Modelling to inform interventions during Highly Pathogenic Avian Influenza outbreaks in Great Britain

Avian influenza is a highly contagious disease, affecting both wild birds and domestic poultry. The poultry industry suffers substantial economic losses due to this disease, both in Great Britain (GB) and around the world. The 2021-22 outbreak in GB has been the largest in the country's history, and seasonal outbreaks are expected to continue to occur. Mathematical models are increasingly used during outbreaks of a range of diseases to inform future scenarios and to guide control measures. This project involves developing a national-scale mathematical model of avian influenza transmission around GB, in collaboration with the UK Government's Animal and Plant Health Agency (APHA). It builds on our previous work with APHA during the 2021-22 outbreak, in which we spent six weeks developing a preliminary transmission model to project future spread of the virus and to guide control interventions. In the current project, we will build on our previous rapid-response research, taking advantage of the longer timescale of this project to develop a flexible modelling framework with a high level of rigour. This includes fitting the parameters of the transmission model to a range of data sources, and accounting for both transmission between poultry premises within GB and importations of infection from elsewhere. By working closely with APHA, we will ensure that the model can be run on APHA computer systems, permitting its use by policy advisors to guide interventions in future outbreaks. Once we have developed the transmission model, we will use it to explore the effectiveness of a range of different control interventions that could be applied during future outbreaks in GB. A benefit of our collaboration with APHA is that we are in a position to use the model to test practical strategies that could be deployed effectively. We will also develop a user-friendly software tool and Graphical User Interface based on the model, allowing the user to change model parameters themselves and test different control interventions without requiring specialist knowledge about the computing code. To encourage others to use the software, we will run an outbreak simulation exercise in which we will provide simulated outbreak data to policy advisors, who will then use the tool to determine optimal interventions. Similar exercises have been conducted before for a range of other livestock diseases. This exercise will be conducted at the start of the third year of this project, enabling any feedback to be incorporated into the model and software tool. We will also run a two-day workshop for other researchers in which we describe the modelling framework and software tool, and demonstrate their use. In summary, this project will involve the development of a national epidemiological modelling resource that can be used to plan control measures during future avian influenza outbreaks in GB. It complements existing research on avian influenza by providing a tool that will be used by policy advisors for the foreseeable future to determine optimal interventions during outbreaks.