Developing snakebite risk model using venomous snake habitat suitability as an indicating factor: An application of species distribution models in public health research

Snakebite envenoming is an important public health problem in Iran, despite its risk not being quantified. This study aims to use venomous snakes habitat suitability as an indicator of snakebite risk, to identify high-priority areas for snakebite management across the country. Thus, an ensemble approach using five distribution modeling methods: Generalized Boosted Models, Generalized Additive Models, Maximum Entropy Modeling Generalized Linear Models, and Random Forest was applied to produce a spatial snakebite risk model for Iran. To achieve this, four venomous snakes habitat suitability (Macrovipera lebetina, Echis carinatus, Pseudocerastes persicus and Naja oxiana) were modeled and then multiplied. These medically important snakes are responsible for the most snakebite incidents in Iran. Multiplying habitat suitability models of the four snakes showed that the northeast of Iran (west of Khorasan-e-Razavi province) has the highest snakebite risk in the country. In addition, villages that were at risk of envenoming from the four snakes were identified. Results revealed that 51,112 villages are at risk of envenoming from M. lebetina, 30,339 from E. carinatus, 51,657 from P. persicus and 12,124 from N. oxiana. This paper demonstrates application of species distribution modeling in public health research and identified potential snakebite risk areas in Iran by using venomous snakes habitat suitability models as an indicating factor. Results of this study can be used in snakebite and human-snake conflict management in Iran. We recommend increasing public awareness of snakebite envenoming and education of local people in areas which identified with the highest snakebite risk.