Dr. Charles Macal shares how his work has helped predict the spread of COVID, and how modeling is an important tool for stopping future pandemics. COVID-19 has been dominating our lives and the news for more than a year now. Behind those news stories were scientists from a wide variety of fields working together to understand the virus, how it spread, and how best to beat it.
As the COVID-19 pandemic unfolded, the modeling community mounted an impressive response to support decision makers with forecasts of how the disease could progress. Forecasts at the national and state levels have been common, and in some instances, county-level predictions have been developed. Few have accounted for the dynamic nature of transmission at the city level, considering the locations and nature of interactions and behaviors that directly impact the contacts that individuals have in passing on the COVID infection.
Argonne National Laboratory has developed CityCOVID, a very detailed agent-based model of the spread of COVID-19 in the Chicago area. Argonne is providing public health officials at the city, county and state levels model results and forecasts of new cases and hospitalizations, which are key concerns of decision makers. Forecasts reflect varying assumptions about individual behavior and government guidance on shutdown and reopening. Forecasts also reflect uncertainties in the data, people’s behavior, and in key aspects of the SARS-CoV-2 virus and how it spreads. Argonne has addressed the school reopening question, the effects of holiday gatherings on COVID-19 spread, and many other questions posed by decision makers. CityCOVID provides results of highly granular spatial and temporal detail, which is enabled by Argonne’s supercomputing and artificial intelligence (AI) resources and extensive experience in the modeling of infectious diseases.
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