Evidence map›Paper›PMID 41068838›Full record

ArticleBMC biology2025

Requirements for designing cluster randomised control trials to detect suppression of malaria vector population densities.

Penelope A Hancock, Tin-Yu J Hui, Patric S Epopa, Azize Milogo, Andrew R McKemey, Franck A Yao, Abdoulaye Diabaté, Austin Burt

Abstract read
In one paragraph

Article in BMC biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Penelope A HancockDepartment of Infectious Disease Epidemiology, Imperial College London, London, UK. p.hancock@imperial.ac.uk.
Tin-Yu J HuiDepartment of Life Sciences, Imperial College London, London, UK.
Patric S EpopaInstitut de Recherche en Sciences de La Santé/Centre Muraz, Bobo-Dioulasso, Burkina Faso.
Azize MilogoInstitut de Recherche en Sciences de La Santé/Centre Muraz, Bobo-Dioulasso, Burkina Faso.
Andrew R McKemeyDepartment of Life Sciences, Imperial College London, London, UK.
Franck A YaoInstitut de Recherche en Sciences de La Santé/Centre Muraz, Bobo-Dioulasso, Burkina Faso.
Abdoulaye DiabatéInstitut de Recherche en Sciences de La Santé/Centre Muraz, Bobo-Dioulasso, Burkina Faso.
Austin BurtDepartment of Life Sciences, Imperial College London, London, UK.

Funding

Bill and Melinda Gates Foundation 224253/Z/21/Z
6 · The paper itself

Abstract

backgroundNovel interventions for mosquito-borne disease control which release modified mosquitoes that are sterilised or genetically modified to cause offspring inviability are progressing towards field applications. Cluster randomised control trials (CRCTs) could provide robust assessment of intervention efficacy in suppressing mosquito populations in field environments, but guidance on designing CRCTs to detect mosquito suppression impacts is limited.

resultsWe developed statistical models to simulate CRCTs, informed by a 5-year time series measuring densities of malaria vector species from the Anopheles gambiae complex in four villages in western Burkina Faso. We estimated requirements for parallel and step wedge designs, varying the targeted vector species, the suppression effect and the monitoring regime. For a suppression effect of 50%, 21-22 clusters were required to detect suppression with 90% power when all An. gambiae complex species were targeted, while 24-26 clusters were required when only An. coluzzii was targeted and 60-66 clusters were required when only An. gambiae was targeted. For stronger suppression effects, required trial sizes depended less on target species, with 9-10 clusters being sufficient to detect a 90% suppression effect. We investigated how reducing sampling effort, by sampling fewer houses and restricting sampling to rainy season months, affected statistical power.

conclusionsOur results provide empirically based guidance for designing CRCTs to evaluate interventions aiming to suppress malaria vector populations.

Indexed as

AnophelesMalariaMosquito ControlMosquito VectorsRandomized Controlled Trials as TopicAnimalsBurkina FasoPopulation DensityCluster randomised control trialsGene driveGenetically modified organismGeostatistical modelMalariaMosquito-borne diseaseSterile insect techniqueVector control

Identifiers

PMID41068838
PMCPMC12512543

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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.