Developing new targets and milestones from standard surveillance data

Background To better understand transmission dynamics, we characterized Plasmodium falciparum genetic diversity in Eswatini, where transmission is low and sustained by importation. Methods Twenty-six P. falciparum microsatellites were genotyped in 66% of confirmed cases (2014–2016; N = 582). Population and within-host diversity were used to characterize differences between imported and locally acquired infections. Logistic regression was used to assess the added value of diversity metrics to classify imported and local infections beyond epidemiology data alone. Results Parasite population in Eswatini was highly diverse (expected heterozygosity [HE] = 0.75) and complex: 67% polyclonal infections, mean multiplicity of infection (MOI) 2.2, and mean within-host infection fixation index (FWS) 0.84. Imported cases had comparable diversity to local cases but exhibited higher MOI (2.4 vs 2.0; P = .004) and lower mean FWS (0.82 vs 0.85; P = .03). Addition of MOI and FWS to multivariate analyses did not increase discrimination between imported and local infections. Conclusions In contrast to the common perception that P. falciparum diversity declines with decreasing transmission intensity, Eswatini isolates exhibited high parasite diversity consistent with high rates of malaria importation and limited local transmission. Estimates of malaria transmission intensity from genetic data need to consider the effect of importation, especially as countries near elimination.

Eliminating malaria from a defined region involves draining the endemic parasite reservoir and minimizing local malaria transmission around imported malaria infections. In the last phases of malaria elimination, as universal interventions reap diminishing marginal returns, national resources must become increasingly devoted to identifying where residual transmission is occurring. The needs for accurate measures of progress and practical advice about how to allocate scarce resources require new analytical methods to quantify fine-grained heterogeneity in malaria risk. Using routine national surveillance data from Swaziland (a sub-Saharan country on the verge of elimination), we estimated individual reproductive numbers. Fine-grained maps of reproductive numbers and local malaria importation rates were combined to show ‘malariogenic potential’, a first for malaria elimination. As countries approach elimination, these individual-based measures of transmission risk provide meaningful metrics for planning programmatic responses and prioritizing areas where interventions will contribute most to malaria elimination.DOI: http://dx.doi.org/10.7554/eLife.09520.001