Mapping the Burden of COVID-19 in the United States

Ian F Miller; Alexander D Becker; Bryan T Grenfell; C. Jessica E Metcalf

This model is aimed specifically at projecting the age distribution of cases over a wide variety of transmission scenarios, and not at producing epidemiological forecasts. As such, we do not vary the components of our model linked to interventions, (e.g. contact rates) over time or by location We chose to investigate a scenario in which 20% of the population in each county becomes infected. A 20% cumulative infection rate represents a pessimistic scenario for the short term (i.e., the next several months) but perhaps an optimistic scenario in the long term 14 . We intentionally ignore spatial variation in the progression of the epidemic in order to simplify comparisons of disease burden between regions. As our aim is to provide general estimates about relative distribution of disease burden rather than to make precise predictions of case load over time, we sought to identify patterns of disease burden that are robust to different assumptions about the . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity. transmission is relatively slow, contact patterns exhibit a strong age structure, and clinically presenting individuals are effectively quarantined. In contrast, the 'pessimistic scenario' (R0 = 6, Θ = 0, bC = 1) is characterized by high transmission, well-mixed contact patterns, and ineffective quarantine.