Phys.org April 26, 2023
When certain conditions are met, the passage of viruses from one species to another can ultimately lead to the emergence of a zoonosis. To make better predictions of interactions between mammals and viruses in general, an international team of researchers (Canada, UK, USA – University of Oklahoma, Georgetown University, Washington University) developed an algorithm to sample thousands of species of mammals and even more thousands of viruses to identify which host-virus interactions to explore further. The algorithm represents the system as a network of interactions between viruses and mammals that the algorithm must then complete. It takes the network we already know and projects it into a new space which in turn allows them to make predictions. To validate the model, they selected 20 key viruses that have the potential to jump the species barrier and infect humans. According to the researchers their model makes it possible to map the results to better understand virus-mammal interactions on a global scale, spatial predictions, indicates specifically in which group of mammals and in which location certain types of viruses are likely to be found. The team identified two geographic regions to explore, the Amazon basin in South America, where the interactions between hosts and viruses are more original than elsewhere and where new interactions are more likely to be observed, and Central Africa, where new hosts have been found that are potential carriers of zoonotic viruses. Their next steps are to make the information easily accessible and user-friendly for partners in the field, make it easier for stakeholders to adopt their model… read more. Open Access TECHNICAL ARTICLEÂ
Graphical abstract. Credit: Patterns, April 24, 2023