Data mapping is revealing how and why diseases spread

A new scientific model for tracking diseases shows that carriers of rat-borne Lassa fever will double to 406,725 carriers by 2070
Healthcare workers in protective equipment bury a 13-year-old boy who died of Lassa fever on March 5, 2014 in Bo district, Sierra LeoneLam Yik Fei/Getty Images

The spread of human diseases has been mapped, giving scientists a way of predicting the spread from animals to humans.

The team behind the map have already used it to predict how rat-borne Lassa fever will spread across the world by 2070. They say it's a "major improvement" in our understanding of the spread of diseases.

The model uses climate change, population growth and land use to predict how diseases that originate in livestock and wildlife – which make up 60 per cent of "emerging infectious diseases" – spread.

Lassa fever was used by the team to illustrate the model, with land use, crop yields, temperature, rainfall and access to healthcare across 400 locations helping to track and predict the spread of the disease. The fever is "endemic" across West Africa and is spread by rats.

The model predicts that the disease will double to 406,725 carriers by 2070 because of "climate change and a growing human population".

"We hope it can be used to help communities prepare and respond to disease outbreaks, as well as to make decisions about environmental change factors that may be within their control," said Kate Jones, lead author of the UCL study.

First author David Redding said the research shed light on how the environment interacts with the "mechanics" of disease.

"Our new approach successfully predicts outbreaks of individual diseases by pairing the changes in the host's distribution as the environment changes with the mechanics of how that disease spreads from animals to people, which hasn't been done before," he said.

The team hope their model will prevent disease, as well as "help decision makers assess the impact of intervention or change in national government policies".

"Importantly, the model also has the potential to look at the impact of global change on many diseases at once, to understand any trade-offs that decision makers may have to make," said Jones.

The study has been published in Methods in Ecology and Evolution.

This article was originally published by WIRED UK