Applying species distribution models in public health research by predicting snakebite risk using venomous snakes’ habitat suitability as an indicating factor

Abstract

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 modelling methods: Generalized Boosted Models, Generalized Additive Models, Maximum Entropy Modelling, 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 lebetinus, Echis carinatus, Pseudocerastes persicus and Naja oxiana) were modelled 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. lebetinus, 30,339 from E. carinatus, 51,657 from P. persicus and 12,124 from N. oxiana. Precipitation seasonality was identified as the most important variable influencing distribution of the P. persicus, E. carinatus and M. lebetinus in Iran. Precipitation of the driest quarter was the most important predictor of suitable habitats of the N. oxiana. Since climatic variables play an important role in shaping the distribution of the four venomous snakes in Iran, thus their distribution may alter with changing climate. This paper demonstrates application of species distribution modelling 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.

Estimating and predicting snakebite risk in the Terai region of Nepal through a high-resolution geospatial and One Health approach

“…As is the case for other covariates, its interpretation depends on the study circumstances. In Iran, it was considered an indicator of prey availability for snakes and linked to snake habitat suitability 14 . Elevated NDVI values have been associated with higher number of hospitalizations in Nigeria and northern Ghana, in particular during the periods of high agricultural activity, which is also related to higher snake-human contact and higher snakebite incidence 43 .…”

“…Environmental drivers like temperature and precipitation are common factors in geospatial analyses of snakebite 13 , 14 , 17 , 44 . They are found in many cases to be the main factors modulating the incidence or risk of snakebite, while varying in importance according to study conditions.…”

“…They are found in many cases to be the main factors modulating the incidence or risk of snakebite, while varying in importance according to study conditions. For example, in Iran, precipitation seasonality was the most prevalent climatic covariate determining the habitat suitability leading to snakebite risk 14 , while in Mozambique, temperature seasonality was the predominant covariate 13 . Despite the Terai’s sub-tropical climate, the range of the average minimum temperature of the coldest month (BIO6) was 1.8–10.9 °C.…”

Promoting co-existence between humans and venomous snakes through increasing the herpetological knowledge base

“…The need for understanding HSC is especially pressing in the context of climate change, since several recent studies suggest possible increases in HSC as humans and snakes respond via shifting distributions and behaviours ( Yousefi et al, 2020 ). Where range extensions occur in areas where existing levels of conflict is low, the necessary medical infrastructure may be lacking [ Zacarias and Loyola, 2019 ]) and will require increased training for doctors, scaling up of medical infrastructure and instigation of outreach programmes, concurrent with collecting more precise data for monitoring and mapping predicted and current areas of human-snake conflict ( Heathcote et al, 2019 ; Longbottom et al, 2018 ; Rifaie et al, 2017 ).…”

Estimating Snakebite Risk in the Terai, Nepal: A High-Resolution Geospatial and One Health Analysis

“…In Iran, it was considered an indicator of prey availability for snakes and linked to snake habitat suitability. 14 Elevated NDVI values have been associated with higher number of hospitalizations in Nigeria and northern Ghana, in particular during the periods of high agricultural activity, which is also related to higher snake-human contact and higher snakebite incidence. 38 In our study, its 'protective' effect can indeed be the consequence of better access to prey associated with healthier ecosystems, explained in the Terai by the higher NDVI values of the multiple dense forests distributed along the region.…”