Requirements for designing cluster randomised control trials to detect suppression of malaria vector population densities
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Background
Novel 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.
Results
We 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.
Conclusions
Our results provide empirically based guidance for designing CRCTs to evaluate interventions aiming to suppress malaria vector populations.
Novel 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.
Results
We 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.
Conclusions
Our results provide empirically based guidance for designing CRCTs to evaluate interventions aiming to suppress malaria vector populations.
Date Issued
2025-10-09
Date Acceptance
2025-09-10
Citation
BMC Biology, 2025, 23
ISSN
1741-7007
Publisher
BMC
Journal / Book Title
BMC Biology
Volume
23
Copyright Statement
© The Auther(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Identifier
10.1186/s12915-025-02414-5
Subjects
Cluster randomised control trials
Gene drive
Geostatistical model
Malaria
Vector control
Sterile insect technique
Genetically modified organism
Mosquito-borne disease
Publication Status
Published
Article Number
303