Molecular surveillance of antimalarial partner drug resistance in sub-Saharan Africa: a spatial-temporal evidence mapping study.

BACKGROUND: Molecular markers for antimalarial drug resistance can be used to rapidly monitor the emergence and spatial distribution of resistance to artemisinin-based combination therapies (ACTs). Little has been done to analyse molecular surveillance efforts or to assess surveillance coverage. This study aimed to develop an evidence map to characterise the spatial-temporal distribution and sampling methodologies of drug resistance surveillance in sub-Saharan Africa, specifically focusing on markers associated with ACT partner drugs.
METHODS: By use of a systematic search, we identified studies that reported data on the following mutations associated with ACT partner drug resistance: pfmdr1 Asn86Tyr, Tyr184Phe, Asp1246Tyr, and copy number variation and pfcrt Lys76Thr, with sample collection occurring in sub-Saharan Africa between Jan 1, 2004, and Dec 31, 2018, corresponding to the uptake of ACTs. For each identified study, we extracted information on its sampling and laboratory methods, author and publication affiliations, years of sampling and of publication, geographic coordinates of the study sites, and prevalence of the partner drug resistance-associated markers. We used linear models to test whether urbanicity, population density, and endemicity were predictors of drug resistance survey sites and linear regressions to identify associations between the number of resistance surveys within a given country and the at-risk malaria population in 2010, the per-capita GDP in 2010, and the mean amount of funding directed to malaria and to determine trends in marker prevalence over time. For country case studies with three or more datapoints, we assessed global spatial autocorrelation using Moran's I.
FINDINGS: Our search yielded 254 studies encompassing 492 year-specific and location-specific surveys from 35 malaria-endemic countries, the most complete set of molecular partner drug surveillance data to date. We observed a median time lag of 3·1 years (95% CI 1·0-7·7) from final sample acquisition to publication. 22 (49%) of the 44 countries in the study region conducted, on average, one or fewer studies every 3 years. The locations of surveillance sites were positively associated with urbanicity (p<0·0001), and the abundance of country-level data was associated with reported donor funding in 2004-18 (p=0·0011) and local government funding in 2004-09 (p=0·014). Nearly all molecular markers displayed significant regional trends over time and global spatial autocorrelation in space. For selected countries with more widespread coverage of surveillance data, some markers also displayed spatial heterogeneity.
INTERPRETATION: In most sub-Saharan countries, molecular data on antimalarial resistance might not be representative of the temporal and geographic heterogeneity of partner drug resistance, and likely do not represent the true spatially dependent distribution of partner drug resistance. Our results highlight several inefficiencies that can be improved upon to develop more accurate data landscapes, including the expansion of sentinel surveillance systems, syndemic usage of research samples, and increased participation in reporting published and unpublished data to centralised platforms.