Mapping the risk of snakebites in Ecuador

Study models open species occurrence data to map the risk of poisoning by snakebites in densely populated communities of Ecuador

GBIF-mediated data resources used : 9,111 species occurrences
Bothrops atrox
Common lancehead (Bothrops atrox) observed near Tena, Ecuador by Felix Fleck. Photo via iNaturalist (CC BY-CN 4.0

Ophidism, the medical term for poisoning from snake venom, is a serious public health issue, especially in the tropics. While social and temporal aspects of snakebites have been studied, not much is known
about the geographic spread of snakebite risk.

With 39 venomous snakes, Ecuador’s species richness is among the highest in the world. As assessment of actual bite rates are expensive at a large scale, this study takes a correlative approach, mapping the risk of snakebites by modelling GBIF-mediated occurrences of medically relevant species.

The models suggest a low risk in the central Andean region, while risk in the adjacent coastal and Amazonian regions is high, findings that confirm previous reports of snakebites. Applying these results to a map of local rural areas, the authors identified 187 densely populated communities with high risk of snakebites.

While the study doesn’t use actual incidence data in the models, it represents significant progress in snakebite risk assessments. The authors call for the implementation of a national snakebite reporting system to improve understanding of the patterns of ophidism in Ecuador.

Link to original article

Yañez-Arenas C, Díaz-Gamboa L, Patrón-Rivero C, López-Reyes K and Chiappa-Carrara X (2018) Estimating geographic patterns of ophidism risk in Ecuador. Neotropical Biodiversity. Informa UK Limited 4(1): 55–61. Available at: https://doi.org/10.1080/23766808.2018.1454762.

  • {{'resourceSearch.filters.countriesOfResearcher' | translate}}:
  • Mexico
  • {{'resourceSearch.filters.countriesOfCoverage' | translate}}:
  • Ecuador
  • {{'resourceSearch.filters.topics' | translate}}:
  • Human health
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  • Data users
  • GBIF network
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  • Data analysis