Grand Challenges: Towards an Early Warning System for Increased Probability of Community Infection by SARS-Cov-2 Variants

Summary:

This research will develop an early-warning (weeks to months) and long-term planning (climate change projections) system for the probability of infection by SARS-CoV-2. The system will use the relationship between climate and COVID-19 mortality that we established in May 2020. We were the first interdisciplinary team of virologists and climatologists to show an association between climate conditions and mortality displacement. In Year 1 we will revisit the empirical relationship that we established, using new information collected since Spring 2020. We will augment this relationship by using artificial intelligence approaches to include additional relevant atmospheric fields (wind, and solar radiation); the PI visited the European Center for Medium-range Weather Forecast (ECMWF) getting familiarized with AI methodologies applied to weather and climate forecasting. Based on this relationship, we will produce maps showing future sensitivity to COVID as derived from long term climate projections over Maryland. In Year 2, in collaboration with the private sector, we will be transmitting to the University of Maryland COVID-19 weekly and seasonal advisories and warnings focusing on DC, Maryland, and Virginia. In Year 3, we will investigate the possibility to replace the empirically derived relation between COVID-19 mortality and climate with physical principles-based modeling of the spread of droplets carrying SARS-CoV-2.

PI: Augustin Vintzileos (CMNS),
Assistant Research Scientist, ESSIC