Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations.
Scott, N
Hussain, SA
Martin-Hughes, R
Fowkes, FJI
Kerr, CC
Pearson, R
Kedziora, DJ
Killedar, M
Stuart, RM
Wilson, DP
- Publisher:
- BioMed Central
- Publication Type:
- Journal Article
- Citation:
- Malaria Journal, 2017, 16, (1), pp. 1-14
- Issue Date:
- 2017-09-12
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Full metadata record
Field | Value | Language |
---|---|---|
dc.contributor.author | Scott, N | |
dc.contributor.author | Hussain, SA | |
dc.contributor.author | Martin-Hughes, R | |
dc.contributor.author | Fowkes, FJI | |
dc.contributor.author | Kerr, CC | |
dc.contributor.author | Pearson, R | |
dc.contributor.author | Kedziora, DJ | |
dc.contributor.author | Killedar, M | |
dc.contributor.author | Stuart, RM | |
dc.contributor.author | Wilson, DP | |
dc.date.accessioned | 2022-09-01T03:06:32Z | |
dc.date.available | 2017-09-06 | |
dc.date.available | 2022-09-01T03:06:32Z | |
dc.date.issued | 2017-09-12 | |
dc.identifier.citation | Malaria Journal, 2017, 16, (1), pp. 1-14 | |
dc.identifier.issn | 1475-2875 | |
dc.identifier.issn | 1475-2875 | |
dc.identifier.uri | http://hdl.handle.net/10453/161166 | |
dc.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. | |
dc.format | Electronic | |
dc.language | eng | |
dc.publisher | BioMed Central | |
dc.relation.ispartof | Malaria Journal | |
dc.relation.isbasedon | 10.1186/s12936-017-2019-1 | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.subject | 0605 Microbiology, 1108 Medical Microbiology, 1117 Public Health and Health Services | |
dc.subject.classification | Tropical Medicine | |
dc.subject.mesh | Chemoprevention | |
dc.subject.mesh | Communicable Disease Control | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Incidence | |
dc.subject.mesh | Malaria | |
dc.subject.mesh | Models, Economic | |
dc.subject.mesh | Mosquito Control | |
dc.subject.mesh | Nigeria | |
dc.subject.mesh | Resource Allocation | |
dc.subject.mesh | Chemoprevention | |
dc.subject.mesh | Communicable Disease Control | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Incidence | |
dc.subject.mesh | Malaria | |
dc.subject.mesh | Models, Economic | |
dc.subject.mesh | Mosquito Control | |
dc.subject.mesh | Nigeria | |
dc.subject.mesh | Resource Allocation | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Malaria | |
dc.subject.mesh | Chemoprevention | |
dc.subject.mesh | Incidence | |
dc.subject.mesh | Models, Economic | |
dc.subject.mesh | Communicable Disease Control | |
dc.subject.mesh | Mosquito Control | |
dc.subject.mesh | Resource Allocation | |
dc.subject.mesh | Nigeria | |
dc.title | Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations. | |
dc.type | Journal Article | |
utslib.citation.volume | 16 | |
utslib.location.activity | England | |
utslib.for | 0605 Microbiology | |
utslib.for | 1108 Medical Microbiology | |
utslib.for | 1117 Public Health and Health Services | |
pubs.organisational-group | /University of Technology Sydney | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Engineering and Information Technology | |
pubs.organisational-group | /University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre | |
utslib.copyright.status | open_access | * |
pubs.consider-herdc | false | |
dc.date.updated | 2022-09-01T03:06:26Z | |
pubs.issue | 1 | |
pubs.publication-status | Published | |
pubs.volume | 16 | |
utslib.citation.issue | 1 |
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.
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