Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations
Abstract 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...
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ftdoajarticles:oai:doaj.org/article:ca6fc29e8f89497990b8f141c7aa2b97 2023-05-15T15:12:34+02:00 Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations Nick Scott S. Azfar Hussain Rowan Martin-Hughes Freya J. I. Fowkes Cliff C. Kerr Ruth Pearson David J. Kedziora Madhura Killedar Robyn M. Stuart David P. Wilson 2017-09-01T00:00:00Z https://doi.org/10.1186/s12936-017-2019-1 https://doaj.org/article/ca6fc29e8f89497990b8f141c7aa2b97 EN eng BMC http://link.springer.com/article/10.1186/s12936-017-2019-1 https://doaj.org/toc/1475-2875 doi:10.1186/s12936-017-2019-1 1475-2875 https://doaj.org/article/ca6fc29e8f89497990b8f141c7aa2b97 Malaria Journal, Vol 16, Iss 1, Pp 1-14 (2017) Allocative efficiency Budgeting Malaria Mathematical model Nigeria Optimization Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2017 ftdoajarticles https://doi.org/10.1186/s12936-017-2019-1 2022-12-31T11:21:00Z Abstract 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. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Malaria Journal 16 1 |
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Directory of Open Access Journals: DOAJ Articles |
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English |
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Allocative efficiency Budgeting Malaria Mathematical model Nigeria Optimization Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
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Allocative efficiency Budgeting Malaria Mathematical model Nigeria Optimization Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 Nick Scott S. Azfar Hussain Rowan Martin-Hughes Freya J. I. Fowkes Cliff C. Kerr Ruth Pearson David J. Kedziora Madhura Killedar Robyn M. Stuart David P. Wilson Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations |
topic_facet |
Allocative efficiency Budgeting Malaria Mathematical model Nigeria Optimization Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
description |
Abstract 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. |
format |
Article in Journal/Newspaper |
author |
Nick Scott S. Azfar Hussain Rowan Martin-Hughes Freya J. I. Fowkes Cliff C. Kerr Ruth Pearson David J. Kedziora Madhura Killedar Robyn M. Stuart David P. Wilson |
author_facet |
Nick Scott S. Azfar Hussain Rowan Martin-Hughes Freya J. I. Fowkes Cliff C. Kerr Ruth Pearson David J. Kedziora Madhura Killedar Robyn M. Stuart David P. Wilson |
author_sort |
Nick Scott |
title |
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_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_sort |
maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations |
publisher |
BMC |
publishDate |
2017 |
url |
https://doi.org/10.1186/s12936-017-2019-1 https://doaj.org/article/ca6fc29e8f89497990b8f141c7aa2b97 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Malaria Journal, Vol 16, Iss 1, Pp 1-14 (2017) |
op_relation |
http://link.springer.com/article/10.1186/s12936-017-2019-1 https://doaj.org/toc/1475-2875 doi:10.1186/s12936-017-2019-1 1475-2875 https://doaj.org/article/ca6fc29e8f89497990b8f141c7aa2b97 |
op_doi |
https://doi.org/10.1186/s12936-017-2019-1 |
container_title |
Malaria Journal |
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16 |
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1 |
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1766343237579046912 |