Preliminary Report Integrated Survey Dadu District, Sindh Province

December 2012

Preliminary report

Integrated Survey

Dadu District, Sindh province, Pakistan

.I. Context

Sindh province of Pakistan is bordered to the west by the Indus River and Baluchistan, to the north by Punjab, to the east by the Indian states of Gujarat and Rajasthan and to the south by the Arabian Sea. The capital of the province is Karachi, Pakistan's largest city and financial hub.

The 23 districts making up the Sindh province are: Kambar Shahdadkot, Larkana, Shikarpur, Ghotki, Sukkur, Khairpur, Khashmore, Nau Shahro Feroze, Jacobad, Badin, Shaheed Benazir Abad (Nawabshah), Thatta, Jamshoro Sanghar, Matiari, Dadu, Tando allay Yar, Tando Mohammad Khan, Hyderabad, Mirpurkhas, Umerkot, Tharparket, Sanghar and Karachi.

Dadu district (Figure 1) has four Talukas namely Dadu, Khaipur Nathan Shah (K.N.Shah), Mehar and Johi1. The district is bordered by the following districts - Naushero Feroze in the East, Khirthar Range in the West, Kambar Ali Khan and Warah districts in the north, and Thalo Bula Khan in the South. The district is estimated at 7866 square kilometers. There are 52 Union Councils (UCs) in Dadu district2.

Figure 1: Map showing Nutrition survey areas in Dadu district

1 Pakistan emergency situational analysis, District Dadu; iMMAP Pakistan, November 2012 2 Dadu district comprises Talukas of Mehar, Khairpur Nathan Shah (KN Shah), Dadu and Johi. The union councils (UCs) for Mehar Taluka are Radhan, Mangwani, Bothro, Shah Punjo and Kolachi; K.N.Shah are Khaipur Nathan Shah, Sita Road, Kakar, Mitho Babar, Kande Chuki, Thalho, Burira, Gozo and Chhore Qamber and Nau Goth. Dadu Taluka has Pat (Rural), Allahabad, Makhdoom, Sial, Pipri, Mian Yar Muhammad Kalhoro and Khudabad. Johi Taluka has Johi (Urban), Drigh Bala, Tando Rahim Khan (at Wahi Pandhi), Phulji, Pat Gul Muhammad, Chhinni and Sawro. 2

In Dadu district, ACF International and Merlin International Non-Governmental Organizations (INGOs) are the organizations that implement targeted nutrition interventions (Community Management of Acute Malnutrition-CMAM) in various UCs since 2011.

The broad situation of the nutritional status in Pakistan is well reported in the 2011 Pakistan National Nutrition Survey (NNS) which indicates that malnutrition rates are unacceptably high and reports around 57% of the 30,000 households surveyed nationally face food insecurity3. The report indicates a Global Acute Malnutrition (GAM) rate of 17.5% and a Severe Acute Malnutrition (SAM) rate of 6.6% among children under-five years in Sindh province. In addition, the prevalence of chronic malnutrition (stunting) and underweight has been critically high among under five (U5) children in Sindh, with stunting and underweight rates of 49.8%, and 40.5% respectively3. Health experts have noted that the increasing rate of chronic and acute malnutrition in the country is primarily due to poverty, high illiteracy rate among mothers and lack of government commitment towards ensuring food security to each and every citizen. Part of the challenge has been as a result of inherent inadequate practices in infant feeding practices and access to “right” foods4. In regard to infant and young child nutrition (IYCN), NNS 2011 survey results, also revealed that across Pakistan only 40.5% of mothers had initiated breastfeeding within one hour of birth, and 47.9% started to introduce semi-solid foods to their children before the recommended period of 6 months of age. Further to this, only 4.6% of women provided a minimum diversified diet for their children aged 6-23 months.

Micronutrient deficiencies are also widespread in Sindh province, with more than 60% of women reported anemic, and 49.5% of women reported having zinc deficiency. The UNICEF report on evaluation of CMAM4 notes that even though Pakistan has achieved high coverage for some nutrition interventions such as Vitamin A supplementation and salt iodization, huge gaps exist in terms of coverage of essential health and nutrition services and the country ranks low in many nutrition indicators.

After the 2010 Pakistan monsoon floods hit, the ACF-CA/UNICEF Flood Affected Nutrition Survey (FANS) conducted in October/November 2010 showed GAM rate of 22.9% and a SAM rate of 6.1%5 in Southern Sindh province. ACF also, conducted other nutrition surveys in Dadu district in the periods; October- November 2007, June 2008, and October 2011. The design of the nutrition surveys varied (although all based on SMART methodology) and were conducted at different seasons of the year, so that results are not strictly comparable. However they are important in giving a picture of the evolution of nutrition situation of Dadu district at various points in time throughout a five-year period and are summarized in Table 9 in the results section of this report. These trends show that GAM rates have been above the World Health Organization's (WHO) 15% emergency threshold even before the 2010 floods.

Pakistan has a government strategy to address malnutrition, as laid out in the Pakistan Integrated Nutrition Strategy (PINS), a multi-sectoral strategy that has been developed in 2011. PINS recognizes the nutritional problem, particularly high GAM and stunting rates and defines clear short term, medium term, and long term interventions and targets by using the immediate, underlying, and basic interventions. The implementation of the strategy recommends a National and Provincial Multi-sectoral Nutrition Board, creation of a simple Nutrition Information System and an intersectoral working group. The intersectoral working group will be made up of the 5-6 nutrition-related sectors that provide technical input to the Nutrition Board, and that mainstreams nutrition into all development and humanitarian projects.

3 National Nutrition Survey of Pakistan. Department of pediatrics and child health, Aga Khan University, Pakistan, Pakistan Medical Research Council (PMRC), Nutrition Wing, Cabinet Division, Government of Pakistan. Supported by Unicef Pakistan. Nov 2011. 4 Evaluation of community management of acute malnutrition (CMAM); Pakistan country case study, UNICEF, July 2012 5Flood Affected Nutrition Surveys, Sindh Province, October-November 2010, Unicef, ACF-CA, Department of Health of Pakistan 3

A coordinating body of nutrition-oriented donors was envisaged and would function as a donor pool where agencies and organizations developing nutrition related projects or programs for funding can submit proposals to be taken up by interested donors in a coordinated way6. An operational plan for PINS has been published with key nutrition interventions7. In addition, there has been a recent plan by the Ministry of Health (MoH) to start implementation of nutrition activities through the Pakistani People Health care Initiative (PPHI) in 4 districts while supporting national NGOs to continue implementing in 11 districts in Sindh.

ACF has supported integration of CMAM activities to the health system’s Basic Health Units (BHUs) activities from September 2011 up to date (December 2012). In this endeavor, ACF supports one Nutrition Stabilization Centre (SC) and 9 Supplementary Feeding (SFP)/ Outpatient Therapeutic Program (OTP) Sites8. Supplies for treatment of malnutrition are provided by UNICEF and WFP. Merlin International has also supported emergency treatment of malnutrition in 12 OTP/SFP sites9 in Dadu District. Children with SAM and Moderate Acute Malnutrition (MAM) under the age of five and Pregnant and Lactating Women (PLW) are the beneficiaries.

To ensure sustainability in treatment of malnutrition in the district, ACF’s nutrition program has also built the capacity of the District Health Office (DHO) staff in CMAM. This has mainly been done through trainings delivered to health care providers, Lady Health Workers (LHWs), Community Health Workers (CHWs) and Community Nutrition Volunteers (CNVs).

Between September 2011 and December 2012, a total of 3,910 SAM and 9,671 MAM children, as well as 4,451 MAM PLW’s were treated and recovered in the CMAM program. Also, 185 SAM cases with medical complications recovered in the stabilization center at Mehar Hospital.

In order to continue monitoring the nutritional situation in Dadu district, and to inform program actions in future nutrition intervention in the district, ACF implemented a nutrition survey in Dadu in December 2012.

.II. Objectives

The survey was guided by the following objectives:

• To determine the prevalence of acute malnutrition among 6-59 months old children; • To estimate crude and under-five mortality rates; • To investigate household food security and food consumption practice; • To estimate morbidity rates of children below five years; • To determine the Infant and Young Child Feeding Practices (IYCF) among children 0-23 months of age; • To determine the proportion of households with access to safe water and sanitation; • To give appropriate recommendations for intervention programs in the district.

6 Pakistan Integrated Nutrition Strategy (PINS) operational plan (July 2011-Dec 2012) 7 Scaling Up a Set of Direct Nutrition Interventions: Four Key elements: CMAM, Infant and young child feeding and hygiene, multi micro nutrient supplementation and deworming, food fortification, access to safe water and sanitation. PINS Operational Plan; July –December 2012 8 Mounder (Mounder UC), Bahawalpur (Bahawalpur UC), Kamal Khan (Kamal Khan UC), Qasbo (Torre UC), Bughio (Bughio UC), Essa Khan (Buttra UC), Dogar (Pariya UC), Nao Goth (Nao Goth UC) and Mangwani (Magwani UC) BHU/OTP sites distributed in the Talukas of Dadu, K.N. Shah, Johi and Mehar 9 RHC Sita Road, RHC Drigh Bala, GD Kakar, Mitho Babar, GD Chhini, Tando Rahim Khan, BHU Patgul Mohammad, BHU Sawro, BHU Chowkandi, BHU Rawat Khan Leghari, BHU Phulji Village and RHC Radhan OTP and SFP sites in the same district 4

.III. Methodology

The nutrition survey undertaken in Dadu district employed the Standardized Monitoring and Assessment of Relief and Transitions (SMART) methodology and was conducted during the period of 3rd to 14th December 2012.

Calculation of sample size The sample size was calculated based on parameters listed in Tables 2 and 3.

Table 1: Sample size calculation for anthropometric survey

Parameters for sample size calculation Estimated prevalence 10 19.5% Precision 5% Design effect 1.8 Average household size11 7 % under five 14% % non response 3% Households to be included 552 Children to be included 473

Emergency Nutrition Assessment (ENA) for SMART software was used to calculate the sample size for anthropometric and mortality surveys as 552 and 480 households respectively. The larger sample size of the two--552 households - was used (Table 2). In the calculation of the mortality sample size, a recall period of 101 days was used on the basis of beginning of recall period being the time of the break of the Ramadhan fast (24th August 2012). This was the most memorable event and would be ideal for reference in the retrospective mortality questions. After determining the number of households that would be completed effectively in one day (that is 15 households), the appropriate number of clusters were determined (numbering 37). The minimum number of children that would need to be measured (473) was also determined. The minimum population to be included was 3,261 (Table 3).

Table 2: Sample size calculation for mortality survey

Parameter for sample size calculation Estimated CMR 0.70 Precision 0.4 Design effect 1.8 Recall period (Days) 101 Average household size 7 % non response 3 Population to be included 3,261 Households to be included 480

10 Based on the on Nutrition survey, K.N. Shah and Mehar Dadu Taluka, Sindh province Pakistan. October-November 2011 11 Pakistan health and demographic data 5

Two-stage cluster sampling was employed to randomly assign clusters to villages and randomly select households for measurement thus:

Stage One: The primary sampling unit (PSU) is a village while the basic sampling unit (BSU) is a household12.

Dadu survey has variety of conditions that influence accessibility to villages. Common ones include insecurity as well as blockade on pass roads due to climatic conditions such as flooding. The survey area list of villages, which are the smallest units, had their approximate population indicated13 and their situation accessed. There was credible information that all the 36 villages in Bothro UC out of the total 1,592 villages listed for each of the 52 UCs, were not accessible due to insecurity14. As such the entire Bothro’s UC villages were not included in the first stage of sampling and thus the unveiled survey results will not be representative of the mentioned UC. With the use of the ENA for SMART software 37 clusters were randomly assigned to the villages that were accessible in Dadu district, employing probability proportional to population size (PPS) method.

Stage Two: In the second stage, ballot and systematic random sampling methods were used accordingly. 15 households were selected in each village. In some villages, a complete list of households was obtained while in others, where it was possible to establish a pattern in the household's arrangement, segmentation was done and systematic random sampling used to select households within the identified segments.

There are two areas that could not be accessed during the survey, despite the fact that they were included in the first stage of sampling. In one village (Misri Khan Chandio in UC Pariya in Taluka K.N. Shah) insecurity broke out the day before data collection while in the second village (Aitibar Chandio in UC Fareed Abad in Taluka Mehar) the bridge connecting it to Dadu (known as Fareed Abad Bridge) was swept away by floods. These villages were represented by clusters 11 and 27 respectively. They were replaced by Reserve clusters (RC) in Village Torri, UC Chinni, Taluka Johi and another RC in village Hussain Depar, UC Qazi Arif, Taluka Mehar.

In all selected households all 6 to 59 months children were measured. A mortality questionnaire was also administered in all households including those without children. The questionnaires collecting information on food security, water sanitation and hygiene (WASH) as well as infant and young child nutrition (IYCN) were also administered.

.IV. Results

This preliminary report gives a brief overview of nutrition overview and factors that affect the nutrition situation of Dadu district. A more comprehensive report will follow. All the households targeted (552) were interviewed and all 6-59 months children (712) measured. 17 children were missing from the households while 1 child was reported as paralyzed and as such, it would not be possible to take anthropometric measurement on the child (Table 4).

12 The definition of a household used referred to a shelter whose residents ate from the same “cooking pot” and whose members were not necessarily related to one another 13 Village directory of villages in Sindh, Goth bad directorate of Revenue Board, 1987/ 1988 revised in 2010/ 2011 14 Background information of Dadu district situation prior to survey 6

Table 3: Information related to sample size, absent households and missing children

Information Households interviewed 552 Children measured 712 Replaced households 0 Absent households 0 Paralyzed children 1 Missing children 17

.IV.1. Nutrition Indicators (WHO standards 2006, and NCHS 1977 standards)

GAM and SAM rates were calculated in ENA software (ENA 2011) with 5 SMART flags being excluded (final n = 707).

• The prevalence of oedema was 0% in Dadu. • Dadu district had a prevalence of GAM of 13.0% (10.3%-16.4%) and SAM of 3.8% (2.5%- 5.7%) based on weight-for-height z-scores results, World Health Organization (WHO) 2006 standards, 95% Confidence Interval. According to WHO interpretation level of malnutrition prevalence, these results showed that the U5 nutritional situation was serious. It is worthwhile to note that the previous surveys that were stratified for Talukas of K.N Shah and Mehar were homogenous and as such, the current survey was designed as one for the whole district of Dadu. Therefore the two surveys, (one done in November 2011 and the present one) are not rigorously comparable but the trends observed with GAM and SAM rates give a picture of a likely nutritional situation taking note that there are factors that could be linked in the improvement of the nutrition situation in Dadu district. • The analysis based on MUAC showed similar results with prevalence of GAM of 15.2% (11.9% - 19.2%, Table 6).

In the final report (to be released in the coming weeks) various factors that contributed to low GAM rates will be further discussed.

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Table 4: Prevalence of wasting among 6-59 months children, WHO 2006 Standards (SMART flags excluded)

Indicators Dadu survey (December 2012) GAM16 13.0 % WHZ (<-2 z-score) or oedema (10.3% - 16.4%) WHO, 200615 standards (n=707) 17 SAM 3.8 % WHZ (<-3 z-scores) or oedema (2.5% - 5.7%)

GAM 12.1 % WHZ (<-2 z-score) or oedema (9.6% - 15.2%) NCHS 1977 standards (n=710) SAM 1.3 % WHZ (<-3 z-scores) or oedema (0.5% - 3.5 %)

Table 5: Prevalence of GAM and SAM based on MUAC Indicators Dadu survey (December 2012) n=712 GAM (108) 15.2 % (< 125 mm and/or oedema) (11.9% - 19.2%) SAM (23) 3.2 % (< 115 mm and/or oedema) (2.0% - 5.1%)

Table 6: Prevalence of chronic malnutrition (stunting) and underweight, WHO 2006 Standards (SMART flags excluded) Indicators Dadu survey (December 2012) Stunting (305) 43.4 % HAZ (<-2 z-score) (37.1% - 50.1%) (n=702) Underweight (224) 31.7 % WAZ (<-2 z-score) (25.9% - 38.2%) (n=706)

• The results showed critically high levels of stunting and underweight as indicated in Table 7 and in comparison with WHO thresholds outlined in Table 8. • The GAM rates were relatively low while the stunting and underweight rates remained high in Dadu district. It is important to note that the prevalence of chronic malnutrition (stunting) and underweight has been critically high among U5 children Sindh province wide with the stunting and underweight rates of 49.8%, and 40.5% respectively3.

15World Health Organization (WHO); Multicentre Growth Reference Study Group. Assessment of differences in linear growth among populations in the WHO Multicentre Growth reference Study, 2006 16 Global Acute Malnutrition- includes children less that -2 z-score and/or oedema 17 Severe acute malnutrition-include children less that -3 z-score and/or oedema 8

Table 7: Comparison of rates of wasting, stunting and underweight in Dadu Survey to the WHO thresholds Index (based on the Description-Critical/ Dadu district survey results- total) Very high WHO 2006 Global Wasting >15% 13.0% If > 20%, then Very Critical Global Stunting >40% 43.4% Global Underweight >30% 31.7%

Malnutrition in Dadu in Consequent surveys

Previous nutrition surveys have been conducted in Dadu district utilising various designs but majorly using the SMART standard methodology. The general picture given by the malnutrition rates reported in these surveys was that of GAM rates above 15%, which is the WHO critical threshold that qualifies for emergency intervention. The comparison of results of the previous surveys in relation to the current survey is tabulated (Table 9) and illustrated in Figure 2 below.

The nutrition survey results unveiled in December 2012 in Dadu nutrition survey shows a drop in SAM and more significant in GAM. This notwithstanding, the following points would be noted in relation to the current GAM rates:

There is presence of Non-Governmental Organization (NGOs); namely ACF International and Merlin International who are supporting nutrition intervention program (CMAM) in various UCs in Dadu district for more than a year. There has been active screening at community level, admission and treatment of children in SC, OTP and SFP as well as of pregnant and lactation women in SFP. This has likely contributed significantly to reduction of wasting among Dadu district population.

Table 8: Summary of the nutrition surveys conducted in Dadu district including current survey (2007- 2012).

Dadu District Nutrition survey results Indicators Oct-Nov 2007 June 2008 Oct 2011 Dec 2012

GAM19 17.8% 28.3% 19.5% 13.0 % WHZ (<-2 z- (14.8% -20.9%) (23.6% - 33.0%) (17.6% -21.5%) (6.4% – 10.3%) WHO, score) or oedema 18 2006 20 standards SAM WHZ (<-3 z- 3.2% 5.7% 5.3% 3.8 % scores) or (1.9% - 4.5%) (3.8% - 7.6%) (4.2% - 6.6%) (2.5% - 5.7%) oedema

18World Health Organization (WHO); Multicentre Growth Reference Study Group. Assessment of differences in linear growth among populations in the WHO Multicentre Growth reference Study, 2006. 19 Global Acute Malnutrition- includes children less that -2 z-score and/or oedema 20 Severe acute malnutrition-include children less that -3 z-score and/or oedema 9

Results can also be summarized as in Figure 2:

Figure 2: Summary of the nutrition surveys conducted in Dadu district (2007- 2012)

Summary of the Nutrition surveys completed in Dadu District 30% WHO-GAM

25% WHO-SAM 20% NCHS-GAM 15% NCHS-SAM 10% WHO Critical GAM 5% WHO critical SAM 0% (Asian Region) Oct-Nov 2007 June 2008 Oct 2011 Dec 2012

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.IV.2. Health indicators

• The measles vaccination coverage was 53.0%. The Dadu district medical officer in charge of epidemiology noted that there was a possibility of low coverage reporting in immunization in the sense that the impact of the core strategy on immunization (routine immunization) has not been optimal in meeting the target coverage of 80%21. Previous nutrition survey of Dadu - as verified through health card and care takers’ recall – in June 2008 indicated measles coverage of 3.0% and 44.2% while the survey implemented in November 2011 reported 5.8% and 61.4% of immunized children respectively. The current reported immunization is consistently low and below the national coverage targets of between 80% and 90%3. Provincial health ministry undertook preliminary investigations and launched emergency response to the outbreak the month of December 2012.

In the month of October 2012, 6 cases of measles were reported in Dadu district in the village Bug Burirra in UC Burirra, Taluka K.N.Shah. Action was taken immunize children with measles vaccine; nevertheless, district wide scale up of immunization is necessary to forestall upsurge of any cases of measles in the district22.

• Results of coverage on children who have been dewormed were 25.9% (Table 10). This proportion is below target established through WHO World Health Assembly (2001) that recommends a target of 50% by countries to reduce the prevalence and the intensity of soil-transmitted helminthes, and a target of regular deworming of at least 75% of school-age children at risk23.

• The Bacillus Calmette–Guérin (BCG), a vaccination against tuberculosis coverage was 64.1%. This is far below target of 90% as set by national EPI guidelines24.

• The Vitamin A coverage for 6-59 months old children was 87.8% while that of children 6-11 months was 83.5%. Both coverage rates are below the national targets of 90% coverage (Table 11).

Table 9: Measles and BCG vaccination, and deworming coverage

Vaccination coverage Verified by: n % Card: 188 27.3 % Measles (≥9-59m) n=689 Recall: 177 25.7 % Total 365 53.0 % Card 265 31.9% BCG (6-59 months) n=729 Scar 202 23.7 % Total 467 64.1 % Deworming coverage (≥12 months) Recall 165 25.9% n=638

21 Dadu presentation on measles coverage. Dadu district. Dr Zahid, 2012 22 Disease early warning system and response in Pakistan; Weekly epidemiological bulletin: Volume 3, Issue 42, Wednesday 24 October 2012 (DEWS) 23 WHO (2010) Working to overcome the global impact of neglected tropical diseases: first WHO report on neglected tropical diseases. Geneva: WHO 24 Pakistan Expanded Programme on Immunization (EPI) guidelines, PILDAT May 2010 11

Table 10: Vitamin A supplementation coverage Vitamin A n % supplementation Children 6-59 m (n=729) 640 87.8 % Children 6-11 m (n=91) 77 83.4 %

.IV.3. Morbidity

• The percentage of children who were reported to be sick two weeks prior to the survey was 64.7%. • Percentage of children with fever as reported illness in the last two weeks of the interview was 78.8% (Table 13). • The occurrence of watery diarrhoea was high (32.2%; Table 13). • Other diseases prevalence (12.1%) were reported as chronic chest infection, other chronic diseases, ear infection, hepatitis, kidney problems, scabies, skin diseases, suspected TB, Tetanus, unknown diseases, and vomiting.

Table 11: Proportion of ill among 6-59 months children

Morbidity number ill % Proportion of children reported during the two 472 64.7 % weeks prior survey (n=729)

Table 12: Illnesses that occurred to children in the previous two weeks

Illness (n=416) Number ill %

Diarrheal (watery) 152 32.2 %

Diarrheal (bloody) 7 1.5 %

Fever 372 78.8 %

Fever with chills 66 14.0 % Cough or/and Cough with difficult 288 61.0 % breathing Others25 57 12.1 %

25 Chronic chest infection, other chronic disease, ear infection, hepatitis, kidney problems, scabies, skin diseases, suspected TB, Tetanus, Unknown diseases, vomiting 12

.IV.4. Retrospective mortality rates

Household mortality information was obtained retrospectively over 101 days prior to interview and results are presented in Table 14. The crude mortality rate (0.44 (0.26-0.77) (95% CI) and under-five mortality rate (0.64 deaths/10,000 under-five children/day) were below 0.4 deaths/10,000 under five children /day and 0.9 deaths/ persons /day respectively for South Asian region26.

Table 13: CMR and U5MR (101-day recall period)

MORTALITY 27 CMR 0.44 (0.26-0.77) (95% CI) (total deaths/10,000 people / day) U5MR (deaths in children under five/10,000 children under five 0.64 (0.28-1.47) (95% CI) / day)

.V. Preliminary Conclusions and initial recommendations

Malnutrition levels are below the critical global acute malnutrition (GAM) threshold of 15%. However, assessment of other factors that influence the nutritional status of individual such as household food security, WASH and IYCN will give appropriate picture regarding aggravating factors that could place the rate of malnutrition as serious. Comprehensive analysis of factors that affect malnutrition in Dadu will be released in the final nutrition survey report.

.V.1. Initial Recommendations

• Continued implementation and also scale-up of the Community Management of Acute Malnutrition (CMAM) intervention program to cover all Talukas in Dadu district. Interventions should be strengthened to enable early referral of moderately malnourished children to reduce the number of children who slip to severe forms of malnutrition (SAM).

• Strengthen integrated approach to prevention of malnutrition and morbidity through effective WASH messages at the household level.

• Immediate scale up of EPI services to address low immunization coverage and to establish monitoring mechanism to ensure proper and timely reporting of in the district.

A more comprehensive report with additional indicators and further analysis will be released in due course

26 The Sphere Project: Humanitarian charter and Minimum standards in Humanitarian response; Version 2011. 27 Crude mortality rate is calculated as the number of deaths per 10,000 persons per day while under-five mortality is the number of deaths per 10,000 under five year old children per day. 13