Chasing the COVID-19 Pandemic through Modeling
- Mathematical Models in Understanding COVID-19
- Institute for Pure and Applied Mathematics, UCLA
- August 10, 2020
The emergence of the COVID-19 pandemic is forcing policymakers to make crucial decisions about unprecedented scenarios. Mathematical models allow us to leverage available data to forecast the impacts of different policies using computational experiences. As a result, mathematical modeling has had a major effect on COVID-19-related policy decisions around the world. A wide range of models have been used to inform decisions from nationwide lockdowns and testing policies to targeting strategies of contact tracing.
The implementation and effectiveness of policies have been influenced by the quality of the mathematical modeling, the communication of the modeling, and the communication of the policies. Although there are some success stories, models have also sometimes been misused or misunderstood in designing policy. Models and policy will be most effective when (1) the modeling is appropriate to the situation at hand, and (2) the public understands and buys into the policy aims. It is also crucial to develop policy as important questions arise. For example, how can low- and middle-income countries (LMIC) cope with the impact of COVID-19 and the impact of policies to mitigate its spread? Additionally, how can we understand the heterogeneous situations – in concert with heterogeneous policies and behaviors of people – in the United States, Europe, New Zealand, and elsewhere?