4/7/23

How Well Did the World do Modeling Covid?

https://youtu.be/PKMXev-HdI8

Dr. Murray and his team searched the body of COVID-19 modeling globally from the start of the pandemic and reviewed 7,628 models, articles and websites. Of these, the number of models with available data was 180. They then evaluated the performance of all these models against what happened during the pandemic, using performance measures that included forecasting skill. They were able to draw conclusions when the modeling community performed well in forecasting the pandemic, differentiating between types of models, countries, and key periods of the pandemic. Using this information, Dr. Murray makes recommendations on how we can do a better job in the future, and shares lessons learned on how to validate models in global health more broadly.

Dr. Christopher J.L. Murray is Chair of Health Metrics Sciences at the University of Washington and Director of the Institute for Health Metrics and Evaluation (IHME). His career has focused on improving population health worldwide through better evidence. A physician and health economist, his work has led to the development of innovative methods to strengthen health measurement, analyze the performance of health systems, understand the drivers of health, and produce forecasts of the future state of health.

Previous

Likelihood-Based Methods for Fitting Stochastic Epidemic Models to Noisy Data

Next

Infectious Disease Surveillance and Modeling through Spatial Big Data