Central Yobe exceeds the emergency threshold of 2 deaths in children under five / 10,000 children under five / day. By domain, crude mortality rate ranged from 0.26-0.63 total deaths / 10,000 people / day. Under five mortality rate ranged from 0.68 to 2.06 deaths in children under five / 10,000 children under five / day. The crude mortality rate (CMR) did not exceed the emergency threshold of 1 death/10,000 persons / day in any of the domains.

Overall, data quality for the survey data was high. With respect to anthropometry data, all domains had less than 3.0% of values excluded as outliers (SMART flags). Standard deviation for Weight-for-Height Z-scores for all surveys fell within an acceptable range (0.8-1.2). Data quality was “excellent” in 4 domains (North Adamawa, Central Borno, MMC/Jere, and Central Yobe) and “acceptable” in the remaining 4 domains (South Adamawa, South Borno, South Yobe, North Yobe) according to SMART classifications.

III

Figure 0.1: Prevalence of global acute malnutrition based on weight-for-height z-scores (and/or oedema), children 0-59 months in NE Nigeria

Table 0.1: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema), children 0-59 months in NE Nigeria

Southern Northern Southern Central MMC/ Jere Northern Central Yobe Southern Adamawa Adamawa Borno Borno Yobe Yobe n = 547 n = 530 n = 527 n = 499 n = 446 n = 547 n = 564 n = 572 Prevalence of global (32) 5.9 % (28) 5.3 % (47) 8.9 % (58) 11.6 % (58) 13.0 % (78) 14.3 % (58) 10.3 % (61) 10.7 % malnutrition (<-2 z- (3.8 - 9.0 (3.1 - 8.8 (6.7 - 11.7 (8.8 - 15.2 (10.2 - 16.4 (10.6 - 18.9 (7.3 - 14.2 (8.3 - 13.6 score and/or oedema) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) Prevalence of (30) 5.5 % (23) 4.3 % (41) 7.8 % (55) 11.0 % (52) 11.7 % (69) 12.6 % (46) 8.2 % (52) 9.1 % moderate malnutrition (3.5 - 8.4 (2.6 - 7.3 (5.6 - 10.7 (8.3 - 14.6 (8.8 - 15.3 (9.4 - 16.8 (5.6 - 11.7 (7.3 - 11.3 (<-2 z-score and >=-3 z- 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) score, no oedema) Prevalence of severe (2) 0.4 % (5) 0.9 % (6) 1.1 % (3) 0.6 % (6) 1.3 % (9) 1.6 % (12) 2.1 % (9) 1.6 % malnutrition (<-3 z- (0.1 - 1.5 (0.3 - 2.6 (0.5 - 2.8 (0.2 - 1.8 (0.6 - 2.9 (0.7 - 3.9 (1.1 - 4.2 (0.8 - 3.0 score and/or oedema) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.)

Figure 0.2: Prevalence of acute malnutrition based on MUAC cut off's (and/or oedema), children 6-59 months in NE Nigeria

Table 0.2: Prevalence of acute malnutrition based on MUAC cut off's (and/or oedema), children 6-59 months in NE Nigeria

Southern Northern Southern Central MMC/ Jere Northern Central Yobe Southern Adamawa Adamawa Borno Borno Yobe Yobe n = 491 n = 491 n = 482 n = 451 n = 430 n = 495 n = 511 n = 530 Prevalence of global (20) 4.1 % (14) 2.9 % (20) 4.1 % (34) 7.5 % (14) 3.3 % (52) 10.5 % (34) 6.7 % (39) 7.4 % malnutrition (<-2 z- (2.5 – 6.5 (1.5 - 5.2 (2.3 - 7.4 (4.5 - 12.3 (1.8 - 5.7 (7.1 - 15.3 (4.2 - 10.3 (5.4 - 10.0 score and/or oedema) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) Prevalence of (17) 3.5 % (11) 2.2 % (13) 2.7 % (26) 5.8 % (12) 2.8 % (40) 8.1 % (18) 3.5 % (33) 6.2 % moderate malnutrition (2.0 - 6.0 (1.2 - 4.2 (1.6 - 4.5 (3.3 - 9.9 (1.6 - 4.9 (5.5 - 11.7 (2.3 - 5.4 (4.5 - 8.6 (<-2 z-score and >=-3 z- 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) score, no oedema) Prevalence of severe (4) 0.6 % (3) 0.6 % (7) 1.5 % (8) 1.8 % (2) 0.5 % (12) 2.4 % (16) 3.1 % (6) 1.1 % malnutrition (<-3 z- (0.2 – 1.8 (0.2 - 1.9 (0.5 - 4.0 (0.7 - 4.2 (0.1 - 1.9 (1.3 - 4.6 (1.7 - 5.8 (0.5 - 2.7 score and/or oedema) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.)

VII

Figure 0.3: Crude and under five mortality rates in NE Nigeria

VIII

Table 0.3: Crude and under five mortality rates in NE Nigeria

Southern Northern Southern Central MMC/ Jere Northern Central Yobe Southern Adamawa Adamawa Borno Borno Yobe Yobe n = 566 n = 542 n = 593 n = 581 n = 549 n = 569 n = 557 n = 555 Crude mortality rate 0.43 0.44 0.26 0.55 0.30 0.50 0.63 0.36 (total deaths /10,000 (0.26-0.69 (0.30-0.65 (0.17-0.41 (0.35-0.85 (0.16-0.57 (0.36-0.68 (0.39-1.01 (0.24-0.54 people / day) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) Under five mortality rate 1.01 0.99 0.97 1.69 0.78 1.90 2.06 0.68 (deaths in children under (0.55 -1.84 (0.53-1.82 (0.56-1.67 (0.96-2.91 (0.34-1.78 (1.31-2.72 (1.24-3.38 (0.29-1.55 five / 10,000 children 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) 95% C.I.) under five / day)

Breastfeeding practices were assessed as a measure of infant and young child feeding (IYCF). Survey results suggest that the proportion of children who continued breastfeeding at one year (assessed among children aged 12-15 months) was over 90% in all three states, but then steadily declined; continued breastfeeding at two years (assessed among children aged 20-23 months) ranged from 31.1-40.9% by state.

In terms of child health, survey results identify several important gaps in management of common childhood morbidities. In all three states, less than 5% of children aged 0-59 months with symptoms of diarrhoea in the two weeks preceding the survey, received treatment with both oral rehydration salts (ORS) and zinc. Children in Adamawa with symptoms of acute respiratory infection (ARI), a proxy for pneumonia, in the two weeks preceding the survey were nearly twice as likely to receive antibiotic treatment as children in Borno and Yobe. Among children with fever in the two weeks preceding the survey, less than a quarter in Adamawa and approximately 10% in Yobe and Borno received Artimisinin-based Combination Therapy (ACT), first line treatment for malaria. Despite national protocols recommending universal use of diagnostic testing to confirm malaria, less than 10% of children with fever were tested in all three states.

Survey results further suggest gaps in preventative services. Measles vaccination coverage was well below the 95% threshold; among children aged 12-59 months coverage (as determined by observation of vaccination card or maternal recall) was 59.8%, 55.6% and 36.3% in Adamawa, Borno and Yobe, respectfully. Additionally, less than one in ten households reported receiving services during the last Maternal Newborn and Child Health Week (MNCHW) campaign in all three states. Coverage of anthelminthic drugs among children aged 12-59 months was also well below target coverage— 13.1% in Adamawa, 3.8% in Borno, and 5.0% in Yobe.

Prevalence of acute malnutrition among all women of reproductive age (15-49 years) was assessed by mid-upper arm circumference. As with children, prevalence of acute malnutrition (≤ 221 mm) was highest in Northern Yobe. By state, prevalence of severe malnutrition (MUAC < 214 mm) was highest among women of reproductive age in Yobe (9.6%) followed by Borno (4.9%) and Adamawa (3.3%). Only about half of women surveyed in the three states are achieving minimum dietary diversity for women of reproductive age (MDD-W)—50.1% in Adamawa, 42.1% in Borno and 43.3% in Yobe.

Discussion / Conclusion

The results presented represent the only population-representative estimates for all accessible areas of the emergency states for 2016. These data provide evidence that prevalence of GAM remains at serious levels in much of Borno and Yobe states. Prevalence of acute malnutrition is generally comparable with estimates of GAM from the 2015 Nigeria NNHS for Borno (11.5%), Yobe (10.9%), and Adamawa (7.1%) states. However, under five mortality rates exceed emergency thresholds in Central Yobe, and are very high in Central Borno and Northern Yobe. There remain critical gaps in both preventive services and clinical management of common childhood morbidities. Low coverage of measles vaccination is particularly concerning given the ongoing measles outbreak in Borno state.

These estimates should be understood as representative of accessible areas of N.E. Nigeria. Acute malnutrition prevalence, mortality rates, and other indicators are likely poorer in newly liberated and inaccessible areas. Large areas of the assessed domains remain inaccessible, particularly in Borno. Additionally, this assessment was conducted during the end of hunger season and following a surge in emergency response programs, factors that might also contribute

X to the lower estimated prevalence of acute malnutrition in these surveys relative to estimates from other small-scale surveys.

Based on these results the following is recommended: - Nutrition emergency response can be focused to areas with higher prevalence of acute malnutrition. All children with acute malnutrition should have access to treatment. However, survey results suggests the response can be further focused within the emergency states, including newly liberated areas. - Continue strengthening ongoing food and nutrition response which may be attributable for the declines in acute malnutrition prevalence observed including increased outreach and treatment of acute malnutrition through CMAM programs as well as general food distributions. - Improve coverage of public health interventions including deworming medication and measles vaccinations. Measles vaccination campaigns should be an immediate priority given low coverage in the context of an ongoing outbreak. - Strengthen management of common childhood illnesses such as malaria, pneumonia and diarrhoea at accessible primary health centers; utilize community health volunteers to improve coverage where health centers are inaccessible. - Surveillance activities can be narrowed to areas with higher prevalence. Given limited funds, survey scope can be limited to a smaller area (Borno and Yobe). Narrowing focus would free funds to sample more clusters in Borno and fund additional small-scale rapid surveys in newly accessible areas. - As a sector, a few targeted and high quality small-scale survey should be organized immediately in newly accessible areas to provide representative estimates of acute malnutrition and mortality.

Contents

Executive Summary ...... ii Contents ...... 1 List of Acronyms ...... 2 Justification ...... 4 1.1. Objectives ...... 7 2. Methodology ...... 8 2.1 First Stage Sampling ...... 8 2.2 Second Stage Sampling ...... 9 2.3 Sample Size Calculation ...... 10 2.4 Case Definitions and Inclusion Criteria ...... 11 2.5 Training and Supervision ...... 12 2.6 Data Analysis ...... 13 3. Results ...... 14 3.1 Final Sample and Data Quality ...... 14 3.2 Anthropometric results (based on WHO standards 2006): ...... 20 Acute Malnutrition (WHZ and/or Bilateral Oedema) ...... 20 Acute Malnutrition (MUAC and/or Bilateral Oedema ...... 23 Underweight ...... 26 Stunting ...... 29 3.3 Mortality results ...... 34 3.4 Child Health ...... 35 Measles Vaccination Coverage ...... 35 Diarrhoea, Oral Rehydration Therapy and Zinc Supplementation ...... 38 Acute Respiratory Infection (ARI) and Treatment ...... 41 Fever, Prevention of Malaria, and Antimalarial Treatment ...... 43 3.5 Infant and Young Child Feeding ...... 49 3.6 Public Health Campaigns, Maternal, Newborn, and Child Health Week (MNCHW) ...... 51 Deworming ...... 52 Fortified Blended Foods ...... 55 3.7 Women’s Nutrition ...... 56 Dietary Diversity ...... 58 3.8 Water and Sanitation ...... 62 4. Conclusion and Recommendations ...... 66 References ...... 68 Annexes ...... 70 Annex 1. Acknowledgments ...... 70 Annex 2. Lower Government Areas and Estimated Population, by Survey Domain ...... 71 Annex 3. Maps of Lower Government Areas, by Survey Domain and Accessibility ...... 73 Annex 4. List of nutrition indicators and definitions ...... 75 Annex 5. Calendar of Local Events ...... 78 Annex 6. Selected Clusters ...... 79 Annex 7. Plausability Checks...... 89

List of Acronyms ACT Artemisinin-based Combination Therapy ANC Antenatal Care ARI Acute Respiratory Infection CI Confidence Interval CMAM Community-based Management of Acute Malnutrition EA Enumeration Areas ENA Emergency Nutrition Assessment EPI Expanded Programme on Immunisation FGON Federal Government of Nigeria FMOH Federal Ministry of Health GAM Global Acute Malnutrition HAZ Height for Age Z-score HH Household IPT Intermittent Preventive Treatment ITN Insecticide Treated Net IYCF Infant and Young Child Feeding KAP Knowledge Attitudes and Practice LGA Local Governmental Area MAM Moderate Acute Malnutrition MDG Millennium Development Goals MNCHW Maternal Newborn and Child Health MICS Multiple Cluster Indicator Survey MUAC Mid-Upper Arm Circumference NBS National Bureau of Statistics NCHS National Center for Health Statistics NDHS Nigeria Demographic and Health Survey NIS Nutrition Information System NMCSP National Malaria Control Strategic Plan NNHS National Nutrition and Health Survey NPopC National Population Commission NSHDP National Strategic Health Development Plan NSPAN National Strategic Plan of Action for Nutrition ORS Oral Rehydration Salts ORT Oral Rehydration Therapy PHC Primary Health Care PPS Probability Proportional to Size PSU Primary Sampling Unit RDT Rapid Diagnostic Testing SAM Severe Acute Malnutrition SD Standard Deviation SMART Standardized Monitoring and Assessment of Relief and Transition SOML Saving One Million Lives SP Sulphadoxine Pyrimethamine UNHCR United Nation High Commission for Refugees

UNICEF United Nations Children's Fund USAID United States Agency for International Development VAD Vitamin A Deficiency WASH Water Sanitation and Hygiene WAZ Weight for Age Z-score WB World Bank WHZ Weight for Height Z-score WFP United Nations World Food Programme WHO World Health Organization

Justification

The Boko Haram conflict was declared to be a state of emergency at the beginning of 2012 by the government of Nigeria. In May 2013, the area under the state of emergency was extended to include all of Adamawa, Borno and Yobe states in Northeastern Nigeria. The conflict has impacted freedom of movement, livelihoods, markets, and humanitarian access in North East Nigeria, Niger, Chad and Northern Cameroon.

Within Nigeria, the humanitarian emergency is currently focused in Borno, Yobe and Adamawa states. The insurgency and political violence in these states has caused population displacement. According to the International Organization of Migration’s (IOM) October 2016 report, there are approximately 1.4 million, 170,070 and 124,706 internally displaced persons (IDPs) in Borno, Adamawa and Yobe states respectively.

The most recent state level estimates of global acute malnutrition from the National Nutrition and Health Survey July to September 2015 found 10.9% (8.6-13.7 95% CI) in Yobe, 11.5% (8.8- 14.9 95% CI) and in Borno and 7.1% (5.0- 10.1 95% CI) in Adamawa.[3] These results suggested a serious prevalence of GAM in the three states. However, prevalence was as high in other states in northern Nigeria. It is possible that these results masked pockets of acute malnutrition potentially occurring as a result of intense political violence restricting humanitarian access. Several LGAs in Borno were inaccessible at the time of data collection for the 2015 NNHS.

Information on the nutrition situation since the emergency declaration in April 2016 remains limited. A few, small scale Standardized Monitoring and Assessment of Relief and Transitions (SMART) and Emergency Food Security Assessment (EFSA) surveys conducted in Jere LGA Borno (April 2016), Jasuko LGA Yobe (May 2016), Gujba & Gulani LGAs Yobe (July 2016), Konduga LGA Borno (July 2016), Mondugo town (August 2016). Results of these assessments are presented in Figure 1.1. These surveys suggest a large variability in prevalence by LGA. Within Borno, the survey in Kaga LGA found prevalence below emergency thresholds (13.0% GAM, 3.4% SAM) whereas a survey in Monguno town suggested a prevalence twice as high (27.3% GAM, 8.7% SAM). Survey results released during data collection suggest even higher prevalence of acute malnutrition by MUAC in some camps in Borno. While these surveys provide the most reliable information on the current nutrition situation in the N.E. region, there were too few to provide a comprehensive or clear picture of conditions in the region.

Figure 1.1: Nutrition survey and screening results in Borno and Yobe states -8th Sept, 2016.

Source: UNICEF, ACF, MSF, ALIMA, WFP, FEWS NET

During the same time period, screening data were also collected by NGO and UNICEF supported teams in Yobe and Borno states. Screening generally assess prevalence of acute malnutrition using mid-upper arm circumference (MUAC) and/or bilateral oedema. Results of screenings conducted by UNICEF between May 2 and August 8, 2016 are presented in Figure 1.2. Available screening data suggests in some sites, prevalence of SAM and GAM peaked at over 50% and 80%. The results of the screening show that the prevalence of SAM is much lower in sites where more exhaustive screening was conducted (over 5,000 children screened). The primary aim of screenings is the identification and referral of children for treatment. As such methods of selecting children are variable, as is the experience level and training of teams. Samples for these screenings range from a few hundred to several thousand children. However, despite these limitations, results from these assessments have been used in the response in the absence of population representative data. These data have raised concerns about potential areas with possible emergency or even famine levels of malnutrition.

Figure 1.2: Percentage of internally displaced children screened by UNICEF who were acutely malnourished (MUAC), 2nd May to 8th August 2016

Note: Numeric value is the number of children screened. Source: UNICEF

As part of an effort to improve the information available to monitor the nutrition crisis in North East of Nigeria, UNICEF and the nutrition sector established a surveillance system, triangulation of data from (1) repeated cross-sectional surveys on standardized groupings of LGAs, (2) exhaustive MUAC screening of children from 6-59 months in newly accessible areas, and (3) real- time CMAM programme and stocks data to ensure that all children diagnosed with SAM are receiving emergency therapeutic care. The data presented in this report represent the first of a series of planned repeated cross-sectional surveys.

1.1. Objectives

The overall goal of this assessment is to establish the extent and the severity of acute malnutrition and determine the contributing factors of malnutrition in North East Nigeria to inform the ongoing emergency response.

The specific objectives of the survey were as follows:  Determine all-cause mortality among the general population (crude death rate) and among children 0 to 59 months (under-five death rate);  Determine the prevalence of acute malnutrition among children 0 to 59 months of age using WHZ and bilateral oedema and among children 6 to 59 months using Mid Upper Arm Circumference (MUAC);  Determine the prevalence of chronic malnutrition and underweight among children 0 to 59 months of age;  Determine the prevalence of acute malnutrition among women 15 to 49 years of age using MUAC;  Estimate coverage of Maternal Newborn and Child Health Week (MNCHW) campaigns  Assess the prevalence of diarrhoea and use of ORS and zinc among children under-five years two weeks preceding the survey;  Assess the prevalence of fever and use of antibiotics among children under-five years two weeks preceding the survey;  Estimate coverage of deworming among children 12 to 59 months of age within the last six months;  Determine the coverage of measles immunization among children 12 to 23 months of age;  Determine the proportion of under five children with Acute Respiratory Infection (ARI) symptoms and proportion of children with fever who received treatment;  Determine the ownership and universal access of mosquito nets, and utilization of mosquito nets by children 0 to 59 months of age;  Assess breastfeeding practices among children 0 to 23 months of age;  Assess dietary diversity among women 15 to 49 years of age;  Estimated coverage of corn soy blend (CSB) distribution among all households;  Estimate household access to safe water and sanitation facilities.

2. Methodology

This survey, part of the Nigeria Nutrition and Food Security Surveillance System, was designed as cross-sectional household surveys using a two stage cluster sampling design consistent with the SMART methodology. These methods produce results representative of a groupings of local government areas (LGAs) as domains. Domains were created considering livelihood zones, geographic proximity and socio-cultural homogeneity.[1]

The survey area consists of 65 LGAs within the three states of Adamawa, Borno and Yobe. The 65 LGAs were divided into 10 domains: 2 in Adamawa, 3 in Yobe and 5 in Borno states. LGAs were grouped as follows:

Table 2.1. Survey Domains

Domain LGAs Included 1 Southern Adamawa Demsa, Gombi, Guyuk, Lamurde, Numan, Shelleng, Yoa North, Ganye, Jada, Mayo-Belwa, Teungo, Fufore, Yola South 2 Northern Adamawa Girie, Hong, Madagali, Maiha, Michika, Mubi North, Mubi South, Song 3 Northern Borno Abadam, Mobbar, Guzamala, Kukawa, Nganzai 4 Southern Borno Askira/Uba, Bayo, Biu, Chibok, Haul, Kwaya Kusar, Shani 5 East Borno Bama, Dikwa, Gwoza, Kala/Balge, Ngala 6 Central Borno Damboa, Gubio, Kaga, Konduga, Mafa, Magumeri, Marte, Monguno, 7 MCC/Jere Maiduguri, Jere 8 Central Yobe Bade, Borsari, Geidam, Jakusko 9 Southern Yobe Damaturu, Fika, Fune, Gujba, Gulani, Nangere, Potiskum, Tarmuwa 10 Northern Yobe Karasuwa, Machina, Nguru, Yunusari, Yusufari

2.1 First Stage Sampling

The sample was selected using a two-stage cluster design. The clusters for each domain were drawn independently using probability proportional to size (PPS) method. For Yobe and Adamawa, clusters were selected from the updated national master sample frame with the support from National Population Commission (NPC). Estimated populations for each EA are 2016 populations projected from the 2006 census as calculated by NPC. No EAs were excluded a priori.

Given recent large scale population movement, an updated sampling frame was built for Borno. A list of lowest possible unit (villages or camps) available were used for sampling. Population estimates from the September-October 2016 polio campaign microplan were used for settlements. Population estimates for internally displaced persons (IDP) camps were from the latest International Organization on Migration (IOM) Displacement Tracking Matrix (DTM) report (version September 13) available at the time of the survey.[2]

Several wards were excluded a priori as they were determined to be inaccessible given the

8 ongoing conflict. Accessibility was determined by state level security officers and informed by access during the most recent polio campaign. Two of the domains in Borno (North and East) were determined to be too inaccessible at the time of this survey to proceed with data collection. In the three surveyed domains in Borno, 75% of villages were accessible representing 87% of the estimated population of these domains. Estimated population (total and accessible) are provided in Annex 2. Estimates of accessible populations includes persons in areas that were only accessible with a military escort.

Of the originally selected clusters 13 were either inaccessible or abandoned including: 2 clusters (1 abandoned, 1 inaccessible) in North Adamawa, 1 cluster in Southern Adamawa (inaccessible), 2 clusters in MMC/Jere (1 abandoned, 1 inaccessible), 3 clusters in Central Borno (inaccessible), 2 clusters in Central Yobe (1 abandoned, 1 inaccessible), 2 clusters in Southern Yobe (inaccessible), and 1 cluster in Northern Yobe (inaccessible).

The 3 inaccessible clusters in Central Borno were all in Monguno LGA. Following a bombing in the areas during field work, teams were evacuated and clusters in the areas were excluded. As 10% of the clusters were inaccessible, SMART guidance recommends the use of replacement clusters. Of the 4 replacement clusters, 1 was also in Monguno and therefore only 3 of the 4 replacement clusters were used.

2.2 Second Stage Sampling

Within selected clusters, households were selected using systematic random selection. With the support of a community leader, teams mapped and listed all households within the cluster. The following definition was used to identify a household:

“A person or a group of persons, related or unrelated, who live together and share a common source of food and livelihood, and recognize one person as a head.”

In many cases, compounds contained multiple households. Abandoned households were not listed. Household listing was performed using a paper form. Team leaders enter the total number of households in the cluster into the tablet. Sampling interval was automatically calculated on the tablet and displayed along with the random start number.

Households that were absent at the time of the visit were re-visited at least three times before being marked absent. Households in which one or more children 0-59 months of age or women 15-49 years of age were absent at the time of the visit were also re-visited. Households that refused were not replaced.

All eligible children and women were measured. The head of household was the respondent for the household enumeration, mortality questionnaire, and other household level questions (e.g., water and sanitation). For questions about children, the primary caregiver served as the respondent. One randomly selected women of reproductive age (15-49 years) was randomly selected using the tablet for questions on women’s dietary diversity.

2.3 Sample Size Calculation

The sample sizes for anthropometry and mortality have been calculated using the ENA for SMART application. Sample size was calculated to ensure adequate prevalence of global acute malnutrition (GAM) of children aged 6-59 months as well as crude mortality rate.

Details on the on the estimated values and source for each parameter are provided in Tables 2.3.1 and 2.3.2. Sample size for GAM was calculated using an estimated prevalence for the three states using results from the National Nutrition and Health Survey (NNHS) 2015.[3] To be conservative, a prevalence of 15% was used for the sample size calculation; this represents the upper confidence interval of the estimate for Borno, the state with the highest prevalence of the three sampled states. Estimates for design effect as well as demographic data were also estimated based on the results of the 2015 NNHS.

Table 2.3.1: Sample size calculation parameters for global acute malnutrition

Parameters Value Source/Assumption Estimated Prevalence of GAM (%) 15% Estimate for three states based on NNHS 2015 Precision recommended by SMART methodology Precision 3.5 given 15% prevalence Design Effect for WHZ 1.4 Estimate for three states based on NNHS 2015 Children to be Included 609 Average Household Size 6 NNHS 2015: Borno Estimate % of Children Under Five Years Old 20% NNHS 2015: Borno Estimate Percent of Non-response 5% NNS 2015: Three states estimate Households Households to be Included 594

An estimated CDR of 1.1 deaths per 10,000 population per day was used in calculating sample size for mortality. Available data from recent small-scale emergency surveys in N.E. Nigeria (SMART surveys) available at the time suggested mortality rates ranging from 0.38 to 1.03 deaths per 10,000 population per day. A CDR of 1.1 was used for calculation to be conservative given reports of increasing violence.

Sample size for mortality was estimated with a recall period beginning January 1, 2016. A longer recall period was used to allow the survey to collect data about mortality during periods of increased violence in early 2016, including the period leading up to the declaration of the nutrition emergency. This was perceived as important given the limited mortality information available for this time period. January 1, 2016 (New Year’s Day) was believed to be a memorable date in N.E. Nigeria.

By domain, data collection concluded between October 25 and November 5 resulting in recall periods of 298 days in Southern Adamawa, 295 days in Northern Adamawa, 299 days in Southern Borno, 304 days in Central Borno, 292 days in MMC/Jere, 303 days in Central Yobe, 302 days in Southern Yobe, and 309 day recall in Northern Yobe.

Table 2.3.2: Sample size calculation parameters for crude mortality rate

Parameters Value Source/Assumption Estimate from observed CDR in recent mortality surveys Estimated prevalence CDR 1.1 in NE Nigeria (range: 0.38-1.03). Precision 0.33 Precision recommended by SMART for a CDR around 1 Estimated from observed design effect in recent Design Effect for CDR 2 mortality surveys NE Nigeria (range: 1-2.1) Recall from January 1, 2016 - memorable date, interest Recall Period in Days 270 in all of 2016 mortality Individuals to be Included 3129 Average Household Size 6 NNHS 2015: Borno Estimate Percent of Non-response 5% NNS 2015: Three states estimate Households Number of Households to 549 be included

To reach the calculated sample size, a sample of 30 cluster each with 20 households was selected in each domain.

2.4 Case Definitions and Inclusion Criteria

A full list of indicators as well as their case definitions and age inclusion is provided as Annex 4. The following is a summary:

- Child Nutrition Acute malnutrition among children age 0-59 months (by weight-for-height and/or oedema); acute malnutrition among children age 6-59 months (by MUAC and/or oedema); underweight, chronic malnutrition among children age 0-59 months.

- Mortality Crude death rate and under-five death rate.

- Child health Measles vaccination coverage among children; proportion of children under five with fever, Acute Respiratory Infection (ARI) and diarrhoea who received an ACT, antibiotics, and ORS and zinc respectively; household mosquito net ownership, universal coverage of mosquito net and utilization of mosquito net by under-five children and intermittent preventive treatment in children.

- Public Health Campaigns MNCHW coverage; Deworming among children 12-59 months; coverage of corn soy blend (CSB) distributions.

- Women’s Nutrition Acute malnutrition among women age 15-49 years; dietary diversity among women. 11

- Water, Sanitation and Hygiene Household water treatment, Presence of water and soap at household handwashing station.

Age was recorded as exact date of birth if documentation (either a birth certificate or vaccine card) was available. In all other cases, age was estimated in months using a local events calendar. The calendar of local events used during field work is included as Annex 5

Anthropometry was measured according to WHO recommendations.[4] Selected children were weighed without clothes using SECA scales (100g precision). Children were measured on a measuring board (precision of 0.1cm). Children less than 87 cm were measured lying down, while those greater than or equal to 87 cm were measured in standing up position. MUAC was measured using standard UNICEF tapes at the mid-point of the left upper arm of the children (precision of 0.1cm). Bilateral pitting oedema was assessed by the application of normal thumb pressure for at least 3 seconds to both feet.

All the team members were given referral forms and all children found to be severely acutely malnourished were referred to the closest CMAM facility.

2.5 Training and Supervision

Survey training was organized from October 10 to 14 in Nasarawa state. The training included 3 days of theoretical training, a standardization test, and a field test. Training was facilitated by experts from UNICEF, National Bureau of Statistics (NBS), and the Centers for Disease Control and Prevention (CDC).

The training included the following: - An overview of the survey and its objectives, as well as an introduction to SMART methods - Interviewing and general communication skills - Segmentation and systematic random selection of households - Consent forms and identification of individuals to measure or interview - Classroom and practical training on how to complete the questionnaires - Estimation of age in months and validation using the calendar of local events - Classroom and practical training on proper anthropometric measurements technique - The standardization test to assess accuracy and precision of height, weight and MUAC - The identification and referral of cases of severe acute malnutrition - Household enumeration, data entry, and transmission of questionnaires using tablets

A pilot test was organized in Nasarawa before the commencement of data collection, in order to assess the tools and evaluate the actual data collection process before deployment of the teams.

Survey staff were selected by the NBS. All selected individuals were current residents of Borno, Yobe, or Adamawa. Selected individuals were literate in at least English and Hausa. 39 individuals were selected of which 28 were retained as enumerators. Selection was based on performance

12 during the standardization test, field test, and a written examination. The 28 individuals made up fourteen teams, each composed of a measurer and an assistant.

Teams were supervised in the field by 2 field coordinators, senior staff from the NBS, as well as five supervisors selected based on performance during the training. Supervisors were in charge of no more than 3 teams. Supervisors were responsible for the daily organisation and supervision of teams' work. The regional coordinators provided support to supervisors based on need, coordinated security and movement plans, and targeted additional supervision based on feedback received daily from survey coordinators.

An additional training, involving both theoretical training and a field test, was organized in the northern states for a few poorly performing teams. Four additional supervisors were also trained following the beginning of field work to provide additional supervision.

2.6 Data Analysis

Data were entered directly into 3G enabled tablets (Galaxy tab 4 7.0’’) using a questionnaire built in Open Data Kit (opendatakit.org) and transmitted to an ONA online server (ona.io) as soon as connected to a network. The ENA application (version July 9, 2015) was used for analysis of anthropometry and mortality data. Stata (version 14.2) was used for transformation of the data from the ONA output to ENA as well as for analysis of additional indicators.

Tablets were programmed with internal quality checks during field work including a prompt for a re-measurement of potential errors in anthropometric measurements. Enumerators were prompted to re-measure all anthropometric indicators if measurements were outside of the WHO flag criteria (HAZ was below –6 or above +6, WAZ was below –6 or above +5, WHZ was below –5 or above +5, or BMIZ was below –5 or above +5).[4] An additional 5% of children were randomly selected for re-measurement. Second measurements were used in the analysis when taken.

For analysis, Z-scores for each child were calculated based on the WHO 2006 growth references population. Extreme values were excluded during analysis based on SMART flag criteria. SMART flags exclude anthropometric indices with -3 to 3 for WHZ, -3 to 3 for HAZ, -3 to 3 for WAZ, from observed mean. The number of values excluded for each indicator is presented in Table 3.2.9.

3. Results

3.1 Final Sample and Data Quality

Data collection took place between October 17 and November 11, 2016 in Adamawa, Borno, and Yobe states. Table 3.1.1 provides details on the number of clusters completed and sample size in terms of households, children (0-59 months) and women (15-49 years of age) by domain. For children, both the number surveyed and the number measured are provided as not all children interviewed consented to measurement.

By domain the number of households surveyed ranged from 540 to 589. Households that were absent upon re-visit or refused were not replaced. Response rates ranged from 96.4% (Northern Adamawa) to 98.4% (Central Yobe). The number of children aged 0-59 months surveyed ranged from 491 to 594. By state, average household size ranged from 5.2-5.6. Children represented 15.6 to 18.0% of household members by state.

Table 3.1.1. Final sample of households, women and children, by domain

Total number of Average Number children under five percent of Number of women Clusters Average years of age HH of HHs 15-49 Surveyed HH Size members Surveyed years of Surveyed Measured age 0-59 age months State Adamawa 57 1105 5.2 1120 1091 17.8 1321 Borno 88 1719 5.5 1557 1504 15.6 1828 Yobe 85 1667 5.6 1737 1727 18.0 1851 Domain Southern Adamawa 29 565 5.1 560 553 17.5 678 Northern Adamawa 28 540 5.4 560 538 18.4 643 Southern Borno 30 589 5.7 547 539 15.2 665 Central Borno 30 581 4.9 519 511 16.8 542 MCC & Jere 28 549 5.6 491 454 15.4 621 Central Yobe 28 551 5.6 580 578 18.1 617 Southern Yobe 28 549 5.9 594 586 17.6 655 Northern Yobe 29 567 5.0 563 563 18.8 579

Additional information on the sample of children measured for nutrition indicators is presented in Tables 3.1.2. For each domain, the table presents the age and sex distribution of children 6-59 months of age. Note that some anthropometry indicators were measured among children under six months of age (not shown in Table 3.1.2). The sex ratio was not significant (p<0.05) for all domains suggesting the samples were balanced in terms of sex. By domain, the ratio of boys to girls ranged from 0.98-1.15 (Table 3.1.3). The ratio of children age 6-23 months to children 30-59 months ranged from 1.00-1.26. This ratio is expected to be approximately 0.85, suggesting our samples had a higher proportion of younger children than expected. The high proportion of younger children may reflect a true deviation of the age structure of the population, possibly due to ongoing displacement in the area or sampling bias.

Table 3.1.2: Distribution of age and sex of sample, by domain

Boys Girls Total Ratio Age groups (months) no. (%) no. (%) no. (%) Boy:girl South Adamawa 6-17 76 (53.9) 65 (46.1) 141 (28.5) 1.2 18-29 73 (57.5) 54 (42.5) 127 (25.7) 1.4 30-41 59 (52.7) 53 (47.3) 112 (22.6) 1.1 42-53 47 (51.1) 45 (48.9) 92 (18.6) 1.0 54-59 10 (43.5) 13 (56.5) 23 (4.6) 0.8 Total 265 (53.5) 230 (46.5) 495 (100) 1.2 North Adamawa 6-17 63 (48.8) 66 (51.2) 129 (25.8) 1.0 18-29 62 (51.2) 59 (48.8) 121 (24.2) 1.1 30-41 63 (53.4) 55 (46.6) 118 (23.6) 1.1 42-53 57 (54.3) 48 (45.7) 105 (21.0) 1.2 54-59 11 (40.7) 16 (59.3) 27 (5.4) 0.7 Total 256 (51.2) 244 (48.8) 500 (100) 1.0 Southern Borno 6-17 62 (50.8) 60 (49.2) 122 (25.2) 1.0 18-29 75 (53.2) 66 (46.8) 141 (29.1) 1.1 30-41 52 (43.7) 67 (56.3) 119 (24.5) 0.8 42-53 49 (54.4) 41 (45.6) 90 (18.6) 1.2 54-59 7 (53.8) 6 (46.2) 13 (2.7) 1.2 Total 245 (50.5) 240 (49.5) 485 (100) 1.0 Central Borno 6-17 58 (49.2) 60 (50.8) 118 (25.8) 1.0 18-29 65 (53.7) 56 (46.3) 121 (26.5) 1.2 30-41 65 (53.3) 57 (46.7) 122 (26.7) 1.1 42-53 44 (54.3) 37 (45.7) 81 (17.7) 1.2 54-59 8 (53.3) 7 (46.7) 15 (3.3) 1.1 Total 240 (52.5) 217 (47.5) 457 (100) 1.1 MMC / Jere 6-17 46 (43.8) 59 (56.2) 105 (23.9) 0.8 18-29 57 (49.1) 59 (50.9) 116 (26.4) 1.0 30-41 57 (45.6) 68 (54.4) 125 (28.4) 0.8 42-53 54 (61.4) 34 (38.6) 88 (20.0) 1.6 54-59 4 (66.7) 2 (33.3) 6 (1.4) 2.0 Total 218 (49.5) 222 (50.5) 440 (100) 1.0 Northern Yobe 6-17 64 (53.3) 56 (46.7) 120 (24.2) 1.1 18-29 68 (50.7) 66 (49.3) 134 (27.1) 1.0 30-41 58 (46.0) 68 (54.0) 126 (25.5) 0.9 42-53 49 (54.4) 41 (45.6) 90 (18.2) 1.2 54-59 18 (72.0) 7 (28.0) 25 (5.1) 2.6 Total 257 (51.9) 238 (48.1) 495 (100) 1.1 Central Yobe 6-17 75 (56) 59 (44) 134 (26.1) 1.3 18-29 55 (44.7) 68 (55.3) 123 (24) 0.8 30-41 71 (54.6) 59 (45.4) 130 (25.3) 1.2 42-53 53 (53.0) 47 (47.0) 100 (19.5) 1.1 54-59 10 (38.5) 16 (61.5) 26 (5.1) 0.6 Total 264 (51.5) 249 (48.5) 513 (100) 1.1 Southern Yobe 6-17 77 (47) 87 (53) 164 (30.7) 0.9 18-29 70 (52.2) 64 (47.8) 134 (25.0) 1.1 30-41 60 (50.4) 59 (49.6) 119 (22.2) 1.0 42-53 56 (53.3) 49 (46.7) 105 (19.6) 1.1 54-59 7 (53.8) 6 (46.2) 13 (2.4) 1.2 Total 270 (50.5) 265 (49.5) 535 (100) 1.0 16

Table 3.1.3 presents a summary of the data quality. Overall, data quality was high. All domains had less than 3.0% of values excluded as outliers (SMART flags). Standard deviation for WHZ for all surveys fell within an acceptable range (0.8-1.2). Tests of skewness, kurtosis and Poisson distribution, generally suggest that the WHZ distributions were normal. Statistical tests for rounding, referred to as digit preference, suggest that there was no notable preference for any digit in weight measurements (as if generally the case when digital scales are used). For height and MUAC, digit preference scores were highest in Southern Borno. All other domains had values of 10 or less (“acceptable”).

Overall, data quality was “excellent” in 4 domains (North Adamawa, Central Borno, MMC/Jere, and Central Yobe) and “acceptable” in 4 domains (South Adamawa, South Borno, South Yobe, North Yobe) according to SMART classifications. Results by indicator are color coded in Table 3.1.3 on a scale from excellent (dark green) to problematic (orange). Full plausibility reports are provided as Annex 7.

Table 3.1.3. Summary of Child Anthropometry Data Quality

Digit Preference Score Age Flagged Sex Poisson Ratio Skewness Kurtosis Data Ratio SD WHZ WHZ

6-23/ WHZ WHZ

(%) M/F (P-value) 30-59

Weight Height MUAC

1.1% 1.15 1.18 4 5 6 1.11 -0.13 -0.35 0.02 S. Adamawa

1.5% 1.05 1.00 4 7 7 1.08 0.13 -0.08 0.01 N. Adamawa

2.2% 1.02 1.18 7 14 13 1.09 -0.08 -0.09 0.34 S. Borno

2.0% 1.11 1.10 5 9 8 0.99 -0.06 -0.35 0.17 C. Borno

1.8% 0.98 1.01 6 10 10 0.99 0.06 -0.22 0.57 MMC/Jere

2.1% 1.06 1.00 4 8 9 1.06 -0.06 -0.06 0.01 C. Yobe

2.1% 1.02 1.26 3 6 6 1.11 0.09 -0.02 0.39 S. Yobe

2.7 1.08 1.05 6 8 8 1.13 0.18 -0.28 0.02 N. Yobe

In addition to the tests presented above, the proportion of children with complete date of birth is an important measure of the quality of age data. For children aged 0-59 months, age was recorded as an exact date of birth if recorded on a birth certificate or vaccination card available

17 at the time of the visit. When unavailable, age in months was estimated using a local events calendar. Table 3.1.3 presents the proportion of children for which exact date of birth was available by domain and by team. The proportion of children with documented date of birth varied considerably by domain (range: 6.2 – 46.2%) and by team (range: 2.2- 74.6). This is likely affected by regional differences in availability of age documentation. Where vital registration and age documentation are poor, measures that include age (such as stunting and underweight) may be affected.

Table 3.1.4. Proportion of children with complete data of birth, age reported in months or missing, by domain and team

Age reported in Complete date of Missing (%) months (%) birth (%) Domain Southern Adamawa 51.8 47.9 0.4 Northern Adamawa 59.1 40.2 0.7 Southern Borno 75.9 23.6 0.5 Central Borno 93.4 6.4 0.2 MCC & Jere 53.8 46.2 0.0 Central Yobe 88.1 11.9 0.0 Southern Yobe 72.4 27.3 0.3 Northern Yobe 93.8 6.2 0.0 Team 1 78.7 20.8 0.5 2 77.3 22.7 0.0 3 77.8 21.1 1.0 4 76.7 23.3 0.0 5 90.5 9.5 0.0 6 25.4 74.6 0.0 7 45.8 54.0 0.2 8 67.0 33.0 0.0 9 65.8 34.2 0.0 10 73.8 26.3 0.0 11 90.2 8.7 1.1 12 97.5 2.2 0.4 13 81.8 18.2 0.0 14 74.7 25.0 0.3

Figure 3.1.1 prevents graphically the age in months of all children 0-59 months included in the survey, a visual illustration of the quality of age estimation. The figure provides some evidence of age heaping, peaks and troughs in the distribution throughout the five years, particularly around 24, 36, and 48 months of age. Age heaping affects quality of underweight and stunting estimates. Overall, the distribution is acceptable given the low proportion of children with documentation but shows a need for improvement.

Figure 3.1.1. Distribution of Children by Age in Months

Similarly, Figure 3.1.2 presents age in years for women of reproductive age. Clear heaping is evident around five year markers (20, 25, 30, 35, 40, and 45). This pattern is consistent with previous surveys in Nigeria, and is likely due with poor vital registration in the region and low literacy levels in the region. Given the age heaping, results for women based on age categories should be interpreted with caution.

Figure 3.1.2. Distribution of Women by Age in Years

3.2 Anthropometric results (based on WHO standards 2006):

Anthropometric measurements in children were converted into z-scores using the World Health Organization Child Growth Standards.[5] Three child malnutrition indicators are presented— acute malnutrition, chronic malnutrition and underweight. Acute malnutrition is most responsive to changes in diet and the most dangerous form of malnutrition in terms of mortality risk; as such it is the primary indicator of interest in the context of an emergency.

Acute Malnutrition (WHZ and/or Bilateral Oedema)

Tables 3.2.1 present prevalence of acute malnutrition by state and domain among children 0-59 months of age based on weight-for-height z-scores and/or oedema, disaggregated by sex. Age disaggregation by domain for children 6-59 months of age is presented in Table 3.2.2.

Prevalence of global acute malnutrition (GAM) was above 10%, an emergency threshold in Borno (11.3%) and Yobe (11.4%). In these states prevalence of severe acute malnutrition was 1.1% and 1.7%, respectively. By domain, prevalence of global acute malnutrition was highest in Northern Yobe (14.3%), followed by MMC & Jere (13.0%). Prevalence was higher among boys than girls in all domains with the exception of Northern Adamawa and Central Borno. Disaggregation by child’s age shows that prevalence of global acute malnutrition is highest among children in the younger age cohorts (6-11 months and 12-23 months).

Table 3.2.1: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by sex, children 0-59 months, by state and domain

Prevalence of global malnutrition Prevalence of moderate malnutrition Prevalence of severe malnutrition Number of (<-2 z-score and/or oedema) (<-2 z-score and >=-3 z-score, no oedema) (<-3 z-score and/or oedema) children 0-59 All Boys Girls All Boys Girls All Boys Girls months

State Adamawa (60) 5.6% (33) 6.2% (27) 5.0% (53) 5.1% (31) 5.9% (22) 4.2% (7) 0.6% (2) 0.4% (5) 0.8% 1077 [4.1,7.8] [4.2,9.1] [3.1,8.0] [3.6,7.0] [4.0,8.6] [2.4,7.2] [0.3,1.3] [0.1,1.5] [0.3,2.0] Borno (163) 11.3% (90) 12.3% (73) 10.2% (148) 10.1% (82) 11% (66) 9.2% (15) 1.1% (8) 1.3% (7) 1.0% 1472 [9.7,13.0] [10.0,14.9] [8.2,12.6] [8.5,12.0] [8.8,13.7] [7.2,11.7] [0.7,1.9] [0.6,2.7] [0.5,2.1] Yobe (197) 11.4% (107) 12.1% (90) 10.7% (167) 9.7% (91) 10.3% (76) 9.0% (30) 1.7% (16) 1.8% (14) 1.7% 1683 [9.7,13.3] [9.7,15.0] [8.6,13.2] [8.3,11.2] [8.2,12.9] [7.1,11.2] [1.2,2.6] [1.0,3.2] [1.0,3.0] Domain S. Adamawa (32) 5.9 % (21) 7.1 % (11) 4.4 % (30) 5.5 % (20) 6.8 % (10) 4.0 % (2) 0.4 % (1) 0.3 % (1) 0.4 % 547 [3.8 - 9.0] [4.3 - 11.5] [2.0 - 9.4] [3.5 - 8.4] [4.2 - 10.9] [1.7 - 9.1] [0.1 - 1.5] [0.0 - 2.6 ] [0.0 - 3.1] N. Adamawa (28) 5.3 % (12) 4.5 % (16) 6.1 % (23) 4.3 % (11) 4.1 % (12) 4.6 % (5) 0.9 % (1) 0.4 % (4) 1.5 % 530 [3.1 - 8.8] [2.3 - 8.7 ] [3.4 - 10.6] [2.6 - 7.3] [2.1 - 8.1 ] [2.4 - 8.5 ] [0.3 - 2.6] [0.0 - 2.8 ] [0.6 - 3.9 ] Southern Borno (47) 8.9 % (30) 11.2 % (17) 6.5 % (41) 7.8 % (27) 10.1 % (14) 5.4 % (6) 1.1 % (3) 1.1 % (3) 1.2 % 527 [6.7 - 11.0] [7.6 - 16.2] [4.6 - 9.2 ] [5.6 - 10.] [6.7 - 14.9] [3.6 - 8.0 ] [0.5 - 2.8] [0.2 - 5.0 ] [0.4 - 3.4 ] Central Borno (58) 11.6 % (30) 11.3 % (28) 12.0 % (55) 11.0 % (29) 10.9 % (26) 11.1 % (3) 0.6 % (1) 0.4 % (2) 0.9 % 499 [8.8 - 15.2] [8.0 - 15.8] [7.8 - 17.8] [8.3 - 14.] [7.6 - 15.5] [7.0 - 17.1] [0.2 - 1.8] [0.0 - 2.9 ] [0.2 - 3.3 ] MCC & Jere (58) 13.0 % (30) 13.6 % (28) 12.4 % (52) 11.7 % (26) 11.8 % (26) 11.5 % (6) 1.3 % (4) 1.8 % (2) 0.9 % 446 [10.2 - 16.4] [9.8 - 18.6] [8.8 - 17.1] [8.8 - 15.3] [8.1 - 16.9] [7.8 - 16.6] [0.6 - 2.9] [0.7 - 4.7 ] [0.2 - 3.6 ] Central Yobe (58) 10.3 % (33) 11.5 % (25) 9.0 % (46) 8.2 % (26) 9.1 % (20) 7.2 % (12) 2.1 % (7) 2.4 % (5) 1.8 % 564 [7.3 - 14.2] [7.4 - 17.3] [5.8 - 13.8] [5.6 - 11.7] [5.6 - 14.4] [4.2 - 12.1] [1.1 - 4.2] [0.9 - 6.2 ] [0.8 - 4.2 ] Southern Yobe (61) 10.7 % (32) 11.1 % (29) 10.2 % (52) 9.1 % (28) 9.7 % (24) 8.5 % (9) 1.6 % (4) 1.4 % (5) 1.8 % 572 [8.3 - 13.6 ] [7.4 - 16.2] [7.1 - 14.6] [7.3 - 11.3] [6.6 - 14.1] [5.9 - 12.0] [0.8 - 3.0] [0.4 - 4.7 ] [0.8 - 4.1 ] Northern Yobe (78) 14.3 % (42) 14.9 % (36) 13.6 % (69) 12.6 % (37) 13.1 % (32) 12.1 % (9) 1.6 % (5) 1.8 % (4) 1.5 % 547 [10.6 - 18.9] [10.5 - 20.] [9.4 - 19.3] [9.4 - 16.] [9.1 - 18.6] [8.2 - 17.5] [0.7 - 3.9] [0.6 - 4.8 ] [0.3 - 7.3 ] The prevalence of oedema is 0.0 % in all domains.

Table 3.2.2: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or oedema, children 6-59 months, by domain Severe wasting Moderate wasting Normal Age Groups (months) Total no. Oedema (<-3 z-score) (>= -3 and <-2 z-score ) (> = -2 z score) No. (%) No. (%) No. (%) No. (%) Southern Adamawa 6-17 139 1 (0.7) 12 (8.6) 126 (90.6) 0 (0) 18-29 125 0 (0) 8 (6.4) 117 (93.6) 0 (0) 30-41 111 0 (0) 1 (0.9) 110 (99.1) 0 (0) 42-53 89 0 (0) 5 (5.6) 84 (94.4) 0 (0) 54-59 23 0 (0) 1 (4.3) 22 (95.7) 0 (0) Total 487 1 (0.2) 27 (5.5) 459 (94.3) 0 (0) Northern Adamawa 6-17 124 1 (0.8) 9 (7.3) 114 (91.9) 0 (0) 18-29 115 1 (0.9) 3 (2.6) 111 (96.5) 0 (0) 30-41 115 2 (1.7) 2 (1.7) 111 (96.5) 0 (0) 42-53 102 0 (0) 6 (5.9) 96 (94.1) 0 (0) 54-59 27 0 (0) 0 (0) 27 (100) 0 (0) Total 483 4 (0.8) 20 (4.1) 459 (95) 0 (0) Southern Borno 6-17 120 3 (2.5) 14 (11.7) 103 (85.8) 0 (0) 18-29 136 0 (0) 15 (11) 121 (89) 0 (0) 30-41 116 1 (0.9) 3 (2.6) 112 (96.6) 0 (0) 42-53 89 1 (1.1) 6 (6.7) 82 (92.1) 0 (0) 54-59 13 0 (0) 0 (0) 13 (100) 0 (0) Total 474 5 (1.1) 38 (8) 431 (90.9) 0 (0) Central Borno 6-17 115 0 (0) 17 (14.8) 98 (85.2) 0 (0) 18-29 118 0 (0) 17 (14.4) 101 (85.6) 0 (0) 30-41 118 2 (1.7) 9 (7.6) 107 (90.7) 0 (0) 42-53 77 1 (1.3) 7 (9.1) 69 (89.6) 0 (0) 54-59 15 0 (0) 0 (0) 15 (100) 0 (0) Total 443 3 (0.7) 50 (11.3) 390 (88) 0 (0) MMC / Jere 6-17 103 0 (0) 21 (20.4) 82 (79.6) 0 (0) 18-29 112 2 (1.8) 13 (11.6) 97 (86.6) 0 (0) 30-41 119 0 (0) 11 (9.2) 108 (90.8) 0 (0) 42-53 83 3 (3.6) 5 (6) 75 (90.4) 0 (0) 54-59 6 0 (0) 0 (0) 6 (100) 0 (0) Total 423 5 (1.2) 50 (11.8) 368 (87) 0 (0) Central Yobe 6-17 131 5 (3.8) 15 (11.5) 111 (84.7) 0 (0) 18-29 120 3 (2.5) 7 (5.8) 110 (91.7) 0 (0) 30-41 128 2 (1.6) 6 (4.7) 120 (93.8) 0 (0) 42-53 100 1 (1) 10 (10) 89 (89) 0 (0) 54-59 24 0 (0) 3 (12.5) 21 (87.5) 0 (0) Total 503 11 (2.2) 41 (8.2) 451 (89.7) 0 (0) Southern Yobe 6-17 156 7 (4.5) 23 (14.7) 126 (80.8) 0 (0) 18-29 131 1 (0.8) 8 (6.1) 122 (93.1) 0 (0) 30-41 116 0 (0) 4 (3.4) 112 (96.6) 0 (0) 42-53 103 1 (1) 7 (6.8) 95 (92.2) 0 (0) 54-59 13 0 (0) 3 (23.1) 10 (76.9) 0 (0) Total 519 9 (1.7) 45 (8.7) 465 (89.6) 0 (0) Northern Yobe 6-17 116 5 (4.3) 23 (19.8) 88 (75.9) 0 (0) 18-29 131 2 (1.5) 20 (15.3) 109 (83.2) 0 (0) 30-41 123 1 (0.8) 7 (5.7) 115 (93.5) 0 (0) 42-53 88 0 (0) 9 (10.2) 79 (89.8) 0 (0) 54-59 24 0 (0) 1 (4.2) 23 (95.8) 0 (0) Total 482 8 (1.7) 60 (12.4) 414 (85.9) 0 (0) 22

Acute Malnutrition (MUAC and/or Bilateral Oedema

Mid-upper arm circumference in combination with bilateral oedema is commonly used in emergency nutrition programs, including in Nigeria, for diagnosis and referral of children aged 6- 59 months. Prevalence of acute malnutrition based on MUAC and/or oedema among children aged 6-59 months is presented in Tables 3.2.3 and 3.2.4.

Prevalence of acute malnutrition as assessed by MUAC and/or oedema was highest in Yobe (7.9%) followed by Borno (4.4%) and Adamawa (3.6%). Prevalence of severe malnutrition was also highest in Yobe (2.0%). By domain prevalence of acute malnutrition by MUAC was highest in Northern Yobe (10.5%). Prevalence was higher among girls than boys in all domains with the exception of Southern Borno. In all domains, the majority of children identified as acutely malnourished by MUAC were under 24 months of age.

While MUAC and WHZ are unique indicators, identifying different children as acutely malnourished, they both suggest a similar pattern—prevalence of acute malnutrition in Borno and Yobe is higher relative to Adamawa.

Table 3.2.3: Prevalence of acute malnutrition based on MUAC cut off's (and/or oedema) and by sex, children 6-59 months, by state and domain Prevalence of global malnutrition Prevalence of moderate malnutrition Prevalence of severe malnutrition Number of children (< 125 mm and/or oedema) (< 125 mm and >= 115 mm, no oedema) (< 115 mm and/or oedema) 6-59 months All Boys Girls All Boys Girls All Boys Girls

State Adamawa (34) 3.6% (16) 3.3% (18) 4.0% (28) 3.0% (13) 2.8% (15) 3.3% (6) 0.6% (3) 0.5% (3) 0.7% 982 [2.5,5.2] [1.9,5.5] [2.5,6.4] [2.0,4.6] [1.5,5.1] [2.0,5.4] [0.3,1.3] [0.2,1.6] [0.2,2.1] Borno (68) 4.4% (30) 3.9% (38) 4.8% (51) 3.3% (20) 2.5% (31) 4.2% (17) 1.1% (10) 1.5% (7) 0.7% 1363 [3.2,5.9] [2.4,6.3] [3.3,7.0] [2.4,4.5] [1.6,3.9] [2.8,6.2] [0.6,1.9] [0.7,3.1] [0.3,1.5] Yobe (125) 7.9% (53) 6.7% (72) 9.1% (91) 5.9% (38) 4.9% (53) 7.0% (34) 2.0% (15) 1.8% (19) 2.1% 1536 [6.4,9.7] [4.9,9.2] [7.3,11.4] [4.8,7.3] [3.3,7.0] [5.3,9.2] [1.3,2.9] [1.0,3.3] [1.4,3.3] Domain Southern Adamawa (20) 4.1 % (10) 3.8 % (10) 4.4 % (17) 3.5 % (9) 3.4 % (8) 3.5 % (3) 0.6 % (1) 0.4 % (2) 0.9 % 491 [2.5 – 6.5] [1.9 - 7.2 ] [2.4 - 8.1] [2.0 - 6.0] [1.6 - 7.1 ] [1.8 - 6.9] [0.2 – 1.8] [0.1 - 2.7 ] [0.2 - 3.4] Northern Adamawa (14) 2.9 % (6) 2.4 % (8) 3.3 % (11) 2.2 % (4) 1.6 % (7) 2.9 % (3) 0.6 % (2) 0.8 % (1) 0.4 % 491 [1.5 - 5.2] [1.0 - 5.7 ] [1.5 - 7.2 ] [1.2 - 4.2] [0.5 - 5.2 ] [1.3 - 6.4 ] [0.2 - 1.9] [0.2 - 3.2 ] [0.1 - 3.0 ] Southern Borno (20) 4.1 % (13) 5.3 % (7) 2.9 % (13) 2.7 % (7) 2.9 % (6) 2.5 % (7) 1.5 % (6) 2.5 % (1) 0.4 % 482 [2.3 - 7.4] [2.2 - 12.4] [1.5 - 5.5 ] [1.6 - 4.5] [1.3 - 6.2 ] [1.2 - 5.1 ] [0.5 - 4.0] [0.8 - 7.4 ] [0.1 - 3.1 ] Central Borno (34) 7.5 % (12) 5.1 % (22) 10.2 % (26) 5.8 % (10) 4.2 % (16) 7.4 % (8) 1.8 % (2) 0.8 % (6) 2.8 % 451 [4.5 - 12.3] [2.9 - 8.7 ] [5.5 - 18.3] [3.3 - 9.9] [2.2 - 7.9 ] [3.7 - 14.6] [0.7 - 4.2] [0.2 - 3.4 ] [1.2 - 6.5 ] MCC & Jere (14) 3.3 % (5) 2.3 % (9) 4.2 % (12) 2.8 % (3) 1.4 % (9) 4.2 % (2) 0.5 % (2) 0.9 % (0) 0.0 % 430 [1.8 - 5.7 9] [1.0 - 5.3 ] [2.1 - 8.2 ] [1.6 - 4.9 ] [0.5 - 4.3 ] [2.1 - 8.2 ] [0.1 - 1.9] [0.2 - 3.8 ] [0.0 - 0.0 ] Central Yobe (34) 6.7 % (14) 5.3 % (20) 8.1 % (18) 3.5 % (7) 2.7 % (11) 4.4 % (16) 3.1 % (7) 2.7 % (9) 3.6 % 511 [4.2 - 10.3] [2.7 - 10.1] [5.2 - 12.3] [2.3 - 5.4 ] [1.2 - 5.9 ] [2.8 - 6.9 ] [1.7 - 5.8] [1.2 - 5.9 ] [1.8 - 7.1 ] Southern Yobe (39) 7.4 % (18) 6.8 % (21) 8.0 % (33) 6.2 % (14) 5.3 % (19) 7.2 % (6) 1.1 % (4) 1.5 % (2) 0.8 % 530 [5.4 - 10.0 ] [4.1 - 11.0] [5.5 - 11.5] [4.5 - 8.6 ] [2.9 - 9.5 ] [4.6 - 11.0] [0.5 - 2.7] [0.5 - 4.9 ] [0.2 - 3.0 ] Northern Yobe (52) 10.5 % (21) 8.2 % (31) 13.0 % (40) 8.1 % (17) 6.6 % (23) 9.7 % (12) 2.4 % (4) 1.6 % (8) 3.4 % 495 [7.1 - 15.3 ] [4.6 - 14.2] [8.3 - 19.8] [5.5 - 11.] [3.7 - 11.4] [5.8 - 15.7] [1.3 - 4.6] [0.6 - 4.0 ] [1.7 - 6.5 ]

Table 3.2.4: Prevalence of acute malnutrition by age, based on MUAC cut off's and/or oedema, children 6-59 months, by domain Severe wasting Moderate wasting Normal Age groups (months) Total no. (>= 115 mm and Oedema (< 115 mm) (> = 125 mm) < 125 mm) No. (%) No. (%) No. (%) No. (%) Southern Adamawa 6-17 140 2 (1.4) 10 (7.1) 128 (91.4) 0 (0) 18-29 127 1 (0.8) 7 (5.5) 119 (93.7) 0 (0) 30-41 111 0 (0) 0 (0) 111 (100) 0 (0) 42-53 90 0 (0) 0 (0) 90 (100) 0 (0) 54-59 23 0 (0) 0 (0) 23 (100) 0 (0) Total 491 3 (0.6) 17 (3.5) 471 (95.9) 0 (0) Northern Adamawa 6-17 127 1 (0.8) 5 (3.9) 121 (95.3) 0 (0) 18-29 119 1 (0.8) 5 (4.2) 113 (95) 0 (0) 30-41 116 1 (0.9) 1 (0.9) 114 (98.3) 0 (0) 42-53 102 0 (0) 0 (0) 102 (100) 0 (0) 54-59 27 0 (0) 0 (0) 27 (100) 0 (0) Total 491 3 (0.6) 11 (2.2) 477 (97.1) 0 (0) Southern Borno 6-17 121 3 (2.5) 7 (5.8) 111 (91.7) 0 (0) 18-29 141 4 (2.8) 4 (2.8) 133 (94.3) 0 (0) 30-41 117 0 (0) 0 (0) 117 (100) 0 (0) 42-53 90 0 (0) 2 (2.2) 88 (97.8) 0 (0) 54-59 13 0 (0) 0 (0) 13 (100) 0 (0) Total 482 7 (1.5) 13 (2.7) 462 (95.9) 0 (0) Central Borno 6-17 117 4 (3.4) 10 (8.5) 103 (88) 0 (0) 18-29 121 3 (2.5) 11 (9.1) 107 (88.4) 0 (0) 30-41 121 1 (0.8) 4 (3.3) 116 (95.9) 0 (0) 42-53 77 0 (0) 1 (1.3) 76 (98.7) 0 (0) 54-59 15 0 (0) 0 (0) 15 (100) 0 (0) Total 451 8 (1.8) 26 (5.8) 417 (92.5) 0 (0) MMC / Jere 6-17 105 1 (1) 6 (5.7) 98 (93.3) 0 (0) 18-29 115 1 (0.9) 4 (3.5) 110 (95.7) 0 (0) 30-41 120 0 (0) 1 (0.8) 119 (99.2) 0 (0) 42-53 84 0 (0) 1 (1.2) 83 (98.8) 0 (0) 54-59 6 0 (0) 0 (0) 6 (100) 0 (0) Total 430 2 (0.5) 12 (2.8) 416 (96.7) 0 (0) Northern Yobe 6-17 120 9 (7.5) 20 (16.7) 91 (75.8) 0 (0) 18-29 134 3 (2.2) 12 (9) 119 (88.8) 0 (0) 30-41 126 0 (0) 7 (5.6) 119 (94.4) 0 (0) 42-53 90 0 (0) 1 (1.1) 89 (98.9) 0 (0) 54-59 25 0 (0) 0 (0) 25 (100) 0 (0) Total 495 12 (2.4) 40 (8.1) 443 (89.5) 0 (0) Central Yobe 6-17 134 5 (3.7) 10 (7.5) 119 (88.8) 0 (0) 18-29 121 5 (4.1) 6 (5) 110 (90.9) 0 (0) 30-41 130 6 (4.6) 1 (0.8) 123 (94.6) 0 (0) 42-53 100 0 (0) 1 (1) 99 (99) 0 (0) 54-59 26 0 (0) 0 (0) 26 (100) 0 (0) Total 511 16 (3.1) 18 (3.5) 477 (93.3) 0 (0) Southern Yobe 6-17 164 5 (3) 20 (12.2) 139 (84.8) 0 (0) 18-29 133 1 (0.8) 11 (8.3) 121 (91) 0 (0) 30-41 117 0 (0) 2 (1.7) 115 (98.3) 0 (0) 42-53 103 0 (0) 0 (0) 103 (100) 0 (0) 54-59 13 0 (0) 0 (0) 13 (100) 0 (0) Total 530 6 (1.1) 33 (6.2) 491 (92.6) 0 (0) 25

Underweight

Underweight refers to the proportion of children with low weight-for-age. It can be interpreted as the number of children that are too thin for their age. Tables 3.2.5 presents prevalence of underweight among children 0-59 months by state and domain, disaggregated by sex. Age disaggregation is presented in 3.2.6 for children 6-59 months.

Prevalence of underweight in Yobe (36.1%) and Borno (33.1%) was nearly twice that in Adamawa (17.1%). Correspondingly, prevalence of severe underweight in Yobe (11.9%) and Borno (11.0%) exceed that in Adamawa (3.8%). In all three states, prevalence is higher among boys than girls. By domain, the prevalence of underweight was highest in Central Borno (42.4%).

Table 3.2.5: Prevalence of underweight based on weight-for-age z-scores by sex, children 0-59 months, by state and domain

Prevalence of underweight Prevalence of moderate underweight Prevalence of severe underweight Number of children (<-2 z-score) (<-2 z-score and >=-3 z-score) (<-3 z-score) 0-59 months All Boys Girls All Boys Girls All Boys Girls

State Adamawa (190) 17.1% (106) 18.4% (84) 15.7% (151) 13.3% (82) 14.0% (69) 12.6% (39) 3.8% (24) 4.4% (15) 3.1% 1079 [14.4,20.2] [14.9,22.4] [12.4,19.6] [11.3,15.7] [11.2,17.2] [9.9,15.9] [2.6,5.5] [2.7,7.2] [1.8,5.2] Borno (511) 33.1% (275) 34.9% (236) 31.3% (339) 22.2% (184) 23.5% (155) 20.8% (172) 11.0% (91) 11.4% (81) 10.5% 1481 [30.0,36.4] [30.9,39.1] [27.6,35.3] [19.6,25.0] [20.4,26.9] [17.5,24.6] [9.2,13.0] [9.2,14.1] [8.2,13.4] Yobe (611) 36.1% (323) 37.1% (288) 35.1% (430) 25.2% (224) 25.5% (206) 24.9% (181) 10.9% (99) 11.6% (82) 10.2% 1696 [32.9,39.5] [32.7,41.8] [31.1,39.3] [23.0,27.6] [22.0,29.3] [21.9,28.2] [9.0,13.1] [9.3,14.4] [8.0,12.8] Domain Southern Adamawa (85) 15.7 % (50) 17.1 % (35) 13.9 % (62) 11.4 % (36) 12.3 % (26) 10.4 % (23) 4.2 % (14) 4.8 % (9) 3.6 % 543 [11.8 - 20.5] [12.5 - 22.9] [9.3 - 20.3 ] [8.7 - 14.8] [9.0 - 16.7] [6.9 - 15.2] [2.6 - 6.9] [2.4 - 9.2 ] [1.8 - 7.2] Northern Adamawa (105) 19.6 % (56) 20.7 % (49) 18.5 % (89) 16.6 % (46) 17.0 % (43) 16.2 % (16) 3.0 % (10) 3.7 % (6) 2.3 % 536 [16.5 - 23.2] [15.7 - 26.7] [14.5 - 23.3] [13.6 - 20.1] [12.4 - 22.7] [12.1 - 21.5] [1.8 - 4.9] [1.7 - 7.7 ] [1.1 - 4.7 ] Southern Borno (152) 28.6 % (83) 30.7 % (69) 26.3 % (104) 19.5 % (57) 21.1 % (47) 17.9 % (48) 9.0 % (26) 9.6 % (22) 8.4 % 532 [23.1 - 34.8] [23.3 - 39.3] [20.1 - 33.7] [14.5 - 25.8] [15.5 - 28.1] [12.0 - 26.0] [6.9 - 11.] [6.1 - 14.9] [5.6 - 12.4] Central Borno (211) 42.4 % (115) 43.4 % (96) 41.2 % (135) 27.1 % (75) 28.3 % (60) 25.8 % (76) 15.3 % (40) 15.1 % (36) 15.5 % 498 [34.2 - 51.0] [34.8 - 52.4] [31.0 - 52.2] [21.9 - 33.0] [22.6 - 34.8] [18.1 - 35.3] [11.2 - 20.5] [11.1 - 20.1] [9.7 - 23.8] MCC & Jere (148) 32.8 % (77) 34.4 % (71) 31.3 % (100) 22.2 % (52) 23.2 % (48) 21.1 % (48) 10.6 % (25) 11.2 % (23) 10.1 % 451 [28.4 - 37.6] [28.7 - 40.] [25.9 - 37.] [18.8 - 26.0] [18.6 - 28.5] [16.7 - 26.4] [7.8 - 14.4 ] [7.7 - 15.9] [6.4 - 15.6] Central Yobe (185) 32.7 % (107) 37.2 % (78) 28.1 % (142) 25.1 % (84) 29.2 % (58) 20.9 % (43) 7.6 % (23) 8.0 % (20) 7.2 % 566 [27.9 - 37.9] [31.2 - 43.5] [22.7 - 34.1] [21.4 - 29.1] [24.5 - 34.4] [16.3 - 26.4] [5.0 - 11.4 ] [5.0 - 12.6 ] [4.4 - 11.7 ] Southern Yobe (213) 36.8 % (105) 36.2 % (108) 37.4 % (144) 24.9 % (69) 23.8 % (75) 26.0 % (69) 11.9 % (36) 12.4 % (33) 11.4 % 579 [31.4 - 42.5] [28.3 - 44.9] [30.7 - 44.6] [21.1 - 29.1] [17.6 - 31.3] [21.1 - 31.4] [8.9 - 15.7 ] [8.8 - 17.2 ] [7.8 - 16.4 ] Northern Yobe (213) 38.7 % (111) 38.9 % (102) 38.3 % (144) 26.1 % (71) 24.9 % (73) 27.4 % (69) 12.5 % (40) 14.0 % (29) 10.9 % 551 [32.4 - 45.3] [31.8 - 46.6] [30.5 - 46.9] [22.1 - 30.6] [20.1 - 30.4] [21.4 - 34.5] [9.1 - 17.0 ] [9.5 - 20.2 ] [7.4 - 15.7 ]

Table 3.2.6: Prevalence of underweight by age, based on weight-for-age z- scores, children 6-59 months, by domain

Severe underweight Moderate underweight Normal Oedema Age groups (months) Total no. (<-3 z-score) (>= -3 and <-2 z-score ) (> = -2 z score) No. (%) No. (%) No. (%) No. (%) Southern Adamawa 6-17 136 6 (4.4) 20 (14.7) 110 (80.9) 0 (0) 18-29 126 9 (7.1) 19 (15.1) 98 (77.8) 0 (0) 30-41 111 3 (2.7) 10 (9.0) 98 (88.3) 0 (0) 42-53 90 2 (2.2) 12 (13.3) 76 (84.4) 0 (0) 54-59 23 2 (8.7) 1 (4.3) 20 (87) 0 (0) Total 486 22 (4.5) 62 (12.8) 402 (82.7) 0 (0) Northern Adamawa 6-17 126 5 (4) 20 (15.9) 101 (80.2) 0 (0) 18-29 118 8 (6.8) 29 (24.6) 81 (68.6) 0 (0) 30-41 115 2 (1.7) 22 (19.1) 91 (79.1) 0 (0) 42-53 102 0 (0) 11 (10.8) 91 (89.2) 0 (0) 54-59 27 1 (3.7) 4 (14.8) 22 (81.5) 0 (0) Total 488 16 (3.3) 86 (17.6) 386 (79.1) 0 (0) Southern Borno 6-17 117 12 (10.3) 24 (20.5) 81 (69.2) 0 (0) 18-29 138 19 (13.8) 33 (23.9) 86 (62.3) 0 (0) 30-41 117 6 (5.1) 20 (17.1) 91 (77.8) 0 (0) 42-53 90 8 (8.9) 21 (23.3) 61 (67.8) 0 (0) 54-59 13 1 (7.7) 2 (15.4) 10 (76.9) 0 (0) Total 475 46 (9.7) 100 (21.1) 329 (69.3) 0 (0) Central Borno 6-17 116 22 (19) 28 (24.1) 66 (56.9) 0 (0) 18-29 118 26 (22) 36 (30.5) 56 (47.5) 0 (0) 30-41 117 18 (15.4) 35 (29.9) 64 (54.7) 0 (0) 42-53 77 8 (10.4) 21 (27.3) 48 (62.3) 0 (0) 54-59 15 0 (0) 5 (33.3) 10 (66.7) 0 (0) Total 443 74 (16.7) 125 (28.2) 244 (55.1) 0 (0) MMC / Jere 6-17 105 13 (12.4) 23 (21.9) 69 (65.7) 0 (0) 18-29 114 14 (12.3) 32 (28.1) 68 (59.6) 0 (0) 30-41 120 14 (11.7) 24 (20) 82 (68.3) 0 (0) 42-53 84 7 (8.3) 17 (20.2) 60 (71.4) 0 (0) 54-59 6 0 (0) 2 (33.3) 4 (66.7) 0 (0) Total 429 48 (11.2) 98 (22.8) 283 (66) 0 (0) Northern Yobe 6-17 115 25 (21.7) 33 (28.7) 57 (49.6) 0 (0) 18-29 132 22 (16.7) 45 (34.1) 65 (49.2) 0 (0) 30-41 123 13 (10.6) 27 (22) 83 (67.5) 0 (0) 42-53 90 4 (4.4) 27 (30) 59 (65.6) 0 (0) 54-59 25 2 (8) 5 (20.0) 18 (72.0) 0 (0) Total 485 66 (13.6) 137 (28.2) 282 (58.1) 0 (0) Central Yobe 6-17 130 14 (10.8) 33 (25.4) 83 (63.8) 0 (0) 18-29 121 11 (9.1) 33 (27.3) 77 (63.6) 0 (0) 30-41 127 8 (6.3) 33 (26) 86 (67.7) 0 (0) 42-53 100 4 (4) 30 (30) 66 (66) 0 (0) 54-59 26 2 (7.7) 4 (15.4) 20 (76.9) 0 (0) Total 504 39 (7.7) 133 (26.4) 332 (65.9) 0 (0) Southern Yobe 6-17 160 27 (16.9) 38 (23.8) 95 (59.4) 0 (0) 18-29 131 20 (15.3) 43 (32.8) 68 (51.9) 0 (0) 30-41 117 12 (10.3) 20 (17.1) 85 (72.6) 0 (0) 42-53 103 6 (5.8) 31 (30.1) 66 (64.1) 0 (0) 54-59 13 0 (0) 8 (61.5) 5 (38.5) 0 (0) Total 524 65 (12.4) 140 (26.7) 319 (60.9) 0 (0)

Stunting

Stunting is a measure of chronic malnutrition which occurs as a result of inadequate nutrition over a longer period. Stunting is assessed by length or height-for-age Z-scores (HAZ). Tables 3.2.7 presents prevalence of stunting among children 0-59 months by state and domain, disaggregated by sex. Age disaggregation is presented in 3.2.8 for children 6-59 months.

Prevalence of stunting is higher in Yobe (51.3%) and Borno (47.0%) than in Adamawa (37.7%). Based on WHO classification of malnutrition, prevalence in Yobe and Borno is critical (above 40%) and prevalence in Adamawa is serious (between 30 and 40%). One in five children in Yobe and Borno are severely stunted (22.9% and 20.4%, respectively). Stunting prevalence is higher in boys than girls in all three states. By domain, prevalence was highest in Central Borno (58.6%).

Table 3.2.7: Prevalence of stunting based on height-for-age z-scores and by sex, children 0-59 months, by state and domain

Prevalence of stunting Prevalence of moderate stunting Prevalence of severe stunting Number of (<-2 z-score) (<-2 z-score and >=-3 z-score) (<-3 z-score) children 0-59 All Boys Girls All Boys Girls All Boys Girls months

State Adamawa (388) 37.7% (226) 41.7% (162) 33.2% (249) 24.3% (149) 27.8% (100) 20.5% (139) 13.3% (77) 13.9% (62) 12.6% 1041 [33.3,42.2] [36.6,47.0] [28.3,38.5] [21.4,27.6] [24.0,31.9] [16.7,25.0] [10.7,16.4] [10.7,17.9] [9.6,16.5] Borno (706) 47.0% (391) 51.6% (315) 42.4% (381) 26.6% (207) 28.3% (174) 24.8% (325) 20.4% (184) 23.2% (141) 17.6% 1434 [43.6,50.4] [47.2,55.8] [38.1,46.9] [24.1,29.2] [25.3,31.6] [20.9,29.1] [18.0,23.1] [19.8,27.0] [14.8,20.8] Yobe (854) 51.3% (456) 53.7% (398) 48.8% (470) 28.4% (237) 28% (233) 28.8% (384) 22.9% (219) 25.6% (165) 20.1% 1662 [47.5,55.0] [49.4,57.9] [43.8,53.9] [26.1,30.8] [24.3,32.1] [25.8,32.0] [19.4,26.7] [21.6,30.2] [16.4,24.2] Domain Southern Adamawa (202) 38.8 % (117) 41.9 % (85) 35.1 % (133) 25.5 % (80) 28.7 % (53) 21.9 % (69) 13.2 % (37) 13.3 % (32) 13.2 % 521 [32.5 - 45.4] [34.8 - 49.4] [28.2 - 42.8] [21.2 - 30.] [23.4 - 34.] [16.3 - 28.] [9.8 - 17.] [9.1 - 19.0] [9.1 - 18.] Northern Adamawa (186) 35.8 % (109) 41.3 % (77) 30.1 % (116) 22.3 % (69) 26.1 % (47) 18.4 % (70) 13.5 % (40) 15.2 % (30) 11.7 % 520 [29.9 - 42.1] [34.4 - 48.5] [23.4 - 37.8] [18.8 - 26.2] [21.2 - 31.8] [13.8 - 24.0] [9.7 - 18.4 ] [10.3 - 21.7] [7.4 - 18.0 ] Southern Borno (240) 45.9 % (128) 48.1 % (112) 43.6 % (136) 26.0 % (65) 24.4 % (71) 27.6 % (104) 19.9 % (63) 23.7 % (41) 16.0 % 523 [39.0 - 52.9] [40.1 - 56.2] [35.3 - 52.3] [20.9 - 31.8] [19.5 - 30.2] [19.9 - 37.0] [15.4 - 25] [17.3 - 31.] [11.1 - 22.] Central Borno (282) 58.6 % (159) 63.1 % (123) 53.7 % (129) 26.8 % (77) 30.6 % (52) 22.7 % (153) 31.8 % (82) 32.5 % (71) 31.0 % 481 [50.5 - 66.3] [53.8 - 71.5] [43.3 - 63.8] [22.0 - 32.3] [24.7 - 37.1] [16.4 - 30.6] [25.6 - 38.7] [25.5 - 40.5] [23.7 - 39.] MCC & Jere (184) 42.8 % (104) 49.1 % (80) 36.7 % (116) 27.0 % (65) 30.7 % (51) 23.4 % (68) 15.8 % (39) 18.4 % (29) 13.3 % 430 [38.6 - 47.1] [42.6 - 55.] [30.9 - 43.] [23.9 - 30.3] [25.7 - 36.1] [18.2 - 29.6] [12.6 - 19.7] [13.9 - 24.] [9.6 - 18.1] Central Yobe (280) 50.1 % (152) 53.0 % (128) 47.1 % (161) 28.8 % (78) 27.2 % (83) 30.5 % (119) 21.3 % (74) 25.8 % (45) 16.5 % 559 [44.1 - 56.1] [46.7 - 59.1] [39.1 - 55.2] [24.4 - 33.7] [21.7 - 33.4] [24.5 - 37.3] [16.6 - 26.8] [20.0 - 32.6] [11.6 - 23.0] Southern Yobe (287) 51.2 % (147) 53.1 % (140) 49.3 % (161) 28.7 % (78) 28.2 % (83) 29.2 % (126) 22.5 % (69) 24.9 % (57) 20.1 % 561 [44.8 - 57.5] [45.3 - 60.7] [41.1 - 57.6] [25.0 - 32.7] [21.4 - 36.1] [24.7 - 34.2] [16.8 - 29.4] [17.9 - 33.5] [14.4 - 27.2] Northern Yobe (287) 53.0 % (157) 55.7 % (130) 50.0 % (148) 27.3 % (81) 28.7 % (67) 25.8 % (139) 25.6 % (76) 27.0 % (63) 24.2 % 542 [46.0 - 59.8] [48.7 - 62.4] [40.1 - 59.9] [23.6 - 31.3] [24.6 - 33.2] [20.5 - 31.9] [19.2 - 33.4] [20.3 - 34.8] [16.8 - 33.7]

Table 3.2.8: Prevalence of stunting by age based on height-for-age z-scores, children 6-59 months, by domain

Severe stunting Moderate stunting Normal Age groups (months) Total no. (<-3 z-score) (>= -3 and <-2 z-score ) (> = -2 z score) No. (%) No. (%) No. (%) Southern Adamawa 6-17 132 16 (12.1) 30 (22.7) 86 (65.2) 18-29 121 22 (18.2) 37 (30.6) 62 (51.2) 30-41 107 12 (11.2) 33 (30.8) 62 (57.9) 42-53 86 12 (14.0) 22 (25.6) 52 (60.5) 54-59 23 5 (21.7) 9 (39.1) 9 (39.1) Total 469 67 (14.3) 131 (27.9) 271 (57.8) Northern Adamawa 6-17 121 10 (8.3) 21 (17.4) 90 (74.4) 18-29 114 31 (27.2) 34 (29.8) 49 (43) 30-41 114 19 (16.7) 28 (24.6) 67 (58.8) 42-53 101 6 (5.9) 26 (25.7) 69 (68.3) 54-59 27 2 (7.4) 3 (11.1) 22 (81.5) Total 477 68 (14.3) 112 (23.5) 297 (62.3) Southern Borno 6-17 122 20 (16.4) 19 (15.6) 83 (68.0) 18-29 137 41 (29.9) 42 (30.7) 54 (39.4) 30-41 111 16 (14.4) 40 (36.0) 55 (49.5) 42-53 89 21 (23.6) 24 (27.0) 44 (49.4) 54-59 13 2 (15.4) 4 (30.8) 7 (53.8) Total 472 100 (21.2) 129 (27.3) 243 (51.5) Central Borno 6-17 113 23 (20.4) 34 (30.1) 56 (49.6) 18-29 116 56 (48.3) 31 (26.7) 29 (25) 30-41 111 49 (44.1) 23 (20.7) 39 (35.1) 42-53 75 16 (21.3) 28 (37.3) 31 (41.3) 54-59 15 1 (6.7) 6 (40) 8 (53.3) Total 430 145 (33.7) 122 (28.4) 163 (37.9) MMC / Jere 6-17 100 9 (9) 21 (21) 70 (70) 18-29 108 28 (25.9) 32 (29.6) 48 (44.4) 30-41 117 22 (18.8) 30 (25.6) 65 (55.6) 42-53 82 7 (8.5) 27 (32.9) 48 (58.5) 54-59 5 2 (40) 1 (20) 2 (40) Total 412 68 (16.5) 111 (26.9) 233 (56.6) Central Yobe 6-17 129 24 (18.6) 39 (30.2) 66 (51.2) 18-29 118 35 (29.7) 43 (36.4) 40 (33.9) 30-41 125 37 (29.6) 38 (30.4) 50 (40.0) 42-53 100 15 (15.0) 24 (24.0) 61 (61.0) 54-59 26 4 (15.4) 8 (30.8) 14 (53.8) Total 498 115 (23.1) 152 (30.5) 231 (46.4) Southern Yobe 6-17 159 26 (16.4) 40 (25.2) 93 (58.5) 18-29 128 42 (32.8) 39 (30.5) 47 (36.7) 30-41 110 30 (27.3) 33 (30.0) 47 (42.7) 42-53 101 25 (24.8) 32 (31.7) 44 (43.6) 54-59 13 2 (15.4) 5 (38.5) 6 (46.2) Total 511 125 (24.5) 149 (29.2) 237 (46.4) Northern Yobe 6-17 115 25 (21.7) 29 (25.2) 61 (53) 18-29 130 54 (41.5) 38 (29.2) 38 (29.2) 30-41 120 29 (24.2) 36 (30.0) 55 (45.8) 42-53 89 18 (20.2) 29 (32.6) 42 (47.2) 54-59 25 6 (24.0) 5 (20.0) 14 (56.0) Total 479 132 (27.6) 137 (28.6) 210 (43.8)

Table 3.2.9 present summary statistics for each anthropometric indicator. Mean z-scores for all indicators and for all domains are negative, suggesting that the populations assessed are malnourished relative to the WHO reference population.

Standard deviation can be understood as a measure of heterogeneity of the sample as well as data quality. Standard deviations for WHZ and WAZ z-scores all fall within ±0.8-1.2 (acceptable levels). Standard deviations for HAZ z-scores are on average wider (range 1.18-1.35). Design effects for WHZ z-scores range from are less than 2.0 for all domains, and less than 1.5 for all domains in Borno and South Yobe suggesting relatively low heterogeneity in acute malnutrition.

Z-scores are not available for children that were absent at the time of the visit, children with oedema, and children for whom measurements could not be take (e.g., disability). Z-scores are considered out of range and excluded for analysis if they are more extreme than ±3 SDs from the observed mean of the domain (SMART flags).

Table 3.2.9: Mean z-scores, Design Effects and excluded subjects, by domain Design Effect z-scores Mean z- z-scores not Indicator n out of scores ± SD available (z-score < -2) range Weight-for-Height Southern Adamawa 547 -0.16±1.11 1.56 7 6 Northern Adamawa 530 -0.34±1.08 1.93 16 8 Southern Borno 527 -0.47±1.09 1.00 8 12 Central Borno 499 -0.76±0.99 1.15 10 10 MMC / Jere 446 -0.88±0.99 1.00 37 8 Northern Yobe 547 -0.75±1.13 1.84 1 15 Central Yobe 564 -0.65±1.06 1.70 4 12 Southern Yobe 572 -0.64±1.11 1.00 10 12 Weight-for-Age Southern Adamawa 543 -0.97±1.09 1.83 7 10 Northern Adamawa 530 -0.34±1.08 1.93 16 8 Southern Borno 532 -1.42±1.10 2.15 5 10 Central Borno 498 -1.81±1.14 3.49 8 13 MMC / Jere 451 -1.61±1.06 1.04 36 4 Northern Yobe 551 -1.69±1.09 2.34 0 12 Central Yobe 566 -1.59±1.02 1.53 2 12 Southern Yobe 579 -1.62±1.13 1.85 9 6 Height-for-Age Southern Adamawa 521 -1.60±1.21 2.19 7 32 Northern Adamawa 520 -1.52±1.30 2 15 19 Southern Borno 523 -1.90±1.30 2.45 6 18 Central Borno 481 -2.29±1.35 3.03 9 29 MMC / Jere 430 -1.77±1.20 1 36 25 Northern Yobe 542 -2.09±1.28 2.53 1 20 Central Yobe 559 -2.06±1.18 1.94 4 17 Southern Yobe 561 -2.07±1.24 2.15 8 25

3.3 Mortality results

Crude and under five mortality rates are measures of all-cause mortality occurring during the recall period. Deaths both from conflict as well as natural causes contribute to all-cause mortality. Both crude and under five mortality rates were highest in Central Yobe, 0.63 (0.39-1.01 95% CI) and 2.06 (1.24-3.38 95% CI), respectively. Estimates for under five mortality in Central Yobe should be interpreted with caution given the wide confidence interval and higher standard error. By domain crude mortality rate ranged from 0.26-0.63 total deaths / 10,000 people / day. Under five mortality rate ranged from 0.68 to 2.06 deaths in children under five / 10,000 children under five / day.

Under-five mortality rates exceeded the emergency thresholds of 2 deaths in children under five / 10,000 children under five / day in Central Yobe. The upper confidence intervals for U5MR in Central Borno and Northern Yobe also exceeded 2.0, suggesting it is possible that U5MR exceeds emergency thresholds in these domains as well. Crude mortality rates did not exceed emergency thresholds of 1 deaths/10,000 persons / day.

Table 3.3.1: Mortality rates

Crude mortality rate Under five mortality rate (total deaths /10,000 people / (deaths in children under five / Number of day) 10,000 children under five / day) households Rate [CI] Design Effect Rate [CI] Design Effect

Domain Southern Adamawa 0.43 2.06 1.01 1.32 566 [0.26-0.69 ] [0.55 -1.84 ] Northern Adamawa 0.44 1.35 0.99 1.36 542 [0.30-0.65 ] [0.53-1.82 ] Southern Borno 0.26 1.19 0.97 1.00 593 [0.17-0.41 ] [0.56-1.67 ] Central Borno 0.55 2.17 1.69 1.80 581 [0.35-0.85 ] [0.96-2.91 ] MCC & Jere 0.3 2.58 0.78 1.64 549 [0.16-0.57] [0.34-1.78] Central Yobe 0.63 3.11 2.06 2.06 557 [0.39-1.01] [1.24-3.38] Southern Yobe 0.36 1.40 0.68 1.80 555 [0.24-0.54] [0.29-1.55] Northern Yobe 0.50 1.07 1.90 1.04 593 [0.36-0.68] [1.31-2.72]

3.4 Child Health

Measles Vaccination Coverage

Measles is a highly contagious viral respiratory tract infection known to be an important cause of death among young children particularly in emergency contexts. Symptoms include high fever, coughing and skin rashes and it can be fatal if not treated quickly. About 1 to 5 percent of children with measles die from complications of the disease.[6]

Measles vaccination is one of the immunizations provided as part of the Nigerian Expanded Programme on Immunization (EPI), a program initiated in 1979. A child is considered adequately immunized against measles after receiving only one dose of vaccine (around 9 months of age).

An outbreak of measles was recorded in Borno state in 2016, with nearly 4,000 cases between January and September.[7] Several reactive measles campaigns have been organized by the Borno State Ministry of Health, primarily in camps for internally displaced persons (IDPs) in Borno state.[7] The World Health Organization (WHO) estimated that more than 35,000 children were vaccinated as part of the emergency measles campaigns as of mid-November, primarily in camps in MMC and Jere, Borno.[8]

In this survey, mothers were asked to provide vaccination card and interviewers copied vaccination information from the cards onto the questionnaire. If the child had no vaccination card, the respondent was asked to recall the vaccine given to the child.

Overall, measles vaccination coverage among children 12-59 months as determined by observation of vaccination card or maternal recall was reported to be 59.8%, 55.6% and 36.3% in Adamawa, Borno and Yobe, respectfully (Table 3.3.1, Figure 3.3.1). These represent an increase in coverage in Borno and Yobe relative to the estimates from the 2015 National Nutrition Survey (27.9% and 7.1%, respectively). Coverage in Adamawa remained approximately the same (61.1%). However, coverage in all three states remains well below the National target of 80% coverage.[9]

Vaccination coverage was higher among children 24-59 months than among children 12-23 months in all three states. Coverage was lowest in Northern Yobe (28.8%). In Borno, coverage in MMC & Jere (63.5%) and Southern Borno (57.1%) were nearly twice that of Central Borno (33.7%). These results indicate a need to continue strengthening routine and supplemental immunization activities.

Tables 3.4.1 Percentage of children age 12-59 months vaccinated against measles, by state and domain

Children 12-59 months Children 12-23 months Children 24-59 months Number of Number of Number of Measles Vaccination children age Measles Vaccination children age Measles Vaccination Card children age Vaccine Card Seen 12-59 Vaccine Card Seen 12-59 Vaccine Seen 12-59 months months months

State Adamawa 59.8 22.4 857 57.5 27.1 224 60.6 20.6 633 [50.9,68.0] [16.5,29.5] [47.1,67.3] [18.8,37.5] [51.5,69.0] [14.9,27.9] Borno 55.6 19.1 1205 49.1 22.2 313 57.8 18 892 [47.8,63.1] [14.4,24.8] [40.9,57.4] [16.0,30.0] [49.7,65.5] [13.1,24.2] Yobe 36.3 8.7 1327 34.6 12.4 345 36.9 7.4 982 [28.8,44.5] [5.7,13.2] [25.7,44.6] [7.1,20.7] [29.1,45.5] [5.0,11.0] Domain Southern Adamawa 59.5 23.9 422 57.3 25.6 117 60.3 23.3 305 [47.5,70.4] [16.1,34.0] [43.1,70.3] [15.2,39.8] [48.0,71.4] [15.2,33.9] Northern Adamawa 60.2 19.8 435 57.9 29.9 107 61 16.5 328 [47.6,71.6] [12.4,30.1] [44.3,70.5] [18.4,44.6] [47.9,72.7] [10.0,25.9] Southern Borno 57.1 21.9 420 52.8 24.5 106 58.6 21 314 [41.7,71.3] [13.4,33.7] [36.2,68.8] [13.8,39.7] [42.7,72.9] [12.5,33.2] Central Borno 33.7 9.7 401 26.1 8.7 115 36.7 10.1 286 [22.7,46.7] [4.4,20.2] [17.3,37.3] [4.4,16.5] [24.4,51.0] [3.8,24.3] MCC & Jere 63.5 20.8 384 57.6 27.2 92 65.4 18.8 292 [52.4,73.4] [14.2,29.5] [44.9,69.4] [17.1,40.2] [54.0,75.3] [12.0,28.2] Central Yobe 34.1 10.8 437 34.3 12 108 34 10.3 329 [24.4,45.3] [6.3,17.7] [23.9,46.4] [5.9,22.9] [23.7,46.1] [5.9,17.6] Southern Yobe 41.1 9.1 453 38.7 14.5 124 41.9 7 329 [28.4,55.0] [4.4,17.7] [23.9,56.0] [6.2,30.3] [28.8,56.4] [3.5,13.4] Northern Yobe 28.8 5.7 437 25.7 8 113 29.9 4.9 324 [18.1,42.6] [2.3,13.3] [14.4,41.5] [2.8,20.6] [18.8,44.2] [2.0,11.5]

Figure 3.4.1 Percentage of children age 12-59 months vaccinated against measles, by domain

Diarrhoea, Oral Rehydration Therapy and Zinc Supplementation

After pneumonia, diarrhoea is the second leading cause of death in children worldwide.[10] As risk factors for diarrhoea—consumption of contaminated water and to unhygienic practices in food preparation and disposal of stools—can increase in the context of a humanitarian emergency, prevalence of diarrhoea is often observed to increase.

Humanitarian updates suggest that during the period of the survey diarrhoea, along with suspected malaria and suspected pneumonia, remained a major causes of consultation at primary health centers in the northeast.[11,12] Given concerns about increased risk of diarrhoeal disease, and in particular potential for outbreaks of diarrhoeal diseases such as cholera or Shigella dysentery, humanitarian partners have prepositioned Interagency Diarrhoeal Disease Kits (IDDKs) at the Ministry of Health in Borno. Along with other supplies, kits contain ORS and zinc.[13]

WHO and UNICEF recommend zinc with ORS in the treatment for diarrhoea. [3] Diarrhoea is treated with low-osmolarity oral rehydration salt (ORS) to replenish water and electrolytes lost in loose stools. Zinc deficiency is associated with immune system dysfunctions, growth retardation, and a high risk of morbidities, including diarrhoea. Studies show that supplemental zinc, when combined oral rehydration solutions (ORS), provides therapeutic benefits, reducing the duration and the severity of the diarrhoea episodes.[14]

In this survey, mothers (or caregiver) were asked whether any of their children under age 5 had diarrhoea at any time during the preceding two weeks. If yes, the mother was asked if the child was given ORS and/or Zinc. ORS includes only commercial varieties, not home formulations. As both symptoms of diarrhoea as well treatment are based on maternal recall, the validity of this indicator may be affected by recall biases.

Table 3.3.2 shows the percent of children with symptoms of diarrhoea in the two weeks preceding the survey as well as receipt of ORS and/or zinc among children with diarrhoea symptoms. Two week prevalence of diarrhoea was highest in Yobe (29.2%) followed by Adamawa (25.4%) and Borno (16.9%). These prevalences are higher than those recorded in the 2015 NNHS (17.0%, 13.8%, and 5.0%, respectively) however, these differences may in part be explained by seasonality as data collection for the NNHS occurred in July to September.[3]

By domain, prevalence was highest in Southern Yobe (31.5%) followed by Northern Yobe (30.7%). No other domain had prevalence over 30%. Overall, prevalence was slightly higher among males (24.3%) than females (21.3%). Prevalence was highest among children aged 6-23 years of age; prevalence was 31.5% among children aged 12-23 months and 29.9% among children aged 6-11 months.

Less than 5% of children with symptoms of diarrhoea in Adamawa, Borno, and Yobe received treatment with both ORS and zinc. The proportion of children receiving ORS was higher than the proportion receiving zinc in all three states—Adamawa (25.2% and 7.1%, respectively), Borno (20.3% and 3.7%, respectively) and Yobe (21.2% and 17.1%, respectively). These estimates represent an improvement in clinical management of diarrhoea relative to that observed in the 2015 NNHS with the exception of coverage of zinc in Borno which declined slightly.

By domain the proportion of children of children with symptoms of diarrhoea receiving ORS [range: 13.9% (Central Borno) to 26.1% (MMC & Jere)] was also greater than the proportion receiving zinc [range 1.3% (Southern Borno) to 24.6% (Southern Yobe)] in all domains. 38

The finding that coverage of ORS is higher than that of zinc among children with symptoms of diarrhoea is consistent with findings from previous NNHS surveys and has been attributed to greater knowledge of ORS than zinc supplementation among caregivers.

Coverage or treatment intervention is not strongly correlated with prevalence of diarrhoea symptoms. Comparing Southern and Northern Yobe domains, while prevalence of diarrhoea symptoms is approximately equal (31.5% and 30.7%, respectively), coverage of ORS is 1.8 times higher and coverage of zinc supplementation is 3.3 times higher in Southern Yobe compared to Northern Yobe.

Tables 3.4.2 Percentage of children age 0-59 months with diarrhoea in the previous two weeks who received oral rehydration salts (ORS) or zinc, by sex, age, state and domain

Number of children age 0-59 months with Number of children Had diarrhoea in Number of diarrhoea in the last two weeks: age the last two children age Oral 0-59 months with weeks 0-59 months rehydration Zinc Both diarrhoea in the salts (ORS) last two weeks

Sex Male 24.3 2267 23 11.4 3.9 572 [21.8,27.1] [18.8,27.7] [7.9,16.3] [2.4,6.2] Female 21.3 2147 21.6 6.8 1.7 480 [19.0,23.7] [17.2,26.8] [4.1,11.2] [0.7,4.4] Age in months 0-5 17 474 16.6 4.5 1.3 87 [13.3,21.4] [9.9,26.4] [1.5,12.8] [0.3,5.1] 6-11 29.9 538 29.9 7.8 4.5 167 [26.0,34.1] [22.1,39.1] [4.5,13.2] [2.0,10.0] 12-23 31.5 882 21 10.7 2.3 286 [27.6,35.7] [16.2,26.7] [6.8,16.5] [1.0,5.4] 24-35 23 924 22.5 7.9 2.7 232 [19.6,26.8] [16.7,29.7] [4.8,12.9] [1.3,5.6] 36-47 18.1 942 18.6 12.1 3.9 175 [15.1,21.5] [12.3,27.0] [7.2,19.7] [1.7,8.9] 48-59 16.3 641 24.4 10.4 1.8 105 [12.8,20.4] [15.8,35.7] [5.2,19.7] [0.3,12.0] State Adamawa 25.4 1120 25.2 7.1 2.4 288 [22.2,29.0] [18.6,33.1] [3.7,13.2] [0.9,6.6] Borno 16.9 1557 20.3 3.7 2 266 [13.3,21.2] [14.7,27.5] [2.0,6.7] [0.9,4.4] Yobe 29.2 1737 21.2 17.1 4.3 498 [25.8,32.9] [15.8,27.8] [11.2,25.2] [2.1,8.6] Domain Southern Adamawa 24.6 560 24.6 6.5 1.4 138 [20.3,29.6] [15.4,37.1] [2.6,15.5] [0.2,10.0] Northern Adamawa 26.8 560 26 8 4 150 [22.4,31.7] [19.1,34.3] [3.2,18.7] [1.3,11.8] Southern Borno 14.1 547 15.6 1.3 0 77 [8.9,21.6] [7.6,29.2] [0.2,7.4] 0 Central Borno 19.5 519 13.9 5 4 101 [14.7,25.3] [8.3,22.2] [2.1,11.1] [1.5,10.0] MCC & Jere 17.9 491 26.1 4.5 2.3 88 [12.1,25.7] [16.3,39.2] [1.9,10.7] [0.6,7.7] Central Yobe 23.8 580 15.2 9.4 4.3 138 [18.5,30.1] [9.2,24.1] [4.3,19.2] [1.7,10.8] Southern Yobe 31.5 594 26.7 24.6 5.9 187 [25.9,37.7] [17.9,38.0] [15.0,37.6] [2.3,14.1] Northern Yobe 30.7 563 14.5 7.5 0.6 173 [26.0,36.0] [9.1,22.3] [2.4,21.4] [0.1,4.1] 40

Acute Respiratory Infection (ARI) and Treatment

Acute respiratory infections (ARI) are a heterogeneous and complex group of diseases that constitute the major causes of mortality and morbidity among under-five children in Nigeria, and globally. Most of these deaths are caused by pneumonia and bronchiolitis. According to a study conducted in Nigeria, the overall incidence of ARI is 6-8 episodes during the first 5 years of life.[15] As with diarrhoea, prevalence of ARI varies seasonally. Previous research from Nigeria suggests that the peak of infection corresponded to the rainy season (July-November).[16]

WHO guidelines recommend that all children with fast breathing are classified as having “pneumonia” and treated with oral amoxicillin.[17]

In the survey, the prevalence of ARI has been estimated by asking mothers (or caretakers) whether the child had had cough accompanied by short, rapid breathing in the two weeks prior to the survey. The estimate is based on mothers' perception and not on a diagnosis by a health professional, therefore this finding needs to be interpreted with caution.

Among children under five years of age, the percent with symptoms of acute respiratory infection during the two weeks preceding the survey was highest in Yobe (11.8%), followed by Adamawa (9.1%) and Borno (7.4%). Nearly half of the children in Adamawa (49.7%) and nearly a quarter in Borno and Yobe (25.9% and 26.4%, respectively) were given antibiotics. Antibiotics were reportedly administered more commonly as pills or syrups than injections (not shown).

Prescription of antibiotics varied greatly by domain. Less than one in five children with symptoms of ARI in Northern Yobe (18.0%) and MMC & Jere (18.6%) received antibiotics compared to three in five children in Northern Adamawa (60.4%). These differences do not correspond with major differences in receipt of any medication (including antibiotics as well as paracetamol, aspirin, ibuprofen and other medications). No major differences in two week prevalence or receipt of antibiotics were observed by gender. Antibiotic treatment was least prevalent among children aged 0-5 months (20.8%).

Tables 3.4.3 Percentage of children age 0-59 months with symptoms of acute respiratory infection (ARI) in the previous two weeks who received antibiotics, by sex, age, state and domain

Number of children age 0-59 Number of Had symptoms Number of months with symptoms of ARI in children age 0-59 of ARI in the children age 0-59 the last two weeks: months with last two weeks months symptoms of ARI Any medication Antibiotics

Sex Male 9.4 2260 73.3 34.6 210 [7.9,11.1] [66.0,79.6] [27.6,42.3] Female 8.8 2143 75.1 32.6 192 [7.1,10.8] [67.3,81.5] [25.5,40.7] Age in months 0-5 5.4 474 59.8 20.8 26 [3.6,8.0] [38.1,78.3] [8.3,43.2] 6-11 10.3 538 73.4 36.7 54 [7.7,13.6] [59.9,83.6] [24.6,50.7] 12-23 10.2 882 73.4 37.4 91 [8.0,12.9] [61.4,82.7] [27.2,48.8] 24-35 9.9 924 77.7 33 94 [7.7,12.5] [66.4,86.0] [23.0,44.9] 36-47 9.2 942 80 37.9 85 [7.1,11.9] [67.6,88.5] [25.7,51.8] 48-59 7.8 641 66.8 23.9 52 [5.5,11.0] [53.0,78.2] [14.3,37.3] State Adamawa 9.1 1114 82.2 49.7 102 [6.8,12.0] [73.6,88.4] [39.4,59.9] Borno 7.4 1554 63.8 25.9 114 [5.5,9.9] [54.4,72.2] [17.6,36.3] Yobe 11.8 1735 77 26.4 186 [8.9,15.5] [67.3,84.6] [17.9,37.1] Domain Southern Adamawa 8.8 558 81.6 42.9 49 [5.9,12.9] [69.9,89.5] [31.6,54.9] Northern Adamawa 9.5 556 83 60.4 53 [6.4,14.0] [68.8,91.5] [40.8,77.1] Southern Borno 5.1 545 75 46.4 28 [2.8,9.3] [64.1,83.5] [27.0,67.0] Central Borno 8.3 518 53.5 20.9 43 [5.7,11.9] [36.0,70.2] [9.2,40.9] MCC & Jere 8.8 491 62.8 18.6 43 [5.6,13.4] [48.0,75.5] [9.3,33.9] Central Yobe 7.8 580 66.7 26.7 45 [5.1,11.7] [50.3,79.8] [13.8,45.3] Southern Yobe 15.4 592 80.2 28.6 91 [10.1,22.7] [65.9,89.5] [16.9,44.0] Northern Yobe 8.9 563 76 18 50 [6.2,12.5] [63.4,85.3] [7.8,36.2]

Fever, Prevention of Malaria, and Antimalarial Treatment

Fever is a major manifestation of many acute infections in children, including malaria. Malaria is endemic in Nigeria, with year round transmission. Plasmodium falciparum is the predominant parasite species. Children in Nigeria have an estimated average of 2-4 episodes annually.[18] Malaria is most prevalent after the end of the rainy season (July – November). Previous national surveys found prevalence of fever to be lowest in the North East region.[3]

In 2010 the World Health Organization started recommending universal use of diagnostic testing to confirm malaria infection and apply appropriate treatment based on the results. According to the new guidelines, treatment solely on the basis of clinical suspicion should only be considered when a parasitological diagnosis is not accessible. Children with severe malaria symptoms, such as fever or convulsions, should be taken to a health facility and subjected to diagnostic testing.[18]

In the context of the survey, mothers (or caregivers) were asked whether their children under age 5 had fever in the two weeks before the survey. Fever is measured as a proxy for suspected malaria. If fever was reported, mothers (or caregivers) were asked if a blood sample was taken and whether the child had been given any antimalarial drugs, in particular Artemisinin-based Combination Therapy (ACT). ACT is considered first line treatment in Nigeria; neither chloroquine nor SP are adequate for national first-line use.

The proportion of children under five with reported symptoms of fever is provided in Table 3.3.4 along with measures of clinical management including proportions tested for malaria and receiving anti-malarial drugs. Fever prevalence in the two weeks preceding the survey peaked in the 12-23 age group (42.7%), while it was less common in children below six months of age (13.4%), a pattern consistent with that observed in the 2015 NNHS. Prevalence was highest in Adamawa (42.1%) followed by Yobe (37.2%) and Borno (31.1%). By domain, prevalence ranged from 27.1% (MMC & Jere) to 43.7% (Southern Adamawa). No significant differences were observed by sex.

Despite WHO recommendations, less than 10 percent of children with fever in the last two weeks were tested for malaria—6.2% in Adamawa, 5.1% in Borno, and 5.4% in Yobe. In all domains with the exception of Northern Adamawa, less than 6% of children with symptoms of fever in the preceding two weeks received malaria diagnostic tests.

Among all children with symptoms of fever, receipt of antimalarial medications was highest in Adamawa (56.3%) followed by Yobe (39.1%) and Borno (32.7%). However, less than half of all children receiving antimalarial treatment received ACTs, first-line treatment for malaria in Nigeria. Receipt of ACT in Adamawa (24.0%) was nearly double that of Yobe (12.2%) and Borno (9.1%). Receipt of ACT was significantly associated with reported testing in Adamawa and Yobe (p<0.01) but not Borno (p=0.40). The proportion of children receiving ACTs varied by domain ranging from 5.4% in Central Yobe to 28.4% in Northern Adamawa. Table 3.3.1 also provides the proportion of children receiving any antimalarial medication including SP/Fansidar, Chloroquine, Amodiaquine, Quinine, ACT, or any other anti-malarial.

The use of antimalarial treatment (included ACT) generally increased with age, from 28.9% among children less than 6 months of age to over 50 percent for children above 4 years of age, while antibiotic treatment is quite stable at around 15% for all age cohorts (range: 12.5-18.7%). No significant difference was noted between boys and girls receiving appropriate antimalarial drugs.

These data suggest that despite national programs, proper clinical management of malaria with first line treatment remains below the national target (80%) as specified in the National Malaria Strategic Plan.[18] However, the data suggest improved coverage of ACTs in Borno and Yobe relative to data from the 2015 NNHS which reported that no children with fever were given ACTs.

Tables 3.4.4 Percentage of children age 0-59 months with fever in the last two weeks who were tested for malaria and/or received anti-malarial drug or antibiotics, by sex, age, state and domain

Number of Number of children age 0-59 months with fever in the last No. of children children age two weeks who: Had fever in age 0-59 Had blood the last two Were given months with taken from a Were given Were given weeks 0-59 months anti- fever in the last finger or heel ACT antibiotics malarials two weeks for testing

Sex Male 36.7 2260 5.7 42.5 15.9 15.6 840 [34.1,39.5] [4.0,8.0] [37.2,47.9] [12.8,19.6] [12.6,19.1] Female 35.6 2143 5.5 44 15.1 15 754 [32.5,38.8] [4.0,7.6] [38.9,49.4] [11.7,19.2] [12.2,18.4] Age in months 0-5 13.4 474 5 28.9 7.1 12.5 65 [10.3,17.4] [1.4,16.3] [17.6,43.5] [2.6,17.9] [6.0,24.4] 6-11 37.6 538 4.6 35.1 11.1 18.7 197 [32.7,42.8] [2.4,8.5] [27.5,43.6] [7.0,17.0] [13.2,25.8] 12-23 42.7 882 4.4 44.7 17.6 15.9 370 [38.3,47.3] [2.7,7.3] [38.3,51.3] [13.5,22.6] [12.2,20.4] 24-35 39.6 924 4.9 42.4 14.7 14.3 363 [35.9,43.4] [2.7,8.5] [35.6,49.5] [10.6,20.1] [10.5,19.1] 36-47 36.2 942 7.2 44.5 16.5 15 352 [32.3,40.3] [4.7,11.0] [37.9,51.3] [12.7,21.2] [11.2,19.6] 48-59 37.5 641 6.9 51.5 18.1 13.9 246 [33.2,41.9] [4.2,11.1] [43.2,59.7] [13.2,24.2] [9.4,20.1] State Adamawa 42.1 1114 6.2 56.3 24 21.7 462 [37.3,47.0] [4.2,9.2] [48.9,63.5] [19.2,29.7] [17.2,27.2] Borno 31.1 1554 5.1 32.7 9.1 9.8 494 [26.9,35.5] [3.0,8.6] [24.8,41.8] [5.4,15.0] [6.8,13.9] Yobe 37.2 1735 5.4 39.1 12.2 13.7 638 [33.7,40.8] [3.7,7.9] [33.0,45.6] [8.7,16.8] [10.6,17.5] Domain Southern Adamawa 43.7 558 4.9 55.3 21.7 16.8 244 [37.2,50.5] [2.4,9.6] [45.4,64.8] [16.6,27.9] [11.9,23.2] Northern Adamawa 39.2 556 8.7 58.3 28.4 31.2 218 [33.1,45.7] [6.1,12.3] [47.6,68.2] [18.7,40.7] [23.0,40.8] Southern Borno 35.6 545 5.2 37.6 10.8 7.7 194 [26.9,45.4] [2.1,12.2] [24.5,52.8] [4.3,24.7] [4.1,14.0] Central Borno 32.2 518 4.8 31.1 12 9.6 167 [26.1,39.0] [1.9,11.4] [20.5,44.3] [5.6,23.9] [4.8,18.1] MCC & Jere 27.1 491 5.3 28.6 6 12 133 [22.0,32.8] [2.3,11.8] [16.3,45.2] [2.7,12.8] [6.9,20.2] Central Yobe 35.2 580 5.4 33.3 5.4 16.7 204 [29.0,41.8] [2.5,11.2] [25.4,42.3] [2.6,10.8] [11.2,24.1] Southern Yobe 38.5 592 5.7 43.4 17.5 11.4 228 [33.1,44.2] [3.4,9.5] [33.6,53.8] [11.5,25.9] [7.2,17.5] Northern Yobe 36.6 563 4.9 35.9 7.8 15.5 206 [30.3,43.4] [2.2,10.6] [25.2,48.2] [4.0,14.6] [9.8,23.7]

Use of mosquito nets, particularly insecticide- treated bed nets, is an important preventive measure to reduce incidence of malaria.

In order to achieve universal coverage in 2009, Nigeria started the National Malaria Control Strategic Plan (NMCSP) which include a coordinated strategy to deliver two nets to every household across the country. Seasonal malaria chemoprevention (SMC) is recommended by WHO for children during the malaria season in areas of highly seasonal transmission.

The following two tables provide data related to prevention of malaria. During the survey, respondents were asked whether they possess any type of mosquito net in their household and, if so, how many. These data are presented in Table 3.3.5. For households with children, caregivers were asked whether each child aged 0-59 months had received any pills or syrup to prevent malaria and whether they had slept under a bednet during the night proceeding the survey. These data are presented in Table 3.3.6.

The results indicate that more than 70 percent of households in Borno (74.0%) and Yobe (70.5%) and nearly 60 percent in Adamawa (57.7%) possess at least one mosquito net. However, less than a third of households have the recommended number of bednets, one net per two persons—32.0% in Borno, 27.7% in Yobe, and 22.5% in Adamawa. Among children residing in households with bednets, only three in four slept under a bednet during the night proceeding the survey—75.4% in Borno, 75.2% in Yobe, and 70.5% in Adamawa. Utilization did not vary notably by age cohort (range: 72.8-75.9%). No significant difference in utilization of bednets was observed by gender. When compared with statistics from the 2015 NNHS, these data suggest improvements in the proportion of households with bednets as well as the the proportion of children under five sleeping under the nets last night. In Borno the proporiton of children sleeping under nets during the night before the survey nearly doubled from 32.5% in 2015 to 59.9%. However, there remains a need for both improved coverage of bednets as well as education on utilization given evidence of households where bednets are not currently in use by children.

All children aged 0-59 months were asked whether they received seasonal malaria chemoprevention for malaria. In Nigeria, SMC/IPT is generally taken for three days at the beginning of the month. Coverage of SMC was highest in Adamawa (14.6%) followed by Yobe (9.1%) and Borno (6.0%). By domain, coverage ranged from 16.9% (Northern Adamawa) to 4.2% (Southern Borno). Coverage was slightly higher among children aged 48-59 months (12.0%, range: 8.0-12.0%). No significant differences in SMC coverage were observed by gender.

Tables 3.4.5 Households ownership of mosquito nets, by state and domain

Percent of households with at least: Number of households One Mosquito One Mosquito Net Net per Two Persons

State

Adamawa 57.7 22.5 1105 [51.6,63.6] [19.2,26.3] Borno 74.0 32.0 1719 [69.2,78.3] [28.1,36.1] Yobe 70.5 27.7 1667 [63.9,76.4] [24.0,31.8] Domain

Southern Adamawa 56.6 22.8 565 [48.3,64.6] [18.5,27.8] Northern Adamawa 59.6 22.0 540 [51.5,67.2] [17.1,28.0] Southern Borno 75.6 29.9 589 [67.1,82.4] [23.1,37.7] Central Borno 59.2 25.5 581 [49.1,68.6] [18.9,33.4] MCC & Jere 79.1 36.2 549 [71.4,85.1] [30.4,42.5] Central Yobe 77.0 33.9 551 [65.5,85.4] [26.4,42.4] Southern Yobe 66.8 24.2 549 [55.7,76.4] [18.8,30.6] Northern Yobe 70.7 27.7 567

[59.4,80.0] [21.6,34.7]

Tables 3.4.6 Percentage of children age 0-59 months receiving seasonal malaria chemoprevention and percent who slept under a mosquito net the night before the survey, by sex, age, state and domain

Number of children age 0-59 Received Seasonal months who slept under a Number of Malaria bednet last night: children age 0-59 Chemoprevention Among children months (SMC) Among all in home with at children least on bednet

Sex Male 9.5 54.4 74.2 2260 [7.5,12.1] [49.9,58.9] [70.0,78.1] Female 9.6 54.7 73.7 2142 [7.5,12.2] [50.5,58.9] [69.7,77.4] Age in months 0-5 8 54.4 75 474 [5.4,11.5] [48.0,60.7] [68.3,80.7] 6-11 7.8 57.5 75.8 538 [5.1,11.7] [51.0,63.7] [69.5,81.2] 12-23 9.9 52.7 73.4 882 [7.2,13.5] [47.7,57.7] [68.2,78.0] 24-35 8.8 52.7 73 924 [6.6,11.6] [47.4,58.0] [68.0,77.5] 36-47 10.2 53.6 72.8 942 [7.6,13.7] [48.6,58.5] [67.6,77.4] 48-59 12 59.2 75.9 641 [8.8,16.2] [53.7,64.4] [70.3,80.7] State Adamawa 14.6 45.4 70.5 1114 [10.6,19.7] [38.2,52.8] [63.6,76.5] Borno 6 59.9 75.4 1553 [4.0,8.9] [53.6,65.8] [69.7,80.3] Yobe 9.1 57.4 75.2 1735 [5.6,14.4] [49.8,64.7] [67.9,81.3] Domain Southern Adamawa 13.3 45.3 70.5 558 [8.5,20.1] [35.9,55.1] [61.3,78.3] Northern Adamawa 16.9 45.5 70.4 556 [10.7,25.6] [34.9,56.5] [59.7,79.2] Southern Borno 4.2 56.8 71.4 544 [2.2,7.9] [44.8,68.0] [59.2,81.1] Central Borno 4.6 40.3 61 518 [2.2,9.6] [29.1,52.7] [47.3,73.1] MCC & Jere 7.9 70.5 83 491 [4.4,14.0] [61.6,78.0] [76.4,88.0] Central Yobe 4.3 69.3 84.5 580 [2.1,8.8] [56.0,80.0] [74.9,90.9] Southern Yobe 13.5 51.2 69.9 592 [7.2,24.1] [38.9,63.3] [56.1,80.8] Northern Yobe 5.3 56.7 74 563 [2.6,10.5] [44.3,68.3] [63.7,82.3] 48

3.5 Infant and Young Child Feeding

Breast milk provides all the nutrients, vitamins and minerals an infant needs for growth during their first six month of life. Breastfeeding also protects children from infection. As a result, early and exclusive breastfeeding are among the most economical and safe public health interventions. However, many mothers stop breastfeeding early. This is particularly true in the context of an emergency where factors such as stress, displacement and distributions of infant formula may contribute to early interruption. Emergency interventions in North East Nigeria have therefore included counselling on Infant and Young Child Feeding (IYCF) aimed at encouraging proper breastfeeding and complementary feeding practices.

UNICEF recommends early initiation of breastfeeding whereby a child is put to breast within one hour of birth. Exclusive breastfeeding is recommended for the first six months of life. Continued breastfeeding is recommended for two years or more.

In the context of the survey, mothers (or caregivers) were asked whether their children aged 0-23 months had ever been breastfed. For all children who had ever been breastfed, mothers (or caregivers) were asked how long after birth did they first put the child to breast and whether the child was breastfed on the day preceding the survey during the day or night. Indicators for continued breastfeeding at one and two years of age are derived from the question regarding breastfeeding during the day proceeding the survey, asked to all mothers or caregivers of children 0-23 months. Sample sizes for continued breastfeeding within each domain are small and therefore the confidence intervals around these estimates are wide.

Overall the proportion of children aged 0-23 months who were ever breastfed was over 90% in all three states. By domain, the proportion ever breastfed ranged from 93.1-98.0%. However, only half (46.7%) of children in Borno and just over one in five children in Adamawa (24.1%) and Yobe (20.7%) were put to breast within one hour of birth. While more than 9 in 10 children continued breastfeeding at one year of age, the proportion declined after a year. The percent of children who continued breastfeeding at two years (age 20-23 months) was lowest in Adamawa (31.1%) but less than half in all three states. No significant differences in breastfeeding practices were documented by sex.

Tables 3.5.1 Percentage of children who ever breastfed, initiated breastfeeding within an hour, continued breastfeeding at one year of age, and continued breastfeeding at two years of age, by sex, age, state and domain

Among children ever breastfed:

Children Number Percent of Children who Percent of children ever of children who continued who continued breastfed children initiated breastfeeding at one breastfeeding at two (0-23 age 0-23 breastfeeding year years months) months within an hour (12-15 months) (20-23 months) (0-23 months) % [CI] N % [CI] N

Sex Male 95.8 961 31.1 95.7 174 36.0 101 [94.1,97.0] [26.4,36.1] [91.5,97.9] [26.4,46.8]

Female 95.4 933 33.5 92.2 170 36.2 109 [92.9,97.0] [28.6,38.8] [86.5,95.6] [26.0,47.8]

Age in months

0-5 97.5 474 38.1 — —

[95.2,98.7] [32.2,44.5]

6-11 98.3 538 30.1 — —

[96.8,99.1] [24.5,36.4]

12-23 92.9 882 30.4 — —

[90.0,95.0] [25.6,35.6]

State

Adamawa 96.2 481 24.1 95.4 80 31.1 55 [93.3,97.9] [17.8,31.9] [89.9,98.0] [20.1,44.7]

Borno 93.8 660 46.7 90.4 121 40.9 70 [90.9,95.9] [38.3,55.3] [81.9,95.1] [28.2,54.9]

Yobe 97.6 753 20.7 97.6 143 35.2 85 [95.4,98.7] [15.9,26.4] [92.4,99.3] [26.2,45.5]

Domain

S. Adamawa 96.0 253 19.3 100 41 37.5 24 [91.4,98.2] [12.5,28.7] [20.2,58.7]

N. Adamawa 96.5 228 33.2 87.2 39 22.6 31 [93.5,98.1] [21.8,46.9] [73.1,94.5] [12.4,37.5]

Southern Borno 94.8 229 50.7 97.6 42 31.6 19 [90.4,97.2] [36.3,65.0] [85.7,99.6] [17.2,50.7]

Central Borno 93.1 232 24.5 89.4 47 46.4 28 [86.9,96.5] [14.8,37.9] [71.7,96.5] [24.7,69.6]

MCC & Jere 93.5 199 53.8 84.4 32 43.5 23 [87.4,96.7] [39.4,67.6] [66.7,93.6] [22.8,66.7]

Central Yobe 98.0 251 23.6 100 39 42.4 33 [93.0,99.5] [15.5,34.2] [29.9,55.9]

Southern Yobe 97.3 263 16.4 96.6 59 33.3 21 [93.0,99.0] [10.1,25.6] [87.1,99.2] [17.3,54.4]

Northern Yobe 97.5 239 26.6 97.8 45 29.0 31 [94.9,98.8] [17.9,37.6] [86.9,99.7] [16.7,45.5]

3.6 Public Health Campaigns, Maternal, Newborn, and Child Health Week (MNCHW)

The Maternal Newborn and Child Health Week (MNCHW) Programme was launched in Nigeria in 2009 as part of the strategy of the Federal Ministry of Health (FMOH) of Nigeria to accelerate the achievement of the health Millennium Development Goals. The MNCHW has been regularly implemented in Nigeria since 2010 as a bi-annual campaign-style programme. During the week, primary healthcare services are offered in health facilities, from house to house, and at community health posts. The maternal and child health services offered include routine and emergency antenatal, intrapartum and postnatal care; routine and emergency obstetric and newborn care; infant and young child nutrition and supplementation; routine immunizations, malaria prevention and distribution of mosquito nets, PMTCT programmes and care of HIV exposed or infected children, health and Water, Sanitation and Hygiene (WASH) education and effective primary health care service and management of common childhood illnesses.[19] MNCHW campaigns have continued in the North East since the emergency declaration. The most recent MNHCW campaign prior to the survey occurred in May 2016.

Less than one in six households lived in an areas where MNCHW campaign activities were available—15.3% in Yobe, 11.5% in Adamawa and 11.0% in Borno. And of them, only a fraction received any health services during the campaign. Effective coverage of MNHCW interventions was less than 9 percent of households in all three domains. By domain, the percent of households receiving some services during a MNCHW campaign was highest in Southern Borno (11.9%) and lowest in Northern Adamawa (4.3%).

Of those receiving services through the MNCHW campaigns, the location where services were received varied considerably by domain. In Southern Adamawa, Southern Yobe and Northern Yobe, health facilities were the primary location where services were received. In Northern Adamawa services were primarily received at beneficiaries’ homes. Whereas in all Borno domains and Central Yobe, services were primarily received at another site such as a mobile health post.

These data suggest that MNCHW campaigns have relatively low geographic coverage in the North East. As such, for priority interventions for which the sector aims to achieve near universal coverage, such as vaccinations, Vitamin A and deworming medications, multiple methods of distribution will likely be necessary.

Tables 3.6.1. MNCHW coverage and location of service provision, by state and domain

Percentage Percentage Households who received some Number of of HHs of HHs who services during a MNCHW campaign, households who lived received location: receiving in an area some Number some where services of HHs At their services At a health At another there was during a own during a facility site a MNCHW MNCHW house MNCHW campaign campaign campaign

State

Adamawa 11.5 6.7 1105 62.7 16.8 20.5 69 [6.6,19.4] [3.6,12.2] [29.0,87.3] [2.2,64.3] [5.4,54.0] Borno 11.0 9.4 1719 10.0 87.4 2.7 156 [7.1,16.7] [5.9,14.6] [3.6,24.6] [72.2,94.8] [0.6,12.0] Yobe 15.3 7.0 1667 63.1 33.0 3.2 113 [10.2,22.3] [4.4,11.0] [44.1,78.7] [17.9,52.6] [1.0,9.6] Domain S. Adamawa 13.6 8.1 565 69.6 21.7 8.7 46 [6.8,25.3] [4.0,16.0] [28.6,92.9] [2.9,72.3] [1.8,33.3] N. Adamawa 7.8 4.3 540 39.1 0 60.9 23 [3.2,17.7] [1.3,13.3] [5.1,88.4] [11.6,94.9] S. Borno 14.4 11.9 589 14.3 85.7 0 70 [7.2,26.9] [5.7,23.1] [3.0,47.2] [52.8,97.0] Central Borno 6.5 6.5 581 7.9 92.1 0 38 [3.0,13.6] [3.0,13.6] [1.9,27.1] [72.9,98.1] MCC & Jere 10.4 8.7 549 6.3 87.5 6.3 48 [5.1,19.9] [4.1,17.8] [1.7,20.0] [66.0,96.2] [1.0,29.6] Central Yobe 15.6 7.3 551 20.0 75.0 2.5 40 [7.0,31.3] [3.3,15.3] [2.8,68.3] [30.7,95.3] [0.3,20.2] S. Yobe 17.7 7.7 549 83.3 11.9 4.8 42 [10.0,29.3] [3.8,14.9] [63.6,93.5] [4.4,28.3] [1.3,16.3] N. Yobe 10.2 5.5 567 71.0 29.0 0 31

[4.2,22.7] [2.2,12.9] [24.1,95.0] [5.0,75.9]

Deworming

Helminths are a group of parasites including schistosomiases and soil-transmitted helminths. They can impair nutritional status by causing internal bleeding which can lead to loss of iron and anaemia; malabsorption of nutrients; diarrhoea and loss of appetite. The nutritional impairment caused by schistosome and soil-transmitted helminth infections during childhood has been shown to have a significant impact on growth and development of children. Periodic deworming of children can reduce the transmission of schistosome and soil-transmitted helminth infections.

UNICEF recommends a minimum coverage threshold of 70 percent at which countries can expect to observe reductions in child mortality from this intervention. Deworming medications are 52 distributed as part of the MNHCW campaigns as well as part of routine health care at facilities.

In the context of the survey, mothers (or caregivers) were asked whether their children aged 12- 59 months had received any deworming medication in the six months preceding the survey. A child was recorded as having received treatment if the caregiver reported receipt of anthelminthic drug. No distinction was made between receipt of anthelminthic drugs as part of the MNHCW campaign and other distribution methods.

Overall coverage was reported to be well below the recommended threshold – 13.1% in Adamawa, 3.8% in Borno, and 5.0% in Yobe. Coverage gradually increased with age, highest among children aged 48-59 months (9.3%) and lowest among children aged 12-23 months (5.4%). Coverage was slightly higher among boys (7.7%) than girls (6.4%).

Tables 3.6.2. Percentage of children age 12-59 months given an anthelminthic drug in the past 6 months, by sex, age, state and domain

Children age 12-59 months given an anthelminthic drug % [CI] N

Sex Male 7.7 1744 [5.8,10.3] Female 6.4 1645 [4.7,8.8] Age in months 12-23 5.4 882 [3.5,8.2] 24-35 6.2 924 [4.5,8.7] 36-47 8.1 942 [5.6,11.5] 48-59 9.3 641 [6.7,12.6] State Adamawa 13.1 857 [8.8,19.1] Borno 3.8 1205 [2.3,6.3] Yobe 5.0 1327 [3.0,8.4] Domain Southern Adamawa 13.3 422 [7.8,21.6] Northern Adamawa 12.9 435 [7.0,22.5] Southern Borno 2.9 420 [1.2,6.9] Central Borno 3.5 401 [1.2,9.6] MCC & Jere 4.7 384 [2.3,9.4] Central Yobe 4.8 437 [1.6,13.4] Southern Yobe 4.6 453 [2.2,9.6] Northern Yobe 6.2 437 [2.3,15.5]

Fortified Blended Foods

Fortified blended foods (FBFs) are partially precooked and milled cereals, soya, beans, pulses fortified with micronutrients (vitamins and minerals). Corn Soya Blend (CSB) is the main blended food distributed by World Food Program (WFP). CSB is commonly used in the context of an emergency, distributed to providing adequate energy and micronutrients.

During the months preceding the survey WFP and partners worked to increase the number of people receiving food assistance, nearly doubling the number of beneficiaries between March and August.[20] There have also been efforts to shift the strategy for food assistance from cash based interventions to in-kind distributions. Distributions of food assistance were ongoing in targeted locations in Borno and Yobe states during the time of the assessment.[21]

In the survey, respondents were shown example packaging of CSB distributed in Nigeria and asked whether they had received any of the product in the three months preceding the survey. Results from the survey suggest that coverage was less than 3% in all three states. By domain, coverage ranged from 0.2% (Southern Borno) to 5.3% (Central Yobe) of households.

Tables 3.6.3. Percentage of households receiving corn soy blend (CSB) in the last three months, by state and domain

Households who received CSB % [CI] N

State

Adamawa 1.9 1105 [1.0,3.7] Borno 1.1 1719 [0.4,2.7] Yobe 2.5 1667 [1.2,5.1] Domain Southern Adamawa 1.8 565 [0.6,4.7] Northern Adamawa 2.2 540 [1.0,4.8] Southern Borno 0.2 589 [0.0,1.2] Central Borno 1.7 581 [0.4,6.8] MCC & Jere 1.5 549 [0.4,5.1] Central Yobe 5.3 551 [1.7,15.2] Southern Yobe 0.9 549 [0.3,2.8] Northern Yobe 2.5 567

[0.8,7.1]

3.7 Women’s Nutrition

Malnutrition among women has important implications for both her health and that of her children. Malnourished women experience increased susceptibility to infections, slow recovery from illness, and a heightened risk of adverse pregnancy outcomes.

In this survey, the nutritional status of women was assessed using MUAC. Commonly used as an indicator of child malnutrition and wasting, the MUAC can be used as an indicator of maternal nutritional status because of its high correlation with maternal weight and body mass index. As increases of MUAC during pregnancy are generally less than 0.5 cm, MUAC can also be used to define under nutrition in pregnant women.

In this survey, nutritional status was assessed among all women of reproductive age (15-49 years). Women with MUAC < 221 mm were classified as acutely malnourished, while women whose MUAC was between 214 and 221 mm were classified as moderately malnourished and women whose MUAC fell below 214 mm were classified as severely malnourished.

Prevalence of severe malnutrition (MUAC < 214 mm) was highest among women of reproductive age in Yobe (9.6%) followed by Borno (4.9%) and Adamawa (3.3%). Prevalence of malnutrition (MUAC ≤ 221 mm) was also highest in Yobe. These estimates suggest a similar pattern to that observed in the 2015 NNHS. By domain, prevalence of malnutrition was highest in Northern and Central Yobe.

In addition, the prevalence of acute malnutrition was reported more than three times higher for teenagers (15 to 19 years) than adult women (20 to 49 years), 21.8 percent compared to 7.1 percent.

Tables 3.7.1. Acute malnutrition among women of reproductive age (15-49 years), by age, state and domain

MUAC in millimeters Number of women age 15-49

≤ 221 mm < 214 mm years

Age Group

15-19 years 21.8 12.6 1029 [18.8,25.1] [10.3,15.5] 20-49 years 7.1 3.7 3971 [6.1,8.2] [3.0,4.5] State Adamawa 7.0 3.3 1321 [5.3,9.2] [2.2,4.8] Borno 9.2 4.9 1828 [7.5,11.3] [3.6,6.5] Yobe 15.7 9.6 1851 [13.6,18.1] [7.8,11.8] Domain Southern Adamawa 6.9 3.2 678 [4.7,10.1] [1.9,5.5] Northern Adamawa 7.2 3.3 643 [4.9,10.3] [2.0,5.3] Southern Borno 6.2 3.3 665 [4.1,9.1] [2.1,5.3] Central Borno 10.9 4.2 542 [8.0,14.6] [2.7,6.6] MCC & Jere 11.0 6.3 621 [8.0,14.8] [4.1,9.5] Central Yobe 17.2 11.2 617 [13.3,21.9] [8.0,15.4] Southern Yobe 13.9 8.9 655 [10.8,17.8] [6.1,12.7] Northern Yobe 18.0 9.5 579

[14.8,21.7] [7.2,12.4]

Figure 3.7.1. Acute malnutrition among women of reproductive age (15-49 years), by domain

Dietary Diversity

In the context of an emergency, diets can be dominated by one or a few staple foods given constraints on food choices. Poor dietary diversity has been shown to be associated with poor micronutrient adequacy of diets.[22] In the survey, dietary diversity was measured to assess micronutrient adequacy among women of reproductive age. This group is often nutritionally vulnerable because of the physiological demands of pregnancy and lactation.

In the survey, one randomly selected women of reproductive age (15-49 years) was selected from each household containing at least one eligible women. Selection was done automatically on the tablets and sample weights were adjusted accordingly. Questions were asked consistent with the formulation recommended in the 2016 guidance document from the Food and Agriculture Organization (FAO), Minimum Dietary Diversity for Women: A Guide to Measurement.[23] The indicator can be understood as a measure of whether women are receiving adequate amounts of the following vitamins and minerals: thiamin, riboflavin, niacin, Vitamin B6, folate, Vitamin B12, Vitamin A, Vitamin C, calcium, iron, and zinc.

The questionnaire asks women about consumption of different food groups during the day prior to the survey. Food are then re-categorized into ten food groups: (1) grains, white roots and tubers, plantains, (2) pulses, (3) nuts and seeds, (4) dairy, (5) meat, poultry and fish, (6) eggs, (7) dark green leafy vegetables, (8) other vitamin A-rich fruits, (9) other vegetables, and (10) other fruits. The Minimum Dietary Diversity in Women (MDD-Women) indicator is a dichotomous indicator of whether or not a women has consumed at least five out of the ten defined food groups.[23] The MDD-W was developed as a proxy indicator to reflect the micronutrient adequacy of women’s diets, a contrast to the household dietary diversity (HDDS) indicator which is a proxy for household-level access to kilocalories (dietary energy).

The proportion of women of reproductive age meeting minimum dietary diversity was highest in Adamawa (50.1%) followed by Yobe (43.3%) and Borno (42.1%). Of the ten food groups assessed, the mean number consumed during the day proceeding the survey by women of reproductive age was less than 5 in all three states—4.5 in Adamawa, 4.4 in Yobe, and 4.2 in Borno. The proportion of women of reproductive age consuming iron rich foods was lowest in Yobe (44.3%). The proportion consuming Vitamin A rich foods was lowest in Borno (65.0%). 58

By domain, the proportion of women meeting minimum dietary diversity, the proportions consuming iron rich food, and the proportion consuming Vitamin A rich foods were all lowest in Central Borno (31.4%, 28.2% and 56.5%, respectively). For all domains, the proportion of women consuming Vitamin A rich foods during the day preceding the survey was higher than the proportion consuming iron rich foods.

The proportion of women meeting minimum dietary diversity, consuming iron rich foods, and consuming Vitamin A rich foods were all slightly higher among teenagers (aged 15-19 years) than adult women (20-49 years). This is a contrast to the pattern of acute malnutrition as measured by MUAC.

Tables 3.7.2. Dietary diversity among women of reproductive age (15-49 years), by age, state and domain

Percentage of women 15-49 years: Mean Meeting number of Minimum Number of Consuming Consuming food groups Dietary Diversity women age iron rich foods Vitamin A rich consumed for Women of 15-49 years yesterday foods yesterday yesterday (of Reproductive 10) Age (MDD-W)*

Age Group

15-19 years 49.4 52.6 72.2 4.4 645 [42.9,56.0] [46.7,58.5] [66.6,77.2] [4.2,4.7] 20-49 years 43.9 50.6 68.4 4.3 3090 [40.3,47.5] [46.9,54.4] [64.6,71.9] [4.2,4.5] State Adamawa 50.1 60.0 71.1 4.5 932 [43.5,56.7] [53.6,66.0] [65.0,76.5] [4.3,4.8] Borno 42.1 48.0 65.0 4.2 1401 [36.3,48.1] [42.4,53.6] [59.1,70.5] [4,4.4] Yobe 43.3 44.3 73.8 4.4 1402 [36.8,50.0] [37.5,51.4] [67.1,79.6] [4.2,4.6] Domain Southern Adamawa 50.4 62.7 71.4 4.6 481 [41.4,59.4] [54.5,70.2] [62.8,78.7] [4.2,5.0] Northern Adamawa 49.5 55.1 70.6 4.5 451 [41.0,58.0] [45.2,64.5] [62.8,77.4] [4.2,4.8] Southern Borno 51.6 47.7 64.8 4.5 495 [41.4,61.6] [38.9,56.6] [54.1,74.2] [4.1,4.8] Central Borno 31.4 28.2 56.5 4.0 454 [23.1,41.0] [19.5,38.9] [44.1,68.0] [3.7,4.2] MCC & Jere 38.8 55.1 68.1 4.1 452 [29.9,48.6] [45.9,64.0] [59.4,75.7] [3.7,4.5] Central Yobe 45.1 56.7 74.7 4.4 460 [34.6,56.0] [46.7,66.2] [63.7,83.3] [4.0,4.7] Southern Yobe 44.9 38.5 72.8 4.5 475 [34.5,55.7] [27.9,50.3] [61.3,81.9] [4.1,4.9] Northern Yobe 37.3 42.7 75.0 4.2 467

[27.7,48.1] [30.7,55.6] [64.7,83.0] [3.9,4.5] *≥5 food groups yesterday

Figure 3.7.1 contains histograms illustrating the distribution in terms of number of food groups consumed by state. The proportion of women consuming each food group is presented in Figure 3.7.2. While some food groups were consumed by nearly all respondents (e.g., grains), very few respondents consumed organ meats, eggs, or Vitamin A rich fruits. Patterns of consumption are similar by state.

Figure 3.7.1. Distribution of dietary diversity scores among women of reproductive age (15-49 years), by state

Figure 3.7.2. Proportion of women of reproductive age (15-49) consuming each food group, by state

3.8 Water and Sanitation

Safe treatment of drinking water and proper hygiene and sanitation are important cornerstones of public health. In the context of an emergency with mass displacement, people may become resettled in locations without adequate water, access to means to treat water, sufficient latrines and handwashing stations. Unsafe drinking water can be a carrier of many diseases such as cholera, schistosomiasis, and typhoid.

In the survey households were asked whether they treat the water used for drinking. Among households that reported treating water, methods used were recorded. All methods used were recorded. Drinking water is considered appropriately treated if one the following methods of treatment is used: boiling; adding bleach or chlorine; using a water filter; or using solar disinfection. Use of solar disinfection was assessed but is not presented here as no household in the survey reported using this method.

Sanitation was assessed through a series of observations. Survey teams observed whether there was a location in the house where household members could wash their hands. If yes, presence of water and soap were each verified. Type of soap was recorded if present.

The percentage of households treating their drinking water by treatment method is presented in Table 3.8.1. Of all households, 17.0% in Adamawa reported treating their drinking water, nearly twice the proportion in Borno (8.9%) or Yobe (9.0%). However, of those that reported treating their water, only one in three used an safe and appropriate water treatment method—26.9% in Adamawa, 34.0% in Borno, and 28.0% in Yobe. The most common methods used, letting it stand and settle and straining through a cloth, are not as effective. These two methods were reported to be the most common water treatment methods in North-East Nigeria in the 2011 MICS. By domain, the proportion of households using an appropriate treatment method was highest in MMC & Jere (42.5%). However, only 7.3% of households in the domain used any treatment method. In Northern Yobe, less than 2% of households reported treating their water.

The percent of households where a place for handwashing was observed is reported in Table 3.8.2. Approximately one in six households in all states had a location for handwashing observed that had both water and soap at the time of the visit. The proportion of households with a location for handwashing was highest in Adamawa (81.0%), however of these households the proportion with both soap and water observed was lowest (20.7%). Conversely, in Borno the proportion of households with a location for handwashing was low (38.0%), however a higher proportion had observed soap and water (44.0%). By domain, both the proportion of household with a location for handwashing (range: 24.6-82.7%) and the proportion with soap and water observed among them (range: 9.5-62.9%) was highly variable.

These results suggest that in all domains, at the time of the visit the majority of households did not have the ability to properly wash their hands at home. Washing hands with water and soap is an important, and cost effective health intervention to reduce the incidence of conditions observed to be prevalent in the surveyed areas (e.g., diarrhoea and pneumonia).

Tables 3.8.1. Percentage of households treating their drinking water by treatment method, by state and domain

Proportion of Number of Water treatment method used among households treating their water: HHs treating households their drinking No. of HHs Add Strain Let it Any Appropriate treating their Use water water, any Boil bleach/ through a stand and Alum Water Treatment drinking water, filter method chlorine cloth settle Method any method

State Adamawa 17 1105 7.2 1.8 29.3 18.9 53.6 9.2 26.9 179 [11.0,25.4] [2.9,16.5] [0.7,5.0] [22.5,37.2] [6.7,43.0] [36.2,70.2] [4.0,19.9] [12.5,48.7] Borno 8.9 1719 5.5 13 42.4 15.5 0.4 14.9 34 156 [6.7,11.7] [2.2,13.0] [6.8,23.6] [27.9,58.3] [7.6,28.9] [0.1,2.8] [8.6,24.6] [23.1,46.9] Yobe 9 1667 7.6 2.6 29.5 17.8 37.2 9.8 28 143 [5.7,13.9] [3.5,15.8] [0.9,7.8] [19.3,42.3] [10.8,27.9] [21.6,56.1] [4.2,21.3] [17.9,41.0] Domain Southern Adamawa 19.1 565 8.3 0.9 25.9 24.1 50.9 11.1 32.4 108 [10.8,31.5] [2.8,22.1] [0.1,6.1] [18.9,34.4] [7.9,54.0] [29.6,71.9] [4.4,25.4] [13.4,59.7] Northern Adamawa 13.1 540 4.2 4.2 38 5.6 60.6 4.2 12.7 71 [7.1,23.1] [1.2,14.0] [1.1,14.8] [22.3,56.8] [1.1,24.5] [37.8,79.5] [0.8,18.7] [4.1,33.0] Southern Borno 11.2 589 10.6 3 59.1 12.1 0 12.1 25.8 66 [7.0,17.6] [3.7,26.6] [0.4,20.5] [33.9,80.3] [4.5,28.7] 0 [5.1,26.0] [12.9,44.8] Central Borno 8.6 581 0 22 34 14 2 26 36 50 [4.7,15.1] 0 [6.2,54.7] [15.9,58.4] [3.0,45.9] [0.2,15.0] [8.6,56.7] [14.6,64.9] MCC & Jere 7.3 549 2.5 20 27.5 20 0 12.5 42.5 40 [4.8,10.9] [0.4,15.4] [8.4,40.4] [10.6,54.8] [6.3,48.2] 0 [5.5,25.9] [24.8,62.4] Central Yobe 15.2 551 4.8 3.6 32.1 13.1 58.3 1.2 21.4 84 [8.2,26.5] [1.5,14.0] [1.0,11.5] [16.2,53.7] [4.8,31.2] [28.5,83.1] [0.1,9.2] [11.5,36.4] Southern Yobe 9.3 549 9.8 2 25.5 23.5 17.6 17.6 35.3 51 [4.5,18.4] [3.2,26.0] [0.2,13.8] [13.3,43.2] [13.7,37.4] [7.5,36.1] [8.2,34.1] [18.1,57.3] Northern Yobe 1.4 567 * * * * * * * 8 [0.7,2.8] *Results suppressed given <10 unweighted households

Tables 3.8.2. Percentage of households where a place for handwashing was observed and availability of soap and/or water, by state and domain

Place for handwashing observed

Percentage of Water is available and: Water is not available and: Number of households where Number of No soap: No soap: households where place for handwashing households a place for Soap No other Soap No other was observed Ash, mud, or Ash, mud, or handwashing was present cleansing present cleansing agent sand present sand present observed agent present present State Adamawa 81 1105 20.7 2.3 65.5 1.6 0.1 9.7 888 [73.1,86.9] [15.2,27.6] [1.2,4.4] [57.2,73.1] [0.7,3.6] [0.0,1.0] [5.5,16.7] Borno 38 1719 44 0.1 37.2 1.1 0.5 17.1 600 [29.2,47.7] [32.1,56.6] [0.0,0.6] [27.7,47.9] [0.4,3.4] [0.1,2.2] [10.8,25.8] Yobe 63.9 1667 22.5 2 65.4 0 0.2 9.9 1091 [54.4,72.4] [15.0,32.4] [1.0,3.9] [55.2,74.3] [0.0,0.9] [5.3,17.6] Domain Southern Adamawa 82.7 565 20.3 3.2 67.7 1.5 0.2 7.1 467 [71.4,90.1] [13.3,29.9] [1.6,6.4] [56.4,77.2] [0.5,4.2] [0.0,1.5] [2.6,17.6] Northern Adamawa 78 540 21.4 0.7 61.5 1.7 0 14.7 421 [66.8,86.1] [14.1,31.1] [0.2,2.1] [49.2,72.5] [0.4,6.8] [7.6,26.7] Southern Borno 34.3 589 62.9 0 23.8 0 1 12.4 202 [21.4,50.1] [43.2,79.1] 0 [13.1,39.2] [0.1,6.8] [4.0,32.4] Central Borno 24.6 581 55.9 0.7 28 0 0 15.4 143 [14.7,38.3] [38.0,72.4] [0.1,5.6] [16.5,43.4] [6.5,32.2] MCC & Jere 46.4 549 31 0 46.7 2 0.4 20 255 [31.1,62.5] [16.7,50.1] 0 [32.1,61.9] [0.6,6.1] [0.0,3.0] [11.7,32.1] Central Yobe 57.5 551 30.3 0.9 57.7 0 0 11 317 [42.1,71.7] [16.5,48.8] [0.3,2.6] [41.1,72.8] [5.7,20.2] Southern Yobe 60.3 549 26.9 2.4 59.5 0 0.3 10.9 331 [44.1,74.5] [13.9,45.7] [0.9,6.5] [40.8,75.8] [0.0,2.1] [3.4,29.8] Northern Yobe 78.1 567 9.5 2.3 80.6 0 0.2 7.4 443 [64.5,87.5] [5.1,17.0] [0.8,6.1] [71.1,87.5] [0.0,1.6] [3.9,13.9]

4. Conclusion and Recommendations

Under five mortality rates exceed the emergency threshold in Central Yobe and are very high in Central Borno and Northern Yobe. The upper confidence intervals for U5MR in these two domains exceeds 2 deaths in children under five / 10,000 children under five / day, suggesting it is possible that U5MR exceeds emergency thresholds in these domains as well. In half of the domains (Southern Borno, central Borno, Central Yobe and Northern Yobe), U5MRs were more than three times CMRs. Crude mortality rates did not exceed emergency thresholds of 1 deaths/10,000 persons / day.

There remain critical gaps in both preventive services and clinical management of common childhood morbidities. Low coverage of measles vaccination (less than 60% in all three states) is particularly concerning given the ongoing measles outbreak in Borno state.

Based on these results the following is recommended: 1. Nutrition emergency response can be focused to areas with higher prevalence of acute malnutrition. All children with acute malnutrition should have access to treatment. However, survey results suggests the response can be further focused within the emergency states, including newly liberated areas. Focus should be placed on the areas where the prevalence of acute malnutrition exceeds serious levels—Central Borno, MMC/Jere, Northern Yobe, Central Yobe, and Southern Yobe—as well as newly liberated areas as they become accessible to humanitarian actors.

2. Continue strengthening ongoing food and nutrition response which may be attributable for the declines in acute malnutrition prevalence documented. During the period of the survey and the months preceding it, there has been an ongoing humanitarian response in the emergency states that included increased outreach and treatment of acute malnutrition through CMAM programs as well as general food and/or cash distributions. Continuing and strengthening these activities should remain a priority.

3. Improve coverage of public health interventions including deworming medication and measles vaccinations. Measles vaccination campaigns have been organized in camps for displaced persons within the emergency areas. However, data suggest that coverage of measles vaccination is low in all domains. A vaccination campaign should therefore be an immediate priority given low coverage in the context of an ongoing outbreak. Additionally, despite ongoing 66

distributions of deworming medication as part of routine activities and through campaigns, coverage remains low.

4. Strengthen management of common childhood illnesses such as malaria, pneumonia and diarrhoea at accessible primary health centers. Survey results indicate that in the emergency states, access to proper diagnostic tests, appropriate medications, and preventive services for common childhood illnesses remain below national benchmarks. While coverage of some interventions, such as use of ACTs to treat fever, have improved relative to the 2015 NNHS, there remains room to improve management of all assessed childhood illnesses. Where the conflict has resulted in considerable destruction to health infrastructure, use of community health volunteers can be prioritized to improve coverage.

5. Surveillance activities can be narrowed to areas with higher prevalence of acute malnutrition. Given limited funds, survey scope can be limited to a smaller area (Borno and Yobe). Narrowing focus would free funds to sample more clusters in Borno, fund additional small-scale rapid surveys in newly accessible areas, and reallocate funds to the ongoing humanitarian programs.

- As a sector, a few targeted and high quality small-scale survey should be organized immediately in newly accessible areas to provide representative estimates of acute malnutrition and mortality. Based on the preliminary results shared in November, sector partners organized small- scale surveys in newly accessible areas of Bama, Dikwa and Monguno LGAs in Borno. These surveys were aimed to provide rigorous, population representative estimates of acute malnutrition and mortality in areas believed by sector partners to have higher prevalence than that observed at the domain level. Rapid screenings should be used to accesses the nutrition situation in newly accessible areas to inform a response to the conditions identified.

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Annexes

Annex 1. Acknowledgments

This survey was carried out by the National Bureau of Statistics (NBS) in coordination with the National Population Commission (NPC), the Federal Ministry of Health (FMOH), and the Nigerial Nutrition in Emergency Working Group (NiEWG). Financial support was provided by the Government of Nigeria, United Nations Children’s Fund (UNICEF), and the United Nations Central Emergency Response Fund (CERF). Technical support was provided by the Centers for Disease Control and Prevention (CDC) and UNICEF through NBS.

Annex 2. Lower Government Areas and Estimated Population, by Survey Domain

Estimated Estimated Total Accessible State LGA Domain Population of Population of LGA LGA Demsa 239,901 239,901 Gombi 194,886 194,886 Guyuk 236,619 236,619 Lamurde 150,132 150,132 Numan 120,746 120,746 Ghelleng 198,400 198,400 1 Southern Adamawa Yola Norht 263,852 263,852 Ganye 218,388 218,388 Jada 244,225 244,225 Mayo-Belwa 203,803 203,803 Adamawa Tuengo 59,261 59,261 Fufore 275,884 275,884 Yola South 259,007 259,007 Girie 173,014 173,014 Hong 225,094 225,094 Madagali 179,445 179,445 Maiha 148,019 148,019 2 Northern Adamawa Michika 206,695 206,695 Mubi North 201,066 201,066 Mubi South 171,606 171,606 Song 256,465 256,465 Abadam 394,480 0 Mobbar 209,847 0 3 Northern Borno Guzamala 113,732 0 Kukawa 499,415 291,995 Nganzai 127,414 47,835 Akira/Uba 395,019 394,970 Bayo 313,641 313,641 Biu 372,499 372,499 Borno 4 Southern Borno Chibok 136,370 136,370 Hawul 238,493 238,493 Kwaya Kusar 217,410 217,410 Shani 304,458 304,458 Bama 578,582 225,193 Dikwa 218,996 92,340 5 East Borno Gwoza 470,711 177,639 Kala/Balge 108,575 19,660

Ngala 401,875 242,296 Damboa 245,811 113,653 Gubio 106,509 75,567 Kaga 127,568 60,770 Konduga 714,484 610,362 6 Central Borno Mafa 162,643 54,525 Magumeri 148,470 148,470 Marte 280,327 0 Monguno 224,226 78,475 Maiduguri 1,924,776 1,924,664 7 MCC Jere Jere 958,818 938,863 Barde 197,176 197,176 Bonsari 153,930 153,930 8 Central Yobe Geidam 221,880 221,880 Jakusko 323,144 323,144 Damaturu 124,152 124,152 Fika 193,104 193,104 Fune 424,252 424,252 Gujba 183,502 183,502 9 Southern Yobe Yobe Gulani 146,011 146,011 Nangere 123,883 123,883 Potiskum 290,408 290,408 Tarmuwa 108,904 108,904 Karasuwa 150,923 150,923 Machina 86,901 86,901 10 Northern Yobe Nguru 212,481 212,481 Yunusari 177,483 177,483 Yusufari 156,698 156,698

Annex 3. Maps of Lower Government Areas, by Survey Domain and Accessibility

Figure. Map of Lower Government Areas by Survey Domain

1. Southern Adamawa 2. Northern Adamawa 3. Northern Borno 4. Southern Borno 5. East Borno 6. Central Borno 7. MCC/Jere 8. Central Yobe 9. Southern Yobe 10. Northern Yobe

Figure. Map of Lower Government Areas in Borno State, by Accessibility

Source: World Health Organization (WHO)

Annex 4. List of nutrition indicators and definitions

S.N Indicators Numerator Denominator 1. Child Nutrition 1.1 Underweight

Number of children under age 5 who fall below minus two Underweight Total number of children age 0- 1.1.1 standard deviations from the median weight for age of the prevalence 59 months WHO standard Number of children under age 5 who fall between below Moderate minus two to greater than or equal to minus three standard Total number of children age 0- 1.1.2 underweight deviations from the median weight for age of the WHO 59 months prevalence standard

Severe Total number of children age 0- 1.1.3 underweight Number of children under age 5 who fall below minus three 59 months prevalence standard deviations from the median weight for age of the WHO standard 1.2 Stunting

Number of children under age 5 who fall below minus two Stunting Total number of children age 0- 1.2.1 standard deviations from the median height for age of the prevalence 59 months WHO standard Number of children under age 5 who fall between below Moderate minus two to greater than or equal to minus three standard Total number of children age 0- 1.2.2 Stunting deviations from the median height for age of the WHO 59 months prevalence standard

Severe Number of children under age 5 who fall below minus three Total number of children age 0- 1.2.3 Stunting standard deviations from the median height for age of the 59 months prevalence WHO standard 1.3 Wasting (Z-Score)

Number of children age 0-59 months who fall below Wasting Total number of children age 0- 1.3.1 minus two standard deviations from the median weight for prevalence 59 months height of the WHO standard Number of children age 0-59 months who fall between Moderate below minus two to greater than or equal to minus three Total number of children age 0- 1.3.2 Wasting standard deviations from the median weight for height of 59 months prevalence the WHO standard

Severe Number of children age 0-59 months who fall below minus Total number of children age 0- 1.3.3 Wasting three standard deviations from the median weight for 59 months prevalence height of the WHO standard

1.4 Acute malnutrition (MUAC &/or bilateral oedema) Wasting Number of children age 6-59 months who fall below Total number of children age 6- 1.4.1 prevalence MUAC 125 mm 59 months Moderate Number of children age 6-59 months fall between below Total number of children age 6- 1.4.2 Wasting MUAC 125 mm and greater or equal to 115 mm 59 months prevalence Severe Number of children age 6-59 months who fall below Total number of children age 6- 1.4.3 Wasting MUAC 115 mm 59 months prevalence 1.5 Acute Malnutrition (WHZ &/ or bilateral oedema )

Acute Number of children age 6-59 months who fall below Total number of children age 6- 1.5.1 malnutrition minus two standard deviations from the median weight for 59 months prevalence height of the WHO standard 75

Moderate Number of children age 6-59 months who fall between acute below minus two to greater than or equal to minus three Total number of children age 6- 1.5.2 malnutrition standard deviations from the median weight for height of 59 months prevalence the WHO standard

Severe acute Number of children age 6-59 months who fall below minus Total number of children age 6- 1.5.3 malnutrition three standard deviations from the median weight for 59 months prevalence height of the WHO standard

2. Mortality

Crude Total number of deaths of any cause occurring during the Total number of persons per 2.1 Mortality recall period (January 1, 2016 and the date of the survey) 10,000 per day Rate

Moderate Total number of deaths among children under five of any Total number of children under 1.1.2 underweight cause occurring during the recall period (January 1, 2016 five per 10,000 per day prevalence and the date of the survey)

3. Child Health Number of children age 9 to 59 months Measles immunization Total number of children 9 to 59 3.1 who received measles vaccine before the coverage months survey Prevalence of diarrhoea Number of children under age 5 years who Total number of children under 3.2 among children under age had diarrhoea in the last two weeks age 5 years 5 years Diarrhoea treatment with Number of children under age 5 years with Total number of children under 3.3 oral rehydration salts diarrhoea in the previous 2 weeks who age 5 years with diarrhoea in the (ORS) and zinc received ORS and Zinc previous 2 weeks Prevalence of fever among Number of children under age 5 years who Total number of children under 3.4 children under age 5 years had fever in the last two weeks age 5 years Number of children under age 5 years who Total number of children under Treatment of fever with 3.5 had fever in the last two weeks who were age 5 years with fever in the ACT treated with ACT previous 2 weeks Number of households with Household availability of (a) at least one mosquito nets Total number of households 3.6 mosquito nets (b) at least one mosquito nets for every surveyed two people Children under age 5 who Number of children under age 5 years who Total number of children under 3.7 slept under a mosquito slept under a mosquito net the previous age 5 who spent the previous night net night in the interviewed households Intermittent preventive Number of children under age 0 - 59 Total number of children from age 3.8 treatment for of children months who received iintermittent 0 - 59 months under age 5 preventive treatment Number of children under age 5 years who Prevalence of ARI among Total number of children under 3.9 had cough and rapid breathing in the last children under age 5 years age 5 years two weeks Number of children under age 5 years who Total number of children under Treatment of ARI with had cough and rapid breathing in the last 3.10 age 5 years with cough and rapid antibiotics two weeks who were treated with breathing in the previous 2 weeks antibiotics

4. Public Health Campaigns

Number of households that lived in an area where MNCHW Geographic Total number of 4.1 Maternal Newborn and Child Health Week activities Coverage households were accessible

Number of households who received services during the Total number of 4.2 MNCHW Coverage Maternal Newborn and Child Health Week households Deworming among Number of children age 12-59 months who given an Total number of children 4.3 children under age 5 anthelmintic drug in the 6 months preceding the survey age 12-59 months Fortified Blended Food Number of households reporting receipt of corn soy Total number of 4.4 Coverage blend (CSB) in the three months preceding the survey households

5. Women Nutrition

Acute Malnutrition Number of women age 15 - 49 years with a MUAC value Total number of women 5.1 prevalence less than or equal to 221 mm age 15 to 49 Moderate Acute Number of women age 15 - 49 years with a MUAC value Total number of women 5.2 Malnutrition that falls between below MUAC 221 mm and is greater age 15 to 49 prevalence than or equal to 214 mm Severe Acute Number of women age 15 - 49 years who fall below Total number of women 5.3 Malnutrition MUAC 214 mm age 15 to 49 prevalence Number of women age 15 - 49 years consuming foods Number of randomly Minimum Dietary 5.4 from less than 5 of 10 dietary groups during the day before selected women age 15 Diversity for Women the survey to 49

6. Water and Sanitation Household water Number of household reported treating drinking water (any Total number of 6.1 treatment method) households Number of household treating drinking water using at least Total number of Household water 6.2 one appropriate method defined as: boiling; adding bleach or households reporting treatment method chlorine; using a water filter; or using solar disinfection treating drinking water Use of Total number of 6.3 handwashing Number of household with handwashing location / facility households location

Annex 5. Calendar Calendarof Local Events of Local Events Northern Nigeria NOVEMBER 2016

Seasons/Religious Holidays & other Month Holidays/ Other 2011 2012 2013 2014 2015 2016 events Events 58 46 34 22 10 January Harmattan New Years Yajin Aiki Moulud (Janairu) Armed forces Chire Tallafi-Mai Maloud, Nigeria End of Uhola festival in Zuru Beginning of National ID card Kagoro day (Kaduna Watan uku centenary Celebration (Kebbi), Maloud celebration registration in Damaturu State) remembrance day Kano Bomb Blast

57 45 33 21 9 February Harmattan Valentine Day Watan hudu,Cup of Fulani Attack (Kolu) (Fabreru) Land Preparation Argungu fishing Moulud nations, Lenting Death of Senator Isiah coronation of New Emir of Change of Damaturu market day, period, Creation of Balat (Kaduna) Kano, Postponeent of the Eid-ul maulud festival APC party general Election 56 44 32 20 8 Beginning of Hot Watan biyar, Good Fulani attack of 3 March Season Fishing Festival Prsidential Election & Friday, Easter villages in kano, Muharam, Gogaramfishing festival National Assembly, (Maris) Land Preparation Immigration Job in Bade Yobe Muharram stampede 55 43 31 19 7 Abduction of Chibok Gubernatorial and state Watan shidda,Eclipse April Hot Season (Rani) Girls in Borno assembly Elections, Easter, Kebbi state Governor of the moon Nyanya Bomb Blast, Oviia Osese Festival of Kogi, (Afirilu) Bring Back Our Girls Xenophobic Attack in South Land Preparation Bye Election Protest, (Azumin africa, sacking Of IGP 54 42 30 18 6 May Hot Season (Rani) Worker's day, Watan Azumin Tsofofi Yobe Millitary base (Mayu) Children's day, State of emargency in Attack, Car Bomb In Adamawa, Borno & Jos, Attack of Yobe; Nasarawa Swearing in of President Beginning of return of IDP's to Gamborun in Borno, Ombatse killing, Buhari their homes in Yobe Democracy day Rajab watan Sha'Aban, Watan Azumin Death of Emir of Tsofofi Gombe

53 41 29 17 5 June Death of Emir and (Uni) Beginning of rains Dana plane Crash Swearing in of new Emir of Kano, Nupe Oro festival (Kabba, kogi ) , Day Celebration (Bida Shanruwan Tsofofi, election of senate Beginning of Ramadan, Return of Niger state), Golden jubilee of President/Speaker House of IDP's to Gala Sha'aban Beginning of Emir of Kano Reps, Beginning of Ramadan Ramadan, Banex Plaza bomb blast (Abuja) 52 40 28 16 4

July Rainy season, Beginning of Okun Land Yam (Uli) Closing of school Ramadan, Bomb Festival (Kogi), End of Zaria Bomb Blast (Kaduna), Karamin Sallah, Death of Dr Ali Ramadan, Ebola Out Karaman Sallah Mongunu Blast in sokoto Break

51 39 27 15 3 Dibit Cultural August Heavy rains Festival Edi-el Fitir, Echori & Kano horse riding Death of Borno state Deputy Eid El Kabir, Opening of (Aginasta) Zuru, Kebbi New yam Festival (Durbar) festival Governor Damaturu/Biu road Karamar Sallah 50 38 26 14 2 September School resumes Watan shara Relocation of Borno state govt Beginning of Hajj, house to Bama, Death of Amna (Satumba) Lokoja flood disaster Sacking of nine attack of FCE Kabuga Sheveng in Adamawa, Beginning of harvest ministers, Kano (Kano) Distribution of national ID card in Durbar Yobe 49 37 25 13 1 October Independence day, Taraba state Gov.plane Edl-el Kabir (Babbar Eid El Kabir, Bomb (Okkutoba) crash Sallah) Tafiya Alhazai, Blast in Emir of kano Death of Borno Commissioner for Plane Crash during Mosque, EIKA End of rains, Harvest enviroment (Waziri Imam) Agagu's burial, Death Featival in Ebira Land of solomon Lar (Kogi); Tafiya Achazai

60 48 36 24 12 0 November Harvest Ekai Festival, End of Hajj, (Nuwamiba) Watan daya Dawowar Alhazai, Dawowan Death of Taraba Alhazai,Muharam Babbar Sallah Gashua students riot in Yobe State Assembly (Wata Daya) or Cika- Babban sallah speaker, Partial Ciki, Kano central eclipse mosque bomb blast

59 47 35 23 11

December/ Harmattan Uhola Cultural Festival Watan biyu Introduction of new Hundred Naira (Dusamba) Christmas, of Zuru, Kebbi Yakowa plane crash End of ASSU strike, Notes, beginning of Murama festival in Borno, Death of Mandela, Uhola Festival in Zuru Muharam, Marriage of Madalla Bomb Blast Watan Shara, Air (Kebbi) , APC General Tukur Burate's son Force base bombing Presidental Election in Gashua Boxing day and raid in Maiduguri Primaries, Death of Ibro (Comedian) 78 Kano 79

Annex 6. Selected Clusters

Domain State LGA Locality EA Note Southern 101 Adamawa Adamawa DEMSA NASSARAWO-DEMSA EMMANUEL JUKUN Southern 102 Adamawa Adamawa DEMSA NZUNGWALING BILISON UBANDOMA Southern 103 Adamawa Adamawa DEMSA KPASHAM DUTSE PRIMARY SCHOOL Southern 104 Adamawa Adamawa FUFORE WURO ABDU WURO ABDU Southern FILINGO BOBBO 105 Adamawa Adamawa FUFORE KAWU ALLINGO BOBBO KAWU Southern 106 Adamawa Adamawa FUFORE WALGA WALGA Southern 107 Adamawa Adamawa GANYE JUSANGUM ALH. MISA JAURO Southern 108 Adamawa Adamawa GANYE SUGU ABDU HAYATU Southern Inaccessible/ 109 Adamawa Adamawa GOMBI WUMGARA ,GARAHA WUMGARA Vacant Southern MARARABA TAWA 110 Adamawa Adamawa GOMBI BOKKI COACH MUSA Southern 111 Adamawa Adamawa GUYUK Bobini Wilson Atiman Southern 112 Adamawa Adamawa GUYUK New Banjiram Pius Ambolam Southern 113 Adamawa Adamawa GUYUK Boshikiri Yabbi Gajau Southern 114 Adamawa Adamawa JADA Jalingo Nyami II Jalingo Nyami II Southern 115 Adamawa Adamawa JADA Jada Umaru Sokoto Southern 116 Adamawa Adamawa JADA Wuro Jatau A Wuro Jatau 'A' Southern 117 Adamawa Adamawa LAMURDE LAMURDE TIBO REDILLY Southern MAYO- 118 Adamawa Adamawa BELWA BOKOKO BOKOKO Southern MAYO- WURO MALLUM 119 Adamawa Adamawa BELWA JIDDA WURO MALLUM JIDDA Southern MAYO- 120 Adamawa Adamawa BELWA GAMBE B GAMBE B Southern G/MALLAMI CATHOLIC 121 Adamawa Adamawa NUMAN NUMAN CHURCH Southern 122 Adamawa Adamawa Shelleng Lababiri Alh. Shuaibu Southern 123 Adamawa Adamawa Shelleng Jihadi Hayatu A. Salihu Southern 124 Adamawa Adamawa TOUNGO SAMARI SAMARI Southern YOLA 125 Adamawa Adamawa NORTH KOWAGOL SALIHU GARBA Southern YOLA 126 Adamawa Adamawa NORTH JIMETA POST OFFICE 80

Southern YOLA 127 Adamawa Adamawa NORTH MALAMRE JAURO INUWA GAWI Southern YOLA 128 Adamawa Adamawa SOUTH NGURORE ARABO TELLA Southern YOLA DANKWAIRON 129 Adamawa Adamawa SOUTH YOLA ADAMAWA Southern YOLA 130 Adamawa Adamawa SOUTH WURO CHEKKE ALH. BELLO MOH'D Northern 201 Adamawa Adamawa GIREI WURO ALH. BINKOLA W/ALH. BI-KOLA Northern 202 Adamawa Adamawa GIREI GIREI ALH. ADAMU YAHYA Northern 203 Adamawa Adamawa GIREI LAINDE FRANCIS BAGONE Northern 204 Adamawa Adamawa HONG MIJILI JAPHET ABUGU Northern 205 Adamawa Adamawa HONG UBA ADAMAWA YELLOW HOUSE (FEMALE) Northern 206 Adamawa Adamawa HONG KWANAN KUKA ANAKUSAYA MAVASHAL Northern 207 Adamawa Adamawa HONG MUNGA JAURO MAMUDA SHALL Northern 208 Adamawa Adamawa MADAGALI MAIGANA MAIGANA MARGIH Northern 209 Adamawa Adamawa MADAGALI MADAGALI POLICE STATION Northern TITUS DALI/ SIMON Inaccessible/ 210 Adamawa Adamawa MADAGALI DUGUM BARKA Vacant Northern FIRST BANK/ USMAN 211 Adamawa Adamawa MADAGALI GULAK KAIGAMA Northern MAJEKEN PRIMARY 212 Adamawa Adamawa MAIHA MAJEKEN SCHOOL Northern 213 Adamawa Adamawa MAIHA NASSARAWO JAURO MUSA HAMMAN Northern 214 Adamawa Adamawa MAIHA WURO KURORI WURO KURORI Northern Inaccessible/ 215 Adamawa Adamawa MICHIKA Thore fulani Thore Fulanis Vacant Northern 216 Adamawa Adamawa MICHIKA MICHIKA International Pri. Sch. Northern 217 Adamawa Adamawa MICHIKA L Daba Bemard Zira/Victor Zira Northern Jauro Adamu Kwaji/Kali 218 Adamawa Adamawa MICHIKA Kali Kasa Clinic Northern MUBI 219 Adamawa Adamawa NORTH MANDRA B MANDRA 'B' Northern MUBI 220 Adamawa Adamawa NORTH VIMTIM WAKILIDANIEL NJARA Northern MUBI 221 Adamawa Adamawa NORTH MUBI ALH. INUWA MUSA Northern MUBI 222 Adamawa Adamawa SOUTH MUBI SHUAIBU BELLO Northern MUBI 223 Adamawa Adamawa SOUTH MUBI JAURO ALH. BAPPA Northern MUBI 224 Adamawa Adamawa SOUTH MOJONGO MOJONGO 81

Northern MUBI 225 Adamawa Adamawa SOUTH SAHUDA JAURO ALIYU BOGENA Northern 226 Adamawa Adamawa SONG SALASA ANGUWAN BATA Northern 227 Adamawa Adamawa SONG BANGA JAURO ADAMU BANGA Northern 228 Adamawa Adamawa SONG WURO JAURO BAKARI WURO JAURO BAKARI Northern 229 Adamawa Adamawa SONG TUNLUNGO TUNLUNGO NJAEMUI ,RUNDU ,SABON GARI MURKE ,ALH. BETI , SABON Northern GARI MURKE ,ALH. 230 Adamawa Adamawa SONG BETI RUNDU Southern 401 Borno Borno Askira/Uba DILLE/HUYIM NKURVU Southern 402 Borno Borno Askira/Uba HUSSARA/TAMPUL GIWA PAZZA Southern 403 Borno Borno Askira/Uba MUSSA KIRDUTU Southern 404 Borno Borno Askira/Uba UBA NBAGA GIWE Southern 405 Borno Borno Askira/Uba UVU UDA HUYA Southern NAINAWA/G.GONI/K,DAU 406 Borno Borno Bayo BARBAYA RAWA Southern 407 Borno Borno Bayo FIKHAYEL ANGUWAN FULANI 1 Southern 408 Borno Borno Bayo JARA DALI GUVABALAK Southern 409 Borno Borno Bayo LIMANTI NAINAWA Southern 410 Borno Borno Bayo TELI BULAMA KABI Southern 411 Borno Borno Biu DUGJA DUGJA PRI DANSHUWA Southern 412 Borno Borno Biu DUGJA TABRA VICTORY SCH Southern 413 Borno Borno Biu GALDIMARI G WULIWA U LEMA Southern 414 Borno Borno Biu GUNDA GUNDA L ABBA Southern 415 Borno Borno Biu MANDARAGIRAU DEBIRO B ILIYA Southern 416 Borno Borno Biu YAWI yalwan bariki b ali Southern 417 Borno Borno Chibok MBALALA NDANGA L HARUNA Southern 418 Borno Borno Hawul GWANZANG GOJIM Southern 419 Borno Borno Hawul KWAYA BURA KWAYABURA AMAZA Southern 420 Borno Borno Hawul PAMA/WAITAM turkuta a 421 Southern Borno Hawul SHAFFA BAMJIKIL 82

Borno Southern Kwaya 422 Borno Borno Kusar KUBUKU DUTCHIKOPALA Southern Kwaya MAMMAN BRIKILA ALH. 423 Borno Borno Kusar KWAYA KUSAR ISA Southern Kwaya 424 Borno Borno Kusar PETA UNGUWAN BUKAR Southern 425 Borno Borno Shani Bargu shadari Southern 426 Borno Borno Shani gasi jauro habu Southern 427 Borno Borno Shani gwalasho feshingo Southern 428 Borno Borno Shani kubo pankilang Southern 429 Borno Borno Shani shani langam geidam Southern 430 Borno Borno Shani walama joli Central 641 Borno Borno Damboa AZIR MULTE Bulama Gulde Central 642 Borno Borno Damboa GUMSURI Wavi lawan yahaya Central 643 Borno Borno Damboa GUMSURI Komdi Lawanty Central 644 Borno Borno Damboa GUMSURI Gurjan Lawan Kano Central 645 Borno Borno GUBIO GUBIO I ALKALIRI 1 Central 646 Borno Borno GUBIO GUBIO II LAWANTI Central 647 Borno Borno Kaga BENISHEIKH WASSARAMTI Central 648 Borno Borno Kaga MAINOK BULAMA INNAMI Central 649 Borno Borno Konduga Ajiri Kolifayo Saleh Central 650 Borno Borno Konduga Ajiri Kondolli Central 651 Borno Borno Konduga AUNO Abba Kashimti Central 652 Borno Borno Konduga AUNO Bulama Umara Central 653 Borno Borno Konduga DALORI Amarwa Bulamari Central 654 Borno Borno Konduga JAKANA Jakan Binami Central 655 Borno Borno Konduga KONDUGA Yandari Bulama Central 656 Borno Borno Konduga KONDUGA Sabon Gari dan A. Central 657 Borno Borno Konduga KONDUGA Mainari Central 658 Borno Borno Konduga MALARI Mainari 659 Central Borno MAFA TAMSUM-GAMDUA GWOZARI BULAMA 83

Borno GARJIRE Central 660 Borno Borno MAFA TAMSUM-GAMDUA ZANNARI MASALLACI Central 661 Borno Borno MAFA TAMSUM-GAMDUA MALA KYARIRI Central 662 Borno Borno Magumeri Galiganna maramari Central 663 Borno Borno Magumeri HOYO/CHINGUA chingowa lawanti Central 664 Borno Borno Magumeri MAGUMERI kasula Central 665 Borno Borno Magumeri MAGUMERI sheriff bukarti Central Inaccessible/ 666 Borno Borno Monguno MONGUNO BAKASSI BADANDA Vacant Central Inaccessible/ 667 Borno Borno Monguno MONGUNO LAWAN BABAGANA Vacant Central Inaccessible/ 668 Borno Borno Monguno MONGUNO DUNGUROM Vacant Central FEDERAL TRAINING 669 Borno BORNO KONDUGA AUNO / CHABBOL CENTER CAMP Central 670 Borno BORNO KAGA BENISHEIKH GSS BENISHEIKH Central Inaccessible/ R671 Borno Borno Monguno MONGUNO BULAMA AJI Vacant Central R672 Borno Borno Konduga DALORI M/Karauwa Central R673 Borno Borno Kaga NGAMDU YANGEBARI Central R674 Borno Borno Damboa DAMBOA Shuwari Bulama Buba 701 MMC Jere Borno Jere DUSUMAN Bulama Dan Ali 702 MMC Jere Borno Jere GALTIMARI LAYIN ADAMU TITRI BULAMA KADAI GONI Inaccessible/ 703 MMC Jere Borno Jere GOMARI UMAR Vacant 704 MMC Jere Borno Jere GOMARI NDOLLORI BULAMARI 705 MMC Jere Borno Jere KHADDAMARI Musari 706 MMC Jere Borno Jere MAIMUSARI Line Masallaci 707 MMC Jere Borno Jere MASHAMARI Alhaji Kaumi B 708 MMC Jere Borno Jere MASHAMARI Kwanan Yobe 709 MMC Jere Borno Jere OLD MAIDUGURI ALAI BUNUNGAL 1545 710 MMC Jere Borno Jere OLD MAIDUGURI THANAWIYATU 711 MMC Jere Borno Maiduguri BOLORI I SHUWARI 4A 712 MMC Jere Borno Maiduguri BOLORI I MUSARI IB 713 MMC Jere Borno Maiduguri BOLORI I SEFCON A 714 MMC Jere Borno Maiduguri BOLORI II BULAMA MODU 715 MMC Jere Borno Maiduguri BOLORI II NGRANNAM SERIA 716 MMC Jere Borno Maiduguri BULABULIN Gidan zana Millionaire Quarters 717 MMC Jere Borno Maiduguri GAMBORU Bagoni street

LAYIN SHEIK IBRAHIM 718 MMC Jere Borno Maiduguri GWANGE I ZAWIYA 719 MMC Jere Borno Maiduguri GWANGE II SAMAILA BORNO BAMA ROAD LAYIN 720 MMC Jere Borno Maiduguri GWANGE III TSAMIYA Government college 721 MMC Jere Borno Maiduguri LAMISULA quarters 722 MMC Jere Borno Maiduguri LIMANTI Zanna dalatu 723 MMC Jere Borno Maiduguri MAISANDARI DALA KAYINJI 3 724 MMC Jere Borno Maiduguri MAISANDARI MUSTAPHA MALLABE 725 MMC Jere Borno Maiduguri MAISANDARI SALTALMARI B B M B Inaccessible/ 726 MMC Jere Borno Maiduguri MAISANDARI BULAMA GAFCHA Vacant 727 MMC Jere BORNO MMC MAISANDARI BAKASI CAMP 728 MMC Jere BORNO JERE BALE GALTIMARI Judumuri 729 MMC Jere BORNO JERE SINIMARI FARM CENTRE 730 MMC Jere BORNO JERE DUSUMAN Ganameri Central 801 Yobe Yobe BADE GASHUA ALH. ADAMU MATANIA Central 802 Yobe Yobe BADE GASHUA ALKALI MOH'D AUWAL Central MAI ANGUWA ALH. 803 Yobe Yobe BADE GASHUA YALWA Central 804 Yobe Yobe BADE GASHUA DOGON MASSUALLI Central 805 Yobe Yobe BADE PAGA A M. MUSA JAJAMI (HM) Central 806 Yobe Yobe BADE KABAYO ALHAJI MALUM Central 807 Yobe Yobe BADE KEBOL GAIDU GATA Central 808 Yobe Yobe BURSARI DAPCHI G.G.S.T.C. 4 Central 809 Yobe Yobe BURSARI YA GANARI MALLAM MAMMAN Central 810 Yobe Yobe BURSARI MASABA MALLAM BOYI Central 811 Yobe Yobe BURSARI GIJIGAIWA BULAMA DUWAKA Central 812 Yobe Yobe BURSARI DAPSO BALA INUWA Central 813 Yobe Yobe GEIDAM MALLARI BULAMA ABBA Central 814 Yobe Yobe GEIDAM SHERURI BILLAMA MAMMADU Central Inaccessible/ 815 Yobe Yobe GEIDAM FUKURTI KASUWA RAWA GANA Vacant Central 816 Yobe Yobe GEIDAM TAWANAWA BULAMA DATTO Central 817 Yobe Yobe GEIDAM GEIDAM MANGA Central 818 Yobe Yobe GEIDAM GEIDAM ALHAJI UMAR GEIDAM 85

Central 819 Yobe Yobe GEIDAM MATAKUSKUM ALHAJI MA'AJI Central 820 Yobe Yobe JAKUSKO JAKUSKO GODIYA BREAD Central 821 Yobe Yobe JAKUSKO GURBANA ALHAJI ISA LARAWA Central 822 Yobe Yobe JAKUSKO GARIN MALLAM GARBA ALI Central 823 Yobe Yobe JAKUSKO GARIN MA AJI BULAMA MUSA Central 824 Yobe Yobe JAKUSKO MARCHA MAINA GAMBO Central 825 Yobe Yobe JAKUSKO GARIN ALHAJI ALHAJI YAWALE Central 826 Yobe Yobe JAKUSKO AMSHI NA MAJI Central 827 Yobe Yobe JAKUSKO GAMAJAM SARKIN PAWA MUSA Central Inaccessible/ 828 Yobe Yobe JAKUSKO DACHIA MASHEKARAN KATABTAB Vacant Central 829 Yobe Yobe JAKUSKO GUYIK BABA MANU JEGURE Central 830 Yobe Yobe JAKUSKO KADAGE MACHIDO ALI Southern 901 Yobe Yobe DAMATURU DAMATURU ATLANTA RESTAURANT Southern 902 Yobe Yobe DAMATURU KASAISA BULAMA ZARAMI Southern 903 Yobe Yobe FIKA GARIN KA AJI GARIN KA'AJI Southern 904 Yobe Yobe FIKA FIKA DANJUMA BARDE Southern 905 Yobe Yobe FIKA TADANGARA MAINA ADAMU Southern 906 Yobe Yobe FIKA TIKAU NANAI/KAISALA MAI ANGUWA ABUBAKAR Southern 907 Yobe Yobe FUNE KURBUNGA JAURO GENDERU Southern 908 Yobe Yobe FUNE BADECHI BULAMA HARUNA Southern 909 Yobe Yobe FUNE MIL - UKU MAIUNGUWA SHAYIBU Southern 910 Yobe Yobe FUNE DAMAGUM BELLO ILIYA 1 Southern 911 Yobe Yobe FUNE BAGANA JAURO KABO Southern 912 Yobe Yobe FUNE ROYEL B. MAI KUDI WANZAM Southern 913 Yobe Yobe FUNE DOGON KUKA SARKI YARIMA Southern 914 Yobe Yobe FUNE JAURO KAUGA JAURO KAUGA Southern Inaccessible/ 915 Yobe Yobe GUJBA SHERHURI BULAMA MALA Vacant Southern 916 Yobe Yobe GUJBA BUNGAI ZAKAR YA'U 86

Southern MOHAMMED AZEEM 917 Yobe Yobe GUJBA BUNI YADI TERAB Southern Inaccessible/ 918 Yobe Yobe GULANI KUMBODORO A LADAN KUMBO DORO Vacant Southern 919 Yobe Yobe GULANI WURO DAUDI HAMMA BUSHE Southern 920 Yobe Yobe GULANI NJOLLOWA B IBRAHIM GARA Southern 921 Yobe Yobe NANGERE MADABAI BULAMA M. YAKUBU Southern 922 Yobe Yobe NANGERE BETTI BETTI J. DUMBO, BAYE Southern 923 Yobe Yobe POTISKUM POTISKUM ALH. BABAYO MOHD Southern 924 Yobe Yobe POTISKUM POTISKUM UNGUWAN TANDARI Southern 925 Yobe Yobe POTISKUM POTISKUM KARA PRIMARY SCHOOL Southern 926 Yobe Yobe POTISKUM POTISKUM ALHAJI ABU Southern 927 Yobe Yobe POTISKUM GANDAFURA WAKILI DAN BIBA Southern 928 Yobe Yobe POTISKUM MAMUDO HOSTEL E Southern 929 Yobe Yobe TARMUA MODU ARIMAMI BULAMA KONDO Southern 930 Yobe Yobe TARMUA CHUDINGEL JAURO UMARU Northern 1001 Yobe Yobe KARASUWA RUGAR ABAKARYARI MOHAMMED WARU Northern 1002 Yobe Yobe KARASUWA GAWU LAWANBE HON. SALE Northern 1003 Yobe Yobe KARASUWA BUDUM MAINA GUDU Northern 1004 Yobe Yobe KARASUWA RUGAR MAMMAN FASHAU MAMMAN Northern 1005 Yobe Yobe KARASUWA FULATARI NA ALI MAI GARI NA ALI Northern 1006 Yobe Yobe KARASUWA LAGEDERI MALLAM KACHALLAH Northern 1007 Yobe Yobe MACHINA DOLEN MACHINA MALLAM ZANGOMA Northern 1008 Yobe Yobe MACHINA KALGIDI MALAM YAHAYA Northern 1009 Yobe Yobe MACHINA GARIN ISA BA-MUSA Northern 1010 Yobe Yobe NGURU GADA LAMIDO CHIROMA Northern 1011 Yobe Yobe NGURU GARBI RAILWAY STATION Northern 1012 Yobe Yobe NGURU YANDAGO KARI KAMBI Northern 1013 Yobe Yobe NGURU NGURU AUDU MAI UNGUWA Northern 1014 Yobe Yobe NGURU NGURU ADAMU YAKUBU 87

Northern 1015 Yobe Yobe NGURU NGURU MOHAMMED DAN KAFO Northern 1016 Yobe Yobe NGURU ASKIMA MAL. ABDULRAHMAN Northern 1017 Yobe Yobe NGURU MALLAM GAMBO MAIGARI ALI Northern 1018 Yobe Yobe NGURU RUGAR M. J. ISA KALO MANU Northern BULAMA MODU Inaccessible/ 1019 Yobe Yobe YUNUSARI LUKURI KANGORAM Vacant Northern 1020 Yobe Yobe YUNUSARI KANNAMMA GONI KALLUMA Northern 1021 Yobe Yobe YUNUSARI KUJERI MALLAM BULAMA Northern 1022 Yobe Yobe YUNUSARI BULAMA KURY BULAMA ILLO Northern 1023 Yobe Yobe YUNUSARI FULATARI HARUNA HARUNA GIDADO Northern 1024 Yobe Yobe YUNUSARI YAWULE ALHAJI KORI Northern 1025 Yobe Yobe YUSUFARI BULA KULOYE ALHAJI MUSTAFA Northern 1026 Yobe Yobe YUSUFARI BULA MADU ALHAJI MOH'D 2 Northern 1027 Yobe Yobe YUSUFARI BULA JAJI ALHAJI KAJIMA Northern 1028 Yobe Yobe YUSUFARI ZANBURMA KALLAMU GONI AJI Northern 1029 Yobe Yobe YUSUFARI MAI NIYA KURA HARU MAI GORO Northern 1030 Yobe Yobe YUSUFARI KAJIMARAM MAI GARI GAMBO Southern Reserve Adamawa Adamawa DEMSA TIKKA BASIC HEALTH CLINIC Southern Reserve Adamawa Adamawa GOMBI JAN JAU 'A' Southern Reserve Adamawa Adamawa LAMURDE GWEH KASSA SAMILA GUMBA Southern Reserve Adamawa Adamawa TOUNGO MUKADA MUKADAS Northern Reserve Adamawa Adamawa HONG UBA ADAMAWA IYA MANPAYA Northern Reserve Adamawa Adamawa MAIHA KEBRE KREBRE Northern MUBI Reserve Adamawa Adamawa NORTH VIMTIM TIMOTHY AUDU Northern Reserve Adamawa Adamawa SONG GOLANTABAL JAURO DOGO TERI Southern Reserve Borno Borno Askira/Uba NGULDE WATAKU Southern Reserve Borno Borno Bayo WUYO FANGARU Southern Reserve Borno Borno Chibok KAUTAKARI KAUTIKARI SOUTH Southern Reserve Borno Borno Hawul BILINGWI GWANGZANG 1 88

Reserve MMC Jere Borno Maiduguri BOLORI II ASHAKA CEMENT Reserve MMC Jere Borno Maiduguri MAISANDARI MOBILE BARRAK B Reserve MMC Jere Borno Maiduguri MAISANDARI ZANNARI 3B Reserve MMC Jere BORNO MMC BOLORI I BUZU QUARTERS Central Reserve Yobe Yobe BADE GASHUA ALH.MOH'D MAI LANTI Central Reserve Yobe Yobe BURSARI GARIN TAKARI ALHAJI SULE Central BULAMA MOHAMMED Reserve Yobe Yobe GEIDAM GEIDAM ASHEMI Central Reserve Yobe Yobe JAKUSKO GWAYO/BOGGOH MUSA HODE Southern Reserve Yobe Yobe DAMATURU DAMATURU ALHAJI BAKARI ISA Southern Reserve Yobe Yobe FUNE NGELZARMA NGELZARMA MARKET Southern Reserve Yobe Yobe GUJBA JAMA ARE JAMA'ARE Southern Reserve Yobe Yobe POTISKUM POTISKUM SHUAYUBU MAI KERO Northern Reserve Yobe Yobe KARASUWA GADAN KARGO MAI GARI KAWUDIMA Northern RUGAR BAUSHE Reserve Yobe Yobe NGURU HARDO MALLAM MOHAMMED Northern Reserve Yobe Yobe NGURU RUGAR L. MADO HARUNA SAYERI Northern Reserve Yobe Yobe YUSUFARI RUGAR BA AMADU BA AMADU

Annex 7. Plausability Checks

Available as a separate file.