Linking science and policy

How can we support science-based decision making when science is complex and challenging to communicate? Compartmental models are commonly used in epidemiology to understand and predict the spread and establishment of infectious disease in populations. Epidemiologists typically implement these mathematical models in complex statistical software packages that require a high level of technical expertise, limiting the accessibility for most audiences.

Epidemix allows users to improve their understanding of key concept of disease dynamics and control, without having to directly deal with mathematical equations and programming language. The app makes it easy for users to follow the links between model outputs and underlying assumptions.

Users can choose from general and disease-specific models and the interface makes it easy to compare the impact of different parameter settings, such as the length of the asymptomatic period or percentage of the population that is protected by a vaccine on disease spread.

Results can be easily exported and shared e.g. with students or collaborators.

Working closely with researchers at the Royal Veterinary College and the City University of Hong Kong, the flexibility of Epidemix allowed us to quickly add models for COVID-19 and African Swine Fever (ASF) to support the link between science and policy in efforts to curtail their spread, and to enhance training of concepts critical to their control to a global audience.