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B0852
Title: An indirect method to monitor the fraction of people ever infected with COVID-19: An application to the United States Authors:  Miguel Sanchez-Romero - Wittgensteincentre for Demography and Human Capital (Austria) [presenting]
Alexia Prskawetz - TU Wien (Austria)
Vanessa di Lego - Wittgensteincentre for Demography and Human Capital (Austria)
Bernardo Lanza Queiroz - CEDEPLAR - Universidade Federal de Minas Gerais (Brazil)
Abstract: The number of COVID19 infections is key for accurately monitoring the pandemics. However, due to differential testing policies, asymptomatic individuals and limited large-scale testing availability, it is challenging to detect all cases. Seroprevalence studies aim to address this gap by retrospectively assessing the number of infections, but they can be expensive and time-intensive. We propose a complementary approach that combines estimated (1) infection fatality rates (IFR) using a Bayesian melding SEIR model with (2) reported case-fatality rates (CFR) to estimate the fraction of people ever infected and detected indirectly. We apply the technique to the U.S due to their remarkable regional diversity and because they count with almost a quarter of all global confirmed cases and deaths. We obtain that the IFR varies from 1.25\% (0.39-2.16\%, 90\% CI) in Florida, the most aged population, to 0.69\% in Utah (0.21-1.30\%, 90\% CI), the youngest population. By September 8, 2020, we estimate that at least five states have already a fraction of people ever infected between 10 and 20 \%. The state with the highest estimated fraction of people ever infected is New Jersey, with 17.3\% (10.0, 55.8, 90\% CI). The results also indicate that with a probability of 90\% the fraction of detected people among the ever infected since the beginning of the epidemic has been less than 50\% in 15 out of the 20 states analyzed.