Investigating the upsurge of malaria prevalence in Zambia between 2010 and 2015: a decomposition of determinants

Abstract Background Malaria is among the top causes of mortality and morbidity in Zambia. Efforts to control, prevent, and eliminate it have been intensified in the past two decades which has contributed to reductions in malaria prevalence and under-five mortality. However, there was a 21% upsurge i...

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Main Authors: Mukumbuta Nawa, Peter Hangoma, Andrew P. Morse, Charles Michelo
Format: Article
Language:English
Published: BMC 2019-03-01
Series:Malaria Journal
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12936-019-2698-x
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author Mukumbuta Nawa
Peter Hangoma
Andrew P. Morse
Charles Michelo
author_facet Mukumbuta Nawa
Peter Hangoma
Andrew P. Morse
Charles Michelo
author_sort Mukumbuta Nawa
collection DOAJ
description Abstract Background Malaria is among the top causes of mortality and morbidity in Zambia. Efforts to control, prevent, and eliminate it have been intensified in the past two decades which has contributed to reductions in malaria prevalence and under-five mortality. However, there was a 21% upsurge in malaria prevalence between 2010 and 2015. Zambia is one of the only 13 countries to record an increase in malaria among 91 countries monitored by the World Health Organization in 2015. This study investigated the upsurge by decomposition of drivers of malaria. Methods The study used secondary data from three waves of nationally representative cross-sectional surveys on key malaria indicators conducted in 2010, 2012 and 2015. Using multivariable logistic regression, determinants of malaria prevalence were identified and then marginal effects of each determinant were derived. The marginal effects were then combined with changes in coverage rates of determinants between 2010 and 2015 to obtain the magnitude of how much each variable contributed to the change in the malaria prevalence. Results The odds ratio of malaria for those who slept under an insecticide-treated net (ITN) was 0.90 (95% CI 0.77–0.97), indoor residual spraying (IRS) was 0.66 (95% CI 0.49–0.89), urban residence was 0.23 (95% CI 0.15–0.37), standard house was 0.40 (95% CI 0.35–0.71) and age group 12–59 Months against those below 12 months was 4.04 (95% CI 2.80–5.81). Decomposition of prevalence changes by determinants showed that IRS reduced malaria prevalence by − 0.3% and ITNs by − 0.2% however, these reductions were overridden by increases in prevalence due to increases in the proportion of more at-risk children aged 12–59 months by + 2.3% and rural residents by + 2.2%. Conclusion The increases in interventions, such as ITNs and IRS, were shown to have contributed to malaria reduction in 2015; however, changes in demographics such as increases in the proportion of more at risk groups among under-five children and rural residents may have overridden the impact of these interventions and resulted in an overall increase. The upsurge in malaria in 2015 compared to 2010 may not have been due to weaknesses in programme interventions but due to increases in more at-risk children and rural residents compared to 2010. The apparent increase in rural residents in the sample population may not have been a true reflection of the population structure but due to oversampling in rural areas which was not fully adjusted for. The increase in malaria prevalence may therefore have been overestimated.
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spelling doaj.art-6584cdd4f6ae484aa3f4aaaf56e118f92022-12-22T00:18:23ZengBMCMalaria Journal1475-28752019-03-0118111010.1186/s12936-019-2698-xInvestigating the upsurge of malaria prevalence in Zambia between 2010 and 2015: a decomposition of determinantsMukumbuta Nawa0Peter Hangoma1Andrew P. Morse2Charles Michelo3School of Public Health, University of ZambiaSchool of Public Health, University of ZambiaDepartment of Geography and Planning, University of LiverpoolSchool of Public Health, University of ZambiaAbstract Background Malaria is among the top causes of mortality and morbidity in Zambia. Efforts to control, prevent, and eliminate it have been intensified in the past two decades which has contributed to reductions in malaria prevalence and under-five mortality. However, there was a 21% upsurge in malaria prevalence between 2010 and 2015. Zambia is one of the only 13 countries to record an increase in malaria among 91 countries monitored by the World Health Organization in 2015. This study investigated the upsurge by decomposition of drivers of malaria. Methods The study used secondary data from three waves of nationally representative cross-sectional surveys on key malaria indicators conducted in 2010, 2012 and 2015. Using multivariable logistic regression, determinants of malaria prevalence were identified and then marginal effects of each determinant were derived. The marginal effects were then combined with changes in coverage rates of determinants between 2010 and 2015 to obtain the magnitude of how much each variable contributed to the change in the malaria prevalence. Results The odds ratio of malaria for those who slept under an insecticide-treated net (ITN) was 0.90 (95% CI 0.77–0.97), indoor residual spraying (IRS) was 0.66 (95% CI 0.49–0.89), urban residence was 0.23 (95% CI 0.15–0.37), standard house was 0.40 (95% CI 0.35–0.71) and age group 12–59 Months against those below 12 months was 4.04 (95% CI 2.80–5.81). Decomposition of prevalence changes by determinants showed that IRS reduced malaria prevalence by − 0.3% and ITNs by − 0.2% however, these reductions were overridden by increases in prevalence due to increases in the proportion of more at-risk children aged 12–59 months by + 2.3% and rural residents by + 2.2%. Conclusion The increases in interventions, such as ITNs and IRS, were shown to have contributed to malaria reduction in 2015; however, changes in demographics such as increases in the proportion of more at risk groups among under-five children and rural residents may have overridden the impact of these interventions and resulted in an overall increase. The upsurge in malaria in 2015 compared to 2010 may not have been due to weaknesses in programme interventions but due to increases in more at-risk children and rural residents compared to 2010. The apparent increase in rural residents in the sample population may not have been a true reflection of the population structure but due to oversampling in rural areas which was not fully adjusted for. The increase in malaria prevalence may therefore have been overestimated.http://link.springer.com/article/10.1186/s12936-019-2698-xMalaria prevalenceUpsurgeInsecticide treated netsIndoor residual sprayingStandard housing
spellingShingle Mukumbuta Nawa
Peter Hangoma
Andrew P. Morse
Charles Michelo
Investigating the upsurge of malaria prevalence in Zambia between 2010 and 2015: a decomposition of determinants
Malaria Journal
Malaria prevalence
Upsurge
Insecticide treated nets
Indoor residual spraying
Standard housing
title Investigating the upsurge of malaria prevalence in Zambia between 2010 and 2015: a decomposition of determinants
title_full Investigating the upsurge of malaria prevalence in Zambia between 2010 and 2015: a decomposition of determinants
title_fullStr Investigating the upsurge of malaria prevalence in Zambia between 2010 and 2015: a decomposition of determinants
title_full_unstemmed Investigating the upsurge of malaria prevalence in Zambia between 2010 and 2015: a decomposition of determinants
title_short Investigating the upsurge of malaria prevalence in Zambia between 2010 and 2015: a decomposition of determinants
title_sort investigating the upsurge of malaria prevalence in zambia between 2010 and 2015 a decomposition of determinants
topic Malaria prevalence
Upsurge
Insecticide treated nets
Indoor residual spraying
Standard housing
url http://link.springer.com/article/10.1186/s12936-019-2698-x
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