01781nas a2200253 4500000000100000008004100001260003200042100001200074700001600086700001400102700001300116700001200129700001900141700001200160700001300172700001500185700001000200245013600210856008900346300001000435490000700445520106100452022001401513 2021 d c12/2021bScientific Reports1 aOchoa C1 aPittavino M1 aMartins S1 aAlcoba G1 aBolon I1 ade Castaneda R1 aJoost S1 aSharma S1 aChappuis F1 aRay N00aEstimating and predicting snakebite risk in the Terai region of Nepal through a high-resolution geospatial and One Health approach. uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8668914/pdf/41598_2021_Article_3301.pdf a238680 v113 a
Most efforts to understand snakebite burden in Nepal have been localized to relatively small areas and focused on humans through epidemiological studies. We present the outcomes of a geospatial analysis of the factors influencing snakebite risk in humans and animals, based on both a national-scale multi-cluster random survey and, environmental, climatic, and socio-economic gridded data for the Terai region of Nepal. The resulting Integrated Nested Laplace Approximation models highlight the importance of poverty as a fundamental risk-increasing factor, augmenting the snakebite odds in humans by 63.9 times. For animals, the minimum temperature of the coldest month was the most influential covariate, increasing the snakebite odds 23.4 times. Several risk hotspots were identified along the Terai, helping to visualize at multiple administrative levels the estimated population numbers exposed to different probability risk thresholds in 1 year. These analyses and findings could be replicable in other countries and for other diseases.
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