New Model Helps To Predict Snakebites In High-Risk Areas

An international research group has created an innovative simulation model for predicting snakebites.

About 1.8 million poisonous snakebites occur around the world annually, killing about 94,000 people. In tropical areas, especially in Southeast Asia and sub-Saharan Africa, snakebites are considered a major cause of death, especially among farmers who encounter snakes in their fields.

That’s why the World Health Organization has launched a strategic plan to reduce snakebites by 50 percent by 2030. An important basis for attaining this goal is expanding relevant scientific research.

In a study led by Takuya Iwamura at Oregon State University, Eyal Goldstein at the School of Zoology at Tel Aviv University, and Kris Murray of Imperial College London and the School of Hygiene and Tropical Medicine in London, researchers designed a model based on an improved understanding of interactions between farmers and snakes in time and space.

The purpose of the model is to determine the probability of a snakebite occurring in certain places (for example, in rice fields vs. tea fields) at various times (hours of the day and months of the year).

The study took advantage of extensive research and data from Sri Lanka, where about 30,000 poisonous snakebites kill approximately 400 people every year.

It focused on six types of snakes, including some of the most venomous in the world — cobra, Russell’s viper, saw-scaled viper, hump-nosed viper, common krait and Ceylon krait.

The researchers matched these snakes then with farmers who grow the three most common crops in the area: rice, tea and rubber.

As examples, the model predicts that the bites of Russell’s viper peak in rice fields during February and August, while the hump-nosed viper prefers rubber plantations in April and May.

The model also determines that in the southeastern part of the studied region, the largest number of snakebites are inflicted by Russell’s viper, one of the most dangerous snakes in Asia. In other parts of this area, snakebites of the less lethal hump-nosed viper are the most common.

First-of-its-kind model

“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,” Goldstein said.

The model can, for example, differentiate between low-risk and high-risk areas. High-risk areas may have double the number of snakebites per 100,000 people.

“Both snakes and people go about their business at different times of the day, in different seasons and in different types of habitats,” said Murray. “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 said their 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.”

Ecological focus

Unlike most studies, which so far have focused mainly on social and economic risk factors, the researchers chose to focus on ecological aspects such as snakes’ movements and habitats, the impact of climate and rainfall, and the respective behaviors of farmers and snakes as key to predicting potential encounters.

Verified against data in Sri Lanka, the model proved very accurate in predicting snakebite patterns in different areas and seasons, as well as the relative contribution of various types of snakes to the overall picture from hospital data.

“Our model can help focus the efforts of snakebite-reduction policies, and serve as a tool for warning, raising awareness and saving human lives,” said Iwamura. “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.”

The researchers want to implement the model in places that don’t yet have accurate snakebite data.

They will also use the model 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.

Other participants in the study include researchers from the Liverpool School of Tropical Medicine, Lancaster University and the University of Kelaniya, Sri Lanka. The paper was published in PLOS Neglected Tropical Diseases in February.

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