Evidence map›Paper›PMID 28899373›Full record

ArticleMalaria journal2017

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

Open access · goldAbstract read
In one paragraph

Article in Malaria journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 pooled it
3.5field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 49 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 2 countries.

Nick ScottBurnet Institute, 85 Commercial Rd, Melbourne, VIC, 3004, Australia. Nick.Scott@burnet.edu.au.
S Azfar HussainBurnet Institute, 85 Commercial Rd, Melbourne, VIC, 3004, Australia.
Rowan Martin-HughesOptima Consortium for Decision Science, Melbourne, Australia.
Freya J I FowkesBurnet Institute, 85 Commercial Rd, Melbourne, VIC, 3004, Australia.
Cliff C KerrOptima Consortium for Decision Science, Melbourne, Australia.
Ruth PearsonBurnet Institute, 85 Commercial Rd, Melbourne, VIC, 3004, Australia.
David J KedzioraBurnet Institute, 85 Commercial Rd, Melbourne, VIC, 3004, Australia.
Madhura KilledarBurnet Institute, 85 Commercial Rd, Melbourne, VIC, 3004, Australia.
Robyn M StuartOptima Consortium for Decision Science, Melbourne, Australia.
David P WilsonBurnet Institute, 85 Commercial Rd, Melbourne, VIC, 3004, Australia.
Burnet Institute · AUMonash University · AUUniversity of Copenhagen · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

methodsA 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.

resultsAllocative 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.

conclusionsSubstantial reductions in malaria morbidity and mortality can be made by optimal targeting of investments to the right malaria interventions in the right areas.

Indexed as

Resource AllocationChemopreventionCommunicable Disease ControlHumansIncidenceMalariaModels, EconomicMosquito ControlNigeriaAllocative efficiencyBudgetingMalariaMathematical modelNigeriaOptimization

Identifiers

PMID28899373
PMCPMC5596957
OpenAlexW2755623470

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.