Evolutionary and epidemiological transitions in the emergence of zoonotic viruses

Summary Before, during, and after a zoonosis (transmission of an animal virus to humans), there are qualitatively different phases in the evolution and epidemiology of the virus. The virus must acquire evolutionary adaptations to first successfully infect, and then to potentially transmit between, humans. If these adaptations are acquired, the virus may be able to cause disease outbreaks that can grow to become epidemics or even pandemics. After which, the virus may be able to adapt stably to humans, so that it becomes endemic. The transitions between these phases are generally understudied: the parameters that control and characterise the transitions are unknown. In this project a combination of modelling and data analysis of epidemiological and genetic data will be used to develop a quantitative understanding of these transitions. We will use the extensive data on SARS-CoV-2 accumulated during the COVID-19 pandemic, and also perform detailed analysis of Influenza A virus - often considered a prime candidate for the next emerging pandemic. Throughout, our focus will be on how understanding the extent and cause of these transitions can be translated into interventions that prevent the development of emerging zoonotic viruses in humans. BBSRC priorities Our project focuses on emerging zoonotic viruses at the animal-human interface, and therefore falls under the area Bioscience for an integrated understanding of health. The project, which recognises that animal health is essential for human health and vice versa, strongly aligns with the key challenge area of One Health. In addition, our research on methods to exploit very large data resources (sequence data, deep mutational scanning) using high-performance computing comes under the area of Data-driven biology, and also under the data-intensive research theme of Transformative Technologies. Our modelling of the evolution of expanding host range, considering both animal and human individuals explicitly, falls under Systems approaches to the biosciences.