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Posted: 14th June 2016

Scientists use environmental changes to predict disease
Rat
Researchers used the model to predict the current pattern of Lassa fever which is transmitted by rats.
New model predicts spread of Lassa fever

A team led by University College London (UCL) has developed a model to predict zoonotic diseases, like Zika and Ebola, using changes in the environment.  

Over 60 per cent of emerging infectious diseases are zoonotic. The most well-known are Ebola and Zika, but there are many other diseases, like Rift Valley fever and Lassa fever, which already affect thousands and are predicted to spread with changing environmental factors.

Kate Jones, professor of Genetics at UCL, described the new model as a ‘major improvement’ in understanding how disease spreads from animals to humans. She hopes that it could be used to prevent disease outbreaks among communities.

“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, on zoonotic transmission,” she said.

“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 be make.”

The new model, published in the journal Methods in Ecology and Evolution, has already proved successful by predicting the current disease patterns of Lassa fever.

Lassa fever is endemic across West Africa and is transmitted by rats. The model predicts the number of people with the disease will double from 195,125 to 406,725 by 2010 due to climate change and growing human population.

Just like Ebola, Lassa virus causes haemorrhagic fever and can be fatal. But how many people are affected by the disease is unclear, as many do not show severe symptoms and those that do are often misdiagnosed with Malaria.

“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,” explains first author, Dr David Redding.

“It allows us to calculate how often people are likely to come into contact with disease-carrying animals and their risk of the virus spilling over. Alongside population increases, the expected future changes to climatic patterns will drive an expansion of the areas of West Africa considered high risk, especially the western most regions around Senegal and Guinea, the coastline of Cote d'ivoire and Ghana, and in Central Nigeria,” he adds.

The team hope to refine the model to consider zoonotic disease transmission within human populations, by including the impact of travel infrastructure, human-to-human contact rates and poverty. 



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