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Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations
BACKGROUND: The high burden of malaria and limited funding means there is a necessity to maximize the allocative efficiency of malaria control programmes. Quantitative tools are urgently needed to guide budget allocation decisions. METHODS: A geospatial epidemic model was coupled with costing data a...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5596957/ https://www.ncbi.nlm.nih.gov/pubmed/28899373 http://dx.doi.org/10.1186/s12936-017-2019-1 |
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author | Scott, Nick Hussain, S. Azfar Martin-Hughes, Rowan Fowkes, Freya J. I. Kerr, Cliff C. Pearson, Ruth Kedziora, David J. Killedar, Madhura Stuart, Robyn M. Wilson, David P. |
author_facet | Scott, Nick Hussain, S. Azfar Martin-Hughes, Rowan Fowkes, Freya J. I. Kerr, Cliff C. Pearson, Ruth Kedziora, David J. Killedar, Madhura Stuart, Robyn M. Wilson, David P. |
author_sort | Scott, Nick |
collection | PubMed |
description | BACKGROUND: The high burden of malaria and limited funding means there is a necessity to maximize the allocative efficiency of malaria control programmes. Quantitative tools are urgently needed to guide budget allocation decisions. METHODS: A geospatial epidemic model was coupled with costing data and an optimization algorithm to estimate the optimal allocation of budgeted and projected funds across all malaria intervention approaches. Interventions included long-lasting insecticide-treated nets (LLINs), indoor residual spraying (IRS), intermittent presumptive treatment during pregnancy (IPTp), seasonal mass chemoprevention in children (SMC), larval source management (LSM), mass drug administration (MDA), and behavioural change communication (BCC). The model was applied to six geopolitical regions of Nigeria in isolation and also the nation as a whole to minimize incidence and malaria-attributable mortality. RESULTS: Allocative efficiency gains could avert approximately 84,000 deaths or 15.7 million cases of malaria in Nigeria over 5 years. With an additional US$300 million available, approximately 134,000 deaths or 37.3 million cases of malaria could be prevented over 5 years. Priority funding should go to LLINs, IPTp and BCC programmes, and SMC should be expanded in seasonal areas. To minimize mortality, treatment expansion is critical and prioritized over some LLIN funding, while to minimize incidence, LLIN funding remained a priority. For areas with lower rainfall, LSM is prioritized over IRS but MDA is not recommended unless all other programmes are established. CONCLUSIONS: Substantial reductions in malaria morbidity and mortality can be made by optimal targeting of investments to the right malaria interventions in the right areas. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12936-017-2019-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5596957 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-55969572017-09-15 Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations Scott, Nick Hussain, S. Azfar Martin-Hughes, Rowan Fowkes, Freya J. I. Kerr, Cliff C. Pearson, Ruth Kedziora, David J. Killedar, Madhura Stuart, Robyn M. Wilson, David P. Malar J Research BACKGROUND: The high burden of malaria and limited funding means there is a necessity to maximize the allocative efficiency of malaria control programmes. Quantitative tools are urgently needed to guide budget allocation decisions. METHODS: A geospatial epidemic model was coupled with costing data and an optimization algorithm to estimate the optimal allocation of budgeted and projected funds across all malaria intervention approaches. Interventions included long-lasting insecticide-treated nets (LLINs), indoor residual spraying (IRS), intermittent presumptive treatment during pregnancy (IPTp), seasonal mass chemoprevention in children (SMC), larval source management (LSM), mass drug administration (MDA), and behavioural change communication (BCC). The model was applied to six geopolitical regions of Nigeria in isolation and also the nation as a whole to minimize incidence and malaria-attributable mortality. RESULTS: Allocative efficiency gains could avert approximately 84,000 deaths or 15.7 million cases of malaria in Nigeria over 5 years. With an additional US$300 million available, approximately 134,000 deaths or 37.3 million cases of malaria could be prevented over 5 years. Priority funding should go to LLINs, IPTp and BCC programmes, and SMC should be expanded in seasonal areas. To minimize mortality, treatment expansion is critical and prioritized over some LLIN funding, while to minimize incidence, LLIN funding remained a priority. For areas with lower rainfall, LSM is prioritized over IRS but MDA is not recommended unless all other programmes are established. CONCLUSIONS: Substantial reductions in malaria morbidity and mortality can be made by optimal targeting of investments to the right malaria interventions in the right areas. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12936-017-2019-1) contains supplementary material, which is available to authorized users. BioMed Central 2017-09-12 /pmc/articles/PMC5596957/ /pubmed/28899373 http://dx.doi.org/10.1186/s12936-017-2019-1 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Scott, Nick Hussain, S. Azfar Martin-Hughes, Rowan Fowkes, Freya J. I. Kerr, Cliff C. Pearson, Ruth Kedziora, David J. Killedar, Madhura Stuart, Robyn M. Wilson, David P. Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations |
title | Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations |
title_full | Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations |
title_fullStr | Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations |
title_full_unstemmed | Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations |
title_short | Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations |
title_sort | maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5596957/ https://www.ncbi.nlm.nih.gov/pubmed/28899373 http://dx.doi.org/10.1186/s12936-017-2019-1 |
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