02749nas a2200301   4500000000100000008004100001260003700042653005700079653002400136653001900160653004100179100001600220700001700236700001200253700001400265700001200279700001700291700001200308700001500320700001400335700001400349245010500363856009900468300001300567490000700580520184600587022001402433       2020                            d  bPublic Library of Science (PLoS)10aPublic Health, Environmental and Occupational Health10aInfectious Diseases10aDracunculiasis10aDracunculiasis (guinea-worm disease)1 aRichards RL1 aCleveland CA1 aHall RJ1 aOuakou PT1 aPark AW1 aRuiz-Tiben E1 aWeiss A1 aYabsley MJ1 aEzenwa VO1 aNgondi JM00aIdentifying correlates of Guinea worm (Dracunculus medinensis) infection in domestic dog populations  uhttps://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0008620&type=printable  ae00086200 v143 aFew human infectious diseases have been driven as close to eradication as dracunculiasis, caused by the Guinea worm parasite (Dracunculus medinensis). The number of human cases of Guinea worm decreased from an estimated 3.5 million in 1986 to mere hundreds by the 2010s. In Chad, domestic dogs were diagnosed with Guinea worm for the first time in 2012, and the numbers of infected dogs have increased annually. The presence of the parasite in a non-human host now challenges efforts to eradicate D. medinensis, making it critical to understand the factors that correlate with infection in dogs. In this study, we evaluated anthropogenic and environmental factors most predictive of detection of D. medinensis infection in domestic dog populations in Chad. Using boosted regression tree models to identify covariates of importance for predicting D. medinensis infection at the village and spatial hotspot levels, while controlling for surveillance intensity, we found that the presence of infection in a village was predicted by a combination of demographic (e.g. fishing village identity, dog population size), geographic (e.g. local variation in elevation), and climatic (e.g. precipitation and temperature) factors, which differed between northern and southern villages. In contrast, the presence of a village in a spatial infection hotspot, was primarily predicted by geography and climate. Our findings suggest that factors intrinsic to individual villages are highly predictive of the detection of Guinea worm parasite presence, whereas village membership in a spatial infection hotspot is largely determined by location and climate. This study provides new insight into the landscape-scale epidemiology of a debilitating parasite and can be used to more effectively target ongoing research and possibly eradication and control efforts  a1935-2735