Abstract and scope of work: Although the majority of COVID-19 cases to date have now occurred in low- and middle-income countries, there are few primary accounts of the epidemiological dynamics and clinical severity of infection in such settings. This circumstance presents an untenable blind spot as policymakers seek to plan… Continue Reading Transmission and severity of SARS-CoV-2 in India
Four months into the pandemic, it has become clear that trends in case counts can be misleading as a metric of transmission because they depend to a great extent on testing policies. Thus, it remains challenging to accurately measure transmission rates over time, determine what proportion of the population remains… Continue Reading Sero-epidemiological modeling for COVID-19 control
When a vaccine for COVID-19 becomes available, it will undoubtedly be in short supply globally, nationally, and locally, raising the question of how that limited vaccine should be prioritized to subpopulations to minimize future cases or deaths. However, this will be complicated by numerous factors, including the heterogeneity of contact… Continue Reading Model-informed vaccine prioritization strategies
COVID-19 will be circulating in the United States for many months to come. However, many states are still relying on biased data and/or downstream indicators to inform their reopening or mitigation decisions. Modelers have not quantified the public health impact of investment in surveillance leading to improved model forecasts and… Continue Reading Design of cost-effective COVID-19 surveillance
COVID-19 was discovered in Wuhan, China in Dec. 2019 and has caused over 13M confirmed infections and 573K deaths world-wide. Government officials at the state and federal level have asked for forecasts to support public health decisions and mitigate the impact of COVID-19. Computational models excel when structured datasets are… Continue Reading Aggregating computational models and human judgment for more accurate forecasts of the US COVID-19 outbreak