Modeling has long been used as a tool to conceptually describe epidemic
dynamics and assess possible interventions. More recently, modeling has also been employed to help inform outbreak preparedness, e.g., anticipating the spread of chikungunya virus, and response, e.g., assessing the impact of Zika virus infection. Nonetheless, its integration into the public health decision
making process remains limited. To help close this gap, it is essential to
ensure that modeling targets match specific public health needs, facilitate the
sharing of data and knowledge about that data, establish standards for assessing and communicating model skill, identify ways to effectively communicate predictions, especially uncertainties, and develop systems for operationalizing models for repeated use. Recent epidemic forecasting challenges, such as the U.S. Government Dengue Forecasting Project, highlight opportunities to evaluate forecasting models in the context of specific public health needs and advance both the science of infectious disease forecasting and the integration of forecasting into decision-making processes.
About the speaker:
Michael Johansson is a Biologist at the Centers for Disease Control and
Prevention Dengue Branch and a Visiting Scientist at the Harvard T.H. Chan
School of Public Health, Center for Communicable Disease Dynamics. He uses statistical and mathematical modeling to investigate infectious disease dynamics and identify ways to improve surveillance, prevention, and control. He also leads the CDC Epidemic Prediction Initiative, the CDC Zika Response Modeling Team, and contributes to various other efforts to advance infectious disease forecasting.