One year into the COVID-19 pandemic, mathematical models continue to be used to make sense of the epidemic and shape public policy decision-making. Researchers at Harvard T.H. Chan School of Public Health led by CHDS’ Faculty Nick Menzies, and at the Yale School of Public Health led by Professor Ted Cohen, have developed a statistical model that provides near real-time projections of COVID-19 epidemiology (“nowcasting”). The estimates (cases, deaths, and cumulative infections) are reported for all 50 states and for over 3,000 counties in the United States on a public, interactive website (www. covidestim.org) that is updated daily.
As part of a new collaboration with Stanford University, the research team works with the Council of State and Territorial Epidemiologists to make these modelling results accessible for state and local health officials, to provide information on the trajectory of COVID-19 and to help identify potential hotspots where mitigation efforts may be most effective. County-level estimates produced by the tool have revealed differences in transmission trends within states, highlighting the importance of real-time, locally-relevant information on COVID-19 trends. Other groups based in Massachusetts and internationally are leveraging the group’s work, allowing opportunities for further collaboration and data-sharing.
As vaccination rollout progresses and new COVID-19 variants emerge, the research team is continuing to modify their approach to better forecast the changing COVID-19 pandemic.