A model that predicts outbreak of zoonotic infections - those beginning in domesticated animals or natural life, for example, Ebola and Zika - in view of changes in atmosphere, populace development and land use has been created by a UCL group of Scientist.

"This model is a major improvement in our understanding of the spread of diseases from animals to people. 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 lead author Professor Kate Jones, UCL Genetics, Evolution & Environment and ZSL.

Around 60 to 75 percent of developing infection sicknesses are alleged "zoonotic occasions", where animals hop into individuals. Bats specifically are known to spread zoonotic infections.

"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. 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," Professor Jones added.

"Our 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," said David Redding, who co-led the study.

"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."

The study published in Methods in Ecology and Evolution tested the new model with Lassa fever.

Thousands of U.S. people are infected every year by zoonotic diseases transmitted by mosquitoes or ticks, such as Rocky Mountain, West Nile virus, dengue, malaria, and chikungunya.

However, other significant zoonotic disease such as Ebola and Zika have been present globally over the last three years.