A framework for counterfactual analysis, strategy evaluation, and control of epidemics using reproduction number estimates
Fig 5
A) Daily confirmed positive cases from hypothetical spreading scenario at UIUC during Fall 2020. The solid dark blue line represents the hypothetical spreading scenario without employing any testing-for-isolation strategies. The solid red line represents the simulated spreading process under UIUC’s testing-for-isolation strategy. The hypothetical spreading scenario captures the worst-case scenario where every individual on campus does not take actions against the pandemic. B) Reverse engineered effective reproduction number at UIUC. The dashed dark blue line illustrates the reverse engineered effective reproduction number of the hypothetical spreading scenario without the implementation of testing-for-isolation strategies. The dashed red line represents the estimated effective reproduction number obtained from the data at UIUC featuring the implemented testing-for-isolation strategy. C) Daily confirmed positive cases from hypothetical spreading scenario at Purdue during Fall 2020 and Spring 2021. Compared to the hypothetical spreading scenario at UIUC, the simulated outbreak at Purdue is less severe since, by assumption, all symptomatic cases are caught and isolated through the voluntary testing-for-isolation strategy. D) Reverse engineered effective reproduction number at Purdue. During the first two months of the Fall 2020 semester, the effective reproduction number of the hypothetical spreading scenario without isolation under surveillance testing consistently exceeds the estimated effective reproduction number obtained from the real spreading data on campus. After October 2020, the reduction in the susceptible population leads to the effective reproduction number of the hypothetical spreading scenario becoming smaller than the estimated effective reproduction number of the COVID-19 data from Purdue.