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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Published in:Malaria Journal
Main Authors: 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
Format: Article in Journal/Newspaper
Language:English
Published: BMC 2017
Subjects:
Online Access:https://doi.org/10.1186/s12936-017-2019-1
https://doaj.org/article/ca6fc29e8f89497990b8f141c7aa2b97
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spelling 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
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Allocative efficiency
Budgeting
Malaria
Mathematical model
Nigeria
Optimization
Arctic medicine. Tropical medicine
RC955-962
Infectious and parasitic diseases
RC109-216
spellingShingle 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
container_volume 16
container_issue 1
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