Grant: Catalyst Grant: Avian Influenza OneHealth Research

Interspecies transmission of viruses represents a significant risk to human and animal health, and food security. Since 1996, the highly pathogenic avian influenza H5Nx viruses have been established as ongoing threat to poultry sector, wild-bird conservation, and human health globally. The latest wave of transmission, associated with H5N1 viruses from subclade 2.3.4.4b, resulted in record levels of infection in wild birds and poultry, severe outbreaks in aquatic mammals, and incursion in cattle and other mammals. This has potential to drive further mammalian adaptation and represents pandemic threat. Although significant genomic surveillance infrastructure exists for H5Nx in global databases, considerable gaps exist in our ability to employ these advances in a prospective manner to forecast the host and antigenic transitions. Fortunately, machine learning approaches to analyse large, high dimension data continue to be developed. Our team will develop predictive genomic models of H5Nx host range and antigenicity to drive real-time risk assessment of novel H5Nx variants. The overarching goal of the proposed research is to develop and validate predictive models for the purposes of genomic host prediction, identification of H5 variants of interest, and prediction of antigenicity. Through this, we will advance approaches for predictive modelling based on genomic data; the output of these models could then be used for prioritising surveillance efforts, further experimental validation informing policy, and prioritising vaccine and therapeutic development in animals and humans. The methodology will be based on already generated genomic data of different granularity, publicly and through collaborating scientists; and on development and validation of advanced machine-learning models which will be deployed for real-time analysis, risk assessment and communication to end users in human, agricultural and wildlife animal health, and environmental health.