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ITN Access and Use Report - 2017

Hannah Koenker, Emily Ricotta, & Bola Olapeju

August 3, 2017 This report is made possible by the generous support of the American people through the United States Agency for International Development (USAID) under the terms of USAID/JHU Cooperative Agreement No: AID-OAA-A-14-00057. The contents do not necessarily reflect the views of USAID or the United States Government.

Recommended citation:

Koenker H, Ricotta E, Olapeju B. August 2017. Insecticide-Treated Nets (ITN) Access and Use Report. Baltimore, MD. PMI | VectorWorks Project, Johns Hopkins Center for Communication Programs.

ITN Access and Use Report – August 3 2017 2 Table of Contents

ITN Access and Use Report – August 3 2017 3 Abbreviations

DHS Demographic and Health Survey MICS Multiple Cluster Indicator Survey MIS Malaria Indicator Survey ITN Insecticide-treated net IRS Indoor Residual Spraying LLIN Long-lasting insecticidal net PMI President’s Malaria Initiative

Updates

This report was updated August 3, 2017. This report now contains results from 95 household surveys in 44 countries.

Questions and comments can be directed to [email protected] for inclusion in subsequent updates of this report.

Key findings across PMI focus countries

Overall  All but 6 PMI countries have the majority of their regional use:access ratios above 80.

 Three countries, Mozambique, Senegal and Guinea, have a mix of regions at the red, yellow, and green categories, with specific regions showing that low use of available nets is likely due to dry season, higher altitude, and/or lower prevalence.

 Four countries appear to have below target use:access ratios over most of the country: Ghana, Nigeria, Senegal, and Zimbabwe. Senegal’s use:access appears, however, to be highly seasonally driven. Nigeria’s use:access ratios have improved in many instances between the 2013 and 2015 surveys.

 Zimbabwe and Nigeria have the lowest use:access ratios, looking at the most recent datasets. Additional research in Nigeria indicates that zonal and seasonal influences contribute to larger net use variations in some areas of the country.

 ITN access remains well below target for the majority of countries, indicating more nets are needed to fill gaps within households.

Wealth Quintiles  Five countries (Ghana, Guinea, Nigeria, Senegal, and Zimbabwe) show below-target use:access ratios when viewed by wealth quintile.

ITN Access and Use Report – August 3 2017 4  Of the 18 countries with available data, six demonstrate a mild pro-poor trend in use:access ratios, with poorest households having better use of available nets compared to richer households. Of these six, all are above the 80 targets. The remaining 12 countries show no observable differences in use:access among wealth quintiles.

 Nigeria shows a pro-poor trend in use:access in 2015, 2011, and 2008, but pro-rich trends in 2013.

Urban/Rural  There are no programmatic differences in urban/rural use:access ratios, apart from Ghana, where mean use:access is 0.44 in urban areas and 0.74 in rural areas, and in Mozambique, where urban areas have moderately better use:access (0.85) compared to rural areas (0.77).

Use of ITNs in IRS and non-IRS households  Use:access ratios are not programmatically different between sprayed and unsprayed households.

Background

National results for ownership, access, use, and the use:access ratio have been described in Koenker et al previously in detail1. However, national results conceal variations by region, which may result from differences in survey timing vis à vis rainy season (among other reasons). Variations in other subgroups such as wealth quintile or urban/rural residence may offer ways to identify target groups that do not use their available nets to the fullest degree.

Definitions

“Ownership”: the proportion of households that own at least 1 ITN. Ownership indicator provides an estimate of the minimum threshold for ITN coverage – if the household has at least one. However, ownership does not take into account whether the household has enough nets for all family members.

“Access”: the proportion of the population with access to an ITN within their household. Also called “population access” or “ITN access”. This indicator is calculated based on the number of ITNs in the household and the number of household members. Over a large sample, it calculates the proportion of people who should have (in principle, based on the assumption that one ITN can be used by two people in the household) an ITN to sleep under. It cannot be calculated on an individual basis.

1 Koenker H, Kilian A (2014) Recalculating the Net Use Gap: A Multi-Country Comparison of ITN Use versus ITN Access. PLoS ONE 9(5): e97496. doi: 10.1371/journal.pone.0097496

ITN Access and Use Report – August 3 2017 5 “Use”: the proportion of the population that slept under an ITN the night before the survey. Also called “population use” to distinguish it from use of ITNs by children under five or pregnant women.

“Use:access ratio”: the result when dividing use by access (i.e. use/access). Gives an estimate of the proportion of the population using nets, among those that have access to one within their household. As it is a ratio, it is not technically a percentage, although it can be interpreted as such. This indicator provides data on the behavioral gap for net use – rather than a use gap because not enough nets are available.

Methods

For each dataset three indicators were calculated: individual access to ITN within the household, individual use of ITN the previous night, and household ownership of at least one ITN. The ratio of population ITN use to population ITN access within the household was calculated and is referred to here as the use:access ratio.

ITN use was calculated in the household member file, as was access to an ITN. This appropriately weights the access ratio for each household according to the number of members in each household. (Running the access calculation and calculating the mean within the household file does not take into account the number of people in each household, making that result an unweighted mean.) However, ITN ownership is calculated within the household file. Data management and analysis was done using Stata 14 (Stata Corporation, College Station, Texas, USA). All analyses accounted for survey design including sampling weights where applicable using the survey command family in Stata.

The survey indicator of access to ITN within the household was calculated from the datasets of individual household members as recommended by MERG2. First, an intermediate variable of “potential ITN users” was created by multiplying the number of ITN in each household by a factor of 2.0. In order to adjust for households with more than one net for every two people, the potential ITN users were set equal to the defacto population in that household if the potential users exceeded the number of people in the household. Second, the population access indicator was calculated by dividing the potential ITN users by the number of de-facto members for each household and determining the overall sample mean of that fraction.

Use of an ITN the previous night was calculated for each de facto member of the household, i.e. those present in the house the previous night, as recommended by MERG using the listings of net users from the net roster2. Household ownership of at least one ITN was also calculated for each dataset based on the

2 MEASURE Evaluation, MEASURE DHS, President's Malaria Initiative, Roll Back Malaria Partnership, UNICEF, et al. (2013) Household survey indicators for malaria control.

ITN Access and Use Report – August 3 2017 6 number of ITN observed in the household and defining an ITN as a long-lasting insecticidal net (LLIN) identified by its label or a net that was treated with an insecticide within the last 12 months.

Access, use, and ownership were stratified by region, by rural/urban status (residence), wealth quintile, and where available, whether the household had received IRS in the last 12 months for each country. Cluster weighted univariate regressions were conducted to assess whether significant differences existed between strata.

ITN Access and Use Report – August 3 2017 7 Results

National results for ownership, access, use, and the use:access ratio have been described in Koenker et al in detail (Koenker, 2014), and national results for all countries are presented below in Table 1 for quick reference. However, national results conceal variations by region, which may result from differences in survey timing in regards to rainy season. Regional or provincial results, indicators by wealth quintile and by urban or rural residence are presented below for each country where data is available.

Key Global Findings:

% of % of population with % of population Ratio of households access to an ITN within that used an ITN use:access owning ≥1 ITN their own household the previous night Median (2005-2015) 54.7% 37.2% 31.5% 0.87 Mean (2005-2015) 52.2% 37.3% 31.3% 0.81 Median pre-2010 40.0% 22.5% 19.8% 0.81 Median post-2010 59.4% 40.1% 35.0% 0.87 Mean pre-2010 35% 22% 18% 0.77 Mean post-2010 58% 43% 36% 0.82 Minimum 3.5% 1.5% 0.3% 0.11 Maximum 93.0% 78.8% 68.6% 1.19

Results for ratio of use:access are color-coded as follows:

Note 1: Color coding of use:access ratios and explanation

Use:access ratio is good, with at least 80% of those with access to an ITN ≥0.80 using one the previous night

≥0.60- Use:access ratio is below target level; improvements should be made <0.80

Use:access ratio is poor; explore reasons for non-use of available nets, such as <0.60 dry season, low-transmission area, and IRS activities.

Table 1: National results for ITN ownership, access, use, and use:access ratio in PMI Focus Countries

ITN Access and Use Report – August 3 2017 8 % of population % of population % of households with access to an that used an ITN Ratio of Country | Survey | Year owning ≥1 ITN ITN within their the previous use:access own household night Angola MIS 2006-7 27.5 14.5 11.9 0.82 Angola MIS 2011 34.5 19.0 18.9 0.99 Angola DHS 2015-16 30.9 19.7 17.6 0.89 Benin DHS 2006 24.5 14.7 14.7 1.00 Benin DHS 2011-12 81.8 64.0 62.6 0.98 Cambodia DHS 2005 4.5 3.1 3.0 0.96 DRC DHS 2007 9.2 4.2 4.3 1.03 DRC MICS 2010 51.0 30.1 30.9 1.03 DRC DHS 2013-2014 70.0 46.5 50.2 1.08 Ghana DHS 2008 41.7 30.1 20.9 0.69 Ghana MICS 2011 49.3 38.0 27.8 0.73 Ghana DHS 2014 68.3 59.0 35.7 0.60 Ghana MIS 2016 73.0 65.8 41.7 0.63 Guinea DHS 2005 3.5 1.5 1.1 0.77 Guinea DHS 2012 47.4 25.3 18.9 0.75 Kenya DHS 2008 55.7 42.3 35.1 0.83 Kenya DHS 2014 58.9 48.2 42.6 0.88 Kenya MIS 2015 62.5 52.5 47.6 0.91 Lao MICS 2012 47.9 40.2 40.9 1.02 Liberia MIS 2009 47.2 25.4 22.8 0.90 Liberia MIS 2011 49.7 30.8 32.1 1.04 Liberia DHS 2013 54.6 37.0 31.7 0.86 Madagascar DHS 2008 57.0 34.7 36.6 1.05 Madagascar MIS 2011 80.5 57.3 68.4 1.19 Madagascar MIS 2013 69.2 47.8 55.0 1.15 Madagascar MIS 2016 79.5 62.1 68.2 1.10 Malawi DHS 2010 56.8 37.6 29.0 0.77 Malawi MIS 2012 55.0 37.2 40.9 1.10 Malawi MICS 2013-14 78.0 56.6 53.9 0.95 Malawi DHS 2014 70.2 51.8 52.5 1.01 Malawi DHS 2015-16 56.9 38.8 33.9 0.87 Mali DHS 2006 50.0 29.7 21.4 0.72 Mali A&P 2010 85.9 61.6 56.2 0.91 Mali DHS 2013 84.4 65.1 60.4 0.93 Mali MIS 2015 93.0 69.5 63.8 0.92 Mozambique DHS 2011 54.7 37.0 29.4 0.80 Myanmar DHS 2015-16 27.0 21.2 15.6 0.74 Nigeria DHS 2008 8.0 4.8 3.2 0.68 Nigeria MIS 2010 41.5 28.7 23.3 0.81

ITN Access and Use Report – August 3 2017 9 Nigeria MICS 2011 41.1 28.6 12.3 0.29 Nigeria DHS 2013 49.5 36.1 12.9 0.36 Nigeria MIS 2015 68.8 54.7 37.3 0.68 Rwanda 2007-8 DHS 55.6 38.1 39.7 1.04 Rwanda DHS 2010 82.0 64.2 57.7 0.90 Rwanda MIS 2013 82.6 65.9 60.9 0.92 Rwanda DHS 2014-2015 80.6 63.8 61.4 0.96 Senegal MIS 2006 36.3 17.5 12.2 0.69 Senegal MIS 2008 60.4 34.9 22.9 0.66 Senegal DHS 2010 66.2 38.1 28.9 0.76 Senegal cDHS 2012 72.8 57.4 40.7 0.71 Senegal cDHS 2014 74.4 58.4 40.4 0.69 Senegal cDHS 2015 76.8 66.0 51.0 0.77 Tanzania THMIS 2007-8 39.2 25.4 20.3 0.80 Tanzania DHS 2010 63.8 46.6 45.1 0.97 Tanzania THMIS 2011 90.9 74.5 68.4 0.92 Tanzania DHS 2015-16 65.6 55.9 49.0 0.88 Uganda MIS 2009 46.7 31.6 25.6 0.81 Uganda DHS 2011 59.8 44.7 35.0 0.78 Uganda MIS 2014-15 90.2 78.8 68.6 0.87 Zambia DHS 2007 53.3 33.9 23.0 0.68 Zambia DHS 2013-14 67.7 46.6 34.9 0.75 Zambia MIS 2015 79.8 65.0 56.9 0.88 Zimbabwe DHS 2005-2006 9.1 4.8 2.4 0.50 Zimbabwe DHS 2010 28.8 20.2 8.7 0.43 Zimbabwe MICS 2014 44.7 34.0 24.1 0.71 Zimbabwe DHS 2015 47.9 37.2 8.5 0.23

ITN Access and Use Report – August 3 2017 10 Table 2: National results for ITN ownership, access, use, and use:access ratio in non PMI-Focus countries

% of % of population % of population households with access to an that used an Ratio of Country | Survey | Year owning ≥1 ITN within their ITN the use:access ITN own household previous night Burkina Faso DHS 2010 56.9 36.1 31.5 0.87 Burkina Faso MIS 2014 89.8 71.2 67.0 0.94 Burundi DHS 2010 52.0 39.1 37.8 0.97 Burundi MIS 2012 66.0 46.0 48.6 1.06 Cameroon DHS 2011 18.3 10.8 7.6 0.71 Central African Republic MICS 49.2 31.1 33.3 1.07 2010 Chad MICS 2010 42.0 27.7 9.2 0.33 Chad DHS 2014-2015 51.0 39.9 21.7 0.54 Comoros DHS 2012 59.1 41.2 38.3 0.93 Congo (Brazzaville) DHS 2011-12 33.1 22.6 26.0 1.15 Cote d’Ivoire DHS 2012 67.3 49.0 33.2 0.68 Gabon DHS 2012 36.1 26.9 26.7 0.99 Gambia DHS 2013 68.9 45.3 36.9 0.82 Guyana DHS 2012 25.6 22.3 21.1 0.95 Haiti DHS 2012 18.8 10.8 7.1 0.65 Mauritania MICS 2011 43.5 24.2 15.1 0.62 Namibia DHS 2006 20.2 12.8 5.5 0.43 Namibia DHS 2013 24.4 18.1 3.9 0.22 Niger DHS 2006 43.0 19.6 4.4 0.22 Niger DHS 2012 61.3 37.3 13.8 0.37 Sao Tome DHS 2008 60.8 51.0 45.9 0.90 Sierra Leone DHS 2008 36.6 19.2 18.8 1.02 Sierra Leone MICS 2010 37.8 18.2 20.7 1.13 Sierra Leone DHS 2013 64.4 37.7 41.8 1.11 Suriname MICS 2010 6.6 4.7 4.1 0.89 Swaziland DHS 2006 4.4 2.3 0.3 0.11 Swaziland MICS 2010 10.1 7.6 1.1 0.15 Timor Leste DHS 2009 40.9 25.5 29.2 1.14 Togo MICS 2010 57.1 38.0 34.6 0.91 Togo DHS 2013 65.4 48.8 33.6 0.69

ITN Access and Use Report – August 3 2017 11 PMI Focus Countries

Angola

Two surveys were available in Angola, the 2006-2007 MIS and the 2011 MIS. Rains in the south are from February through April. In the north, rain is from October to May. The northernmost parts of Angola experience rain throughout most of the year. The 2006-2007 survey took place from November, 2006 through March, 2007. Fieldwork for the 2011 MIS was completed January through May, 2011. In 2006-7, 101 of 2,599 households reported being sprayed with IRS (4%); in 2011, 505 of 8,030 households reported spraying (6%); in 2015-16, 239 of 16,109 households reported spraying (1%). An integrated measles/ITN campaign for children under 5 was done in 2006. A subnational universal coverage campaign was done in 2011. Angola’s universal coverage campaign began in 2013 and continued into 2016. (Angola MOP FY15).

2015-16 201 2011 DHS 2006-7 1 2015-16 2006-7 2011 2015-16 2006-7 2011 2015-16 2006-7 MIS MIS MIS MI DHS MIS MIS DHS MIS MIS DHS S % of population with access % of population that used an % of households owning ≥1 ITN to an ITN within their own Ratio of use:access ITN the previous night household Zone Stable Mesoend 20 36 37 11 19 25 10 21 23 0.91 1.11 0.93 emic § Hyperen 51* 30 36 30* 17 24 25* 17 21 0.83 1.00 0.88 demic Instable Mesoend 23 37 22* 12 20 14* 8 19 9* 0.67 0.95 0.67 emic Luanda 23 35 27* 11 19 16* 9 17 16* 0.82 0.89 0.98

ITN Access and Use Report – August 3 2017 12 2015-16 201 2011 DHS 2006-7 1 2015-16 2006-7 2011 2015-16 2006-7 2011 2015-16 2006-7 MIS MIS MIS MI DHS MIS MIS DHS MIS MIS DHS S % of population with access % of population that used an % of households owning ≥1 ITN to an ITN within their own Ratio of use:access ITN the previous night household

Region Cabinda§ 54 61 35 33 46 27 25 47 31 0.77 1.04 1.14 Zaire 47 46* 35 30 28 22 37 28 23* 1.22 1.00 1.05 Uige 55 41* 40 29 22* 25 28 19* 22* 0.98 0.87 0.87 Luanda 23* 35* 27* 11* 19* 16* 9* 17* 16* 0.81 0.89 0.98 Kwanza 35 29* 29* 19 16* 22* 12 14* 15* 0.60 0.84 0.68 norte Kwanza 19* 27* 40 9* 16* 31 6* 19* 19* 0.62 1.17 0.61 sul Malange 49 19* 30 33 12* 18* 24 13* 16* 0.74 1.04 0.90 Lunda 64 25* 44* 45 13* 31 41 17* 30 0.93 1.31 0.98 norte Benguela 23* 47 27 15* 24 18* 7* 24* 16* 0.46 1.03 0.92 Huambo 22* 40* 45* 12* 20* 27 14 23* 29 1.18 1.15 1.11 Bie 11* 3* 34 6* 1* 22 6 2* 22* 1.01 1.15 0.96 Moxico 66 39* 8* 46 20* 6* 35 22* 6* 0.76 1.13 1.08 Kuando 26* 17* 15* 12* 17* 10* 1.16 0.89 kubango Namibe 21* 40* 47* 7* 19* 34* 4* 13* 25* 0.56 0.70 0.73 Huile 12* 45 25* 6* 23 15* 3* 23* 9* 0.55 0.97 0.55 Cunene 10* 14* 19* 5* 8* 10* 3* 8* 8* 0.53 1.05 0.73 Lunda 63 17* 44* 42 8* 31 29 10* 30 0.68 1.34 0.97 sul Bengo 27 52 23* 15* 31 15* 16 30 10* 1.04 0.98 0.62

Wealth

ITN Access and Use Report – August 3 2017 13 2015-16 201 2011 DHS 2006-7 1 2015-16 2006-7 2011 2015-16 2006-7 2011 2015-16 2006-7 MIS MIS MIS MI DHS MIS MIS DHS MIS MIS DHS S % of population with access % of population that used an % of households owning ≥1 ITN to an ITN within their own Ratio of use:access ITN the previous night household Quintile Poorest§ 26 17 28 15 9 18 13 10 15 0.87 1.13 0.85 Poorer 22 31 34* 12 16 23* 10 16 20* 0.83 1.18 0.90 Middle 32 48 35* 16 26 22* 15 27 21* 0.94 1.06 0.93 Richer 28 44 31 14 24 19 11 24 18 0.79 1.00 0.93 Richest 31 37 27 16 21 17 9 17 15 0.56 0.96 0.85

Residen ce Urban§ 29 39 30 15 22 19 11 20 18 0.73 0.91 0.91 Rural 26 32* 32 14 17* 21 13 18 18 0.93 1.06 0.86

IRS No§ 27 34 15 18 12 18 0.80 1.00 Yes 34 46* 13 27* 6 28* 0.46 1.03 *p-value≤0.05 compared to reference group (denoted with §)

Observations While the use:access ratio has been generally high in Angola, the 2011 survey saw all nearly all regions, wealth quintiles, and residences increase their ratio above 0.80. Ownership and access to ITNs tend to increase as wealth increases (peaking in the middle quintile), however, the ratio of use:access declines with wealth in 2006 and 2011, and is relatively similar among wealth quintiles in 2015-16. Overall, access to ITNs remains very low.

ITN Access and Use Report – August 3 2017 14 Implications for programming While access to ITNs is quite low, use of these ITNs is high across most of Angola. There may be seasonal patterns to ITN use particularly in the instable mesoendemic areas. ITN distribution should be increased, and SBCC should be continued throughout the country to maintain the very high use:access ratio here.

ITN Access and Use Report – August 3 2017 15 Benin

Available data for Benin include the 2006 DHS, conducted primarily in September 2006, at the end of the Northern Benin rainy season and just before rains started in the south, and the 2011-2012 DHS, conducted in Littoral in September 2011, just prior to rainy season there, with most fieldwork done in remaining regions in January-March 2012, during their cooler/drier season. In 2011-12, 1,289 households reported being sprayed with IRS, of 17,422 (7%). Benin implemented an under 5 campaign in 2007 and a universal coverage campaign in 2011 and 2014 (Benin MOP FY15).

2011-12 2011-12 2011-12 2006 DHS 2006 DHS 2011-12 DHS 2006 DHS 2006 DHS DHS DHS DHS % of households owning ≥1 % of population that used an ITN the previous night Ratio of use:access ITN Province Alibori§ 8 89 3 68 3 68 0.96 0.96 Atacora 26* 93* 14 77* 13 66 0.93 0.83 Atlantique 13* 75* 9 60* 9 62 1.03 1.01 Borgou 20* 81* 10 62* 10 59 0.93 0.93 Collines 30* 78* 19 62* 19 60 0.99 0.93 Couffo 29* 82* 15 62* 15 60 0.96 0.95 Donga 30* 84 14 64 13 61 0.87 0.93 Littoral 28* 78* 22 65 23 64 1.01 0.97 Mono 25* 74* 16 60* 16 60 1.03 1.00 Oueme 34* 74* 21 58* 22 59 1.06 1.00 Plateau 21* 84 14 68 13 68 0.95 0.98 Zou 27* 79* 16 62* 17 65 1.05 1.04

SES Poorest§ 11 79 6 62 7 61 1.08 0.98 Poorer 17* 81 9 64 10 63 1.08 0.98

ITN Access and Use Report – August 3 2017 16 2011-12 2011-12 2011-12 2006 DHS 2006 DHS 2011-12 DHS 2006 DHS 2006 DHS DHS DHS DHS % of households owning ≥1 % of population that used an ITN the previous night Ratio of use:access ITN Middle 24* 80 13 63 14 62 1.03 0.99 Richer 31* 78 18 64 17 61 0.98 0.97 Richest 39* 80 27 67* 26 65* 0.95 0.97

Residence Urban§ 29 78 19 64 19 62 0.96 0.97 Rural 21* 81* 12 64 12 63 1.04 0.98

IRS No§ 79 63 62 0.98 Yes 94* 79* 70* 0.89 *p-value≤0.05 compared to reference group (denoted with §)

Observations Overall, the ratio between ITN access and ITN use is excellent in Benin, indicating that those who have nets available are using them. There was no significant change between 2006 and 2012 in the ratio, although there was a slight pro-poor trend when looking at wealth quintile in 2006 and the use:access ratio, which disappeared in 2012. In 2006 in general there was a pro-rich trend to ITN ownership, access, and use, although this hid the pro-poor trend in the use:access ratio. By 2012 access and use was relatively consistent among wealth quintiles. In the same vein, in 2006 and 2012 there were differences between urban and rural ownership of nets, but there was no significant difference in access and use. Again the ratio of use:access remained stable between the subgroups and surveys. There was no IRS data collected in the 2006 survey, but the 2012 survey demonstrated that those households with IRS were had significantly higher ownership, access, and use than those without. However, the use to access ratio was higher in the non-IRS group than the IRS group.

Implications for programming Overall improvements in ownership and access appear to reduce disparities among wealth quintiles in Benin, and between urban and rural residents. There is no clear need for prioritizing SBCC messages in certain regions over others; all regions have a use:access ratio of over 0.80.

ITN Access and Use Report – August 3 2017 17 Additional work may be helpful to determine whether dry-season net use and transmission patterns warrant increased SBCC during lower-net use seasons.

ITN Access and Use Report – August 3 2017 18 Cambodia

Cambodia’s 2005 DHS contains information on malaria and ITNs; its 2010 and 2014 DHS surveys do not. Cambodia implemented mass ITN distribution in 2012.

2005 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Region Banteay Mean Chey§ 4.9 3.1 3.5 1.10 Kampong Cham 4.7 3.8 3.0 0.78 Kampong Chhnang 3.5 2.3 2.3 0.97 Kampong Speu 0.5* 0.2* 0.4* 1.66 Kampong Thom 6.4* 4.1 4.3 1.04 Kandal 0.4* 0.2* 0.1* 0.94 Kratie 18.8* 13.4* 11.6* 0.87 Phnom Penh 0.2* 0.1* 0.0* 0.50 Prey Veng Pursat 0.3* 0.1* 0.1* 1.28 Siem Reap 2.8 1.9 1.3 0.69 Svay Rieng Takeo 0.3* 0.2 0.0* 0.20 Otdar Mean Chey 30.4* 20.8* 26.3* 1.26 Battambang & Krong 6.0 3.7* 3.6 0.97 Pailin

ITN Access and Use Report – August 3 2017 19 2005 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Kampot & Krong Kep 3.6 2.5 2.4 0.97 Krong Preah Sihanouk & 11.4* 6.7 7.6 1.13 Kaoh Kong

Preah Vihear & Steung 48.4* 32.3* 30.1* 0.93 Treng Mondol Kiri & Rattanak 38.9* 26.5* 29.3* 1.11 Kiri

Wealth Quintile Poorest§ 9 6 6 1.00 Poorer 6* 4* 4 0.96 Middle 4* 3* 3* 0.97 Richer 2* 2* 1* 0.85 Richest 1* 1* 1* 0.89

Residence Urban§ 2 1 1 0.94 Rural 5* 3* 3* 0.97

Observations Cambodia had an excellent ratio of use:access in 2005, with lower rates in specific regions.

Implications for programming Given the time elapsed since this survey, no programming implications are noted here.

ITN Access and Use Report – August 3 2017 20 DRC

Available data for DRC include the 2013 DHS, the 2010 MICS, and the 2007 DHS. The 2013 DHS was conducted primarily in December-January 2013-2014, during the rainy season (excepting the provinces north of the equator, Oriental and Equatorial, where it was dry). The 2010 MICS was conducted in January-February 2010, also during rainy season in the southern part of the country. The 2007 DHS was fielded from February to July. No IRS data was included in any of the surveys. DRC implemented universal coverage campaigns in 2011-2012 and in 2015-2016.

2007 2013 2007 2010 2013 2007 2013 2007 2013 2010 MICS 2010 MICS 2010 MICS DHS DHS DHS MICS DHS DHS DHS DHS DHS

% of population with access to an % of households owning ≥1 ITN Ratio of use:access ITN within their own household

Province Kinshasa§ 16 52 59 8 29 37 8 35 39 1.10 1.19 1.06 Bandundu 12 42 88* 5 23 63* 5* 24* 70* 1.00 1.07 1.11 Bas-Congo 35* 66* 76* 18* 37* 51* 18* 41 58* 0.97 1.11 1.13 Equateur 4* 28* 83* 2* 13* 57* 2* 14* 63* 1.14 1.08 1.09 Kasai- 7* 19* 58 3* 9* 31 3* 9* 31* 0.99 1.08 1.00 Occidental Kasai- 6* 36* 64 2* 20* 38 2* 24* 43 0.88 1.18 1.11 Oriental Katanga 8* 72* 80* 4* 44* 55* 5* 39 57* 1.11 0.90 1.04 Maniema 13 85* 59 6 64* 37 6* 52* 40 1.10 0.81 1.08 Nord-Kivu 4* 51 60 2* 26 39 2* 27 39 0.97 1.02 0.99 Orientale 3* 72* 47* 2* 51* 33 2* 45 35 0.90 0.88 1.06 Sud-Kivu 6* 50 70* 3* 26 46* 3* 32 51* 1.00 1.22 1.12

ITN Access and Use Report – August 3 2017 21 2007 2013 2007 2010 2013 2007 2013 2007 2013 2010 MICS 2010 MICS 2010 MICS DHS DHS DHS MICS DHS DHS DHS DHS DHS

% of population with access to an % of households owning ≥1 ITN Ratio of use:access ITN within their own household

Wealth Quintile Poorest§ 3 41 59 1 24 39 1 25 42 0.99 1.04 1.09 Poorer 6* 49* 72* 3* 28* 48* 3* 29 53* 1.05 1.04 1.12 Middle 10* 49* 75* 4* 28* 50* 5* 29 55* 1.04 1.04 1.09 Richer 11* 53* 77* 5* 30* 52* 5* 32* 55* 0.95 1.08 1.07 Richest 16* 67* 68* 7* 41* 44* 8* 39* 46 1.07 0.95 1.04

Residence Urban§ 12 58 71 6 35 46 6 34 48 1.05 0.98 1.04 Rural 7* 48* 70 3* 28* 47 3* 29 51 1.00 1.05 1.10 *p-value≤0.05 compared to reference group (denoted with §)

Observations The MICS and DHS data show that there are no particular provinces where ITN use among those with access is worrisome. Nor is ITN use:access ratio related to socio-economic status, or residence. Overall, rates of ITN use are extremely good throughout DRC, assuming nets are available.

Implications for programming There is a need for additional nets to fill gaps at the household level in population access to ITNs; SBCC programming for net use does not appear to need to be targeted to certain areas over others.

ITN Access and Use Report – August 3 2017 22 Ethiopia

The most recent available survey, the 2011 DHS, does not contain the malaria module. The dataset for the 2011 MIS is not available publicly, but ownership results are reported here from the survey report3. An MIS was fielded in late 2015, with funding from PMI and Global Fund, but is not yet available. Ethiopia implemented mass campaigns in 2007, 2010, 2013, but with ongoing large scale ITN distribution since 2005 in all years.

2011 DHS % of population with access % of households % of population that used an ITN Ratio of to an ITN within their own owning ≥1 ITN the previous night use:access household Province Amhara 73.6 B. Gumuz & Gambella 69.0 Diredawa 78.9 Oromia 43.7 SNNPR 57.0 Somali & Afar 45.0 Tigray 65.8

Wealth Quintile Poorest 44.2 Poorer 52.4 Middle 54.6 Richer 31.2 Richest 66.4

3 Ethiopia National Malaria Indicator Survey, 2011. http://www.unicef.org/ethiopia/ET_MIS_2011_Report.pdf

ITN Access and Use Report – August 3 2017 23 2011 DHS % of population with access % of households % of population that used an ITN Ratio of to an ITN within their own owning ≥1 ITN the previous night use:access household Residence Elev <2000m 54.8 Elev >2000m 37.6

ITN Access and Use Report – August 3 2017 24 Ghana

Available data for Ghana include the 2008 DHS, the 2011 MICS, the 2014 DHS, and the 2016 MIS. All surveys were conducted in the September- December period, at the end of the second rainy period. Questions on IRS were not included in the 2008 and 2011 surveys. In 2014, 2,157 households reported spraying with IRS, of 11,835 (18%). In 2016, 779 of 5841 households reported spraying (13%). Ghana implemented mass distributions in 2006-2008, 2011-2012, and 2014-2015.

200 2008 2011 2014 2016 8 2011 2014 2016 2008 2011 2014 2016 2008 2011 2014 2016 DHS MICS DHS MIS DH MICS DHS MIS DHS MICS DHS MIS DHS MICS DHS MIS S % of population with access to % of population that used an % of households owning ≥1 ITN an ITN within their own Ratio of use:access ITN the previous night household Region Western§ 41 43 67 67 30 32 59 59 20 23 38 37 0.66 0.72 0.65 0.63 Central 42 32* 70 83* 30 21* 58 76* 17 17* 42 50* 0.56 0.79 0.73 0.66 Greater 30* 26* 53* 61 24* 20* 49* 54 12* 11* 16* 18 0.51 0.53 0.32 0.34 Accra Volta 43 86* 76* 76* 30 79* 70* 66 22 65* 54* 46 0.72 0.82 0.77 0.69 Eastern 36 78* 73 72 26 71* 64 61 19 49* 38 39 0.72 0.69 0.60 0.65 Ashanti 40 40 70 70 28 28 60 60 19 22 34 43 0.70 0.80 0.57 0.71 Brong 51* 54* 81* 81* 36* 34 70* 72* 32* 27 52* 52* 0.87 0.78 0.75 0.72 Ahafo Northern 54* 67* 71 84* 31 43* 55 77* 23 27 36 51* 0.72 0.64 0.66 0.66 Upper 53* 52 73 94* 37 34 56 88* 26* 28 31 63* 0.71 0.84 0.56 0.72 East Upper 71* 61* 77* 90* 50* 39* 61 80* 42* 31* 38 54* 0.84 0.79 0.61 0.67 West

ITN Access and Use Report – August 3 2017 25 200 2008 2011 2014 2016 8 2011 2014 2016 2008 2011 2014 2016 2008 2011 2014 2016 DHS MICS DHS MIS DH MICS DHS MIS DHS MICS DHS MIS DHS MICS DHS MIS S % of population with access to % of population that used an % of households owning ≥1 ITN an ITN within their own Ratio of use:access ITN the previous night household Wealth Quintile Poorest§ 50 66 80 86 32 45 60 76 28 38 46 61 0.86 0.86 0.77 0.81 Second 46 59* 78 81* 32 43* 64 72 25 36 50 53 0.78 0.82 0.77 0.73 Middle 40* 52* 70* 73* 29 41* 61 65 21* 30* 39* 39 0.70 0.73 0.64 0.61 Fourth 36* 42* 63* 66* 27* 32* 56* 60 17* 21* 25* 32 0.63 0.66 0.46 0.53 Richest 39* 35* 58* 63* 30 29* 54* 57 14* 14* 18* 23 0.47 0.49 0.33 0.40

Residence Urban§ 35 40 60 65 26 31 54 59 15 19 24 30 0.56 0.62 0.44 0.50 Rural 48* 60* 78* 82* 34* 45 64* 72 26* 36* 47* 54 0.77 0.81 0.74 0.74

IRS No§ 49 68 72 38 59 64 36 36 42 0.74 0.61 0.65 Yes 47 72 87* 36 59 78 19 33 44 0.62 0.56 0.57 *p-value≤0.05 compared to reference group (denoted with §)

Observations In 2016, use given access remains extremely low in Greater Accra (0.34), and appears otherwise fairly consistent across regions. Urban households have had consistently lower use:access ratios compared to rural households over the past 9 years. Likewise, in all surveys, use:access ratios decline with increasing wealth. Although each survey was done at generally the same time of year, more work is needed to confirm that rainfall and survey timing were equivalent in all years, particularly by region.

ITN Access and Use Report – August 3 2017 26 Implications for programming It seems likely that low use given access among wealthy and urban households may reflect lower risk perception of malaria. Further investigation into the causes or rationale for low use of nets among these groups is needed. The poorest households are using the nets they have. Seasonal trends, particularly by region, should be examined.

ITN Access and Use Report – August 3 2017 27 Guinea

Available data for Guinea include the 2005 DHS, fielded January to June during dry season and early rains, and the 2012 DHS, which was conducted between June and August during Guinea’s rainy season. Conakry fieldwork was done at the very beginning of rainy season. In 2012 119 households reported spraying with IRS, of 7,109 (1.7%). Guinea implemented an under-five campaign in 2009, and universal coverage campaigns in 2013 and in 2016.

2005 2005 DHS 2012 DHS 2005 DHS 2012 DHS 2005 DHS 2012 DHS 2012 DHS DHS % of households owning % of population with access to an % of population that used an Ratio of use:access ≥1 ITN ITN within their own household ITN the previous night

Region Boké§ 3.9 42 1.7 25 1.0 21 0.57 0.84 Conakry 7.6 36 3.5 19* 3.2 13* 0.92 0.69 Faranah 3.4 64* 1.4 31 0.9 26 0.68 0.85 Kankan 4.6 51 1.5 26 0.9 25 0.58 0.94 Kindia 2.4 42 0.9 21 0.8 14* 0.90 0.67 Labé 0.4 62* 0.3 38* 0.1 18 0.39 0.49 Mamou - 53* - 33* - 12* 0.38 Nzerekore 4.0 45 1.4 23 1.2 22 0.81 0.96

Wealth Quintile Poorest§ 1.8 47 0.6 26 0.3 19 0.48 0.74 Poorer 1.9 49 0.8 26 0.5 21 0.61 0.79 Middle 3.0 52 1.2 28 1.0 20 0.82 0.72

ITN Access and Use Report – August 3 2017 28 2005 2005 DHS 2012 DHS 2005 DHS 2012 DHS 2005 DHS 2012 DHS 2012 DHS DHS % of households owning % of population with access to an % of population that used an Ratio of use:access ≥1 ITN ITN within their own household ITN the previous night

Richer 4.6 50 1.8 27 1.2 21 0.65 0.78 Richest 6.7 39* 3.0 20* 2.8 14* 0.93 0.70

Residence Urban§ 5.7 42 2.4 22 2.1 17 0.87 0.78 Rural 2.7 50* 1.1 27* 0.7 20 0.69 0.73

IRS No§ 47 25 19 0.76 Yes 55 29 26 0.90 *p-value≤0.05 compared to reference group (denoted with §)

Observations Regional variations in household ownership were present in 2012, with Conakry having the lowest rates of ownership. However, DHS data was collected prior to the 2014 mass campaign, which undoubtedly increased coverage. Conakry, Kindia, and most especially Labe and Mamou regions had lower-than-targeted ratios of ITN use:access. Mamou and Labe are in the Fouta Djallon area, which have higher altitudes and cooler temperatures. These low ratios are contributing to the <0.80 ratios observed when looking at SES and at residence. As is observed in some other countries, there is a slight pro-poor trend towards better ITN use:access ratio. There was no difference in ITN ownership, access, or use among households having received IRS and those who did not, although households not receiving IRS had a lower use:access ratio (0.76 compared to 0.90). However, only 119 of 7,109 households reported being sprayed, mostly by private companies.

ITN Access and Use Report – August 3 2017 29 Implications for programming Given the very low ITN use:access ratio in Mamou and Labe, further investigation would be useful to determine whether this is a result of seasonality or altitude (it would have been raining in Mamou at the time of data collection, usually contributing to better use rates) and/or behavioral barriers to net use.

ITN Access and Use Report – August 3 2017 30 Kenya

Kenya has three national surveys and the 2013-14 Regional MICS to include in this analysis. The 2008-2009 DHS was completed between November 2008 and February 2009, during the short rains. The 2013-14 Regional MICS were completed between November and January, also during the short rains. The 2014 DHS was completed between April and October, during the long rains. Kenya has rain periodically throughout the year, with “short rains” in November and December, followed by a dry season from December to March. Long rains occur from April through June, and it is cool and dry again from June through October. The 2010 MIS, implemented by DOMC, is not publically available. The 2015 MIS was fielded in July-August 2015 (long rains), but does not include information on IRS. In 2008-9, 617 households reported being sprayed with IRS, of 9,057 (7%). In 2014, 905 of 36,369 households reported IRS (2%). Kenya implemented mass ITN distributions in 2011-12, and a rolling campaign in 2014-15.

2008- 2013- 2008- 2013- 2008- 2013- 2008- 2013- 2014 2015 2014 2015 2014 2015 2014 2015 2009 14 2009 14 2009 14 2009 14 DHS MIS DHS MIS DHS MIS DHS MIS DHS MICS DHS MICS DHS MICS DHS MICS % of population with access % of households owning ≥1 % of population that used an to an ITN within their own Ratio of use:access ITN ITN the previous night household Region Nairobi§ 51 44 66 47 40 62 42 38 53 0.89 0.95 0.85 Central 33* 38 41* 27* 33* 35* 23* 27* 28* 0.85 0.82 0.81 Coast^ 66* 69* 72 53 58* 58* 46 55* 57 0.87 0.95 1.00 Eastern 60* 56* 62* 44 44 46* 35 37 39* 0.80 0.84 0.85 Nyanza^ 76* 81* 86* 58* 62* 75* 49 61* 71* 0.84 0.98 0.95 Rift 41* 56* 54* 29* 44 48* 22* 35 42* 0.76 0.80 0.87 Valley^ Western^ 71* 82* 79* 51 64* 57* 43 58* 55 0.84 0.91 0.98 North- 73* 49 49* 48 34 33* 46 30* 34* 0.96 0.88 1.02 eastern

ITN Access and Use Report – August 3 2017 31 2008- 2013- 2008- 2013- 2008- 2013- 2008- 2013- 2014 2015 2014 2015 2014 2015 2014 2015 2009 14 2009 14 2009 14 2009 14 DHS MIS DHS MIS DHS MIS DHS MIS DHS MICS DHS MICS DHS MICS DHS MICS % of population with access % of households owning ≥1 % of population that used an to an ITN within their own Ratio of use:access ITN ITN the previous night household

Regional MICS4 Bungoma 78 61 57 0.94 Kakamega 78 63 62 0.98 Nyanza5 92 Turkana 37 22 20 0.90

Wealth quintile Poorest§ 49 51 49 30 36 37 26 31 34 0.87 0.86 0.94 Poorer 58* 61* 63* 41* 46* 52* 32* 41* 49* 0.78 0.89 0.94 Middle 60* 64* 68* 42* 52* 56* 35* 46* 51* 0.83 0.88 0.91 Richer 55 57* 62* 46* 51* 55* 37* 45* 49* 0.80 0.88 0.90 Richest 56 61* 68* 52* 56* 62* 45* 50* 54* 0.87 0.89 0.86

Residence Urban§ 58 56 62 52 49 54 47 46 49 0.90 0.94 0.90

4 Regional MICS in 2013-14 were conducted in four areas of Kenya. Results are presented only for the regional estimates, and not for subanalyses below (wealth quintile etc).

5 The Nyanza regional MICS did not collect data on which household members stayed in the house the previous night, which is necessary for calculating ITN use and ITN access.

ITN Access and Use Report – August 3 2017 32 2008- 2013- 2008- 2013- 2008- 2013- 2008- 2013- 2014 2015 2014 2015 2014 2015 2014 2015 2009 14 2009 14 2009 14 2009 14 DHS MIS DHS MIS DHS MIS DHS MIS DHS MICS DHS MICS DHS MICS DHS MICS % of population with access % of households owning ≥1 % of population that used an to an ITN within their own Ratio of use:access ITN ITN the previous night household Rural 55 61* 63 40* 47 52 32* 41* 47 0.80 0.87 0.91

IRS No§ 55 58 42 48 35 42 0.83 0.88 Yes 65* 77* 46 62* 37 55* 0.80 0.89 *p-value≤0.05 compared to reference group (denoted with §) ^ region received LLINs in the 2011-2012 mass campaign.

Observations Kenya has a relatively high use:access ratio throughout the country and across wealth quintiles and residences, with improvement over the last three available surveys which may be due in part to survey timing. Both access and use increase with increasing wealth, however, use:access ratio is similar across all wealth quintiles. Prior to 2015, urban residents had higher access and use than those in rural areas, but this has evened out in the 2015 survey. In both DHS surveys, households receiving IRS had a higher proportion of ITN ownership, but use:access ratio was the same in both groups.

Implications for programming Kenya is doing well in terms of the proportion of the population using nets when they have access to them. Continued net distributions and SBCC campaigns in areas targeted for ITNs will help in maintaining these high numbers.

ITN Access and Use Report – August 3 2017 33 Lao PDR

The 2011-12 MICS was fielded primarily from October to February, during the drier cooler season.

2011-12 MICS % of population with % of households owning % of population that used access to an ITN within Ratio of use:access ≥1 ITN an ITN the previous night their own household Region Vientiane Capital§ 22 18 17 0.94 Phongsaly 51* 39* 36* 0.92 Luangnamtha 44* 39* 41* 1.06 Oudomxay 86* 74* 80* 1.08 Bokeo 50* 38* 41* 1.06 Luangprabang 69* 57* 60* 1.06 Huaphanh 38* 32* 30* 0.93 Xayabury 49* 45* 48* 1.06 Xiengkhuang 25 21 20 0.94 Vientiane 29 20 16 0.80 Borikhamxay 67* 61* 62* 1.02 Khammuane 51* 42* 42* 1.00 Savannakhet 48* 38* 37* 0.99 Saravane 72* 57* 62* 1.09 Sekong 75* 61* 64* 1.05 Champasack 40* 33* 33* 1.01 Attapeu 84* 71* 74* 1.05

ITN Access and Use Report – August 3 2017 34 2011-12 MICS % of population with % of households owning % of population that used access to an ITN within Ratio of use:access ≥1 ITN an ITN the previous night their own household Wealth Quintile Poorest§ 56 42 48 1.13 Poorer 56 46 48 1.05 Middle 54 47 47 1.00 Richer 46* 40* 39* 0.96 Richest 31* 26* 22* 0.87

Residence Urban§ 35 30 29 0.95 Rural with road 52* 44* 45* 1.03 Rural without road 59* 45* 47* 1.04

Observations Lao PDR has excellent use:access ratios indicating a strong culture of net use. There is a marked decline in ownership, access, and use among wealthier quintiles, but use of nets by those with access remains high in all socioeconomic quintiles. Urban households have lower rates of ownership, use, and access to ITNs, but similar use:access ratios those in rural areas.

Implications for programming Messaging around net use does not appear to need to be targeted to specific groups based on this analysis, but further analysis by high-risk group would be useful.

ITN Access and Use Report – August 3 2017 35 Liberia

The dry season in Liberia lasts from December to April, with the rains occurring between May and November. There were three surveys available in Liberia: the 2008-2009 DHS, the 2011 MIS, and the 2013 DHS. The majority of fieldwork was completed from December 2008 to February of 2009 (dry season), from September to December 2011 (primarily rainy), and from March through July 2013 (both dry and rainy seasons), respectively. In the 2011 MIS, 439 of 4,162 households reported being sprayed with IRS (10%); in 2013, 943 of 9,333 (10%) reported IRS. Liberia conducted mass distribution on a rolling basis between 2008 and 2012, and a national campaign in 2015.

2008- 2008- 2008- 2008- 2011 2011 2013 2011 2013 2011 2013 2009 2009 2009 2009 MIS MIS DHS MIS DHS MIS DHS MIS MIS MIS MIS

% of population with access % of households owning ≥1 ITN to an ITN within their own Ratio of use:access household

Region

Monrovi 34 53 17 34 14 35 0.82 1.03 a§

North 63* 44 41* 26* 49 34* 29 43 0.83 1.12 0.88 Western§§

South 32 36* 16 21* 31* 13 22* 26* 0.81 1.05 0.84 Central

South 60* 61 31* 38 28* 30* 41 24* 0.97 1.08 0.86

ITN Access and Use Report – August 3 2017 36 2008- 2008- 2008- 2008- 2011 2011 2013 2011 2013 2011 2013 2009 2009 2009 2009 MIS MIS DHS MIS DHS MIS DHS MIS MIS MIS MIS

Eastern A

South 66* 64* 39* 40 27* 31* 36 21* 0.79 0.90 0.78 Eastern B

North 57* 51 30* 31 47 28* 34 41 0.93 1.10 0.87 Central

Wealth Quintile

Poorest§ 48 41 26 24 36 22 27 31 0.85 1.13 0.86

Poorer 54 53* 32 32* 44* 30* 35* 38* 0.94 1.09 0.86

Middle 52 49* 28 30 42* 25 32 38* 0.89 1.07 0.90

Richer 43 52* 22 33* 34 21 36* 30 0.95 1.09 0.88

Richest 38 54* 19 34* 29* 16 30 22* 0.84 0.88 0.76

ITN Access and Use Report – August 3 2017 37 2008- 2008- 2008- 2008- 2011 2011 2013 2011 2013 2011 2013 2009 2009 2009 2009 MIS MIS DHS MIS DHS MIS DHS MIS MIS MIS MIS

Residenc e

Urban§ 42 52 22 34 33 20 34 28 0.91 1.00 0.85

Rural 52* 47 28* 28* 42* 25 30 36* 0.89 1.07 0.86

No§ 50 31 36 32 31 1.03 0.86

Yes 48 29 44* 29 36 1.00 0.82

*p-value≤0.05 compared to reference group (denoted with §); §§ As Monrovia was not sampled in 2013 survey, North Western region was used as reference group.

Observations Liberia has consistently had a very high net use:access ratio across the country. The only region in which this ratio is less than 0.80 is South Eastern B, whose ratio is 0.78. All wealth quintiles with the exception of the wealthiest in the 2013 survey (0.76) were above 0.80. Net access seems to be highest in the poorer wealth quintiles. Use is relatively similar among each category. In 2013, households receiving IRS had a higher

ITN Access and Use Report – August 3 2017 38 proportion of ITN ownership and access. There was no difference in proportion using an ITN nor in the use:access ratio between those receiving IRS and those without.

Implications for programming Liberia is doing a very good job both in terms of access and use when compared to other countries. Continued net distributions and SBCC campaigns nationwide will help in maintaining these high numbers.

ITN Access and Use Report – August 3 2017 39 Madagascar

Available data for Madagascar include the 2008 DHS, the 2011 MIS, and the 2013 MIS. The 2008 DHS fieldwork was conducted between November 2008 and July 2009, mainly during dry season but stretching into rainy season in some areas, while the two MIS surveys were conducted primarily between February and April, prior to rainy season. The 2016 MIS was conducted from April-July, in rainy/transmission season. In 2011, 3,710 households out of 9,094 (46%) reported IRS; in 2013, 3,014 of 8,574 (35%) reported IRS; in 2016, 1,268 of 11,284 (11%) reported IRS. The 2008 DHS sampled 22 regions that did not match up directly with the sampled regions in the later MIS surveys; as it is older data, the 2008 regional analysis is excluded in the table below. Madagascar implemented mass distributions in 2009-2010, 2012-2013, and 2015. The 2016 MIS changed the sampled regions, and added categories for operational zone and intervention zone (endemic/non-endemic, not reported here). These two categories are roughly aligned: East, West, and Margin zones are largely endemic, while South and High Central Lands are largely (but not entirely) non-endemic.

20 200 2011 2008 2011 2013 2016 2008 11 2013 2016 8 2011 2013 2016 2008 DHS 2016 MIS MIS DHS MIS MIS MIS DHS M MIS MIS DH MIS MIS MIS IS S % of population with access to % of households owning ≥1 ITN an ITN within their own Ratio of use:access household Trans missio n Zone Equat 78 95 93 51 69 71 76 57 84 83 85 1.11 1.22 1.16 1.11 orial§ Tropic 78 94 90* 51 70 48* 72 53 81 57* 80 1.04 1.17 1.19 1.10 al Sub- 70* 93 90* 40* 63* 31* 59* 37* 84 43* 77* 0.94 1.34 1.37 1.30 desert High 38* 36* 40* 22* 23* 16* 29* 22* 24 13* 27* 1.03 1.07 0.79 0.94 Platea *

ITN Access and Use Report – August 3 2017 40 20 200 2011 2008 2011 2013 2016 2008 11 2013 2016 8 2011 2013 2016 2008 DHS 2016 MIS MIS DHS MIS MIS MIS DHS M MIS MIS DH MIS MIS MIS IS S % of population with access to % of households owning ≥1 ITN an ITN within their own Ratio of use:access household ux

Opera tional Zone East 94 76 86 1.13 West 91 75 82* 1.10 South 90* 59* 77* 1.30 High Centr 24* 14* 13* 0.96 al Lands Margi 90* 74 74* 1.00 n

Regio n Antan anariv 45 31 24 33 20 1.10 0.87 o§ Fianar 60 72* 48* 46* 54* 1.24 1.17 antsoa * Toam 84 95* 72* 69* 76* 1.16 1.11 asina * Mahaj 89 97* 75* 55* 69* 1.18 1.24 anga *

ITN Access and Use Report – August 3 2017 41 20 200 2011 2008 2011 2013 2016 2008 11 2013 2016 8 2011 2013 2016 2008 DHS 2016 MIS MIS DHS MIS MIS MIS DHS M MIS MIS DH MIS MIS MIS IS S % of population with access to % of households owning ≥1 ITN an ITN within their own Ratio of use:access household Toliar 80 94* 63* 39* 51* 1.26 1.30 y * Antsir 79 91* 69* 69* 77* 1.14 1.11 anana * Anala mang a 51* 40* 36* 0.90 Vakin ankar atra 66 57* 57* 1.00 Itasy 19* 10* 9* 0.96 Bongo lava 91 74 77 1.03 Haute Matsi atra 37* 22 26* 1.20 Amor on I Mania 26* 18 18* 0.99 Vatov avy Fitovi nany 94 72 85 1.19 Ihoro mbe 90 65 73 1.13 Atsim 92 67 86 1.27 o

ITN Access and Use Report – August 3 2017 42 20 200 2011 2008 2011 2013 2016 2008 11 2013 2016 8 2011 2013 2016 2008 DHS 2016 MIS MIS DHS MIS MIS MIS DHS M MIS MIS DH MIS MIS MIS IS S % of population with access to % of households owning ≥1 ITN an ITN within their own Ratio of use:access household Atsina nana Atsina nana 93 76 86 1.14 Anala njirof o 96 85 89 1.05 Alaotr a Mang oro 93 79 76 0.96 Boeny 94 81 89 1.10 Sofia 91 79 80 1.00 Betsib oka 97* 77* 86* 1.11 Melak y 96 80 90 1.13 Atsim o Andre fana 86 62 76 1.21 Andro y 89 53 73 1.37 Anosy 93 70 84 1.20 Mena be 92 71 83 1.16

ITN Access and Use Report – August 3 2017 43 20 200 2011 2008 2011 2013 2016 2008 11 2013 2016 8 2011 2013 2016 2008 DHS 2016 MIS MIS DHS MIS MIS MIS DHS M MIS MIS DH MIS MIS MIS IS S % of population with access to % of households owning ≥1 ITN an ITN within their own Ratio of use:access household Diana 92 82 87 1.06 Sava§ 91 77 81 1.06

Wealt h Quint ile Poores 65 92 91 35 62 45 65 39 81 59 79 1.10 1.31 1.29 1.21 t§ 77 Poorer 61* 87* 83* 36 62 49 63* 40 58 73* 1.12 1.25 1.20 1.15 * Middl 71 51* 83* 77* 30* 59 50 60* 32* 59 65* 1.07 1.20 1.17 1.08 e * 60 Richer 52* 73* 75* 32 52* 50 62* 33* 54 64* 1.02 1.15 1.10 1.04 * Riches 52 56* 69* 72* 40* 51* 45 60* 39 45* 60* 0.96 1.02 0.99 1.00 t *

Resid ence Urban § 60 87 85 43 67 63 72 44 72 67 74 1.01 1.07 1.06 1.04 Rural 56 80* 79* 33* 56* 46* 61* 35* 68 54* 67* 1.06 1.21 1.16 1.11

IRS No§ 90 66 54 80 63 1.21 1.17 Yes 67* 46* 34* 54 38* 1.17 1.12

ITN Access and Use Report – August 3 2017 44 20 200 2011 2008 2011 2013 2016 2008 11 2013 2016 8 2011 2013 2016 2008 DHS 2016 MIS MIS DHS MIS MIS MIS DHS M MIS MIS DH MIS MIS MIS IS S % of population with access to % of households owning ≥1 ITN an ITN within their own Ratio of use:access household * *p-value≤0.05 compared to reference group (denoted with §)

Observations Madagascar is the PMI country with the highest observed ITN use:access ratios, rarely dipping below 1.00 except for 0.87 observed in Antananarivo in the 2013 MIS, and 0.79 for the High-Plateaux transmission zone, also in 2013. Madagascar also has a high average number of users per net, driving up their ratio of ITN use:access, in part due to relatively small houses where it is difficult to hang multiple ITNs for a 1:2 net-to-user ratio. There is a consistent trend towards poorer households having higher use:access ratios, perhaps due to smaller house size, as well as the general phenomenon of wealthier households having lower numbers of people per sleeping space. Even in the High Plateau/High Central Lands, where ownership and access to ITNs is quite low, use of ITNs given access is close to 1.0.

Implications for programming ITN use among those with access to a net within their household is excellent in Madagascar, indicating an extremely strong net culture, even in lower risk areas.

ITN Access and Use Report – August 3 2017 45 Malawi

Malawi has five surveys available for analysis. The 2010 DHS was completed between June and September 2010, during the cool dry season. The 2012 MIS was conducted on the edge of the hot wet season, in March and April (rains are variable in March and are mostly complete in April). The 2013-2014 MICS was conducted primarily from December to March, during the hot wet season. The 2014 MIS was conducted in May and June, during high transmission season (cool dry season). The 2015-16 DHS was conducted from October 2015 to February 2016, mainly in the hot wet season. In 2010, 865 of 24,825 households reported IRS (3%); in 2012, 290 of 3,404 (8) reported IRS; in the 2013-14 MICS, 3,353 households reported being sprayed with IRS, of 26,713 (13%). In 2014, 210 of 3,405 households reported IRS (6%). In 2015-16, 1,607 of 26,361 households reported IRS (6%). Malawi implemented mass ITN distributions in 2012 (after the MIS fieldwork), in 6 districts in December 2014, in 4 districts between mid-2014 and January 2016, and in the remaining 19 districts in mid-2016, after the DHS fieldwork.

2 0 2013- 2013- 2013- 2015- 2015- 1 2015- 2010 14 2014 2010 2013-14 2014 2010 14 2014 2015-16 2010 2012 14 2014 2012 MIS 16 16 2 16 DHS MIC MIS DHS 2 MICS MIS DHS MIC MIS DHS DHS MIS MIC MIS DHS DHS M DHS S 0 S S I S

% of house holds % of population that used an ITN the % of population with access to an ITN within their own household Ratio of use:access owni previous night ng ≥1 ITN

Regio n

North 4 56 64 84 78 58 38 64 60 38 27 61 54 34 0.71 0.98 0.96 0.91 0.88 ern§ 4 3 4

ITN Access and Use Report – August 3 2017 46 2 0 2013- 2013- 2013- 2015- 2015- 1 2015- 2010 14 2014 2010 2013-14 2014 2010 14 2014 2015-16 2010 2012 14 2014 2012 MIS 16 16 2 16 DHS MIC MIS DHS 2 MICS MIS DHS MIC MIS DHS DHS MIS MIC MIS DHS DHS M DHS S 0 S S I S

Centr 4 54 57 79* 70* 58 35 58* 53 40 27 59 53 35 0.77 1.13 1.01 1.01 0.86 al 3 4 9 South 3 59 51* 76* 68 56 40 54* 48* 37 31* 48* 51 33 0.78 1.12 0.89 1.07 0.88 ern 3 7 3

Wealt h Quint ile

Poore 3 41 47 67 61 45 24 44 42 28 18 43 45 25 0.75 1.16 0.98 1.07 0.89 st§ 3 6 1 Poore 4 51* 54* 77* 66 54* 32* 52* 46 35* 24* 52* 48 31* 0.75 1.18 1.00 1.05 0.90 r 3 0 4 Middl 4 58* 54 80* 69* 59* 37* 56* 47 38* 29* 54* 51 33* 0.78 1.17 0.96 1.10 0.87 e 3 1 5 Riche 4 61* 57* 82* 78* 60* 40* 61* 62* 40* 30* 56* 60* 35* 0.75 1.11 0.92 0.97 0.87 r 3 1 7 Riche 74* 65* 84* 78* 69* 55* 4 70* 62* 53* 43* 4 64* 57* 45* 0.78 0.96 0.92 0.92 0.85 st 8 6

ITN Access and Use Report – August 3 2017 47 2 0 2013- 2013- 2013- 2015- 2015- 1 2015- 2010 14 2014 2010 2013-14 2014 2010 14 2014 2015-16 2010 2012 14 2014 2012 MIS 16 16 2 16 DHS MIC MIS DHS 2 MICS MIS DHS MIC MIS DHS DHS MIS MIC MIS DHS DHS M DHS S 0 S S I S

Resid ence

Urban 4 64 56 79 75 63 47 65 60 47 38 61 57 42 0.81 1.03 0.93 0.94 0.89 § 4 1 0 4 55* 55 78 69 56 36* 55* 50* 37* 27* 53* 52 32* 0.75 1.11 0.96 1.03 0.87 Rural 3 1 7

4 57 54 78 71 57 37 57 52 38 29 54 52 34 0.77 1.11 0.95 1.00 0.87 No§ 3 0 6 4 68* 64 79 66 63* 46* 57 50 44* 42* 56* 54 38* 0.91 1.07 0.99 1.09 0.87 Yes 4 9 5 *p-value≤0.05 compared to reference group (denoted with §)

ITN Access and Use Report – August 3 2017 48 Observations Malawi continues to have a very high use to access ratio across all categories and regions. Except for 2010, all surveys have been conducted during the rainy season, when people tend to report using their nets more consistently. Net ownership and access still tend to be higher in higher wealth quintiles; however, use of nets, given access, has been consistently strong since 2012. In the DHS surveys, households having received IRS had higher ITN ownership, access, and use, while in MIS surveys these differences are not observed.

Implications for programming Malawi is doing a very good job both in terms of access and use. Continued net distributions and SBCC campaigns nationwide will help in maintaining these high numbers.

ITN Access and Use Report – August 3 2017 49 Mali

Available data for Mali include the 2006 DHS, the 2010 Anemia and Parasitemia survey, the 2012-2013 DHS, and the 2015 MIS. Fieldwork for the 2006 DHS was conducted between April and August, with Bamako region split between April and October. Fieldwork for the 2010 A&P was done in the high transmission period, primarily in September and October (wealth index information was not collected). Fieldwork for the 2012- 2013 DHS was done beginning in late November and into February, during the end of the transmission period and then the cooler season. The 2015 MIS was fielded in September, October, and November, during transmission season. The northern zone of Timbuktu, Gao, and Kidal was not sampled during the 2012-2013 DHS or the 2015 MIS, for security reasons. In 2010, 82 households reported IRS (with no timeframe), of 1,617 (5%); in 2012-12, 842 of 10,105 (8) reported IRS in the last 12 months; in 2015, 272 of 4240 (6%) households reported IRS in the last 12 months. Mali implemented a national under five campaign in 2008, and universal coverage campaigns in 2011-13 and 2015.

2012- 2012- 2012- 2012- 2006 2010 2015 2006 2010 2015 2006 2010 2015 2006 2010 2015 2013 2013 2013 2013 DHS A&P MIS DHS A&P MIS DHS A&P MIS DHS A&P MIS DHS DHS DHS DHS % of population with access to % of households owning ≥1 an ITN within their own Ratio of use:access ITN household Region Kayes§ 44 90 79 95 27 71 58 67 20 62 53 64 0.73 0.88 0.91 0.95 Koulikoro 42 85 81 94 21 57* 61 71 15 50* 56 66 0.69 0.88 0.92 0.93 Sikasso 47 88 88* 98* 25 61 67* 78* 20 59 63* 71* 0.79 0.96 0.94 0.92 Segou 50 87 92* 89* 31 63 77* 63* 23 59 73* 58 0.73 0.94 0.95 0.92 Mopti 65* 87 85* 89* 41* 65 66* 66 28 62 61* 64 0.68 0.95 0.92 0.97 Tombouct 48 85 31 64 26 55 0.85 0.86 ou Gao 45 66* 28 44* 17 47 0.61 1.05 Kidal 29* 55* 15* 28* 1* 16* 0.10 0.60 Bamako 54* 86 77 94 34 60* 57 71 25 51* 51 59 0.74 0.85 0.91 0.83

ITN Access and Use Report – August 3 2017 50 2012- 2012- 2012- 2012- 2006 2010 2015 2006 2010 2015 2006 2010 2015 2006 2010 2015 2013 2013 2013 2013 DHS A&P MIS DHS A&P MIS DHS A&P MIS DHS A&P MIS DHS DHS DHS DHS % of population with access to % of households owning ≥1 an ITN within their own Ratio of use:access ITN household

Wealth Quintile Poorest§ 52 80 94 28 60 68 20 56 63 0.71 0.93 0.93 Poorer 49 86* 94 28 66* 70 21 61* 66* 0.73 0.92 0.94 Middle 44* 87* 90* 26 67* 68 19 63* 62 0.72 0.93 0.91 Richer 49 86* 92 30 67* 69 21 63* 65* 0.71 0.95 0.94 Richest 57* 84* 95 36* 65* 73 26* 59 63 0.73 0.91 0.87

Residence Urban§ 54 87 82 94 33 62 63 71 23 55 58 61 0.71 0.88 0.92 0.86 Rural 48* 86 85* 93 28* 61 65 69 21 57 61 65 0.73 0.92 0.93 0.93

IRS No§ 86 84 93 61 64 70 56 60 64 0.92 0.94 0.92 Yes 91 93* 87* 65 74* 66* 60 67* 60* 0.92 0.90 0.90 *p-value≤0.05 compared to reference group (denoted with §)

Observations Between 2006 and 2010, the use:access ratio for almost all regions increased to above .80, and this was maintained through the 2012-2013 survey. This pattern was the same for both wealth quintiles (when measured) as well as rural and urban sites. ITN ownership, use, and access tended to be higher as wealth increased, although this did not affect the use:access ratio, which was similar among all regions, wealth quintiles, and residencies. Households having received IRS had a marginally higher proportion of all three variables in the 2010 and 2012-2013 surveys, although this pattern reversed in 2015. The use:access ratio was very similar across IRS strata and surveys.

ITN Access and Use Report – August 3 2017 51 Implications for programming Mali continues to have a very strong culture of net use, and access has been sustained at relatively high levels since 2010. Net distribution and SBCC nationally should be continued throughout the country to maintain the very high use:access ratio here.

ITN Access and Use Report – August 3 2017 52 Mozambique

The only available data for Mozambique was the 2011 DHS. Fieldwork was done from May to December 2011, during the dry season. The 2008 MICS did not include data on ITNs. In 2011, 2,930 households reported being sprayed with IRS, of 13,919 (21%). Mozambique implemented mass distribution in rolling campaigns between 2010 and 2014, and in 2016-17.

2011 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Region Niassa§ 47 34 34 1.00 Cabo Delgado 61* 48* 37 0.77 Nampula 60* 48* 44* 0.92 Zambezia 46 31 28 0.90 Tete 47 33 25* 0.76 Manica 54 35 31 0.89 Sofala 57 39 34 0.87 Inhambane 54 44* 20* 0.45 Gaza 45 32 8* 0.25

Wealth Quintile Poorest§ 45 32 26 0.81 Poorer 50* 35* 28 0.80 Middle 52* 36* 30 0.83 Richer 55* 41* 30 0.73

ITN Access and Use Report – August 3 2017 53 2011 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Richest 56* 41* 33* 0.80

IRS No§ 51 36 29 0.80 Yes 55* 39 32 0.82 *p-value≤0.05 compared to reference group (denoted with §)

Observations The majority of regions in Mozambique have a very good use:access ratio, with the exception of Inhambane and Gaza, which had ratios of 0.45 and 0.25, respectively. The ratio was similar among wealth quintiles, averaging 0.79, among urban and rural clusters, averaging 0.81, and between IRS strata, also averaging 0.81.

Implications for programming Population access in Inhambane and Gaza is not lower than that of the other regions, so additional, targeted net distribution is not necessary. However, because use is much lower in these two regions, SBCC campaigns encouraging net use may be needed. These areas experience lower transmission and have historically been targeted for IRS spraying; further investigation of the data may prove helpful.

ITN Access and Use Report – August 3 2017 54 Myanmar

The fieldwork for the 2015-16 Myanmar DHS was carried out in the low-transmission season from December 2015 to April/May 2016. No IRS data was included the survey. Myanmar distributes insecticide-treated nets (ITNs) periodically in most of the malaria-endemic areas. Due to the high rates of ownership of untreated nets, we include additional columns here to report on ownership, access, and use of nets of any kind, for context.

2015-16 DHS Household ownership Use the previous night Use:access Ratio of % of of population % of population population % of of with access population Ratio of with access that used a Ratio of households households to a net of that used an use:access to an ITN net of any use:access owning ≥1 owning any any kind ITN the for nets of within their kind the for ITNs ITN net within their previous any kind own previous own night household night household Region Kachin§ 44 99 34 89 25 58 0.74 0.65 Kayah 85* 99 73* 89 40* 19* 0.55 0.21 Kayin 36 88* 23 66* 22 46 0.96 0.69 Chin 80* 97* 67* 84 40* 17* 0.60 0.20 Sagaing 32 100 28 94* 20 72 0.71 0.77 Taninthayi 77* 97* 63* 88 42* 30* 0.67 0.35 Bago 13* 99 9* 94 5* 85* 0.56 0.90 Magway 27 98 20* 88 16 72* 0.80 0.82 Mandalay 10* 99 8* 86 7* 80* 0.88 0.93

ITN Access and Use Report – August 3 2017 55 2015-16 DHS Household ownership Use the previous night Use:access Ratio of % of of population % of population population % of of with access population Ratio of with access that used a Ratio of households households to a net of that used an use:access to an ITN net of any use:access owning ≥1 owning any any kind ITN the for nets of within their kind the for ITNs ITN net within their previous any kind own previous own night household night household Mon 64* 99 54* 92 36 44 0.67 0.47 Rakhine 6* 96 51* 81* 39* 33* 0.76 0.40 Yangon 6* 100 4* 93 4* 93* 1.00 0.99 Shan 39 85* 29 72* 22 41* 0.76 0.57 Ayeyarwaddy 16* 100 11* 92 8* 87* 0.73 0.94 Naypyitaw 7* 99 4* 87 3* 72* 0.75 0.83

Wealth Quintile Poorest§ 35 94 28 78 23 54 0.82 0.70 Poorer 32 97* 25* 85* 19* 64* 0.76 0.75 Middle 27* 99* 21* 90* 15* 72* 0.71 0.80 Richer 23* 99* 18* 92* 12* 76* 0.67 0.83 Richest 17* 97 14* 93 11* 78* 0.79 0.84

Residence Urban§ 15 98 12 91 9 81 0.75 0.89 Rural 31* 97 25* 86 18* 64* 0.72 0.75 *p-value≤0.05 compared to reference group (denoted with §)

ITN Access and Use Report – August 3 2017 56 Observations While ownership and access of any type of net is nearly universal across most regions of Myanmar, ITN ownership and access lag behind. Regional variations in household ownership of ITNs were present in 2015-16, with Kia having the highest rates (85%) and Yangon and Naypyitaw with the lowest rates of 6 and 7 respectively. There is a negative trend in ownership of ITNs by wealth quintiles with ownership declining as wealth increases. Household ownership of nets was higher in rural compared to urban areas. Population ITN access and use of ITNs demonstrated the same regional, wealth and residential variations seen with household ownership of nets, Use:access ratios for ITNs are below target in many regions and poor in Bago and Kayah regions. Use:access ratios for ITNs were generally higher in each region than for any nets with the exception of Bago, Ayeyarwaddy, and Naypyitaw; this may indicate preferential use of untreated nets in these three regions, and preferential use of ITNs in the other regions.

Implications for programming Use of available ITNs is lowest in the Bago and Kayah regions; additional focus may be needed there to boost rates. Additional data and a seasonal analysis would help to further interpret these findings.

ITN Access and Use Report – August 3 2017 57 Nigeria

Rains in Nigeria begin in the south between February and March and have reached the rest of the country by early summer. They last through September. Fieldwork for the 2008 DHS was conducted from June to October 2008, primarily during the rainy season. The 2010 MIS survey was completed from October to December 2010, during the high transmission season. The 2011 MICS was conducted in February and March, at beginning of rainy season in the south, and during dry season in the north. The 2013 DHS was conducted from February to June 2013, with rain in some areas and not in others. In 2010, 57 households reporting being sprayed with IRS, of 5,895 (1%); In 2013, 827 households of 38,522 reported IRS (2%). Nigeria implemented its first universal coverage campaign starting in 2009 and continuing through 2011, and again in 2014-15. The 2015 MIS was conducted in October and November of 2015 during high transmission season; 138 of 7,745 households reported IRS (2%).

2 2 0 0 1 20 201 2008 2008 1 2008 2011 2008 2011 0 2011 2013 2010 13 2015 2010 1 2013 2015 2010 2013 2015 5 MIC MIC MICS DHS MIS D MIS MIS MI DHS MIS DH MIS DHS MIS DHS M DHS S DHS S M HS CS S I I S S

% of households owning ≥1 ITN % of population that used an ITN the previous night Ratio of use:access

Region

North 3 5 7 40 50 4 20 26 37 41 3 14 12 13 30 0.75 0.72 0.26 0.36 0.73 Central§ 2 5

6 8 43 North East 7 3 54* 61* 0 4 45* 35* 60* 3 42* 12 10 45* 0.75 0.95 0.35 0.24 0.75 * * *

5 9 North West 8 8 63* 49 1 4 34* 39* 33 68* 3 31* 17* 11 54* 0.75 0.91 0.39 0.33 0.80 * *

ITN Access and Use Report – August 3 2017 58 2 2 0 0 1 20 201 2008 2008 1 2008 2011 2008 2011 0 2011 2013 2010 13 2015 2010 1 2013 2015 2010 2013 2015 5 MIC MIC MICS DHS MIS D MIS MIS MI DHS MIS DH MIS DHS MIS DHS M DHS S DHS S M HS CS S I I S S

3 6 South East 10* 32* 57* 7* 23 24* 42 51 4* 13 8* 18* 21* 0.57 0.56 0.24 0.43 0.41 2 4

4 6 South South 10* 43 43* 6* 27 30 33 54 5* 21 16* 15 29 0.83 0.79 0.30 0.44 0.53 4 4

2 5 South West 6 21* 42* 4 16 14* 33 41 2 8 7* 15 21* 0.50 0.51 0.14 0.44 0.51 0 3

Wealth Quintile

4 8 Poorest§ 4 47 55 2 33 31 37 64 2 31 10 9 53 0.80 0.93 0.31 0.26 0.82 9 6

7 4 Poorer 6* 46 54 4 4* 30 32 39 57* 3* 27 14* 15* 45* 0.77 0.89 0.32 0.38 0.79 4 *

6 4 Middle 8* 41* 52 9 5* 32 28 38 57* 4* 27 14* 16* 40* 0.74 0.85 0.28 0.42 0.70 6 *

3 6 Richer 10* 6 37* 46* 4 6* 23* 26* 34 51* 4* 17* 13* 13* 28* 0.68 0.72 0.26 0.37 0.54 * *

Richest 11* 3 36* 42* 5 7* 23* 25* 33 45* 4* 13* 11 12* 22* 0.55 0.59 0.25 0.37 0.49 4 8

ITN Access and Use Report – August 3 2017 59 2 2 0 0 1 20 201 2008 2008 1 2008 2011 2008 2011 0 2011 2013 2010 13 2015 2010 1 2013 2015 2010 2013 2015 5 MIC MIC MICS DHS MIS D MIS MIS MI DHS MIS DH MIS DHS MIS DHS M DHS S DHS S M HS CS S I I S S

Residence

3 6 Urban§ 8 33 42 5 23 23 31 50 3 16 11 13 29 0.62 0.71 0.23 0.41 0.59 3 3

4 7 39 Rural 8 5 46* 55* 3 5 30* 32* 58* 3 25* 13 13 42* 0.71 0.84 0.32 0.33 0.73 * * *

4 6 No§ 49 28 36 55 23 13 37 0.82 0.36 0.68 1 9

7 8 43 Yes 0 63* 3 44* 69* 34 23* 44 0.77 0.53 0.63 * * *

*p-value≤0.05 compared to reference group (denoted with §)

Observations While the use:access ratio started off relatively high in the 2008 and 2010 surveys in the majority of regions, the 2011 and 2013 results dropped below 0.50. In the 2015 survey, some regions and categories have again improved their use:access ratio. North West region had the highest ratio at

ITN Access and Use Report – August 3 2017 60 0.80, with North Central and North East both above 0.70. Poorer wealth quintiles had significantly higher proportions of net access during the 2015 survey than in previous surveys, and the poorest quintiles also had the highest proportion of net use overall, and better use:access ratios than richer households. ITN access has increased steadily from 2008 to 2015 in all geographic zones, and net use likewise reached its highest levels in 2015. In 2015, households in rural regions have improved their use:access ratio since the 2013 survey.

Implications for programming The surveys thus far indicate that Nigeria has an overall ITN ‘use gap’ of 20-60 percentage points, depending on the region and the season in which fieldwork was done. While net access should be improved by nation-wide distributions, SBCC is urgently needed to increase net use throughout the country, as recent studies indicate that multi-channel BCC efforts do improve net use in the country (Kilian et al 2016). Further analysis of recent data is crucial to identify specific reasons for non-use among certain demographics and geographic zones.

ITN Access and Use Report – August 3 2017 61 Rwanda

Four surveys were available for analysis in Rwanda. These included the 2007-2008 interim DHS, the 2010-2011 DHS, the 2013 MIS, and the 2014-2015 DHS. Fieldwork for these surveys occurred from December 2007-April 2008, August 2010 to March 2011, February to April 2013, and November 2014-March 2015. There are two rainy seasons in Rwanda, from March to May and October to November. June to September and December to February are dry. In 2007-8, 447 of 7,377 households (6%) reported being sprayed with IRS; in 2013, 513 of 4,766 households reported IRS (11%). Rwanda implemented mass distributions in 2010-2011, 2012-13, and plans one in 2016.

ITN Access and Use Report – August 3 2017 62 2 0 0 20 7 07 201 - - 2014- 2010- 4- 2007- 2010- 2014 2007- 2010- 2014- 2 2010-2011 2013 20 2013 2013 2013 15 2011 15 2008 2011 -15 2008 2011 15 0 DHS MIS 08 MIS MIS MIS DHS DHS DH DHS DHS DHS DHS DHS DHS 0 D S 8 H D S H S

o f h o u s e h o l % of population with access to an ITN within their own % of population that used an d Ratio of use:access household ITN the previous night s o w n i n

ITN Access and Use Report – August 3 2017 84 Observations Rwanda has consistently had a very high net use:access ratio across the country. All wealth quintiles and residence types were above 0.80. Both net access and use are extremely high, although lower in the poorest quintile. While households receiving IRS had higher ITN ownership in the 2007-2008 survey, and higher ITN access in the 2013 survey, there was no difference in net use or the use:access ratio between groups.

Implications for programming Rwanda is doing an excellent job both in terms of net access and use when compared to other countries. Continued net distributions and SBCC campaigns nationwide will help in maintaining these high numbers.

ITN Access and Use Report – August 3 2017 85 Senegal

There are six surveys with available information in Senegal: 2006 MIS (not presented below), 2008-2009 MIS, 2010-2011 DHS, 2012-2013 continuous DHS, the 2014 continuous DHS, and the 2015 continuous DHS. The fieldwork was conducted from November – December 2006, November 2008 – February 2009, December 2010 – April 2011, September 2012 – June 2013, January – October 2014, and February-October 2015, respectively. Rainy season varies by region, but is generally from May to October. 2014 was a year of historically low rainfalls, particularly in the northern and center-west regions, with rainfalls 30 below the 20-year averages (WFP). For each survey, households reporting being sprayed with IRS in the last 12 months were: 2006 (73/3,063 – 2%); 2008-9 (934/9,291 – 10%); 2010 (973/7,902 – 12%); 2012-13 (644/4,175 – 15%); 2014 (471/4,231 – 11%); 2015 (311/4,188 – 7%). Senegal implemented an under-five campaign in 2007-2009, and universal coverage campaigns in 2010-13, and 2016.

ITN Access and Use Report – August 3 2017 86 2 0 1 2 20 200 - 08 8- 201 2010- 2 - 2010- 2012- 2010- 2012- 2008- 2010- 2012- 2008-2009 2014 2015 2014 2015 200 4 2015 2014 2015 2011 0 20 2011 2013 2011 2013 2009 2011 2013 MIS cDHS cDHS cDHS cDHS 9 cD cDHS cDHS cDHS DHS 1 09 DHS cDHS DHS cDHS MIS DHS cDHS MI HS 3 M S c IS D H S % of population with access to an ITN % of households owning ≥1 ITN Ratio of use:access within their own household Regio n Dakar 3 36 37 56 54 18 18 19 45 46 14 14 13 27 32 0.78 0.78 0.68 0.59 0.70 § 4 9 Zugui 53 76* 80* 3 90* 90* 56* 85* 74* 75* 41* 40* 56* 59* 66* 0.77 0.71 0.66 0.80 0.88 nchor * * 9 Diour 29 56* 65* 1 86* 90* 35* 76* 72* 78* 20 25* 59* 41 70* 0.69 0.71 0.78 0.57 0.90 bel * * 9 Saint- 32 57* 79* 1 76 80* 49* 65* 57 62* 20 47* 63* 47 62* 0.63 0.96 0.97 0.83 1.00 Louis * * Tamb 8 33 acoun 49* 79* 2 83* 92* 49* 53* 65* 79* 16 35* 25 47 52* 0.48 0.71 0.47 0.73 0.66 * da * 8 Kaola 50 83* 88* 0 78* 96* 56* 53* 42 85* 25* 41* 35* 30 66* 0.50 0.73 0.66 0.71 0.78 ck * * 8 43 Thies 79* 53* 2 73 77* 27* 64* 61* 59* 23* 20 38* 42* 42* 0.53 0.74 0.59 0.69 0.72 * * 9 32 Louga 66* 61* 6 87* 75* 29* 81* 69* 54* 11 22* 60* 47* 43* 0.34 0.76 0.74 0.68 0.79 * * 9 59 Fatick 90* 77* 4 88* 95* 46* 77* 67* 85* 51* 26* 56* 56* 69* 0.86 0.57 0.73 0.83 0.81 * * 8 38 Kolda 69* 95* 0 97* 92* 71* 55* 81* 74* 34* 56* 37* 59* 40* 0.89 0.79 0.67 0.73 0.55 * *

ITN Access and Use Report – August 3 2017 87 2 0 1 2 20 200 - 08 8- 201 2010- 2 - 2010- 2012- 2010- 2012- 2008- 2010- 2012- 2008-2009 2014 2015 2014 2015 200 4 2015 2014 2015 2011 0 20 2011 2013 2011 2013 2009 2011 2013 MIS cDHS cDHS cDHS cDHS 9 cD cDHS cDHS cDHS DHS 1 09 DHS cDHS DHS cDHS MIS DHS cDHS MI HS 3 M S c IS D H S % of population with access to an ITN % of households owning ≥1 ITN Ratio of use:access within their own household 9 Mata 29 48 70* 3 85* 78* 37* 65* 62* 57* 20 36* 59* 50* 54* 0.69 0.97 0.91 0.82 0.94 m * * 9 Kaffri 69* 0 74* 93* 45* 68* 49 81* 31* 34* 27 45* 0.69 0.50 0.56 0.55 ne * 8 Kedou 94* 4 82* 90* 75* 58* 70* 73* 46* 32* 49* 41* 0.61 0.55 0.69 0.56 gou * 9 Sedhi 94* 2 84* 98* 70* 70* 69* 83* 60* 55* 47 73* 0.86 0.79 0.68 0.88 ou *

Wealt h Quint ile Poore 8 67 75 83 88 38 48 63 61 74 22 34 35 37 49 0.58 0.71 0.56 0.60 0.66 st§ 8 9 42 Poorer 70 75 86 88 48 70* 65 75 27* 35 46* 45* 57* 0.64 0.73 0.66 0.68 0.76 1 * Middl 8 74* 69* 81 82 41 41* 66 63 68 25 34 54* 49* 59* 0.61 0.83 0.82 0.77 0.87 e 8 6 31 Richer 53* 54* 6 71* 73* 31* 52* 54 64* 24 25* 41 40 55 0.77 0.81 0.79 0.74 0.86 * * 4 Riche 22 42* 42* 5 58* 59* 22* 36* 49* 50* 16* 16* 28 32 36* 0.73 0.73 0.78 0.65 0.73 st * *

ITN Access and Use Report – August 3 2017 88 2 0 1 2 20 200 - 08 8- 201 2010- 2 - 2010- 2012- 2010- 2012- 2008- 2010- 2012- 2008-2009 2014 2015 2014 2015 200 4 2015 2014 2015 2011 0 20 2011 2013 2011 2013 2009 2011 2013 MIS cDHS cDHS cDHS cDHS 9 cD cDHS cDHS cDHS DHS 1 09 DHS cDHS DHS cDHS MIS DHS cDHS MI HS 3 M S c IS D H S % of population with access to an ITN % of households owning ≥1 ITN Ratio of use:access within their own household

Resid ence Urban 5 50 52 66 67 29 30 43 52 58 22 25 35 38 46 0.76 0.83 0.81 0.73 0.80 § 6 8 39 Rural 70* 73* 9 84* 88* 44* 67* 64* 72* 24 32* 45* 42 55* 0.62 0.73 0.67 0.66 0.76 * *

IRS 7 No§ 60 62 74 76 35 37 58 58 65 23 28 41 40 52 0.66 0.76 0.72 0.69 0.79 3 7 Yes 72* 73* 82* 92* 40 46* 57 61 75* 22 35* 38 41 41* 0.55 0.76 0.66 0.68 0.54 7 *p-value≤0.05 compared to reference group (denoted with §)

Stratification by season of interview in 2014 and 2015 continuous DHS. Dry season defined as January-June; early rains July-August; late rains September-October (no fieldwork was done in November or December).

ITN Access and Use Report – August 3 2017 89 2014 cDHS 2015 cDHS

Use/Access Use/Access Use/Access Use/Access Use/Access Use/Access Dry Season Early Rains Late Rains Dry Season Early Rains Late Rains

Dakar 61 46 53 0.61 0.77 0.90

Zuguinchor 64 103 97 0.70 0.96 0.99

Diourbel 51 80 0.78 1.00 1.03

Saint-Louis 78 85 95 0.96 0.97 1.05

Tambacounda 54 79 100 0.22 0.97 0.95

Kaolack 66 81 0.59 0.95 0.99

Thies 60 66 92 0.60 0.78 0.90

Louga 66 97 0.71 0.96

Fatick 66 73 0.76 0.90

Kolda 56 75 96 0.39 1.03 1.03

Matam 75 91 93 0.75 1.10 1.12

Kaffrine 40 72 96 0.26 0.81 0.95

Kedougou 41 96 92 0.24 0.95 0.93

Sedhiou 63 100 0.76 1.00 0.94

ITN Access and Use Report – August 3 2017 90 Observations The continuous DHS, implemented since 2012, sheds additional light on what initially seems to be a low use:access ratio across surveys. While the mean use:access rates across the surveys are mediocre, especially for a Sahelian country with an entrenched culture of net use, analysis by rainy season (second table) shows a pattern of net use that increases during the early rains and peaks during the late rains (September/October), indicating that net use is likely driven by perceived nuisance biting, and diminishes when mosquitoes are less present. Ownership and access seem to be higher on the whole in the lower wealth quintiles than in the wealthier ones. As in many other countries, rural residents have higher access and use rates than urban residents. Households receiving IRS had significantly higher ITN ownership in all surveys; use of ITNs given access.

Implications for programming Even before the 2016 mass campaign, ITN ownership and access were high in Senegal. While reduced rainfall in 2014 may have contributed to lower use of ITNs for those with access, this problem seems to have resolved in the 2015 data, where use:access ratios are nearly all above 0.90 by early rainy season. SBCC campaigns to increase net use in the dry season may still be needed.

ITN Access and Use Report – August 3 2017 91 Tanzania

Available data for Tanzania include the 2007-2008 THMIS, the 2010-2011 DHS, the 2011-2012 THMIS, and the 2015-2016 DHS. Fieldwork for the 2007-8 THMIS was done from October 2008 to February 2008, during the dry season. The 2010-2011 DHS and the 2011-2012 THMIS were conducted primarily from January-April, prior to rainy season. The 2015-2016 DHS was fielded from September to January. In 2007-8, 2,161 households reported being sprayed with IRS, of 8,497 (25%); in 2011-12, 2,309 of 10,040 were sprayed (23%); in 2015-16, 1,139 of 12,562 (9%) were sprayed. Tanzania implemented an under-five campaign in 2009-10, and a universal coverage campaign in 2010-2011 and in 2015-2016.

2007- 2011- 2007- 2011- 2007- 2011- 2011- 2010- 2015- 2010- 2015- 2010- 2015- 2007-8 2010- 2015- 8 2012 8 2012 8 2012 2012 2011 2016 2011 2016 2011 2016 THMI 2011 2016 THM THM TH THM THM THM THMI DHS DHS DHS DHS DHS DHS S DHS DHS IS IS MIS IS IS IS S % of population with access % of households owning ≥1 % of population that used an to an ITN within their own Ratio of use:access ITN ITN the previous night household Region Dodom 28 72 93 39 20 49 79 26 7 54 72 17 0.37 1.09 0.91 0.93 a§ Arusha 32 51* 85 43 21 34* 66* 31* 20* 29* 56* 29* 0.94 0.87 0.84 0.70 Kiliman 30 49* 95 64* 19 36* 81 51* 14 32* 66 36* 0.71 0.90 0.82 0.93 jaro Tanga 39 60* 90 53* 25 46 70* 36* 19* 41* 70 33* 0.77 0.89 1.00 1.05 Morogo 44* 37* 91 55* 33* 26* 79 45* 31* 27* 76 47* 0.94 1.04 0.96 0.95 ro Pwani 48* 69 95 65* 35* 54 84 51* 32* 52 80 48* 0.90 0.97 0.95 1.03 Dar es 71* 62* 79* 66* 55* 46 71* 53* 56* 47 66 54* 1.03 1.02 0.93 0.81 Salaam Lindi 40* 64 96 70* 32* 53 91* 59* 22* 44* 83* 48* 0.67 0.83 0.91 0.82 Mtwara 43* 64* 93 61* 31* 51 85 54* 17* 45* 74 44* 0.57 0.88 0.87 0.86

ITN Access and Use Report – August 3 2017 92 2007- 2011- 2007- 2011- 2007- 2011- 2011- 2010- 2015- 2010- 2015- 2010- 2015- 2007-8 2010- 2015- 8 2012 8 2012 8 2012 2012 2011 2016 2011 2016 2011 2016 THMI 2011 2016 THM THM TH THM THM THM THMI DHS DHS DHS DHS DHS DHS S DHS DHS IS IS MIS IS IS IS S % of population with access % of households owning ≥1 % of population that used an to an ITN within their own Ratio of use:access ITN ITN the previous night household Ruvum 39* 70 95 66* 24 50 83 56* 20* 46* 74 48* 0.82 0.91 0.89 0.79 a Iringa 18 53* 92 46 12 40* 82 35* 6 25* 68 28* 0.47 0.64 0.83 0.69 Mbeya 30 58* 91 50 22 42* 79 38* 16* 31* 60 26* 0.74 0.74 0.75 0.95 Singida 26 34* 95 44 14 22* 78 31 11 18* 74 30* 0.77 0.85 0.95 1.03 Tabora 40* 73 95 91* 21 49 74 74* 8 47 73 76* 0.36 0.96 0.99 0.85 Rukwa 29 67 86 29 18 44 63* 18* 9 50 64 15 0.52 1.13 1.01 0.63 Kigoma 31 58* 95 94* 17 41* 76 86* 12 38* 72 54* 0.74 0.93 0.96 0.70 Shinyan 38 85* 94 79* 19 59* 77 67* 19* 65* 73 47* 1.02 1.10 0.95 0.87 ga Kagera 30 68 92 90* 18 50 75 78* 13* 48 68 67* 0.75 0.97 0.91 0.86 Mwanz 48* 79 96 90* 29 54 73 79* 24* 62* 77 68* 0.85 1.15 1.06 0.84 a Mara 56* 84* 96 91* 31* 59* 76* 79* 30* 62* 73 67* 0.98 1.05 0.95 0.86 Manyar 22 73 89 22* 12 52 67* 15* 11 49 53* 13 0.88 0.93 0.79 0.93 a Njombe 49 40* 17 0.42 Katavi 95* 79* 85* 1.08 Simiyu 98* 83* 84* 1.00 Geita 96* 81* 85* 1.05 Zanz 71* 87* 77* 82* 57* 72* 65* 68* 38* 47 49* 52* 0.67 0.65 0.75 0.77 North Zanz 72* 90* 79* 83* 57* 76* 63* 69* 45* 59 48* 51* 0.80 0.78 0.76 0.74 South

ITN Access and Use Report – August 3 2017 93 2007- 2011- 2007- 2011- 2007- 2011- 2011- 2010- 2015- 2010- 2015- 2010- 2015- 2007-8 2010- 2015- 8 2012 8 2012 8 2012 2012 2011 2016 2011 2016 2011 2016 THMI 2011 2016 THM THM TH THM THM THM THMI DHS DHS DHS DHS DHS DHS S DHS DHS IS IS MIS IS IS IS S % of population with access % of households owning ≥1 % of population that used an to an ITN within their own Ratio of use:access ITN ITN the previous night household Zanz Town 68* 61* 67* 64* 51* 44 52* 47* 42* 38* 41* 37* 0.82 0.85 0.79 0.79 West Pemba 73* 88* 84 80* 61* 71* 72 63* 42* 54 41* 55* 0.69 0.76 0.57 0.87 North Pemba 80* 73 83* 77* 63* 52 62* 58* 54* 44* 54* 56* 0.86 0.83 0.86 0.96 South

Wealth Quintil e Poorest§ 22 57 90 57 12 40 69 50 8 40 65 44 0.67 1.01 0.95 0.88 Poorer 28* 64* 92 64* 16* 44* 72 56 11* 44* 67 48 0.70 0.99 0.93 0.86 Middle 34* 64* 95* 66* 20* 46* 77* 57* 15* 43 70* 48 0.75 0.95 0.91 0.84 Richer 41* 67* 93 71* 27* 50* 78* 59* 21* 47* 70* 52* 0.76 0.96 0.90 0.89 Richest 67* 68* 86* 68* 51* 54* 77* 58* 46* 52* 70* 53* 0.91 0.95 0.90 0.92

Reside nce Urban§ 59 65 87 67 45 51 77 56 43 50 72 54 0.94 0.99 0.94 0.95 Rural 33* 63 92* 65 20* 45* 74* 56 14* 44* 67* 47* 0.71 0.96 0.91 0.85

IRS No§ 38 91 64 24 75 55 20 69 48 0.83 0.92 0.88

ITN Access and Use Report – August 3 2017 94 2007- 2011- 2007- 2011- 2007- 2011- 2011- 2010- 2015- 2010- 2015- 2010- 2015- 2007-8 2010- 2015- 8 2012 8 2012 8 2012 2012 2011 2016 2011 2016 2011 2016 THMI 2011 2016 THM THM TH THM THM THM THMI DHS DHS DHS DHS DHS DHS S DHS DHS IS IS MIS IS IS IS S % of population with access % of households owning ≥1 % of population that used an to an ITN within their own Ratio of use:access ITN ITN the previous night household Yes 62* 91 88* 48* 70* 73* 39* 66 64* 0.81 0.94 0.87 *p-value≤0.05 compared to reference group (denoted with §)

Observations Tanzania has some of the highest rates of ITN use among those with access to an ITN of all PMI countries, and the ratio of use:access has improved since 2007, averaging over 0.90 in 2010-11 and in 2011-12, and 0.88 in 2015-16. The regions with the lowest use:access ratios are Njombe (0.42), and Zanzibar, around 0.75-0.80 in the latest THMIS. Ratios are fairly consistent within a given region for the last two surveys.

As observed in other PMI countries, the earlier THMIS (2007-8) shows a trend in use:access ratios that is pro-rich, which then flattens out entirely in the latter two surveys, indicating that socio-economic status no longer contributes significantly to use rates. Similarly, the difference in use:access ratio between urban and rural residence disappears after the 2007-8 THMIS.

Implications for programming Use:access ratios are good in nearly all regions (between 0.80 and 1.00), and lower in low-transmission regions (Zanzibar and Pemba). Tanzania has implemented significant SBCC for ITN use over the years, in particular on mainland, which may be one of the reasons behind the high use:access ratios. However, additional SBCC appears to be needed in Unguja (less so in Pemba), where malaria risk is lower, to maintain net use behaviors in the face of low transmission.

ITN Access and Use Report – August 3 2017 95 Uganda

Three surveys were available in Uganda, the 2009 MIS, the 2011 DHS, and the 2014-2015 MIS. Fieldwork for the 2009 survey was conducted in November and December of 2009. Fieldwork for the 2011 DHS was conducted from June to November 2011. Fieldwork for the MIS was conducted from December 2014 through February 2015. Uganda has two rainy seasons. It typically rains from March to May and September to November, leaving December to February and June to August dry. Different regions were sampled in both of these surveys, making comparison between years difficult. In 2009, 121 of 4,421 households reported being sprayed with IRS (3%). In 2011, 753 of 9,033 (8) reported IRS. In 2014- 15, 432 of 5,325 (8) reported IRS. Uganda implemented under-five ITN distribution in 2010, and mass distributions in 2013-2014.

2011 2014-15 2009 2011 2014-15 2009 2011 2014-15 2009 2011 2014-15 2009 MIS DHS MIS MIS DHS MIS MIS DHS MIS MIS DHS MIS

% of population with access % of households owning ≥1 % of population that used an to an ITN within their own Ratio of use:access ITN ITN the previous night household

Region

Central 35 59 81 24 49 72 17 35 59 0.71 0.71 0.82 1§

Central 24 60 82 14 49 71 9* 37 59 0.64 0.76 0.83 2

Kampala 49* 57 86 45* 52 78 38* 44* 71* 0.84 0.85 0.90

East 34 38* 82 21 25* 67 18 19* 62 0.86 0.76 0.92 Central

ITN Access and Use Report – August 3 2017 96 2011 2014-15 2009 2011 2014-15 2009 2011 2014-15 2009 2011 2014-15 2009 MIS DHS MIS MIS DHS MIS MIS DHS MIS MIS DHS MIS

Mid 59* 95* 36 79 31* 71* 0.86 0.90 Eastern

North 77* 97* 53* 81* 50* 81* 0.94 1.00 East

Eastern 56 38* 35 0.92

North 67 46 36 0.78

Karamoj 57 37* 35 0.95 a

Mid 64* 94* 43* 84* 31* 75* 0.72 0.90 Northern

West 52 82* 96* 32 60* 85* 31* 46* 72* 0.97 0.77 0.86 Nile

Western 69* 52 41 0.79

Mid 34 94* 22 81 16 76* 0.73 0.94 Western

Southwe 58 97* 43 90* 30 63 0.70 0.70 st

South 44 31 23 0.74

Wealth Quintile

Poorest§ 47 55 91 30 37 77 27 33 72 0.90 0.89 0.94

Poorer 44 58 94* 30 42* 82* 24 33 73 0.80 0.79 0.89

Middle 49 60 93 33 43* 80 26 33 70 0.79 0.77 0.87

Richer 45 62* 88 29 47* 79 21 34 64* 0.72 0.72 0.81

Richest 49 63* 85* 36 54* 76 29 42* 64* 0.81 0.78 0.84

Residen ce

Urban§ 46 59 84 37 51 76 30 42 65 0.81 0.82 0.86

Rural 47 60 92* 31 44* 79 25 34* 69 0.81 0.77 0.87

No§ 46 59 90 31 44 79 26 35 68 0.81 0.79 0.87

Yes 54 72* 94 37 53* 82 28 41* 73 0.76 0.77 0.88

*p-value≤0.05 compared to reference group (denoted with §)

Observations Due to the 2013 universal coverage campaign, the 2014 results are vastly improved in all indicators, and the use:access ratio increased from 2011 to 2014. The percent of the population with access to a net is one of the highest observed among PMI countries. The Southwest region continues to be an under-performer for net use, however. Net access and use both increased between surveys in the majority of regions, wealth quintiles, and residence types. Earlier trends of wealthier households having better ownership, access, and use of ITNs was reversed in 2014. Urban residences had lower ownership, likely reflecting challenges with campaign implementation in urban areas, but access and use were similar among residences. Ownership, access, and use of ITNs was similar whether or not households reported being sprayed with IRS in the previous 12 months.

Implications for programming Uganda is doing a good job both in terms of access and use when compared to other countries. Continued net distributions nationwide will help in maintaining the high proportion of households with access to nets. Additional focus on net use throughout the year may be useful to boost rates in the drier seasons.

ITN Access and Use Report – August 3 2017 99 Vietnam

Vietnam’s last available DHS is from 2002 and does not contain a malaria module. Its MICS surveys from 2006, 2011, and 2013-14 do not contain the ITN module.

Zambia

Zambia has two distinct seasons, with rain from November to April and dry weather from May to October. The 2007 DHS was conducted in May through September 2007, during the dry season. The 2013-2014 DHS was conducted between August 2013 and April 2014, with each province splitting data collection relatively evenly between late 2013 and early 2014, with the exception of Copperbelt, Lusaka, Northwestern, and Western, which conducted fieldwork primarily before the end of 2013. Comparing 2007 to 2013-14 should take into consideration dry season fieldwork in 2007, and rainy season fieldwork (primarily) in 2013-14. The 2015 MIS was fielded in April and May 2015, in the high transmission season. Muchinga province was created just prior to the 2013-14 DHS, and therefore does not have data available for 2007. In 2007, 1,002 of 7,164 households reported being sprayed with IRS (14%). In 2013-14, 5,315 of 15,902 reported IRS (33%). In 2015, 977 of 3574 households reported IRS (27.3%). Zambia implemented targeted distributions in 2007, and mass distributions in 2011 and 2013-2014, and in 2015.

201 2013-14 5 2013-14 2015 2007 2013-14 2015 2007 2013-14 2015 2007 DHS 2007 DHS DHS MI DHS MIS DHS DHS MIS DHS DHS MIS S % of population with access % of households owning ≥1 ITN to an ITN within their own Ratio of use:access household Region Central§ 56 67 73 34 45 60 22 31 53 0.65 0.69 0.88 Copperb 55 75* 77 35 53* 53 24 38* 44 0.69 0.71 0.82 elt Eastern 50 77* 95* 33 51* 78* 20 38* 82* 0.61 0.75 1.05

ITN Access and Use Report – August 3 2017 100 201 2013-14 5 2013-14 2015 2007 2013-14 2015 2007 2013-14 2015 2007 DHS 2007 DHS DHS MI DHS MIS DHS DHS MIS DHS DHS MIS S % of population with access % of households owning ≥1 ITN to an ITN within their own Ratio of use:access household Luapula 81* 63 89* 56* 41 76* 52* 37* 67* 0.93 0.90 0.89 Muching 73 61 51 53 41* 37 0.80 0.70 a Lusaka 50 49* 82 33 34* 65 16 19* 60 0.48 0.56 0.93 Northern 48 60* 81 30 36* 62 24 31 55 0.80 0.86 0.89 Northwe 54 66 81 31 41 66 23 34 51 0.74 0.82 0.77 stern Southern 40* 79* 81 23* 56* 71 12* 41* 60 0.52 0.73 0.85 Western 55 77* 72 38 58* 54 25 55* 50 0.66 0.95 0.92

Wealth Quintile Poorest§ 48 64 79 28 41 60 17 35 55 0.61 0.84 0.91 Poorer 53* 72* 80 35* 46* 62 26* 38* 56* 0.74 0.82 0.89 Middle 55* 72* 79 35* 48* 68 27* 36 63 0.77 0.75 0.93 Richer 51 64 82 33* 46* 66 22* 31* 59 0.67 0.67 0.90 Richest 60* 68* 79 39* 51* 67 24* 34 52 0.62 0.68 0.78

Residen ce Urban§ 52 62 77 34 45 65 22 32 54 0.65 0.71 0.82 Rural 54 72* 81 34 48 65 24 37* 58 0.71 0.78 0.89

ITN Access and Use Report – August 3 2017 101 201 2013-14 5 2013-14 2015 2007 2013-14 2015 2007 2013-14 2015 2007 DHS 2007 DHS DHS MI DHS MIS DHS DHS MIS DHS DHS MIS S % of population with access % of households owning ≥1 ITN to an ITN within their own Ratio of use:access household IRS No§ 53 65 76 34 44 62 23 33 53 0.68 0.75 0.86 Yes 54 75* 89 33 52* 72 21 39* 65 0.64 0.75 0.90 *p-value≤0.05 compared to reference group (denoted with §)

Observations On the whole, the net use:access ratio in Zambia was average in 2007, with the exception of Luapula and Northern provinces who have a ratio 0.80, and Lusaka and Southern whose ratios are around 0.50. There was improvement in use:access ratios throughout the country in 2013-14, except in Central, Copperbelt, and Eastern provinces. The greatest gains were seen in Lusaka, Southern, and Western. As in many other countries, the poorer wealth quintiles have higher use:access ratios than richer ones. There is no programmatic difference in use or access for urban vs rural households. Households receiving IRS reported significantly higher ITN ownership, access, and use; this did not affect the use:access ratio, which programmatically equivalent in all three surveys. We see an improvement in 2015 use:access ratios likely attributable to the survey timing in high transmission season, indicating that there may be strong seasonal patterns to ITN use in Zambia.

Implications for programming Net distribution and SBCC campaigns should be targeted to the regions with the lowest proportions, in an effort to increase both net access and use. Specifically, SBCC campaigns would be useful to improve net use in times and areas of lower transmission and throughout the year.

ITN Access and Use Report – August 3 2017 102 Zimbabwe

Four surveys are available for analysis from Zimbabwe. Fieldwork for the 2005-2006 DHS was conducted from August 2005 to February 2006, which was partly during the rainy season (November to March), and partly during the dry season (April to October). The 2010-2011 DHS was conducted from October 2010 through March 2011, primarily during the dry season. The 2012 MIS is not publicly available. A MICS was fielded in 2014, from February to April, in high transmission season. The 2015 DHS was fielded from July to December, in both dry and early rainy seasons. An MIS was fielded in March-April 2016 but is not yet available. In 2005-06, 1,402 households reported being sprayed with IRS, of 9,285 (15%). In 2010, 1,892 of 9,756 (19%) reported spraying. In 2014, 3,731 of 15,686 households reporting being sprayed with IRS (24%); in 2015, 2,263 of 10,534 (22%) households reported IRS. Zimbabwe implemented targeted distributions in 2008-2010, and mass distributions in 2013-2014.

20 05 2005- 2014 2014 2005- 2010 2015 2005-6 2010 2015 -6 2010 2015 2010 2014 2015 6 2 MIC MIC 6 DHS DHS DHS DHS DHS D DHS DHS DHS MICS DHS DHS 0 S S DHS H S % of population with access % of households owning ≥1 to an ITN within their own Ratio of use:access ITN household Region † 9 46 6 57 5 35 49 46 2 16 36 11 0.40 0.46 0.73 0.24 Manicaland§ † Mashonaland 11 33 5 49 7 24 40 34 2 13 37 9 0.29 0.54 0.93 0.27 Central

ITN Access and Use Report – August 3 2017 103 20 05 2005- 2014 2014 2005- 2010 2015 2005-6 2010 2015 -6 2010 2015 2010 2014 2015 6 2 MIC MIC 6 DHS DHS DHS DHS DHS D DHS DHS DHS MICS DHS DHS 0 S S DHS H S % of population with access % of households owning ≥1 to an ITN within their own Ratio of use:access ITN household † Mashonaland 5 26* 4 53 3 18* 34* 43 2 7* 27* 10 0.67 0.39 0.81 0.22 East Mashonaland 9 22* 4 67* 6 15* 36* 52 4 6* 25* 12 0.67 0.40 0.69 0.22 West Matebeleland 8 41 7 71* 4 29 61* 58 2 13 39 14 0.50 0.45 0.65 0.24 North Matebeleland 6 7* 1 40* 3 3* 5* 32 1 2* 3* 6* 0.33 0.67 0.57 0.20 South Midlands 12 36 3 47 6 23* 27* 38 2 8* 18* 8 0.33 0.35 0.68 0.22 Masvingo 3* 29* 5 55 2* 22* 39* 40 1 6* 28* 8 0.50 0.27 0.71 0.20 Harare 11 15* 2 17 7 10* 18* 11 4 4* 11* 2* 0.57 0.40 0.59 0.20 Bulawayo 6 26* 3 30* 3 17* 20* 20 2 10* 12* 8 0.67 0.59 0.58 0.39

Wealth Quintile Poorest§ 5 35 5 53 3 25 44 38 1 10 32 10 0.33 0.40 0.72 0.26 Poorer 8* 30* 4 55 4 21* 37* 43 1 8 28* 10 0.25 0.38 0.77 0.24 Middle 6 29* 4 59* 3 20* 33* 47 1 8 24* 10 0.33 0.40 0.72 0.21 Richer 8 24* 4 38* 5* 17* 29* 30 3* 8 22* 6* 0.60 0.47 0.75 0.21 Richest 15* 27* 3 38* 9* 18* 26* 28 5* 8 14* 7* 0.56 0.44 0.54 0.23

ITN Access and Use Report – August 3 2017 104 20 05 2005- 2014 2014 2005- 2010 2015 2005-6 2010 2015 -6 2010 2015 2010 2014 2015 6 2 MIC MIC 6 DHS DHS DHS DHS DHS D DHS DHS DHS MICS DHS DHS 0 S S DHS H S % of population with access % of households owning ≥1 to an ITN within their own Ratio of use:access ITN household Residence Urban§ 11 23 3 32 7 15 24 23 4 7 15 6 0.57 0.47 0.60 0.27 Rural 7* 32* 4 56* 4* 22* 38* 43* 2* 9 28* 10* 0.50 0.41 0.74 0.22

IRS No§ 7 22 3 43 4 15 25 33 2 6 16 7 0.50 0.40 0.67 0.21 Yes 15* 57* 7 66* 9* 42* 60* 51* 4* 18* 45* 13* 0.44 0.43 0.76 0.26 † Manicaland, Mashonaland East, and Mashonaland Central comprise 86 of all cases in Zimbabwe. *p-value≤0.05 compared to reference group (denoted with §)

Observations Net use and access is below target across the board, and there were only slight improvements in the proportion of households with access to nets between 2010 and 2015. This pattern of low use and access is seen in all wealth quintiles and residence types. ITN ownership, access, and use were significantly higher in households receiving IRS; however the use:access ratio was similar among both groups. The 2014 MICS shows improvements, likely related to being fielded during high transmission season, but use:access ratios are still under target for the most part – although highest in the higher transmission regions. The 2015 DHS was fielded in dry and early rainy season and shows low use generally, with higher use:access ratios in Bulewayo. While fieldwork was conducted in each region across several months, the of ITNs used the previous night increased steadily over time (data not shown) from 17 in July to 32 in December.

ITN Access and Use Report – August 3 2017 105 Implications for programming With an overall use gap of 20-80 percentage points depending on the season, SBCC campaigns encouraging net use must accompany ITN distribution, as the proportion of people using nets across the country is below target. Given that the majority of cases occur in Manicaland (51%), Mashonaland East (16%), and Mashonaland Central (19%), special attention to boosting the ratio of use:access should be given in those provinces. Further work to assess trends in seasonality would be useful.

ITN Access and Use Report – August 3 2017 106 Appendix: Non PMI-Focus Countries

Burkina Faso

Burkina Faso’s 2010 DHS was conducted primarily in July-December, although some fieldwork occurred in the first half of the year. The 2014 MIS was fielded from September to December, during high transmission season. Rainy season in Burkina Faso is from approximately May to September, with a shorter period in the north. In 2010 only 220 households reported being sprayed with IRS, out of 14,150 (1.6%); in 2014, 289 reported being sprayed with IRS, out of 38,873 (0.7%). Burkina Faso implemented a universal coverage campaign in 2010 and again in early 2014. A third universal campaign is planned for 2016.

2010 DHS 2014 MIS 2010 DHS 2014 MIS 2010 DHS 2014 MIS 2010 DHS 2014 MIS % of population with % of households owning % of population that used access to an ITN within Ratio of use:access ≥1 ITN an ITN the previous night their own household Region Boucle De Mouhon§ 49 90 27 67 26 68 0.95 1.02 Cascades 69* 88 49* 68 44* 68 0.91 1.00 Centre 55 86 35 72 21 60* 0.59 0.84 Centre-Est 46 96* 26 77* 23 79* 0.86 1.02 Centre-Nord 34* 96* 18* 73* 17* 73* 0.95 0.99 Centre-Ouest 62* 90 36* 71 33* 61* 0.91 0.87 Centre-Sud 49 90 24 76 24 75* 0.99 0.99 Est 66* 78* 39* 59* 32* 63 0.84 1.07 Hauts Basins 49 93 29 78 27 70 0.95 0.91 Nord 95* 95* 74* 76* 61* 66 0.82 0.86

ITN Access and Use Report – August 3 2017 107 2010 DHS 2014 MIS 2010 DHS 2014 MIS 2010 DHS 2014 MIS 2010 DHS 2014 MIS % of population with % of households owning % of population that used access to an ITN within Ratio of use:access ≥1 ITN an ITN the previous night their own household Plateau Central 91* 92 71* 71* 67* 64 0.95 0.90 Sahel 47 88 24 66 26 65 1.06 0.98 Sud-Ouest 64* 84* 43 67 40* 60* 0.92 0.89

Wealth Quintile Poorest§ 49 84 29 63 26 64 0.88 1.01 Poorer 53* 92* 34* 72* 30* 69* 0.90 0.96 Middle 57* 94* 36* 74* 33* 71* 0.91 0.96 Richer 60* 94* 37* 75* 34* 70* 0.92 0.94 Richest 65* 87 44* 72* 34* 61 0.78 0.85

Residence Urban§ 60 87 40 71 31 62 0.78 0.87 Rural 56* 91* 35 71 32 69* 0.90 0.97

IRS No§ 57 90 36 71 31 67 0.87 0.94 Yes 75 99 51* 77 46 63 0.91 0.82

Observations Burkina Faso has excellent use of available nets, reflected in use:access ratios that are nearly always above 0.80, with exceptions in 2010 for the richest wealth quintiles, urban areas, and the Centre region (which houses Ouagadougou). However, by 2014 following the country’s second mass

ITN Access and Use Report – August 3 2017 108 ITN campaign, use rates are uniformly good during the high transmission season, across the country. Ownership and access to ITNs are lower among the poorest wealth quintiles in both surveys, indicating a potential failure of ITN campaigns to reach these vulnerable groups.

Implications for programming Program planners should maintain the net use promotion activities currently underway, and explore methods to ensure that ITNs are accessible by the poorest wealth quintiles.

Burundi

Burundi’s 2010 DHS was fielded from August to January 2010-2011, during the minor rainy and short dry season. The 2012 MIS was fielded from November to January 2012-13, during the short dry season. In 2010, 49 households reported being sprayed with IRS out of 8,596 (0.6%), and in 2014, 232 households reported being sprayed, of 4,866 (4.8). Burundi implemented universal coverage campaigns in 2011 and 2014.

2010 DHS 2012 MIS 2010 DHS 2012 MIS 2010 DHS 2012 MIS 2010 DHS 2012 MIS % of population with access % of households owning ≥1 % of population that used to an ITN within their own Ratio of use:access ITN an ITN the previous night household Region Bujumbura§ 67 78 50 63 51 68 1.02 1.09 North 41* 56 29* 42 29* 43 0.99 1.04 Centre-east 54* 56 39* 39 38* 41 0.96 1.04 West 71 69 59 49 58 55 0.98 1.10 South 46* 73 33* 54 29* 56 0.90 1.03

ITN Access and Use Report – August 3 2017 109 2010 DHS 2012 MIS 2010 DHS 2012 MIS 2010 DHS 2012 MIS 2010 DHS 2012 MIS % of population with access % of households owning ≥1 % of population that used to an ITN within their own Ratio of use:access ITN an ITN the previous night household Wealth Quintile Poorest§ 37 47 29 34 27 35 0.95 1.04 Poorer 50* 60* 37* 43* 35* 47* 0.95 1.08 Middle 54* 69* 40* 49* 39* 52* 0.98 1.06 Richer 59* 71* 41* 49* 40* 52* 0.98 1.05 Richest 65* 75* 49* 55* 47* 57* 0.97 1.04

Residence Urban§ 68 75 51 59 52 63 1.01 1.08 Rural 50* 62* 38* 45* 36* 47* 0.96 1.05

IRS No§ 52 62 39 45 38 47 0.97 1.05 Yes 53 80 46 64 40 69 0.87 1.08

Observations Burundi has excellent use of available nets. Ownership and access are significantly lower among the poorest wealth quintile, and among rural populations.

Implications for programming Additional focus on ensuring that ITNs reach the poorest wealth quintile is needed.

ITN Access and Use Report – August 3 2017 110 ITN Access and Use Report – August 3 2017 111 Cameroon

The 2011 DHS was carried out from January to August, spanning dry and rainy seasons. Cameroon conducted mass ITN campaigns in 2011 after the DHS was fielded. Only 226 households reported being sprayed with IRS, out of 7,125 (3.2%). Cameroon conducted a mass distribution in 2011.

2011 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Region Adamaoua§ 19 11 11 0.94 Centre 20 11 9 0.79 Douala 19 13 12 0.93 Est 18 11 9 0.81 Extreme-Nord 13* 7* 2* 0.30 Littoral 21 13 11 0.84 Nord 26* 15* 7* 0.43 Nord-Ouest 23* 12* 11 0.91 Ouest 16 8 6* 0.75 Sud 16 11 9 0.83 Sud-Ouest 17 10 8 0.80 Yaoundé 16* 10 8 0.81

Wealth Quintile Poorest§ 17 9 5 0.49

ITN Access and Use Report – August 3 2017 112 2011 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Poorer 18 10 7* 0.68 Middle 20* 11* 8* 0.74 Richer 19 11* 9* 0.79 Richest 18 13 10* 0.79

Residence Urban§ 18 11 9 0.77 Rural 19 10 7* 0.65

IRS No§ 36 20 14 0.71 Yes 49 33* 24 0.73

Observations Use:access ratios are lowest in the north and extreme-north of the country, potentially reflecting dry season net use habits, and among the poorest quintile, possibly correlated with residence in the north. The center and west of the country show room for improvement in net use:access, although with the very low overall ownership and access rates, this may improve following mass ITN distribution.

Implications for programming Use of available ITNs is lowest in the Nord and Extreme-Nord regions; additional focus may be needed there to boost rates. Additional data and a seasonal analysis would help to further interpret these findings.

ITN Access and Use Report – August 3 2017 113 Central African Republic

The 2010 MICS was fielded in CAR between June and December. The country’s first universal coverage campaign began in September 2010. Ombella Mpoku’s fieldwork was completed prior to the UCC. A second universal LLIN campaign began in December 2014 and continued into mid-20166.

2010 MICS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Region Ombella Mpoku§ 20 12 14 1.23 Lobaye 43* 27* 29* 1.08 Mambere Kadei 46* 30* 29* 0.95 Nana Mambéré 36* 23* 22* 0.99 Sangha Mbaere 41* 25* 28* 1.10 Ouham Pende 66* 40* 42* 1.05 Ouham 75* 45* 49* 1.09 Kémo 33* 20 23* 1.19 Nana Grebizi 50* 31* 34* 1.10 Ouaka 47* 34* 37* 1.08 Haute-Kotto 33* 22* 24* 1.10 Baminigui Bangoran 36* 27* 28* 1.03 Vakaga 32* 26* 30* 1.15

6 http://www.ifrc.org/fr/nouvelles/nouvelles/africa/central-african-republic/la-distribution-de-moustiquaires-pour-sauver-des-vies-en-republique- centrafricaine/

ITN Access and Use Report – August 3 2017 114 2010 MICS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Basse Kotto 70* 47* 49* 1.03 Mbomou 40* 28* 30* 1.07 Haut Mbomou 42* 31* 33* 1.05 Bangui 53* 33* 36* 1.10

Wealth Quintile Poorest§ 47 30 33 1.08 Poorer 50 32 34 1.08 Middle 50 31 34 1.09 Richer 47 28 31 1.10 Richest 55* 34 34 1.02

Residence Urban§ 47 29 32 1.08 Rural 50 32* 34 1.06

Observations CAR shows high rates of use among those with access to a net, across the country. There are no major differences by socioeconomic quintile or by residence.

Implications for programming Increasing access to ITNs by the population as a whole will be important.

ITN Access and Use Report – August 3 2017 115 Chad

The 2004 DHS does not contain the updated ITN roster. The 2010 MICS was conducted from January to May, during the dry season. The 2014- 2015 DHS was conducted primarily from November to March. Rains in Chad are minimal in the northern part of the country, and from May- November in the central and southern portions. Chad conducted mass distributions in 2010 and 2014. A total of 95 households reported being sprayed with IRS in the previous 12 months, of 11,347 households (0.8).

2010 MICS 2015 DHS 2010 MICS 2015 DHS 2010 MICS 2015 DHS 2010 MICS 2015 DHS % of population with access % of households owning ≥1 % of population that used to an ITN within their own Ratio of use:access ITN an ITN the previous night household Region Bhata§ 42 50 25 35 9 15 0.38 0.43 BET 20* 13* 14* 10* 3* 3* 0.22 0.28 Chari Baguirmi 50 48 37* 40 4* 33* 0.10 0.82 Guéra 46 58* 27 41* 5 16 0.17 0.40 Hadjer Lamis 59* 59* 38* 46* 7 8 0.18 0.17 Kanem 35 22* 21 14* 1* 1* 0.07 0.04 Lac 36 44 24 29* 10 10 0.39 0.36 Logone Occidental 18* 58* 10* 48* 1* 14 0.12 0.29 Logone Oriental 32* 57* 19 43* 0* 24* 0.02 0.56 Mandoul 12* 56* 7* 42* 2* 27* 0.25 0.65 Mayo Kebbi 52* 58* 36* 51* 2* 34* 0.06 0.67

ITN Access and Use Report – August 3 2017 116 2010 MICS 2015 DHS 2010 MICS 2015 DHS 2010 MICS 2015 DHS 2010 MICS 2015 DHS % of population with access % of households owning ≥1 % of population that used to an ITN within their own Ratio of use:access ITN an ITN the previous night household Est Mayo Kebbi Ouest 25* 63* 11* 52* 1* 29* 0.11 0.56 Moyen Chari 41 58* 25 47* 3* 44* 0.13 0.93 Ouaddai 46 37* 31 27* 12 15 0.38 0.55 Salamat 57* 52 37* 40* 10 18 0.27 0.45 Tandjilé 44 61* 27 50* 1* 15 0.05 0.30 Wad Fira 20* 10* 14* 7* 3* 2* 0.23 0.27 Ndjaména 73* 56* 55* 47* 48* 44* 0.87 0.94 Barh el Gazal 33 35* 22 22* 1* 3* 0.05 0.15 Ennedi 12* 9* 2* 0.27 Sila 51 31* 28* 20* 6 19 0.21 0.94

Wealth Quintile Poorest§ 25 50 15 38 2 21 0.14 0.54 Poorer 34* 50 21* 39 4* 21* 0.18 0.55 Middle 39* 49 24* 38 5* 18* 0.19 0.49 Richer 49* 51 31* 39 7* 16* 0.23 0.42 Richest 67* 55* 48* 46* 29* 32* 0.60 0.69

Residence Urban§ 61 55 45 45 28 31 0.62 0.68 Rural 36* 50* 23* 38* 4* 19* 0.16 0.50*

ITN Access and Use Report – August 3 2017 117 2010 MICS 2015 DHS 2010 MICS 2015 DHS 2010 MICS 2015 DHS 2010 MICS 2015 DHS % of population with access % of households owning ≥1 % of population that used to an ITN within their own Ratio of use:access ITN an ITN the previous night household

IRS No 77 61 33 0.54 Yes 92* 75* 50* 0.68

Observations Chad’s has very low use:access ratios across most of the country, with exceptions in the capital, Ndjamena, Sila, Chani Begiurmi, and Moyen Chani, for whom data collection occurred in November/December, during transmission season,. While ownership of any ITN remained fairly stable from 2010 to 2015, access to ITNs increased across much of the country. Disparities in ownership, access, and use in rural and urban areas decreased from 2010 to 2014-15. Use:access ratio is much higher in urban areas, particularly Ndjamena, and use is highest in that region. There is a strong pro-rich trend for ownership, access, use, and use:access ratio, which may reflect geographic conditions for these populations.

Implications for programming Additional data is needed to confirm whether use:access ratios systematically improve during rainy season. Increasing access to nets, particularly among poorer and rural populations, is key.

Comoros

The 2012 DHS was fielded between August and December, prior to and during the beginning of the rainy season. In 2012, 624 households reported being sprayed with IRS, of 4,482 surveyed households (14%).

ITN Access and Use Report – August 3 2017 118 2012 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Region Mohéli§ 64 44 43 0.98 Ndzouani 51* 34* 33* 0.98 Ngazidja 67 49 43 0.89

Wealth Quintile Poorest§ 54 33 34 1.02 Poorer 54 36* 36 0.98 Middle 62* 45* 42* 0.93 Richer 64* 45* 40* 0.90 Richest 62* 46* 39* 0.85

Residence Urban§ 57 40 37 0.91 Rural 60 42 39 0.94

IRS No§ 58 41 38 0.93 Yes 67* 47* 44* 0.94

ITN Access and Use Report – August 3 2017 119 Observations Comoros has good use:access ratios, indicating a strong culture of net use. Ownership and access to ITNs is higher among wealthier socioeconomic quintiles.

Implications for programming There is no particular need for targeted BCC messaging to specific regions or groups based on these results.

Republic of Congo (Brazzaville)

The Republic of Congo’s 2011-2012 DHS was fielded from September through February, including the rainy season in the southern part of the country, and covering the short dry season in the northern part. Congo implemented a mass distribution in 2011-12; the DHS captured the first wave of distribution in Pool province, but not in other areas.

2011-2012 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Region Kouilou§ 30 21 26 1.27 Niari 35 23 28 1.20 Lekoumou 29 20* 22 1.11 Bouenza 30 19* 22 1.11 Pool 73* 62* 68* 1.10 Plateaux 40* 27* 31* 1.15 Cuvette 40* 27* 32* 1.18 Cuvette-ouest 41* 27* 30 1.09 Sangha 37 23* 26 1.14

ITN Access and Use Report – August 3 2017 120 2011-2012 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Likouala 57* 39* 51* 1.30 Brazzaville 30 20* 22 1.10 Pointe Noire 19* 12* 15* 1.25

Wealth quintile Poorest§ 43 31 37 1.19 Poorer 36* 24* 29* 1.21 Middle 32* 22* 25* 1.16 Richer 27* 18* 21* 1.14 Richest 26* 18* 17* 0.99

Observations Congo-Brazzaville’s use:access ratios are extremely high, reflecting an average number of users per net higher than 2. It is highest among the poorest wealth quintiles. Access to ITNs is higher in rural areas, and regional differences in ITN access reflect timing of the survey vs the mass campaign in 2011-12.

Implications for programming Additional efforts should be made to ensure access to ITNs, and to maintain BCC messaging for net use, but the use culture in Congo-Brazzaville appears excellent country-wide.

ITN Access and Use Report – August 3 2017 121 ITN Access and Use Report – August 3 2017 122 Cote d’Ivoire

The 2012 DHS was fielded primarily from December 2011 to March 2012, during the late high transmission season/early dry season. There were 135 households reporting being sprayed with IRS, out of 9,686 (1.4%). Cote d’Ivoire implemented mass distribution in 2008 and 2010-2011, and 2014.

2011-2012 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Region Centre§ 71 50 32 0.64 Centre-Est 65 51 37 0.73 Centre-Nord 75 58 46* 0.80 Centre-Ouest 77 55 47* 0.85 Nord 69 50 36 0.72 Nord-Est 85* 61* 46* 0.76 Nord-Ouest 78 51 36 0.69 Ouest 53* 36* 27 0.75 Sud sans Abidjan 69 52 32 0.61 Sud-Ouest 65 50 34 0.69 Ville d'Abidjan 56* 41* 17* 0.41

Wealth Quintiles Poorest§ 70 52 43 0.82 Poorer 72 54 39* 0.72

ITN Access and Use Report – August 3 2017 123 2011-2012 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Middle 66 47 33* 0.71 Richer 66 48 29* 0.61 Richest 60* 44* 23* 0.51

IRS No§ 67 49 33 0.68 Yes 66 46 27 0.59

Observations Use:access ratios are below target in much of the country, and this may reflect survey fieldwork being conducted in the drier season. There is a pro-poor trend in use:access, also reflected in higher use:access among rural populations, and a very low use:access ratio in Abidjan itself.

Implications for programming Additional seasonal analysis would help to pinpoint BCC messaging to promote ITN use at specific times of year and among specific target groups.

ITN Access and Use Report – August 3 2017 124 Gabon

Fieldwork for the 2012 DHS was conducted from January to May, during the short dry and early rainy season. In 2012, 304 of 9,755 households reported being sprayed with IRS (3%).

2012 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Region Libreville-Port Gentil§ 31 23 23 1.00 Estuaire 42* 30* 30* 0.98 Haut-Ogooué 45* 31* 30* 0.97 Moyen-Ogooué 40* 30* 30* 1.00 Ngounié 40* 30* 29* 0.97 Nyanga 47* 36* 37* 1.02 Ogooué Marit.. 54* 44* 45* 1.03 Ogooué-Ivindo 60* 36* 40* 1.11 Ogooué-Lolo 41* 29* 29* 1.00 Woleu-Ntem 38* 27* 25 0.93

Wealth Quintile Poorest§ 42 31 32 1.02 Poorer 42 33 35 1.04 Middle 37* 29 30 1.02

ITN Access and Use Report – August 3 2017 125 2012 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Richer 36* 26* 26* 0.98 Richest 21* 14* 12* 0.81

IRS No§ 37 27 27 1.00 Yes 35 23 21 0.92

Observations Gabon has a strong culture of net use despite low levels of ITN access in 2012.

Implications for programming Increasing access among populations at risk should contribute directly to higher use of ITNs generally.

ITN Access and Use Report – August 3 2017 126 Gambia

Gambia’s 2013 DHS was fielded from February to April, during the dry season. A full 50 of the 52,691 households surveyed in the Gambia reported being sprayed with IRS (Banjul and Kanifing regions had far fewer households reporting spraying). Gambia conducted a mass ITN campaign in 2013.

2013 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Region Banjul§ 55 35 35 1.02 Kanifing 58 34 35 1.00 Brikama 64* 40* 35 0.86 Mansakonko 79* 56* 50* 0.89 Kerewan 74* 52* 40 0.77 Kuntaur 88* 57* 42 0.73 Janjanbureh 88* 59* 51* 0.87 Basse 88* 52* 27 0.52

Wealth Quintile Poorest§ 77 54 44 0.81 Poorer 80 53* 39* 0.74 Middle 75 47* 35* 0.75 Richer 62* 39* 36* 0.92 Richest 55* 33* 30* 0.92

ITN Access and Use Report – August 3 2017 127 2013 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night

Residence Urban§ 61 38 37 0.95 Rural 80* 52* 37 0.71

IRS No§ 62 40 35 0.87 Yes 84* 54* 41* 0.75

Observations Despite survey timing in full dry season, use:acess ratios are relatively high, reflecting the extensive net use culture in the Gambia. Access to ITNs shows a pro-poor trend, also demonstrated in the higher access among rural populations. We also observe higher access to ITNs but a lower use:access ratio among households reporting IRS. Basse region has a particularly poor use of available nets; fieldwork for Basse, furthest inland and drier than other regions, was done in March-April, which is hot season.

Implications for programming While it is unlikely that Gambians would benefit from additional BCC messaging about ITN use, given the strong culture of net use in the country, additional seasonal analysis may illuminate trends in use of the course of the year. Further attention may need to be paid in Basse.

ITN Access and Use Report – August 3 2017 128 Guyana

The 2009 DHS was fielded from February to August, during the rainy and rainier seasons.

2009 DHS % of population % of population % of households with access to an that used an ITN Ratio of use:access owning ≥1 ITN ITN within their the previous night own household Region Region 1 – Barima-Waini§ 38 29 32 1.12 Region 2 – Pomeroon-Supenaam 62* 56* 56* 1.01 Region 3 – Essequibo Islands-West Demarara 23* 19* 19* 1.02 Region 4 – Demerara-Mahaica 14* 12* 11* 0.89 Region 5 – Mahica-Berbice 25* 23* 21* 0.90 Region 6 – East Berbice-Corentyne 45* 41 39 0.95 Region 7 – Cuyuni-Mazaruni 48* 33 33 1.00 Region 8 – Potaro-Siparuni 40 31 29 0.93 Region 9 – Upper Takutu-Upper Essequibo 23* 17* 8* 0.47 Region 10 – Upper Demarara-Berbice 5* 3* 2* 0.62

Wealth Quintile Poorest§ 29 22 22 1.00 Poorer 28 24 24 1.00 Middle 29 25 24 0.96 Richer 25 24 21 0.87

ITN Access and Use Report – August 3 2017 129 2009 DHS % of population % of population % of households with access to an that used an ITN Ratio of use:access owning ≥1 ITN ITN within their the previous night own household Richest 17* 16* 15* 0.91

Residence Urban§ 13 11 10 0.92 Rural 31* 27* 25 0.95

Observations Use:access ratios are good throughout the country with the exception of regions 9 and 10. There are no major differences in use:access ratios among wealth quintiles or urban/rural residence, although there is a very slight pro-poor trend to ITN ownership and access.

Implications for programming Increased messaging on net use may be useful in regions 9 and 10, depending on seasonality analysis and malaria risk in these areas.

ITN Access and Use Report – August 3 2017 130 Haiti

Haiti’s DHS was fielded in 2012 from January to June, during the drier season and beginning of rainy season. There were 1,119 households reporting being sprayed with IRS, of 58,548 (1.9%).

2012 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Region Aire Metropolitaine/ 20 11 8 0.69 Reste-Ouest§ Sud-Est 26 16* 7 0.46 Nord 19 12 5 0.43 Nord-Est 19 10 8 0.81 Artibonite 9* 6* 5* 0.79 Centre 14* 6* 6 0.91 Sud 19 10 7 0.67 Grand'anse 18 9 5* 0.55 Nord-Ouest 17 9 6 0.72 Nippes 36* 23* 12* 0.53 Camps 29* 20* 14* 0.71

Wealth Quintile Poorest§ 9 5 3 0.55 Poorer 10 6 3* 0.57

ITN Access and Use Report – August 3 2017 131 2012 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Middle 19* 11* 7* 0.65 Richer 25* 15* 10* 0.69 Richest 30* 18* 12* 0.67

IRS No§ 19 11 7 0.65 Yes 31* 19* 12* 0.61

Observations We observe quite low ITN ownership and access across Haiti, and mediocre culture of net use, although the available data was collected just prior to transmission season.

Implications for programming Further data will be helpful to interpret seasonal trends in the indicators.

ITN Access and Use Report – August 3 2017 132 Mauritania

The 2011 MICS was fielded primarily from June through September, during high transmission season/rainy season, although still dry in many part of the country.

2011 MICS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Region Hodh Charghy§ 42 21 14 0.66 Hodh Gharby 35 16 8* 0.51 Assaba 54* 26* 17 0.66 Gorgol 57* 33* 20* 0.61 Brakna 76* 47* 28* 0.59 Trarza 64* 39* 25* 0.66 Adrar 79* 40* 2* 0.05 Dakhlett Nouadibou 1* 0* 0* 0.51 Tagant 18* 9* 1* 0.15 Guidimagha 72* 38* 27* 0.71 Tirs-ezemour 1* 0* (0) - Nouakchott 22* 11* 9* 0.77

Wealth Quintile Poorest§ 49 24 18 0.75 Poorer 55* 30* 18 0.61

ITN Access and Use Report – August 3 2017 133 2011 MICS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Middle 48 28 16 0.56 Richer 35* 21* 12* 0.57 Richest 30* 17* 11* 0.64

Observations Like other very dry countries (Niger; Chad), use:access ratios are poor to fair.

Implications for programming Additional data and a seasonal analysis would help to interpret these results. Improved access to ITNs is needed.

ITN Access and Use Report – August 3 2017 134 Namibia

The 2006-7 DHS was fielded from November to March, during the dry and rainy seasons, and the 2013 DHS from January to September, during the rainy and dry seasons. Only the regions of Caprivi, Kavango, Kunene, Ohangwena, Omaheke, Omusati, Oshana, Oshikoto, and Otjozondjupa are considered malaria endemic. In 2013 respondents were asked whether their household was sprayed with IRS in the previous 12 months; 9,128 of 41,627 responded yes (22%). These households were primarily in Caprivi, Kavango, Kunene, Ohangwena, Omusati, Oshana, Oshikoto, and Otjozondjupa.

2006-7 DHS 2013 DHS 2006-7 DHS 2013 DHS 2006-7 DHS 2013 DHS 2006-7 DHS 2013 DHS

% of % of % of population population households with access to that used an Ratio of use:access owning ≥1 an ITN within ITN the ITN their own previous household night

Region

Caprivi§ 54 59 39 46 30 19 0.76 0.42

Erongo 1* 4* 0* 3* 0* 0* 0.37 0.05

Hardap 4* 12* 2* 7* 1* 0* 0.37 0.04

Karas 3* 4* 1* 2* 1* 1* 0.42 0.32

Kavango 32* 41* 16* 25* 11* 10* 0.71 0.39

Khomas 4* 7* 3* 4* 1* 1* 0.51 0.18

ITN Access and Use Report – August 3 2017 135 2006-7 DHS 2013 DHS 2006-7 DHS 2013 DHS 2006-7 DHS 2013 DHS 2006-7 DHS 2013 DHS

Kunene 11* 24* 6* 16* 2* 3* 0.37 0.16

Ohangwena 38* 37* 20* 28* 4* 5* 0.22 0.17

Omaheke 21* 20* 12* 15* 3* 1* 0.23 0.05

Omusati 27* 32* 16* 20* 5* 2* 0.30 0.11

Oshana 38* 42* 23* 31* 9* 7* 0.40 0.22

Oshikoto 30* 39* 16* 28* 4* 3* 0.24 0.10

Otjozondjupa 14* 15* 9* 10* 3* 1* 0.35 0.07

Wealth Quintile

Poorest§ 28 33 15 23 8 6 0.50 0.26

Poorer 31 30* 17* 22* 6 6 0.37 0.26

Middle 23* 29* 15 21* 6 4* 0.40 0.17

Richer 16* 21* 11* 16* 5* 3* 0.49 0.19

ITN Access and Use Report – August 3 2017 136 2006-7 DHS 2013 DHS 2006-7 DHS 2013 DHS 2006-7 DHS 2013 DHS 2006-7 DHS 2013 DHS

Richest 8* 13* 6* 9* 2* 1* 0.36 0.15

Residence

Urban§ 10 15 7 11 4 3 0.53 0.25

Rural 29* 34* 17* 25* 7* 5* 0.40 0.20

No§ 20 15 3 0.20

Yes 45* 29* 7* 0.24

Observations Namibia has low ownership and access, with the exception of Caprivi region, near Angola and Zambia, and very low use:access ratios across the rest of the country. ITN distributions are targeted to particular regions.

ITN Access and Use Report – August 3 2017 137 Implications for programming Namibia’s low culture of net use would benefit from additional SBCC activities and ITN distributions in malarious areas.

The 2006 DHS was fielded from January to June, during the dry season, and in 2012 from January to June, also during dry season. In 2012, 109 households reported being sprayed with IRS, out of 10,750 surveyed households. Niger implemented mass distributions in 2005, 2009, and 2014.

2006 DHS 2012 DHS 2006 DHS 2012 DHS 2006 DHS 2012 DHS 2006 DHS 2012 DHS

Regions

Agadez§ 54 48 23 28 9 14 0.40 0.51

Diffa 42* 64* 23 46* 5* 12 0.22 0.26

Dosso 47 74* 21* 41* 5* 16 0.27 0.39

Maradi 47 67* 22* 39* 3* 11 0.14 0.29

Tahoua 42* 60* 19* 36* 3* 8* 0.17 0.23

Tillabéri 48 52 19* 32* 6* 21* 0.32 0.65

Zinder 42* 56 21* 36* 4* 13 0.20 0.35

ITN Access and Use Report – August 3 2017 138 2006 DHS 2012 DHS 2006 DHS 2012 DHS 2006 DHS 2012 DHS 2006 DHS 2012 DHS

Niamey 17* 68* 9* 43* 4* 28* 0.52 0.66

Wealth Quintile

Poorest§ 44 46 18 25 3 6 0.15 0.25

Poorer 40* 56* 19 33* 3 9* 0.18 0.27

Middle 45 65* 21 39* 4 13* 0.17 0.34

Richer 43 69* 20 42* 4 16* 0.18 0.39

Richest 42 73* 21 47* 9* 24* 0.41 0.50

Residence

Urban§ 37 70 18 45 9 25 0.50 0.56

Rural 44* 60* 20* 36* 3* 11* 0.16 0.32

No§ 61 37 14 0.37

ITN Access and Use Report – August 3 2017 139 2006 DHS 2012 DHS 2006 DHS 2012 DHS 2006 DHS 2012 DHS 2006 DHS 2012 DHS

Yes 67 46 27* 0.59

Observations Niger has good levels of ITN ownership and fair levels of ITN access as of 2012, although dry season fieldwork reveals that nets are used very rarely in the hotter months when available. Additional data collected during rainy/high transmission season would be useful to confirm that households make use of nets at some point in the year.

Implications for programming Additional efforts to encourage ITN use throughout the year would help to reduce malaria transmission in drier seasons; more data is needed to assess net use culture during transmission season.

ITN Access and Use Report – August 3 2017 140 Sao Tome

The 2008 DHS was fielded from September to January 2008-2009 during the short rainy season.

2008 DHS % of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night Region Regiao Centre§ 63 54 47 0.89 Regiao Sul 57 50 48 0.95 Regiao Norte 56 43 41 0.95 Regiao de Principe 68 59 46 0.77

Wealth Quintile Poorest§ 44 38 31 0.81 Poorer 58* 45* 40* 0.90 Middle 65* 54* 49* 0.92 Richer 70* 57* 53* 0.93 Richest 73* 62* 57* 0.92

ITN Access and Use Report – August 3 2017 141 Observations Sao Tome & Principe demonstrate good levels of use:access ratio, and fair levels of ITN ownership and access. There is a strong pro-rich and pro- urban trend to ownership, access, and use.

Implications for programming The poorest and rural households may need specific targeting with BCC messages to improve net use, particularly on Principe.

ITN Access and Use Report – August 3 2017 142 Sierra Leone

Sierra Leone’s 2008 DHS was fielded in April, May and June, just prior to rainy season, and did not contain IRS information. The 2010 MICS was fielded in October, November, and December, in high transmission season, and the 2013 DHS was fielded mostly in June to September (with some data collection in October and November), during rainy season. The rainy season is from May to November. In the 2010 MICS the number of households reporting they had been sprayed in the last 12 months was 1,565 out of 66,571 (2.4%). In 2013, only 550 households reported being sprayed, out of 12,629 (4%). Sierra Leone had a targeted campaign in 2006, and universal coverage campaigns in 2010 and in 2014.

2008 2010 2013 2008 2010 2013 2008 2010 2013 2008 2010 2013

DHS MICS DHS DHS MICS DHS DHS MICS DHS DHS MICS DHS

Region

Eastern§ 33 35 64 18 18 38 19 21 42 1.04 1.15 1.12

Northern 35 39 65 16 18 36* 17 21 41 1.07 1.16 1.13

Southern 45* 40 77* 26* 21 48* 27* 24 56* 1.02 1.13 1.15

Western 34 25* 47* 18 13* 25* 16 13* 23* 0.89 0.99 0.90

Wealth Quintile

ITN Access and Use Report – August 3 2017 143 2008 2010 2013 2008 2010 2013 2008 2010 2013 2008 2010 2013

DHS MICS DHS DHS MICS DHS DHS MICS DHS DHS MICS DHS

Poorest§ 30 29 64 16 15 38 17 17 44 1.08 1.16 1.17

Poorer 34 35* 65 17 17* 39 18 20* 45 1.04 1.15 1.15

Middle 40* 43* 70* 19* 22* 41* 21* 26* 47* 1.06 1.17 1.14

Richer 42* 40* 69* 21* 19* 40* 22* 22* 44 1.06 1.15 1.11

Richest 38* 34* 54* 20* 18* 31* 17 19 29* 0.87 1.04 0.93

Residen ce

Urban§ 36 33 58 19 16 33 18 18 33 0.95 1.10 1.00

Rural 37 38* 68* 19 19* 40* 20 22* 46* 1.05 1.15 1.15

No§ 35 64 19 37 18 42 0.95 1.11

Yes 36* 74 18* 41 21* 44 1.14 1.06

ITN Access and Use Report – August 3 2017 144 Observations We observe excellent use:access ratios in Sierra Leone across the three surveys. The wealthiest quintile appear to use available nets to a lesser degree than poorer quintiles, and similarly, rural populations have higher rates of use and of use:access ratios than urban populations, with the gap widening over time. Sufficient access to ITNs within the household is still below target as of the 2013 DHS, but the mass campaign of 2014 would have brought these numbers up, in principle.

Implications for programming Many use:access ratios are greater than 1.0, indicating that more than 2 people on average are using nets. Increasing access to ITNs in all households will be key.

ITN Access and Use Report – August 3 2017 145 Suriname

The 2010 MICS was fielded from July to September, during the wet season, one of which runs from April to August, and then from November to February. Only two regions, Brokopondo and Sipaliwini, owned bednets, and these regions are classified primarily as rural interior areas. Only 57 households out of 1864 reported being sprayed with IRS (3%). Suriname distributed ITNs in targeted areas between 2006-2008, and in 2010.

2010 MICS

% of population with % of population that % of households owning access to an ITN within used an ITN the previous Ratio of use:access ≥1 ITN their own household night

Region

Paramaribo

Wanica

Nickerie

Coronie

Saramacca

Commewijne

Marowijne

Brokopondo§ 61 37 34 0.92

ITN Access and Use Report – August 3 2017 146 2010 MICS

Sipaliwini 60 46 41* 0.88

Wealth Quintile

Poorest§ 31 21 19 0.90

Poorer 3.2* 2.1* 1.7* 0.82

Middle 0.4* 0.4* 0.3* 0.75

Richer

Richest 0.03* 0.02* 0.03* 1.40

Residence

Rural interior 60 44 39 0.89

Yes§ 84 61 66 1.07

No 60* 44* 38* 0.88

ITN Access and Use Report – August 3 2017 147 Observations Only two regions of Suriname own nets, with fair ITN ownership and access rates. Ownership and access are highest among the poorest wealth quintile, reflecting targeted distributions, but use of available nets is good for most subgroups.

Implications for programming Distribution of nets to these targeted populations will result in their use.

ITN Access and Use Report – August 3 2017 148 Swaziland

2006 DHS was fielded between July 2006 and February 2007, during the rainy season. The 2010 MICS was fielded in August to November, as the dry cooler weather turned to more humid summer. Swaziland distributed nets in 2009-2010 in targeted areas. A total of 621 households reported being sprayed with IRS, 4,834 (13%); 563 of these were in Lubombo region.

2010 2006 DHS 2006 DHS 2010 MICS 2006 DHS 2010 MICS 2006 DHS 2010 MICS MICS

% of population with % of households owning % of population that used access to an ITN within Ratio of use:access ≥1 ITN an ITN the previous night their own household

Region

Hhohho§ 1.6 5.4 0.9 5.0 0.1 0.4 0.06 0.08

Manzini 2.2 4.6 1.2 2.3 0.1 0.6 0.08 0.24

Shiselweni 2.5 1.0* 1.2 0.4* 0.2 0.1* 0.15 0.34

Lubombo 13.2* 34.5* 6.9* 27.4* 0.8* 4.2* 0.12 0.15

Wealth Quintile

Poorest§ 7.3 14.4 3.5 10.2 0.3 1.7 0.08 0.17

Poorer 4.2* 12.0 1.8* 8.4 0.1 1.1 0.07 0.13

ITN Access and Use Report – August 3 2017 149 2010 2006 DHS 2006 DHS 2010 MICS 2006 DHS 2010 MICS 2006 DHS 2010 MICS MICS

Middle 2.4* 9.6* 1.2* 8.2 0.2 1.1 0.13 0.14

Richer 3.5* 9.5* 1.9* 6.1* 0.3 0.7* 0.17 0.12

Richest 4.7 7.0* 2.9 4.8* 0.4 1.0 0.13 0.21

Residence

Urban§ 3.2 5.6 2.1 3.6 0.5 0.9 0.26 0.26

Rural 5.0 12.5* 2.3 8.7* 0.2* 1.2 0.08 0.14

Yes§ 47.6 40.1 5.4 0.13

No 5.1* 3.0* 0.5* 0.18

Observations Swaziland has very low use:access ratios, reflecting low malaria risk across most of the country. The Lubombo region has higher ITN ownership and access due to malaria control interventions there, but net use and use:access ratio are still very low.

ITN Access and Use Report – August 3 2017 150 Implications for programming Net use messages need to be carefully targeted to specific at-risk populations. These subnational analyses are not precise enough to illuminate habits of those at risk for malaria.

ITN Access and Use Report – August 3 2017 151 Timor Leste

The 2009-2010 DHS was fielded from August to January, spanning dry (May-Nov) and wet (Dec-April) seasons.

2009-10 DHS

Region

Aileu§ 52 32 39 1.22

Ainaro 16* 9* 11* 1.23

Baucau 22* 15* 17* 1.16

Bobonaro 42* 25* 31* 1.21

Cova Lima 62* 42 47* 1.13

Dili 51 34 40 1.15

Ermera 27* 14* 17* 1.26

Liquica 38* 20* 24* 1.19

Lautem 53 30 33* 1.09

Manufahi 23* 15* 18* 1.18

ITN Access and Use Report – August 3 2017 152 2009-10 DHS

Manatuto 55 35 43 1.21

Oecussi 54 35 34 0.98

Viqueque 43* 30* 30* 1.00

Wealth Quintile

Poorest§ 24 13 14 1.08

Poorer 31* 18* 21* 1.16

Middle 41* 24* 29* 1.17

Richer 55* 34* 40* 1.17

Richest 55* 38* 42* 1.12

Residence

Urban§ 51 33 38 1.14

Rural 38* 23 27* 1.14

ITN Access and Use Report – August 3 2017 153 Observations Despite relatively low ownership and access of ITNs, Timor Leste has excellent net use culture. There is a strong pro-rich and pro-urban trend to ownership, access, and use, although use:access ratios do not vary programmatically.

Implications for programming There is no particular area or group that would benefit from increased SBCC on net use.

ITN Access and Use Report – August 3 2017 154 Togo

Togo’s MICS was fielded in 2010 from September to November during high transmission season, and the DHS was fielded from November to March 2013-2014, during the dry season. Togo conducted mass distributions 2004, 2008, 2011, and 2014.

2013-14 2013-14 2013-14 2013-14 2010 MICS 2010 MICS 2010 MICS 2010 MICS DHS DHS DHS DHS

Region

Lome§ 44 52 30 39 26 24 0.86 0.61

Maritime (sans Lome) 51* 64* 33* 48* 26 28* 0.81 0.58

Plateaux 57* 72* 39* 52* 37* 40* 0.95 0.78

Centrale 64* 77* 41* 57* 38* 43* 0.92 0.75

Kara 66* 77* 41* 60* 39* 44* 0.95 0.72

Savanes 80* 69* 50* 47* 51* 32* 1.01 0.69

Wealth Quintiles

Poorest§ 57 75 36 50 35 36 0.99 0.72

ITN Access and Use Report – August 3 2017 155 2013-14 2013-14 2013-14 2013-14 2010 MICS 2010 MICS 2010 MICS 2010 MICS DHS DHS DHS DHS

Poorer 63* 75 41* 54 41* 40 0.99 0.73

Middle 60 67* 42 51* 38 35 0.92 0.70

Richer 52 59* 34 44* 29* 29* 0.85 0.67

Richest 55 58* 38 45* 29* 28* 0.78 0.62

Residence

Urban§ 51 58 34 44 28 28 0.83 0.63

Rural 62* 71* 41* 51* 39* 37* 0.95 0.72

Observations Togo’s two surveys reveal high use of available nets during high transmission season, and reductions in net use during dry season, typical for its geography. There is a pro-poor trend in ITN ownership, reflective of Togo’s repeated mass campaigns, and slight pro-poor trends in use:access ratio.

Implications for programming Additional BCC messaging to promote ITN use during drier times of the year would be helpful, but overall Togo has a relatively strong culture of net use.

ITN Access and Use Report – August 3 2017 156 Annex 1: Stata do-file for Report

*** Stata Do-file for PMI Access:Use report using MIS or DHS datasets

* (see www.vector-works.org/resources/llin-use-and-access-for-pmi-countries/)

** Authors: Albert Kilian and Hannah Koenker

** Goals: calculate three indicators –

* 1) household ownership of any ITN;

* 2) population access to ITN;

* 3) population use of ITN the previous night

* Step 1 - prep universal coverage indicators

* in the household data file (HR) – generate a new hhid variable to assist with merging.

* Note: very occasionally hv001 must be multiplied by 10,000 to accomodate longer hv002 strings.

rename hhid hhidx

gen hhid=(hv001*1000)+hv002

gen persid=hhid*100+hv003

foreach var of varlist hml10_*{

gen itn_`var' = `var'==1

egen nitn= rsum (itn*)

label var nitn "# of ITN in household"

ITN Access and Use Report – August 3 2017 157 gen anyitn=nitn>0

label var anyitn "hh has any ITN"

** calculate variable for households with at least 1 ITN for 2 people (p2itn) before doing any merging, if you want

* create de jure members 'person' from hv012 clonevar person=hv012

gen itnpers=nitn/person label var itnpers "ITN per person in household"

* SAVE the household data file (HR)

save, replace

* create a small dataset with only hhid, nitn, anyitn to merge into the household member dataset

keep hhid nitn anyitn

save nitn, replace

* Step 2 - OPEN the household member data set (PR). Population Access MUST be calculated in the

* hh member dataset to do the weighting correctly for individuals (and not by hh)

* generate a separate, comparable hhid to match the datasets on

rename hhid hhidx

gen hhid=(hv001*1000)+hv002

ITN Access and Use Report – August 3 2017 158 gen persid=hhid*100+hv003

* merge the PR file and the new 'nitn' file to bring the nitn variable into the household member (PR) file

merge m:1 hhid using nitn

drop _merge

* generate the 'stayed in the household last night' (defacto members) variable

gen stay=hv103==1

label var stay "stayed in house last night"

* rename the stratification variables -

** region (region or province);

** urban (urban or rural residence);

** ses (wealth quintile),

** irs (household was sprayed in the last 12 months)

clonevar region=hv024

clonevar urban=hv025

clonevar ses=hv270

clonevar irs=hv253

clonevar month=hv006

clonevar year=hv007

clonevar age=hv105

* Step 3 - Still in the household member (PR) file, calculate population access using the MERG method

gen potuse=nitn*2

label var potuse "potential ITN users in hh"

ITN Access and Use Report – August 3 2017 159 egen defacto=sum(stay), by(hhid)

label var defacto "de facto population"

bysort hhid: gen access2 = potuse/defacto

replace access2=1 if potuse/defacto >1

label var access2 "proportion in hh with access"

* gen the useitn variable

gen useitn=hml12==1

** set survey weights using cluster (hv001), strata (hv024) and household sampling weight (hv005)

svyset hv001 [pw=hv005], strata(hv024)

** calculate national population access

svy: mean access2 if stay==1

** calculate stratified population access, use 'logistic' command to assess significant differences from 1st result

svy: mean access2 if stay==1, over(region)

svy: logistic access2 i.region if stay==1

svy: mean access2 if stay==1, over(ses)

svy: logistic access2 i.ses if stay==1

svy: mean access2 if stay==1, over(urban)

svy: logistic access2 urban if stay==1

svy: mean access2 if stay==1, over(irs)

svy: logistic access2 i.irs if stay==1

* Step 4 - still in the household member (PR) file, calculate the mean net use

ITN Access and Use Report – August 3 2017 160 ** calculate national population use of ITNs

svy: mean useitn if stay==1

** calculate stratified population use

svy: mean useitn if stay==1, over(region)

svy: logistic useitn i.region if stay==1

svy: mean useitn if stay==1, over(ses)

svy: logistic useitn i.ses if stay==1

svy: mean useitn if stay==1, over(urban)

svy: logistic useitn urban if stay==1

svy: mean useitn if stay==1, over(irs)

svy: logistic useitn i.irs if stay==1

* SAVE the household member file (PR)

save, replace

* Step 5 - CLOSE the household member file and OPEN the household file.

* rename the needed stratification variables -

** region (region or province);

** urban (urban or rural residence);

** ses (wealth quintile),

** irs (household was sprayed in the last 12 months)

clonevar region=hv024

clonevar urban=hv025

clonevar ses=hv270

ITN Access and Use Report – August 3 2017 161 clonevar irs=hv253

clonevar month=hv006

clonevar year=hv007

save, replace

** calculate ownership of at least one ITN in household file

** set survey weights using cluster (hv001), strata (hv024) and household sampling weight (hv005)

svyset hv001 [pw=hv005], strata(hv024)

** calculate national household ownership of at least 1 ITN

svy: mean anyitn

** calculate stratified household ownership of at least 1 ITN

svy: mean anyitn, over(region)

svy: logistic anyitn i.region

svy: mean anyitn, over(ses)

svy: logistic anyitn i.ses

svy: mean anyitn, over(urban)

svy: logistic anyitn urban

svy: mean anyitn, over(irs)

svy: logistic anyitn i.irs

** GENERATE ANY NET and NET ACCESS FOR PLACES LIKE MYANMAR

** in HR file

clonevar numnet=hml1

ITN Access and Use Report – August 3 2017 162 gen anynet=numnet>0

keep hhid numnet anynet

save numnet, replace

** open PR file

merge m:1 hhid using numnet

drop _merge

gen potusenet=numnet*2

label var potusenet "potential net users in hh"

bysort hhid: gen accessnet = potusenet/defacto

replace accessnet=1 if potusenet/defacto >1

label var accessnet "proportion in hh with access to net of any kind"

ITN Access and Use Report – August 3 2017 163