Modelling the next pandemic: Infectious disease data and analytics

Pandemics are often described as a risk without history. Current methods for assessing pandemic risk are typically based on observational data, which .. Read more is often sparse and incomplete. However, observational data is necessary not only to understand this type of risk but also parameterise infectious disease models that can help fill in the gaps in observational data. These models can help to provide a clearer picture of potential pandemic risk. Stochastic epidemic models can be used to simulate millions of pandemics, with varying initial parameters and differing availability and efficacy of intervention measures. From these millions of simulations, an event catalogue is created by selecting simulated events using a sampling algorithm that accounts for the joint probability of each parameter combination for each scenario and the interarrival time distribution between pandemics. Probabilistic modelling and stochastic simulations can be a powerful tool to quantify pandemic risk.