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.

James Cotton

Professor

My research interests are in the genomics, and particularly population genomics of parasites, particularly those that cause neglected tropical diseases