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CSU 107/2010: THREE ON EQUITY IN MALARIA

Friday, 22nd of October 2010 Print

EQUITY 107/2010:   THREE ON EQUITY IN MALARIA

1)      IS THE SCALE UP OF MALARIA INTERVENTION COVERAGE ALSO ACHIEVING EQUITY?

A review of the literature by Steketee and Eisele. For Internet users, the full text, with figures, is at http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0008409

From the authors’ conclusions: ‘Equitable distribution of interventions is possible; 54% of countries have equitable ITN distribution, 29% have equitable case management coverage and 20% have equitable IPTp coverage. But achieving equity in one area does not assure broad achievement of equity; only Namibia and the Gambia achieved equity for all three intervention strategies, and only the Gambia has equitable moderate or high coverage for the interventions.’

 

Public Library of Science

Is the Scale Up of Malaria Intervention Coverage Also Achieving Equity?

Malaria in Africa is most severe in young children and pregnant women, particularly in rural and poor households. In many countries, malaria intervention coverage rates have increased as a result of scale up; but this may mask limited coverage in these highest-risk populations. Reports were reviewed from nationally representative surveys in African malaria-endemic countries from 2006 through 2008 to understand how reported intervention coverage rates reflect access by the most at-risk populations.

Reports were available from 27 Demographic and Health Surveys (DHSs), Multiple Indicator Cluster Surveys (MICSs), and Malaria Indicator Surveys (MISs) during this interval with data on household intervention coverage by urban or rural setting, wealth quintile, and sex. Household ownership of insecticide-treated mosquito nets (ITNs) varied from 5% to greater than 60%, and was equitable by urban/rural and wealth quintile status among 13 (52%) of 25 countries. Malaria treatment rates for febrile children under five years of age varied from less than 10% to greater than 70%, and while equitable coverage was achieved in 8 (30%) of 27 countries, rates were generally higher in urban and richest quintile households. Use of intermittent preventive treatment in pregnant women varied from 2% to more than 60%, and again tended to be higher in urban and richest quintile households. Across all countries, there were no significant male/female inequalities seen for children sleeping under ITNs or receiving antimalarial treatment for febrile illness. Parasitemia and anemia rates from eight national surveys showed predominance in poor and rural populations.

Recent efforts to scale up malaria intervention coverage have achieved equity in some countries (especially with ITNs), but delivery methods in other countries are not addressing the most at-risk populations. As countries seek universal malaria intervention coverage, their delivery systems must reach the rural and poor populations; this is not a small task, but it has been achieved in some countries.

Article

Richard W. Steketee1*, Thomas P. Eisele2

1 Malaria Control and Evaluation Partnership in Africa (MACEPA)-PATH, Ferney-Voltaire, France, 2 Department of International Health and Development, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisana, United States of America 

Abstract 

Background and Methods

Malaria in Africa is most severe in young children and pregnant women, particularly in rural and poor households. In many countries, malaria intervention coverage rates have increased as a result of scale up; but this may mask limited coverage in these highest-risk populations. Reports were reviewed from nationally representative surveys in African malaria-endemic countries from 2006 through 2008 to understand how reported intervention coverage rates reflect access by the most at-risk populations.

Results

Reports were available from 27 Demographic and Health Surveys (DHSs), Multiple Indicator Cluster Surveys (MICSs), and Malaria Indicator Surveys (MISs) during this interval with data on household intervention coverage by urban or rural setting, wealth quintile, and sex. Household ownership of insecticide-treated mosquito nets (ITNs) varied from 5% to greater than 60%, and was equitable by urban/rural and wealth quintile status among 13 (52%) of 25 countries. Malaria treatment rates for febrile children under five years of age varied from less than 10% to greater than 70%, and while equitable coverage was achieved in 8 (30%) of 27 countries, rates were generally higher in urban and richest quintile households. Use of intermittent preventive treatment in pregnant women varied from 2% to more than 60%, and again tended to be higher in urban and richest quintile households. Across all countries, there were no significant male/female inequalities seen for children sleeping under ITNs or receiving antimalarial treatment for febrile illness. Parasitemia and anemia rates from eight national surveys showed predominance in poor and rural populations.

Conclusions/Significance

Recent efforts to scale up malaria intervention coverage have achieved equity in some countries (especially with ITNs), but delivery methods in other countries are not addressing the most at-risk populations. As countries seek universal malaria intervention coverage, their delivery systems must reach the rural and poor populations; this is not a small task, but it has been achieved in some countries.

Citation: Steketee RW, Eisele TP (2009) Is the Scale Up of Malaria Intervention Coverage Also Achieving Equity? PLoS ONE 4(12): e8409. doi:10.1371/journal.pone.0008409

Editor: Colin J. Sutherland, London School of Hygiene and Tropical Medicine, United Kingdom

Received: September 7, 2009; Accepted: November 24, 2009; Published: December 22, 2009

Copyright: © 2009 Steketee, Eisele. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: RWS is funded by the Malaria Control and Evaluation Partnership in Africa program at PATH through a grant from the Bill and Melinda Gates Foundation. TPE is funded by the Department of International Health and Development, Tulane School of Public Health and Tropical Medicine. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

* E-mail: rsteketee@path.org 

Introduction  

Malaria is not an equitably distributed infection or disease. Young children and pregnant women in rural and poor households in sub-Saharan Africa bear the brunt of malaria's morbidity and mortality [1][8].

As the Roll Back Malaria (RBM) effort set out to halve the malaria burden by 2010 [9], the early years from 1999 through 2004 were characterized by low coverage [10] and unequal distribution of prevention interventions whereby the poorest households had the lowest coverage [11], [12]. With more recent calls for Scale up for Impact (SUFI) [13], [14], malaria elimination [15], [16], and for universal coverage with malaria control interventions [17], addressing those at greatest risk of malaria has been in the forefront of discussions. The call for achieving universal coverage has focused initially on prevention interventions such as insecticide-treated mosquito nets (ITNs), indoor residual spraying (IRS), and prevention during pregnancy with ITNs and intermittent preventive treatment (IPTp). Achieving universal coverage among at-risk populations is warranted as prevention interventions have been shown to benefit even those not directly covered through a “community effect” when high population coverage is achieved [18][20]. Universal coverage would imply that everyone would have the needed preventive and curative interventions (100% and thus fully ‘equitable’). However, while en route to that goal, different intervention delivery strategies could lead to markedly variable coverage levels across the most at-risk populations [11], [21].

The malaria control community might see a dilemma here. As malaria is not an equitable disease, there is both an argument for targeting those at risk and an argument for providing universal population coverage (not specifically targeted) because of the additional community effect benefit. A possible resolution for the dilemma is to seek universal coverage and while achieving this, assuring and documenting that at least the same (equitable) coverage is attained for all populations at risk. In the context of the recent scale up of malaria interventions and the call for universal coverage in sub-Saharan Africa, we examined recent evidence from nationally representative household surveys to document whether national malaria programs have been achieving equity in the delivery of malaria prevention and treatment.

Methods 

Definitions

Inequities in health are considered those differences that are “not only unnecessary and avoidable, but in addition, are considered unfair and unjust” [22]. Inequities are frequently considered on the basis of demographic and/or socioeconomic status, often measured in asset-based wealth quintiles [23], geography (country region, or urban versus rural dwelling), sex, age, and ethnicity. Recent nationally-representative population-based surveys have systematically collected information on wealth quintile, urban and rural dwelling and sex; all of which are considered here. Information from a given country may be available on ethnic or provincial or regional differences, but when examining across many national surveys, these characteristics are not comparable so are not considered here. Comparisons were examined specifically among those most vulnerable: children under the age of 5 years and pregnant women.

Data Considered

Published reports were reviewed from recent nationally-representative household surveys conducted in sub-Saharan African from 2006 through 2008, a period following most recent intervention scale-up efforts, with the reports available by July 2009. In order to optimize the standard approach to data collection, only results from Demographic and Health Surveys (DHS: http://www.measuredhs.com/), UNICEF Multiple Indicator Cluster Surveys (MICS: http://www.unicef.org/statistics/index_24302.html ) and RBM Partnership Malaria Indicator Surveys (MIS: http://www.rollbackmalaria.org/mechanisms/merg.html#MIS ) were considered. The survey results are maintained on the UNICEF Child Info web site (www.childinfo.org) and include standardized information on household ownership and use of ITNs, use of prevention in pregnancy (IPTp and ITNs), and use of malaria treatment for children with recent fever illness. The surveys typically collect information on household location (urban or rural based on country definitions), child sex, and present household wealth quintiles based on a standard household asset index. Some surveys did not include full information on certain characteristics, thus the denominator of surveys varies for certain comparisons. While nationally-representative surveys have been conducted in malaria-endemic countries outside Africa and it is possible that more recent African national survey results may exist, surveys in more than one-half of the malaria-endemic sub-Saharan African countries were available and fitted our inclusion criteria. This group included a spectrum of low (less than 10%) to high (greater than 50%) coverage for the malaria interventions, and the information is summarized here.

Measurements

The following malaria intervention outcome indicators consistent with the recommended RBM definitions were assessed [24]: the proportion of households with at least one ITN; the proportion of children under 5 years old with fever in the past 2 weeks who received an antimalarial: and the proportion of women of reproductive age who received at least two doses of sulfadoxine-pyrimethamine (SP) during their last pregnancy.

We assessed equity in intervention coverage with the following indicators: 1) urban versus rural status of household; 2) highest versus lowest wealth quintile; and 3) male versus female child gender. As there is no single standard for establishing a measure of equity for a given comparison (e.g., when comparing socioeconomic status across quintiles), we established an “equity index” as the ratio between intervention coverage between the two categories for each of the equity indicators outlined above. As such, an equity index greater than 1.0 suggests over representation of intervention coverage among urban households, the wealthiest households and male children.

Additionally, to assess whether malaria intervention coverage was statistically different between measures of equity, we performed a simple Pearson's Chi-square test to determine differences in these outcome indicators by urban versus rural status, highest versus lowest wealth quintile, and use among male versus female children. For these comparisons, the raw survey datasets were not used to ascertain Ch-square test statistics; instead, cells based on sample size and coverage estimates were used to create 2x2 tables. Where sample sizes were not available by wealth quintile (1 study), equal distribution across quintiles was assumed for calculating Chi-square test statistics. This approach does not account for the effect of clustered data as a result of the two-stage cluster sampling designs employed by the DHS, MICS and MIS, and thus the statistical tests used here may slightly overestimate statistical significance. However, we assert that this approach is sufficient for this description of how coverage outcomes differ by equity factors. In general, a coverage indicator was considered equitable if it achieved equal or higher coverage among poor and/or rural populations, with the probability of committing a type-1 error set at 0.05.

As multiple comparisons are presented in the figures, countries were grouped as equitable if the equity index for all variables considered was less than 1.2; countries where the equity index exceeded 1.2 for one or both comparisons were grouped as having inequitable distribution of the intervention coverage.

The prevalence of malaria parasite infections and moderate-severe anemia (Hb<8 g/dl) was assessed among children under 5 years old across eight national MIS's between 2006 and 2008. To show where morbidity was concentrated, differences in these morbidity outcomes were assessed by urban and rural status and poorest versus wealthiest quintiles using a Pearson's Chi-square test statistics, as described above.

Results 

We identified 27 surveys conducted from 2006 through 2008 with nationally-representative data from malaria-endemic countries in Africa with reports published by July 2009. The country data showed a wide range of intervention coverage (from <10% to >60% population coverage) and the reports systematically presented information on urban and rural settings and on household wealth quintile for most but not all of the interventions. Of note, country coverage levels varied for each intervention and some countries with high coverage for one intervention had relatively low coverage for another intervention: for example, Mali had >50% household ownership of ITNs but <10% coverage with IPTp (Figures 1, 2, 3).

    

Figure 1. Equity in household ownership of ITNs.

Percent household ownership of at least 1 ITN, by household residence and poorest versus wealthiest quintile, from national household surveys 2006–2008.  group of countries are those achieving equity across rural-urban and wealth quintiles; bottom group are those not achieving equity across these categories. *Wealth statistically different (P-value<0.05); **Urban/rural statically different (P-value<0.05); ***Wealth and urban/rural statistically different (P-value<0.05); $Data not available for statistical test.

doi:10.1371/journal.pone.0008409.g001

 

Figure 2. Equity in antimalarial treatment of fever in children.

Percent children with a fever in the past 2 weeks receiving any antimalarial, by household residence and poorest versus wealthiest quintile, from national household surveys 2006–2008.  group of countries are those achieving equity across rural-urban and wealth quintiles; bottom group are those not achieving equity across these categories. *Wealth statistically different (P-value<0.05); **Urban/rural statically different (P-value<0.05); ***Wealth and urban/rural statistically different (P-value<0.05); $Data not available for statistical test.

doi:10.1371/journal.pone.0008409.g002

 

Figure 3. Equity in use of intermittent preventive treatment in pregnancy (IPTp).

Percent women 15–49 who received 2 or more doses of sulfadoxine-pyrimethamine for IPTp during their last pregnancy, by rural versus urban residence and poorest versus wealthiest quintile, from national household surveys 2006–2008.  group of countries are those achieving equity across rural-urban and wealth quintiles; bottom group are those not achieving equity across these categories. *Wealth statistically different (P-value<0.05); **Urban/rural statically different (P-value<0.05); ***Wealth and urban/rural statistically different (P-value<0.05); # Data are for sulfadoxine-pyrimethamine preventive use, but did not specify 2+ doses IPTp.

doi:10.1371/journal.pone.0008409.g003

National estimates of household ownership of at least one ITN varied from a high of over 60% in Zambia to approximately 5% in Cameroon (Figure 1). Thirteen (52%) of the 25 countries achieved equitable coverage (richest-to-poorest average equity index = 0.86, [range 0.20 to 1.11]; urban-to-rural average equity index = 0.80, [range 0.34 to 1.19]); see Figure 1, equitable countries in the upper section. There were substantial inequities in the other 12 countries (richest-to-poorest average equity index = 3.27; [range 1.67 to 6.50]; urban-to-rural average equity index = 1.73 [range 1.10 to 3.00]); see Figure 1, lower section.

National coverage estimates of malaria treatment for febrile children under 5 years of age range from 70% in urban Burkina Faso to less than 10% in urban and rural Zimbabwe (Figure 2). Nearly one-third of the countries (8/27) in this analysis achieved coverage that was equitable or favored poor rural households (richest-to-poorest average equity index = 0.81 and urban-to-rural equity index = 0.84); see Figure 2, upper section. Among the 19 countries with inequitable coverage, the greatest disparity is seen by wealth quintile (richest-to-poorest average equity index = 1.81; urban-to-rural average equity index = 1.40) where in five countries the coverage in the poorest households was less than one-half that in the wealthiest households; see Figure 2, lower section.

Population coverage of women receiving IPTp or an antimalarial drug during pregnancy was generally low and exceeded 20% in only 6 (Zambia, Senegal, Malawi, Tanzania, Ghana, and Gambia) of the 22 countries with data available (Figure 3). Although IPTp is meant to reach all women attending antenatal clinic and in many countries the proportion of pregnant women attending antenatal clinic is high, fewer than one-quarter (5/22) of the countries in our analysis achieved equitable or coverage favoring poor rural women; see Figure 3, upper section. In the remaining 17 countries with inequitable coverage, urban women and those in the wealthiest quintile often had a 2-fold or higher coverage compared to rural and poor women; see Figure 3, lower section.

No male-female differences were observed among children using an ITN the previous night (23 studies with data) or receiving malaria treatment for fever illness (14 studies with data) (Figures 4 and 5). While overall use levels varied substantially among the countries, there were no survey results showing marked differences between male and female children for ITN use, while only three countries showed significant differences for treatment of fever illnesses; two favoring males and one favoring females.

 

Figure 4. Equity among male and female children sleeping under an ITN.

Percent male and female children under-5 years of age sleeping under an ITN the previous night, national surveys between 2006 and 2008. All country male-to-female rates are similar with no statistically significantly differences (P-value>0.05).

doi:10.1371/journal.pone.0008409.g004

 

Figure 5. Equity among male and female children receiving antimalarial treatment.

Percent of male and female children under-5 years of age with fever receiving any antimalarial medicines, national surveys between 2006 and 2008. *Statically different with P-value<0.05.

doi:10.1371/journal.pone.0008409.g005

Recent data were available on the prevalence of malaria parasitemia and/or moderate-severe anemia (Hb<8 gm/dl) from 8 DHS and MIS [Angola (2006), Ethiopia (2007), Kenya (2007), Mozambique (2007), Rwanda (2007/8), Tanzania (2008) and Zambia (2006 and 2008)]. These findings confirm that malaria and anemia disproportionately affect children in rural and poor households (Figures 6 and 7). Of note, Zambia achieved substantial increases in malaria intervention coverage between the 2006 and 2008 survey and most of the reduction in parasitemia and anemia is seen in the rural and the poor populations.

 

Figure 6. Malaria parasite prevalence in children.

Percent parasitemia in children under-5 years of age by urban or rural setting and by richest or poorest wealth quintile, national Malaria Indicator Surveys in African countries. *The Rwanda DHS report did not include parasitemia comparisons by wealth quintile. All urban-rural and richest-poorest differences are statistically significant at P-value<0.001 except for Rwanda urban versus rural (X2 = 1.52, P-value = 0.2168). For Zambia, substantial increases in malaria intervention coverage occurred between the 2006 and 2008 surveys and likely accounts for the observed reduction in prevalence, predominantly in rural and poor populations.

doi:10.1371/journal.pone.0008409.g006

 

Figure 7. Moderate-to-severe anemia rates in children.

Anemia rates (Hb<8gms/dl) in children under-5 years of age by urban or rural setting and by richest or poorest wealth quintile, national Malaria Indicator Surveys in African countries. *While testing was done in the Rwanda DHS, the comparisons were provided in different categories and are not comparable to the other studies. **Statically different with P-value<0.05. For Zambia, substantial increases in malaria intervention coverage occurred between the 2006 and 2008 surveys and likely accounts for the observed reduction in severe anemia, predominantly in rural and poor populations.

doi:10.1371/journal.pone.0008409.g007

Discussion 

This analysis of malaria intervention coverage in sub-Saharan Africa shows that many countries have achieved equitable coverage among poor rural households where the burden of malaria is concentrated. The recent progress in malaria control has been sufficiently rapid that we expect that many countries will have both higher and more widely applied intervention coverage in 2009 than might be recorded from these 2006 – 2008 surveys. The analysis also identifies challenges in equitable distribution of interventions that require continued attention as many countries strive to achieve universal coverage for malaria interventions.

Equitable distribution of interventions is possible; 54% of countries have equitable ITN distribution, 29% have equitable case management coverage and 20% have equitable IPTp coverage. But achieving equity in one area does not assure broad achievement of equity; only Namibia and the Gambia achieved equity for all three intervention strategies, and only the Gambia has equitable moderate or high coverage for the interventions.

So, what predicts or determines equity in intervention coverage? While achieving universal coverage will by definition achieve equity, there is no observable dramatic effect whereby countries with higher coverage (50% to 70%) are more likely to have equity at that stage. In fact, across the range from 5% to 70%, coverage per se does not appear from these data to be a critical determinant of equity. At least two factors likely explain the observed inequity in intervention coverage: the policies and choices around delivery strategy used for certain prevention interventions (e.g., the methods used for delivering ITNs, and possibly for IRS) and the existing delivery systems available for providing treatments and the extent of their reach to rural and poor populations (e.g., facility-based and/or community-based services providing treatment for malaria illness or IPTp).

The method of distribution and cost to the end user are critical considerations in achieving equity in ITN coverage [11]. There is growing evidence that equitable household ITN possession is achievable through free wide-scale community distribution [21], [25]-[27]. Partly as a result of such evidence and because ITNs are increasingly viewed as a public good, just like vaccines in children [28], the policies and choices of delivery strategies for ITNs have evolved over the past few years such that there is increasing acceptance that full household population coverage should be sought and any impediments to coverage should be avoided. While it is beyond the scope of this analysis to assess the predominant delivery strategies country by country for the 13 with equitable and 12 with inequitable coverage, it is reasonable to propose that countries with policies that prioritize high household coverage (e.g. an ITN for every sleeping space or one ITN for every two household members), in combination with free wide-scale distribution, will likely improve overall coverage and equity as has been previously observed [12], [21], [29].

For countries using IRS, the spraying is likely to be targeted to certain geographic areas with certain characteristics – typically to urban and peri-urban areas where housing is close together and wall construction materials are amenable to the application of residual insecticides. This targeting may lead to inequity by design, but within these designated areas, the approach of achieving very high coverage (i.e., >90% in the geographically targeted area) should maximize both coverage and equity for that population.

Only two countries (The Gambia and Uganda) reported both high and equitable coverage of treatment of child malaria; and fewer than 50% of febrile children received prompt antimalarial treatment in 14 of the 27 countries studied. In contrast to the variety of delivery methods available for providing prevention commodities (e.g., for ITNs and IRS), it may be more difficult to rapidly achieve equitable coverage of malaria treatment as the largest factor influencing this is overall access to health care. The predominance of infection, illness and severe illness in rural and poor households means that every modality to reach these populations should be pursued. This is not unique to malaria and has been cited as an overarching feature for child health and survival in general [30]. Policies that improve access to health services, such as promoting community outreach and limiting barriers to attending health facilities, will be needed to assure improved and equitable coverage of malaria treatment.

The findings that few countries have achieved more than 20% coverage with IPTp suggests that there remains much work to be done on the initial steps of in-country policy development and delivery strategy with the reproductive health and malaria programs. Given that in many countries a high proportion of pregnant women attend antenatal clinic, with most attending multiple times during pregnancy, there are substantial opportunities for rapid improvement in coverage; and as long as attention is paid to systematically reaching all those who attend, high coverage and good equity may be relatively easy to achieve.

The analysis shows that ITN use and receipt of malaria treatment are equitable among male and female children. The determinants of such equity likely lie principally within the home and are not determined by national policy or health service systems, except perhaps to the extent that they foster a gender-equity message for communities. Mothers and care givers can all be applauded for doing the right thing in all of these countries. Apparently, the only challenge for young boys and girls is that the coverage levels need to rise.

This descriptive assessment of the equity of malaria intervention coverage across countries relied on available national survey reports and relevant analyses. Our analysis did not include assessment of confounding factors; it is clear that wealth and urban-rural dwelling are highly correlated. We also did not adjust our statistical tests for the effect of clustering, which may have biased our results away from the null hypothesis of there being no statistical differences between equity factors. We were also not able to further explore the individual country data to assess additional and potentially important within-country inequities that may exist. For example, “rural” and “urban” categories may hide issues such as “remote rural” versus “rural with access to services”; and wealth quintiles for urban settings may be quite different from wealth quintiles in rural areas. Such additional country-specific analyses do not easily lead to information that can be considered in a multi-country comparison as presented here, but should be considered by individual country programs to further explore their data and their opportunities to expand their program coverage and equity. The goal of this assessment was to examine the extent to which countries have or have not achieved equitable coverage of malaria interventions, defined here as favoring urban and the wealthiest households. For this purpose, the approach used seems adequate as large inequities in coverage clearly exist in some, but not all places.

Equity cannot await universal coverage; it must be programmed at all stages of malaria control scale up. As malaria in Africa is concentrated among children and pregnant women in poor rural areas, the full benefit of malaria control interventions will not be realized unless high coverage among these populations is achieved. Measuring the equity of intervention coverage will remain important in assessing the impact of intervention scale-up on the malaria burden within countries, until universal coverage has been achieved.

Acknowledgments 

We thank Kent Campbell for reviewing this manuscript and providing insightful comments. We would also like to acknowledge the fact that many individuals and organizations in each country contributed to survey design and implementation, data assembly, analysis, and report writing; we are indebted to all their work that allowed these multi-country comparisons.

Author Contributions 

Conceived and designed the experiments: RWS TE. Analyzed the data: RWS TE. Wrote the paper: RWS TE.

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2) EQUITY RATIOS IN LLIN OWNERSHIP, KENYA

 

 

Free MASS bednet distribution is one way to remove income barriers to acquisition and use of malaria bednets.

 

Here are the results from a recent survey in Kenya:

 

‘The equity ratio for all households receiving campaign bed nets was 1.59 (95% CI: 1.29, 1.89). This means that the poorest households were 59% more likely to receive campaign bed nets than the wealthiest households. The equity ratio for CU5s, women of reproductive age, and pregnant women sleeping under an ITN the previous night were all less than 0.8. This means that despite the campaign, the target populations in the wealthiest quintiles were all 20% or more likely to be sleeping under an ITN.’

 

 

Full text is at http://www.malariajournal.com/content/9/1/183

 

Good reading.

BD

 

Research

Bed net ownership in Kenya: the impact of 3.4 million free bed nets

Allen Hightower1 , Rebecca Kiptui2 , Ayub Manya2 , Adam Wolkon1 , Jodi Leigh Vanden Eng1 , Mary Hamel1,3 , Abdisalan Noor4 , Shahnaz K Sharif5 , Robert Buluma6 , John Vulule3 , Kayla Laserson3,7 , Laurence Slutsker1 and Willis Akhwale2

Division of Parasitic Diseases and Malaria, Centers for Disease Control, Center for Global Health, Mailstop F22, 4770 Buford Highway, Atlanta GA 30341, USA

Division of Malaria Control, Ministry of Public Health and Hygiene, KNH Grounds, P.O. Box 20750, Nairobi, Kenya

Kenya Medical Research Institute, Center for Global Health Research, Off Busia Road, Kisian, Kenya

Malaria Public Health and Epidemiology Group, Centre for Geographic Medicine Research-Coast, Kenya Medical Research Institute/Wellcome Trust Research Programme, P.O. Box 43640, 00100 GPO, Nairobi, Kenya

Ministry of Health, Office of the Director of Public Health and Sanitation, Afya House, Cathedral Road, P.O. Box 30016, Nairobi, Kenya P.O. Box 30016, Nairobi

Kenya National Bureau of Statistics, Herufi House, Lt. Tumbo Lane, P.O. Box 30266-00100 GPO, Nairobi, Kenya

Center for Global Health, Centers for Disease Control, 1600 Clifton Road, Atlanta GA 30333, USA

author email corresponding author email

Malaria Journal 2010, 9:183doi:10.1186/1475-2875-9-183

The electronic version of this article is the complete one and can be found online at: http://www.malariajournal.com/content/9/1/183
 
   
   
   

© 2010 Hightower et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

In July and September 2006, 3.4 million long-lasting insecticide-treated bed nets (LLINs) were distributed free in a campaign targeting children 0-59 months old (CU5s) in the 46 districts with malaria in Kenya. A survey was conducted one month after the distribution to evaluate who received campaign LLINs, who owned insecticide-treated bed nets and other bed nets received through other channels, and how these nets were being used. The feasibility of a distribution strategy aimed at a high-risk target group to meet bed net ownership and usage targets is evaluated.

Methods

A stratified, two-stage cluster survey sampled districts and enumeration areas with probability proportional to size. Handheld computers (PDAs) with attached global positioning systems (GPS) were used to develop the sampling frame, guide interviewers back to chosen households, and collect survey data.

Results

In targeted areas, 67.5% (95% CI: 64.6, 70.3%) of all households with CU5s received campaign LLINs. Including previously owned nets, 74.4% (95% CI: 71.8, 77.0%) of all households with CU5s had an ITN. Over half of CU5s (51.7%, 95% CI: 48.8, 54.7%) slept under an ITN during the previous evening. Nearly forty percent (39.1%) of all households received a campaign net, elevating overall household ownership of ITNs to 50.7% (95% CI: 48.4, 52.9%).

Conclusions

The campaign was successful in reaching the target population, families with CU5s, the risk group most vulnerable to malaria. Targeted distribution strategies will help Kenya approach indicator targets, but will need to be combined with other strategies to achieve desired population coverage levels.

Background

The last, large-scale, group-randomized, controlled trial of insecticide-treated bed nets (ITNs) showed that ITNs were efficacious in reducing all-cause post-neonatal mortality in an area of Western Kenya with intense, perennial malaria transmission [1-3]. That trial and others [4-7] helped to define pregnant women and children 0-59 months old (CU5s) as target groups for ITNs in high transmission settings. The findings also suggested that high overall population coverage with ITNs including both target and non-target groups was critical to achieve community level protective effects [3]. These studies emphasized the beneficial effects of high ITN coverage from both health and economic perspectives.

Key determinants of efficacy in this and other ITN studies were the proportion of households with ITNs (ownership), the proportion of individuals properly deploying ITNs each night (usage), and the proportion of nets properly treated with insecticide (treatment). These indicators have been adapted for programme monitoring and evaluation. Indicators for ITN ownership and usage are an integral part of a number of development goals, including those set forth in the Abuja Declaration [8], Roll Back Malaria Strategic Document (RBM) [9], and the Millennium Development Goals [10]. The 2010 RBM targets are: 80% of CU5s sleeping under an ITN during the previous night, and 80% of pregnant women sleeping under an ITN during the previous night. In the past few years, long-lasting ITNs (LLINs) have become widely available; these are nets that are treated during the manufacturing process and are protective for an estimated three years.

One method to rapidly achieve high coverage is a large-scale integrated campaign, where ITN distribution is linked to other child health interventions, such as immunizations or Vitamin A supplementation [11,12]. One of the largest of these campaigns, involving 3.4 million LLINs, was conducted in Kenya in 2006. The outcomes of this campaign, retention of campaign LLINs, and estimates of the indicators to assess Kenya's progress towards goals for ITN coverage at the household level and high-risk populations are reported here. Additionally, the survey provided a measure of the progress of ongoing and substantial efforts to distribute subsidized, socially marketed bed nets over the past four years in Kenya. The survey collected data using a novel approach that has been tested in other countries as being both statistically valid and rapid [13-16].

Methods

The campaign to distribute LLINs

1.4 million LLINs were distributed from July 8 to 14, 2006, primarily in Nyanza and Western provinces, in association with a measles vaccination campaign. Western and Nyanza provinces were chosen to receive nets first because of a high burden of malaria-related morbidity and mortality. The remaining 2.0 million nets were distributed September 23 to 24, 2006 in malaria-affected districts in Rift Valley, Central, Eastern, and Coast Provinces. The target population to receive the nets was children under five years of age. Batches of LLINs were sent to numerous distribution centers (health facilities, schools, etc.) where caretakers would receive one net for each CU5 that accompanied them. At some centers, the children received other health interventions appropriate for the locale (measles vaccination, deworming medication, vitamin A, and iron tablets).

Survey design

There are 46 Districts in Kenya where malaria transmission occurs. Twenty of these Districts were randomly chosen with probability proportional to size within the following three malaria transmission zones that formed the sampling strata for the survey: areas of endemic malaria - 10 districts from Nyanza, Western, and Coast provinces (2006 estimated population: 11.9 million); epidemic malaria - five districts from the Rift Valley (2006 estimated population: 8.6 million); highland/seasonal malaria - five districts from Eastern and Central Provinces (2006 estimated population: 9.2 million). The region containing Nyanza, Western, and Coast Provinces had higher sampling fractions because they contained all but one of the endemic districts in the country and are where the majority of malaria-related morbidity and mortality occurs.

Within each district, five enumeration areas were selected with probability proportional to size. A sample of 21 households was selected for each enumeration area, giving a target sample of 2,100 households. The sampling frame within each cluster was developed through the use of global positioning system (GPS) linked with hand-held computers (PDAs) to allow rapid preliminary mapping of enumeration areas, thereby allowing selection of a simple random sample of houses [13]. Sufficient numbers of districts and enumeration areas were sampled in the Nyanza and Rift Valley provinces and the other two regions to produce statistically reliable estimates and confidence intervals.

Data collection

The survey was conducted from October 17 to November 1, 2006 (Figure 1). Questions and methodology were similar to the 2003 Kenya Demographic and Health Survey (KDHS) to facilitate comparisons [17]. The survey instrument asked questions about the household, the bed nets owned by the household (if any), whether a CU5 or a woman of reproductive age had slept under each specific net during the previous evening, malaria knowledge and awareness of public media messages related to the campaign, and socio-economic questions concerning characteristics of the household. Surveyors noted whether they had actually observed the nets and if so, if they were hanging. Although pregnant women were not specifically targeted by the campaign, they were included in the survey to measure the effectiveness of the targeted campaign for CU5s in reaching them. Socioeconomic data used to construct a wealth index employing the same definitions used in the 2003 KDHS [17].

Figure 1. Districts in the bed net distributions and clusters in the evaluation survey.

PDAs with GPS were used for data collection. The questionnaire was constructed and programmed into the PDAs with appropriate skip patterns and data checks. After a one-week training period, 11 teams of four persons each collected the data in the field over a two week period. Upon survey completion, PDAs were returned to Nairobi, where data were aggregated into a desktop database.

The survey was conducted at the end of the dry season and the early stage of the short rainy season which is not the peak time of malaria transmission. As a result it was not expected to provide the maximum measure of net usage. The objective of this survey was to assess ownership and retention of bed nets distributed during the campaign and to assess bed net ownership in general.

Definitions

A household was defined as everyone who shared a meal at a common gathering place, using the 2003 Kenya DHS definition [17]. An ITN was defined as any bed net that had been treated with insecticide in the last six months. LLINs were counted as ITNs. At the time of the survey, there were only three types of LLINs available in Kenya: SupaNet ExtraPower (socially marketed by Population Services International), Permanets (available commercially and via the campaign), and Olyset nets (available commercially and via the campaign). Pre-campaign bed net ownership levels were based on ownership of non-campaign bed nets. Changes in ownership of these nets between the campaign and the survey were assumed to be negligible. Post-campaign bed net ownership included all types of bed nets. Permanet and Olyset campaign nets had distinctive labeling and packaging. To aid identification, the PDAs used for survey data collection had pictures of each net, and its packaging and labeling, integrated into the computerized questionnaire. Equity ratio was defined as the ratio of intervention coverage proportions in the poorest quintile to the coverage in the wealthiest quintile.

Statistical methods

Consistent with the sampling design, the SAS survey procedures (SAS v9.1.3, SurveyFreq, SurveyLogistic, and SurveyMeans) were used to produce estimates and standard errors using the sampling weights that accounted for the sampling design and the different sampling fractions for each transmission zone. Estimates are precise (half-width of 95% confidence interval) to 2.5% on a national basis (i.e., for all areas with malaria in Kenya), 2.5-4.0% on a regional basis (the three sampling strata based on provinces grouped by the nature of their malaria endemicity), 5% for each wealth quintile, and 6% for CU5. The survey was not designed for making precise statements on bed net ownership or usage for pregnant women. However, precision for women of reproductive age was 5% on a national basis.

Comparisons of indicators before and after the campaign were done by computing the difference in the indicators and computing 95% confidence intervals that accounted for the survey design. The Rao Scott Chi square statistic was used for p-values. Projected numbers of various types of bed nets (ITNs, campaign nets) were computed by multiplying the number of a particular type of bed net in the survey household by its sampling weight and summing this product over all households.

Ethical considerations

The protocol was approved by the Kenya Medical Research Institute Institutional Review Board and the Centers for Disease Control and Prevention. Informed written consent was obtained from each respondent.

Results

Respondents

From October 17 through November 1, 2006, members of 2,059 households were interviewed out of 2,100 targeted. Of the 100 enumeration areas, 85% were classified as rural and 15% as urban, mirroring the characteristics of the 46 campaign districts. On a weighted basis, households with CU5s represented 51.7% of all households in the survey population. Among sampled households, 78.0% had a woman of reproductive age; of these, 37.1% did not have a CU5 (95% CI: 34.7, 39.6%). An estimated 8.3% of the women in the population reported themselves to be pregnant.

Before vs. after campaign comparisons for key indicators

The survey estimated that 3.63 million LLINs were distributed (95% CI: 3.39, 3.87 million), of which 3.38 million were distributed to CU5s (93.9%) (Table 1). The campaign increased the number of bed nets owned by 50%, from 7.2 to 10.9 million. Households owning only campaign nets were 13.8% of all households, which was over one-third of all households receiving campaign nets. Pre-campaign ITN household ownership could be estimated as 36.9% = 50.7 (post-campaign ITN/LLIN HH ownership) -13.8% (households that only owned campaign nets in the survey), and similarly pre-campaign household ownership of any bed net could be estimated at 53.1% (66.9-13.8%). Prior to the campaign, socially marketed nets represented 68.7% of all nets owned. This represents approximately 5.0 million nets (7.24 million* 0.687). After the campaign, they represented 46.0% of all nets owned. Figure 2 presents the distribution of bed net brand ownership before and after the campaign.

Table 1. Key indicators, before and after the campaign *

Figure 2. Distribution of bed net brands owned before and after the campaign*. * Pre-campaign: Number of bed nets = 2,105, Post-Campaign: Number of bed nets = 3,141.

The campaign increased ITN ownership for HH with CU5s by 28.7% (from 46.7% to 74.4%, p < .0001). It increased ITN ownership for HH with women of reproductive age by 18.6% (from 40.3% to 58.9%).

Prior to the campaign, the percent of all nets in households with CU5s that were ITN increased with the wealth quintile. However, even in the wealthiest quintile, less than a third of the homes owned ITNs. After the campaign, the relationship between ITN ownership and wealth disappeared. The smallest increase in ITN ownership was in the wealthiest quintile, 25.5%,. The other wealth quintiles had increases of nearly 40% or more. The increases in all wealth quintiles were statistically significant (p < .001 for all quintiles, Table 2).

Table 2. Percent of all bed nets in households with children under 5 that were ITNs (including LLINs) by wealth quintile before and after the campaign.*

Equity ratios

The equity ratio for all households receiving campaign bed nets was 1.59 (95% CI: 1.29, 1.89). This means that the poorest households were 59% more likely to receive campaign bed nets than the wealthiest households. The equity ratio for CU5s, women of reproductive age, and pregnant women sleeping under an ITN the previous night were all less than 0.8. This means that despite the campaign, the target populations in the wealthiest quintiles were all 20% or more likely to be sleeping under an ITN. Equity ratios with 95% confidence intervals are presented in Figure 3.

Figure 3. Equity ratios for selected indicators*. *An equity ratio of more than 1 means that the poorest quintile was more likely to receive the intervention, less than 1 means that the wealthiest quintile was more likely to receive the intervention. Sample sizes: Number of households: 2059; Number of Households with CU5s: 1113, Number of Households with Women of Reproductive Age (WORA): 1613; Number of CU5s: 1727, Number or WORAs: 2053, Number of Pregnant Women: 182.

Bed nets

There were 3141 bed nets in the 2059 households in the survey. Over half of households surveyed (n = 1080) owned ITNs. One third of all nets were campaign nets. During the survey, 70% of all nets were seen by the interviewers. Summary data with 95% confidence intervals are presented in Table 3.

Table 3. Survey estimates related to bed nets*

Among all bed nets, 66.2% were either treated in the last six months (ie, were ITNs) or were LLINs. More than half (54.8%) of all nets were LLINs. Among all bed nets, 43.1% were obtained at no cost. Nearly two-thirds (67.1%) of all nets were hanging. About a third (30.6%) of all nets were obtained at health facilities (other than as a part of the campaign), and 24.8% were obtained from dukas (small stores), hawkers, kiosks, or textile shops. Almost ninety percent (88.4%) of nets were classified as being in good condition (no holes, tears). For the most popular brand of socially marketed bed net (a non-LLIN), 30.6% had been treated in the last six months.

Households

About two-thirds (66.9%) of all households had at least one bed net of any kind. Over forty percent (41.9%) of households had more than one bed net. Over half (50.7%) of households owned an ITN, and 39.1% of all households had received a campaign LLIN. ITNs were hanging in 41.9% of all households. In households owning ITNs, 82.6% had at least one ITN hanging. Households that owned only campaign nets were 13.8% of all households, which was over one-third of all households receiving campaign nets. Summary data with 95% confidence intervals are presented in Table 4.

Table 4. Survey estimates related to households (HH)*

Households that had neither a CU5 nor a woman of reproductive age comprised 19.2% of all households. In this group, bed net ownership was 16.2% for any ITN, and 33% for any type of bed net. Urban households were more likely than their rural counterparts to have nets of any type. (ITNs: Odds Ratio: 1.37, 95% CI: 1.06, 1.77; Any Net: Odds Ratio: 2.35, 95% CI: 1.70, 2.35). Among all households that received campaign nets, 94.8% had retained all nets and 97.9% percent had retained at least one campaign net. There was no significant variation in retention by malaria transmission zone status.

Children under five

There were 1,727 CU5s living in 1113 households in the survey. Approximately two-thirds (67.5% ) of households with CU5s, received campaign LLINs. The percent of these households receiving campaign LLINs did not vary significantly by region. Just under ninety percent (87.2%) of households with CU5s had a bed net of any type, with 74.4% owning an ITN. Summary data with 95% confidence intervals for households with CU5s are presented in Table 5.

Table 5. Survey estimates for Households (HH) with Children under 5 (CU5s)*

Just over half (51.7%) of CU5s (95% CI: 48.8, 54.7%) slept under an ITN during the previous night. This proportion did not vary significantly by age or sex. There was significant variation by malaria zone/geographic region: endemic: 50.3%; epidemic: 41.4%, highland/seasonal 67.9% (p < .0001). In households with CU5s owning ITNs, 69.0% of children slept under them the previous night, and in households with CU5s owning ITNs that were hanging, 83.5% of children slept under them the previous night. Having received a campaign bed net greatly increased the likelihood that a child under 5 slept under an ITN the previous night (67.7 vs. 28.8%, p < .0001). Overall, 56.5% of the ITNs used by CU5s were campaign nets. Summary data with 95% confidence intervals for CU5s are presented in Table 6.

Table 6. Survey estimates for Children under 5 (CU5s)*

Women of reproductive age

There were 2,053 women of reproductive age (15-49 years, WORAs) living in 1,613 households. There were 182 pregnant women living in 180 households in the survey. Among pregnant women, 58.4% slept under a net of any type during the previous night (95% CI: 50.9, 65.9%); however, only 36.3% of pregnant women slept under an ITN. (95% CI: 29.0, 43.7%). Among all WORAs, 33.0% slept under an ITN during the previous night (95% CI: 30.6, 35.4%). In households that owned one or more ITNs, 55.9% of women of reproductive age slept under an ITN during the previous night. For pregnant women, this number was 56.7%. Summary data for WORAs with 95% confidence intervals are presented in Table 7.

Table 7. Survey estimates for Women of Reproductive Age (WORAs)*

Discussion

The distribution of 3.4 million LLINs dramatically increased ownership, and reached two-thirds of the target households with the population most vulnerable to malaria-related morbidity and mortality. At the time of the campaign, this distribution represented the largest distribution of bed nets ever. While the distribution of bed nets in Ethiopia, undertaken later, was considerably larger (approximately 20.5 million bed nets), [18], the Kenya campaign remains the second largest.

Since 2002, Kenya had an effort to socially market subsidized bed nets [19]. This multi-year programme distributed 5.0 million bed nets vs. the 3.4 million bed nets distributed as part of the campaign. Prior to the campaign, 68.7% of all bed nets were socially marketed. Afterwards, socially marketed bed nets still represented 46.0% of all bed nets owned. The vast majority of these bed nets were sold prior to the development of LLINs. A possible concern has been that the users of socially marketed bed nets might be different than the user of bed nets that are distributed free to a targeted group. Noor et al [20] notes that there is greater coverage of infants in areas where nets were received by free distributions than by social marketing.

When interpreting the impact of the campaign on bed net ownership for all households in the survey, one must remember that only 51.7% had a CU5 and were, therefore, eligible to receive a campaign LLITN. Additionally, over one third of households with women of reproductive age did not have a CU5 in the household. Households with these women, who might potentially become pregnant, were not eligible to receive campaign nets, thus not addressing the cohort of newborns that arrive following the conclusion of a campaign. A number of strategies are thus needed to achieve bed net usage and ownership targets. In addition to campaigns, other important approaches include distribution of ITNs via antenatal clinics as an efficient way to reach pregnant women. In the 2003 Kenya DHS, 88% of pregnant women received antenatal care. Therefore, increasing ITN ownership/usage in this population towards targets via further targeted distributions is achievable.

Within the targeted population (CU5s), the campaign was highly successful. The survey found that 74.4% of households with CU5s now own an ITN, and that 87.2% own a bed net of any type. This would also represent ITN ownership if all of these are treated (only approximately 30% were treated within the past six months at the time of the survey). However, due to logistics and costs of re-dipping, future net distributions will concentrate on simply replacing nets that require retreatment with LLINs. A mass distribution every three years supplemented by those available through health facilities would seem to be the simplest way to keep large numbers of vulnerable populations well supplied with viable LLINs

The survey results demonstrated that retention of campaign bed nets was very high (95% of all households retained all campaign nets). Therefore, few campaign bed nets were being resold or given away. This finding has been replicated elsewhere and has remained the case in later follow-up surveys [16].

Despite the timing of the survey, usage figures were much higher than previous surveys (51.7% of CU5s slept under an ITN vs. 4.6% CU5s under any net the previous night in 2003) [17]. In homes with ITNs, the usage rates were even higher (69.0%) and higher still in homes where ITNs were hanging (83.5%) Finally, in perhaps the best measure of the impact of the campaign, CU5s in homes receiving campaign bed nets were approximately 40% more likely to sleep under an ITN during the previous night (67.7 vs. 28.8%, p <.0001). Nonetheless, the survey found that a substantial number of bed nets were not being hung or used. It is notable that households in the poorest wealth quintile were 59% more likely to receive campaign bed nets, but that target populations in the wealthiest quintile were still 20% or more likely than those in the poorest quintile to actually have slept under an ITN during the previous evening (Figure 3). Behavioural change and education programmes could help close the gap between ownership and usage. These efforts will be a vital part of any strategy to meet bed net ownership and usage targets [20,21].

Conclusion

The campaign successfully increased ITN ownership and usage in targeted vulnerable populations. The survey identified the need for educational and behavioral change campaigns to promote proper usage by vulnerable populations. Finally, the survey quantified the populations of interest not covered by the targeted distribution and for some of these populations, and helped delineate obvious next steps for increasing LLINs ownership.

Future efforts should target getting bed nets to the remaining populations that still do not have them, address eventual replacement of regular ITNs with LLINs, and encourage proper use of the bed nets.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

AH drafted the protocol, helped analyse the data, and wrote the manuscript. RK assisted with the protocol and provided scientific direction for the bed net campaign and the survey. AM provided logistical support for the bed net campaign, and helped with protocol development. AW provided data collection and analysis support, JE provided data collection and analysis support, MH provided scientific assistance on the protocol and the manuscript. AN provided assistance in the mapping and sampling process as well as the manuscript. SS directed the survey and provided input for both the protocol and manuscript. RB provided sampling expertise and data collection assistance. JV provided scientific advice and helped write the protocol and manuscript. KL provided assistance in the protocol and manuscript writing. LS helped write the manuscript and provided assistance for the survey. WA helped write the protocol and provided logistical support for both the bed net campaign and survey.

All authors read and approved the final manuscript.

Acknowledgements

The authors are grateful to the Ministry of Health survey team for their invaluable contribution collection the data for the field survey. We thank the Ministry of Health, and the Division of Malaria Control professional staff for providing support and supervision for the survey. This paper was published with permission from the Director, KEMRI.

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21.  Noor AM, Amin AA, Akwhale WS, Snow RW: Increasing access and decreasing inequity to insecticide-treated net use among rural Kenyan children.

PLoS Medicine 2007 , 4:e255. PubMed Abstract | Publisher Full Text | PubMed Central Full Text

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 3) Ghana and Zambia: Achieving Equity in the Distribution of Insecticide-Treated

Bednets through Links with Measles Vaccination Campaigns

 

http://siteresources.worldbank.org/INTPAH/Resources/Reaching-the-Poor/Ch4.pdf

 

From the discussion:

 

These findings suggest that integration of ITN delivery into measles vaccination

campaigns achieves unprecedented levels of ITN ownership and equity at very low cost. In the study populations, the poorest families’ ITN ownership

rates were comparable to or exceeded those among the least poor. The increase in the equity ratio of ITN ownership in the poorest households compared

with the least poor was substantial, rising from 0.29 to 1.01 in Ghana and from 0.32 to 0.88 in Zambia. Expressed as a difference rather than a rate,

coverage among the poorest households in Ghana increased by 89.6 percentage points compared with 82.7 percentage points for the least poor. In Zambia

the increase was 67.9 percentage points for the poorest and 57.6 percentage points for the least poor. This approach to ITN distribution resulted in a larger coverage increase among the poorest in both relative and absolute terms while ensuring high coverage levels for all wealth groups.



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