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ITN Access and Use Report - 2018
Hannah Koenker, Emily Ricotta, & Bola Olapeju
January 5, 2018
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. January 2018. Insecticide-Treated Nets (ITN) Access and Use Report. Baltimore, MD. PMI | VectorWorks Project, Johns Hopkins Center for Communication Programs.
Table of Contents
ITN Access and Use Report - 2017
Abbreviations
Updates
Key findings across PMI focus countries
Background
Definitions
Methods
Results
Key Global Findings:
PMI Focus Countries
Angola
Benin
Burkina Faso
Cambodia
Cameroon
Cote d’Ivoire
DRC
Ethiopia
Ghana
Guinea
Kenya
Lao PDR
Liberia
Madagascar
Malawi
Mali
Mozambique
Myanmar
Niger
Nigeria
Rwanda
Senegal
Sierra Leone
Tanzania
Uganda
Vietnam
Zambia
Zimbabwe
Appendix: Non PMI-Focus Countries
Burundi
Central African Republic
Chad
Comoros
Republic of Congo (Brazzaville)
Gabon
Gambia
Guinea-Bissau
Guyana
Haiti
Mauritania
Namibia
Sao Tome
Suriname
Swaziland
Timor Leste
Togo
Annex 1: Stata do-file for Report
Abbreviations
DHSDemographic and Health Survey
MICSMultiple Cluster Indicator Survey
MISMalaria Indicator Survey
ITNInsecticide-treated net
IRSIndoor Residual Spraying
LLINLong-lasting insecticidal net
PMIPresident’s Malaria Initiative
Updates
This report was updated January 05, 2018. This report now contains results from 103household surveys in 44 countries.
Questions and comments can be directed to 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.
- 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 ratiosare 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 detail[1]. 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 householdsthat 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.
“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 MERG[2]. 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 de-facto 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 eachde factomember 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 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.
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 households owning ≥1 ITN / %of population with access to an ITN within their own household / % of population that used an ITN the previous night / Ratio of use:accessMedian (2005-2016) / 55.7% / 37.6% / 33.2% / 0.87
Mean (2005-2015) / 53.3% / 38.4% / 32.5% / 0.81
Median pre-2010 / 40.0% / 22.5% / 19.5% / 0.80
Median post-2010 / 61.5% / 41.5% / 36.9% / 0.88
Mean pre-2010 / 34.8% / 21.7% / 17.7% / 0.76
Mean post-2010 / 59.7% / 44% / 37.5% / 0.83
Minimum / 3.5% / 1.5% / 0.3% / 0.11
Maximum / 93.0% / 78.8% / 75.8% / 1.19
Results for ratio of use:access are color-coded as follows:
Note 1: Color coding of use:access ratios and explanation
≥0.80 / Use:access ratio is good, with at least 80% of those with access to an ITN using one the previous night≥0.60-<0.80 / Use:access ratio is below target level; improvements should be made
<0.60 / Use:access ratio is poor; explore reasons for non-use of available nets, such as 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
Country | Survey | Year / % of households owning ≥1 ITN / %of population with access to an ITN within their own household / % of population that used an ITN the previous night / Ratio of use:accessAngola 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
Burkina Faso DHS 2010 / 56.9 / 36.1 / 31.5 / 0.87
Burkina Faso MIS 2014 / 89.8 / 71.2 / 67.0 / 0.94
Cameroon DHS 2011 / 18.3 / 10.8 / 7.6 / 0.71
Cameroon MICS 2014 / 70.2 / 56.1 / 47.1 / 0.84
Cambodia DHS 2005 / 4.5 / 3.1 / 3.0 / 0.96
Cote d’Ivoire DHS 2012 / 67.3 / 49.0 / 33.2 / 0.68
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
Ethiopia MIS 2015 / 63.6 / 49 / 39.7 / 0.81
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
Liberia MIS 2016 / 61.5 / 41.5 / 39.2 / 0.94
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 AP 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
Niger DHS 2006 / 43.0 / 19.6 / 4.4 / 0.22
Niger DHS 2012 / 61.3 / 37.3 / 13.8 / 0.37
Nigeria DHS 2008 / 8.0 / 4.8 / 3.2 / 0.68
Nigeria MIS 2010 / 41.5 / 28.7 / 23.3 / 0.81
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
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
Sierra Leone MIS 2016 / 60.3 / 37.1 / 38.6 / 1.04
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
Senegal cDHS 2016 / 82.4 / 75.7 / 63.1 / 0.83
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
Table 2: National results for ITN ownership, access, use, and use:access ratio in non PMI-Focus countries
Country | Survey | Year / % of households owning ≥1 ITN / %of population with access to an ITN within their own household / % of population that used an ITN the previous night / Ratio of use:accessBurundi DHS 2010 / 52.0 / 39.1 / 37.8 / 0.97
Burundi MIS 2012 / 66.0 / 46.0 / 48.6 / 1.06
Central African Republic MICS 2010 / 49.2 / 31.1 / 33.3 / 1.07
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
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
Guinea-Bissau / 90.1 / 71.1 / 75.8 / 1.07
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
Sao Tome DHS 2008 / 60.8 / 51.0 / 45.9 / 0.90
Sao Tome MICS 2014 / 77.8 / 68.2 / 56.1 / 0.82
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 – January 5, 2018
1
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).
2006-7 MIS / 2011 MIS / 2015-16 DHS / 2006-7 MIS / 2011 MIS / 2015-16 DHS / 2006-7 MIS / 2011 MIS / 2015-16 DHS / 2006-7 MIS / 2011 MIS / 2015-16 DHS% of households owning ≥1 ITN / %of population with access to an ITN within their own household / % of population that used an ITN the previous night / Ratio of use:access
Zone
Stable Mesoendemic § / 20 / 36 / 37 / 11 / 19 / 25 / 10 / 21 / 23 / 0.91 / 1.11 / 0.93
Hyperendemic / 51* / 30 / 36 / 30* / 17 / 24 / 25* / 17 / 21 / 0.83 / 1.00 / 0.88
Instable Mesoendemic / 23 / 37 / 22* / 12 / 20 / 14* / 8 / 19 / 9* / 0.67 / 0.95 / 0.67
Luanda / 23 / 35 / 27* / 11 / 19 / 16* / 9 / 17 / 16* / 0.82 / 0.89 / 0.98
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 norte / 35 / 29* / 29* / 19 / 16* / 22* / 12 / 14* / 15* / 0.60 / 0.84 / 0.68
Kwanza sul / 19* / 27* / 40 / 9* / 16* / 31 / 6* / 19* / 19* / 0.62 / 1.17 / 0.61
Malange / 49 / 19* / 30 / 33 / 12* / 18* / 24 / 13* / 16* / 0.74 / 1.04 / 0.90
Lunda norte / 64 / 25* / 44* / 45 / 13* / 31 / 41 / 17* / 30 / 0.93 / 1.31 / 0.98
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 kubango / 26* / 17* / 15* / 12* / 17* / 10* / 1.16 / 0.89
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 sul / 63 / 17* / 44* / 42 / 8* / 31 / 29 / 10* / 30 / 0.68 / 1.34 / 0.97
Bengo / 27 / 52 / 23* / 15* / 31 / 15* / 16 / 30 / 10* / 1.04 / 0.98 / 0.62
WealthQuintile
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
Residence
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.
Implications for programming
While access to ITNs is quite low, use of these ITNs is high acrossmost 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.
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).
2006 DHS / 2011-12 DHS / 2006 DHS / 2011-12 DHS / 2006 DHS / 2011-12 DHS / 2006 DHS / 2011-12 DHS% of households owning ≥1 ITN / %of population with access to an ITN within their own household / % of population that used an ITN the previous night / Ratio of use:access
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
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. Additional work may be helpful to determine whether dry-season net use and transmission patterns warrant increased SBCC during lower-net use seasons.
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 households owning ≥1 ITN / % of population with access to an ITN within their own household / % of population that used an ITN the previous night / Ratio of use:access
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
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 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.