Model-based assessment of Chikungunya and O'nyong-nyong virus circulation in Mali in a serological cross-reactivity context.

Serological surveys are essential to quantify immunity in a population but serological cross-reactivity often impairs estimates of the seroprevalence. Here, we show that modeling helps addressing this key challenge by considering the important cross-reactivity between Chikungunya (CHIKV) and O'nyong-nyong virus (ONNV) as a case study. We develop a statistical model to assess the epidemiology of these viruses in Mali. We additionally calibrate the model with paired virus neutralization titers in the French West Indies, a region with known CHIKV circulation but no ONNV. In Mali, the model estimate of ONNV and CHIKV prevalence is 30% and 13%, respectively, versus 27% and 2% in non-adjusted estimates. While a CHIKV infection induces an ONNV response in 80% of cases, an ONNV infection leads to a cross-reactive CHIKV response in only 22% of cases. Our study shows the importance of conducting serological assays on multiple cross-reactive pathogens to estimate levels of virus circulation.

Adaptive differentiation of Plasmodium falciparum populations inferred from single-nucleotide polymorphisms (SNPs) conferring drug resistance and from neutral SNPs.

BACKGROUND: Theoretical and experimental data support the geographic differentiation strategy as a valuable tool for detecting loci under selection. In the context of Plasmodium falciparum malaria, few populations have been studied, with limited genomic coverage. METHODS: We examined geographic differentiation in P. falciparum populations on the basis of 12 single-nucleotide polymorphisms (SNPs) in 4 genes encoding drug resistance determinants, 5 SNPs in 2 genes encoding antigens, and a set of 17 putatively neutral SNPs dispersed on 13 chromosomes. We sampled 326 parasite isolates representing 7 P. falciparum populations from regions with varied levels of malaria transmission (Gabon, Kenya, Madagascar, Mali, Mayotte, Haiti, and the Philippines). RESULTS: Frequencies of drug resistance alleles varied considerably among populations (mean F(ST), 0.52). In contrast, allele frequencies varied significantly less for antigenic and neutral SNPs (mean F(ST), 0.16 and 0.24, respectively). This contrasting pattern was more pronounced when only the African populations were considered. Signature of selection was detected for most of the resistant SNPs but not for the antigenic SNPs. CONCLUSION: These data further validate the utility of geographic differentiation for identifying loci under strong positive selection, such as drug resistance loci. This study also provides frequencies of molecular makers of resistance in some overlooked populations.