Détails Publication
Assessing the variability in experimental hut trials evaluating insecticide-treated nets against malaria vectors,
Discipline: Entomologie
Auteur(s): Challenger, J. D., Nash, R. K., Ngufor, C., Sanou, A., Toe, K. H., Moore, S., Tungu, P. K., Rowland, M., Foster, G. M., N'guessan, R., Sherrard-Smith, E. & Churcher, T. S.
Auteur(s) tagués: TOE Kobié Hyacinthe
Renseignée par : TOE Kobié Hyacinthe
Résumé

Experimental hut trials (EHTs) are used to evaluate indoor vector control interventions against malaria vectors in
a controlled setting. The level of variability present in the assay will influence whether a given study is well
powered to answer the research question being considered. We utilised disaggregated data from 15 previous EHTs
to gain insight into the behaviour typically observed. Using simulations from generalised linear mixed models to
obtain power estimates for EHTs, we show how factors such as the number of mosquitoes entering the huts each
night and the magnitude of included random effects can influence study power. A wide variation in behaviour is
observed in both the mean number of mosquitoes collected per hut per night (ranging from 1.6 to 32.5) and
overdispersion in mosquito mortality. This variability in mortality is substantially greater than would be expected
by chance and should be included in all statistical analyses to prevent false precision of results. We utilise both
superiority and non-inferiority trials to illustrate our methodology, using mosquito mortality as the outcome of
interest. The framework allows the measurement error of the assay to be reliably assessed and enables the
identification of outlier results which could warrant further investigation. EHTs are increasingly playing an
important role in the evaluation and regulation of indoor vector control interventions so it is important to ensure
that these studies are adequately powered.

Mots-clés

Experimental hut trials, Insecticide-treated nets, Long-lasting insecticidal nets, Vector control, Anopheles, Power analysis

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