Linked surveillance and genetic data uncovers programmatically relevant geographic scale of Guinea worm transmission in Chad

Abstract

Background Guinea worm (Dracunculus medinensis) was detected in Chad in 2010 after a supposed ten year absence, posing a challenge to the global eradication effort. Initiation of a village-based surveillance system in 2012 revealed a substantial number of dogs infected with Guinea worm, raising questions about paratenic hosts and cross-species transmission. Methodology/Principal Findings We coupled genomic and surveillance data from 2012-2018 cases to investigate the modes of transmission between hosts and the geographic connectivity for genetically similar worm populations. Eighty-six variants across three loci on the mitochondrial genome identified 41 genetically distinct worm genotypes. Spatiotemporal modeling reveals genetically identical worms are within a median range of 18.6 kilometers of each other, but largely within approximately 50 kilometers. Genetically identical worms vary in their degree of spatial clustering, suggesting there may be different factors that favor or constrain transmission. Each worm is surrounded by five to ten genetically distinct worms within a 50 kilometer radius. In an independent population, we show that more variants revealed in whole mitochondrial genome data improved the discrimination between worm pairs. Conclusions/Significance In the largest study linking genetic and surveillance data to date of Guinea worm cases in Chad, we show genetic similarity and modeling can contribute to understanding local transmission. The overlap of genetically distinct worms in quantitatively identified transmission ranges highlights the necessity for genomic tools to link cases. The improved discrimination between worm pairs from variants identified across the complete mitochondrial genome indicates expanding genomic markers could link cases at a finer scale. These results suggest that scaling up genomic surveillance for Guinea worm may provide additional value for programmatic decision-making critical for monitoring cases and intervention efficacy to achieve elimination.

Modeling the levels, trends, and connectivity of malaria transmission using genomic data from a health facility in Thiès, Senegal

“…Innovative efforts have also integrated complementary data from mobile-phone data and travel surveys with malaria parasite genetics [17]. In this work, we demonstrate that malaria parasite genetic data can identify connectivity at a small geographic scale; we utilize spatial models of human movement that have been shown, for various pathogens, to be effective for characterizing genetic linkages [30, 31]. The modeling investigation in this article leads to a better understanding of the levels, trends, and connectivity of malaria in Thiès, Senegal, and can inform decision-making for interventions in local settings.…”

Dracunculiasis Eradication: End-Stage Challenges

“…Adding routine genetic analysis of Guinea worms to ongoing active surveillance, case containment, and case investigation seems the best way forward in South Sudan as research in Chad has shown. 21 With a ratio of more than 60:1 infected domestic dogs to human cases in 2018-2021, dogs have clearly been driving Guinea worm transmission in Chad, where the riverine endemic area resembles Mali's, over the past decade, with incidental infection of humans. The similar 33% and 48% reductions in Guinea worm transmission to humans and dogs in Chad in 1 year (2021) may suggest parallel modes of transmission to humans and dogs by ingestion of infected transport hosts like fish rather than paratenic hosts such as frogs.…”