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Study shows how data can be used to fight Ebola, Lassa and more

Medical professionals at the University College London (UCL) have developed a prediction model that could help communities slow the spread of infectious diseases such as Ebola, Zika and Rift Valley fever, which originate in animals.

The team, led by Professor Kate Jones, looked at various data including changes in land use, crop yields, temperature, rainfall, access to healthcare and past instances of Lassa fever outbreaks to find correlations between environmental effects and the movements of animals that spread the disease and outbreaks. Their findings have been published in the journal Methods in Ecology & Evolution.

The first is a rather shocking one. After studying 408 cases of Lassa fever outbreaks in West Africa between 1967 and 2012 the team predicts that by 2070 cases of Lassa fever will have risen from 195 125 cases to 406 725.

The researchers believe, however, that they have found correlations between environmental usage and weather changes that can be used to predict where outbreaks of Lassa will happen, and thus be used to prevent them.

“Our model can help decision-makers assess the likely impact of any interventions or change in national or international government policies, such as the conversion of grasslands to agricultural lands,” Jones said in a statement.

Critically, Jones believes that the same techniques could be used for other diseases spread between animals and people (known as zoonotic diseases), and by including data around travel and the movement of people may help to avert future catastrophes like the recent Ebola crisis.

“This model is a major improvement in our understanding of the spread of diseases from animals to people,” Jones said. “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.”

[Source – EurekAlert] [Image – CC BY/2.0 NIAID]

 

 

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