An incredibly large number of people around the world – 1.8 million – in an average year are bitten by venomous snakes – and almost 100,000 of them die as a result. Snakebite is a neglected tropical disease affecting millions, and a major cause of death in the tropics – especially among farmers who meet up with snakes in their fields.
The World Health Organization has launched a strategic plan to reduce snakebites by 50% by 2030. An important basis for attaining this goal is expanding relevant scientific research. Previous studies focused on statistical correlates between snakebites and ecological, sociological or environmental factors, but the human and snake behavioral patterns that drive the time-and-space process had not yet been integrated into a single model.
Now, an international research group that included researchers from Tel Aviv University (TAU) has created an innovative simulation model for predicting snakebites based on an improved understanding of interactions between farmers and snakes in both time and space.
The researchers studied Sri Lanka, formerly known as Ceylon, an island country in South Asia located in the Indian Ocean, which is a world hotspot for snakebites with some 30,000 cases annually. The scientists developed a model for predicting snakebites based on the behavior patterns of both farmers and snakes.
The research focused on six types of snakes, some among the most venomous in the world (cobra, Russell’s viper, saw-scaled viper, hump-nosed viper, common krait and Ceylon krait), matching them with farmers who grow the three most common crops in the area: rice, tea and rubber. For example, the model predicts that the bites of Russell’s Viper peak in rice fields in February and August, while the Hump-Nosed Viper usually bites in rubber plantations in April and May.
The model could be used in different countries to predict changes in snakebite patterns resulting from climate change in the future. It can, said the team, become a valuable tool for snakebite prevention policies, saving numerous human lives. They published their study in PLoS (Public Library of Science) Neglected Tropical Diseases under the title “Integrating human behavior and snake ecology with agent-based models to predict snakebite in high-risk landscapes.”
They also determined that in the southeastern part of the studied region, the largest number of snakebites are inflicted by Russell’s viper, one of the world’s most dangerous snakes, while in other parts of this area snakebites of the less lethal hump-nosed viper are the most common.
The study was led by Dr. Takuya Iwamura (currently at Oregon State University) and Eyal Goldstein of TAU’s School of Zoology and Dr. Kris Murray of Imperial College London and that city’s School of Hygiene and Tropical Medicine. Other participants included researchers from the Liverpool School of Tropical Medicine, Lancaster University and the University of Kelaniya, Sri Lanka.
“We built a first-of-its-kind interdisciplinary model, which includes the behavior patterns of both sides – snakes and humans, identifying risk factors at various times and places and warning against them. For example, the model can differentiate between low-risk and high-risk areas, a difference that can be manifested in double the number of snakebites per 100,000 people,” explained Goldstein.
Murray added that “both snakes and people go about their business at different times of the day, in different seasons and in different types of habitats. The model captures all of this to predict encounters between people and snakes in areas where farmers are working. We then factor in the aggressiveness of different snake species to work out how likely an encounter is to result in a bite.”
Iwamura noted that “our approach is to mathematically analyze interactions between snakes and humans, with an emphasis on the ecological perspective. This is a completely new approach to understanding the mechanism that causes snakebites. Unlike most studies, which have so far focused mainly on social and economic risk factors, we chose to focus on the ecological aspects – such as snakes’ movements and habitats, the impact of climate and rainfall, and the respective behaviors of farmers and snakes – as a key to predicting potential encounters.”
Verified against existing data in Sri Lanka, the model was proved very accurate in predicting snakebite patterns in different areas and different seasons, as well as the relative contribution of various types of snakes to the overall picture as seen in hospital data. Now the researchers intend to implement the model in places that don’t yet have accurate snakebite data.
They will use it also to predict future changes resulting from climate change – such as increased rainfall leading to greater snake activity, as well as changes in land use and habitats available to snakes.
“Our model can help focus the efforts of snakebite reduction policies and serve as a tool for warning, raising awareness and saving human lives,” Iwamura concluded. “Moreover, we regard this study as a first stage in a broader project; in the future, we intend to develop more complex models of encounters between humans and wildlife, to support both public health and nature preservation policies in the real world.”