A team of researchers from Swansea University and The University of Queensland is seeking to gain a better understanding of how best to tackle harmful viruses that shift between wildlife and humans and go on to cause global epidemics.
[aoa id=”1″]The number of animal species that a pathogen – a bacterium or virus that causes disease – infects is widely considered an indicator of its risk to shift host species. Pathogens that infect more animal species should be more likely to jump to a new host. But how infected animals are related to one another is also important. If a pathogen infects a number of monkey and ape species, it will probably have a better chance of infecting humans than one that only infects birds or fish.[/aoa]
But in a recent paper published in Trends in Parasitology, the research team shows that zoonotic disease spread (a disease which can be transmitted from animals to people) is not so simple. The team identified a growing number of research studies that demonstrate how host shifting is inexorably linked to the environment. Simply put, different environments provide different opportunities for pathogens to interact with and infect new host species.
Dr Nicholas Clark, from UQ’s School of Veterinary Science, said this was a new line of thinking in this area, changing how we understand and tackle emerging zoonotic diseases: “In the past, we’ve primarily looked at how many different types of animal species a pathogen infects, widely considered an indicator of its risk to shift between host species. This is just one factor, and we’ve found that how infected animals are related is also important. Our research shows that different environments provide new opportunities for pathogens to interact with and infect new host species.”
Dr Konstans Wells of Swansea University explains how developing a model to forecast the next emerging infectious disease events in times of global environmental change is essential: “As a recent study found, climate change may constrain or facilitate the spread of diseases like avian malaria. We simply need to find out more information to help us build a new modelling framework, which could help us forecast disease spread.
“Mathematical tools developed in the study of sensor networks, image processing and pattern recognition, and computational physics can help us predict when and where pathogens will be exposed to animals. Adapting these techniques in human and wildlife health research will be important if we’re to predict future emerging infectious disease epidemics or pandemics.
“Many factors are driving the spread of infectious diseases, making it challenging to predict when and where they’ll emerge next. However, by feeding our growing understanding of disease patterns into models, there’s hope we’ll be able to better forecast disease threads in the future, helping prepare for the next outbreak before it even arrives.”
