Mapping partner drug resistance to guide antimalarial combination therapy policies in sub-Saharan Africa

Hanna Y. Ehrlich (), Amy K. Bei, Daniel M. Weinberger, Joshua L. Warren and Sunil Parikh
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Hanna Y. Ehrlich: Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, CT 06510
Amy K. Bei: Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, CT 06510
Daniel M. Weinberger: Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, CT 06510; Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, CT 06510
Joshua L. Warren: Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, CT 06510; Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, CT 06510
Sunil Parikh: Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, CT 06510

Proceedings of the National Academy of Sciences, 2021, vol. 118, issue 29, e2100685118

Abstract: Resistance to artemisinin-based combination therapies (ACTs) threatens the global control of Plasmodium falciparum malaria. ACTs combine artemisinin-derived compounds with partner drugs to enable multiple mechanisms of clearance. Although ACTs remain widely effective in sub-Saharan Africa, long-standing circulation of parasite alleles associated with reduced partner drug susceptibility may contribute to the development of clinical resistance. We fitted a hierarchical Bayesian spatial model to data from over 500 molecular surveys to predict the prevalence and frequency of four key markers in transporter genes ( pfcrt 76T and pfmdr1 86Y, 184F, and 1246Y) in first-level administrative divisions in sub-Saharan Africa from the uptake of ACTs (2004 to 2009) to their widespread usage (2010 to 2018). Our models estimated that the pfcrt 76T mutation decreased in prevalence in 90% of regions; the pfmdr1 N86 and D1246 wild-type genotypes increased in prevalence in 96% and 82% of regions, respectively; and there was no significant directional selection at the pfmdr1 Y184F locus. Rainfall seasonality was the strongest predictor of the prevalence of wild-type genotypes, with other covariates, including first-line drug policy and transmission intensity more weakly associated. We lastly identified regions of high priority for enhanced surveillance that could signify decreased susceptibility to the local first-line ACT. Our results can be used to infer the degree of molecular resistance and magnitude of wild-type reversion in regions without survey data to inform therapeutic policy decisions.

Keywords: malari; drug resistance; surveillance (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:nas:journl:v:118:y:2021:p:e2100685118

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