The Infection Fatality Rate (IFR) of COVID-19 is difficult to estimate because the number of infections is unknown and there is a lag between each infection and the potentially subsequent death. We introduce a new approach for estimating the IFR by first estimating the entire sequence of daily infections. Unlike prior approaches, we incorporate existing data on the number of daily COVID-19 tests into our estimation; knowing the test rates helps us estimate the ratio between the number of cases and the number of infections. Also unlike prior approaches, rather than determining a constant lag from studying a group of patients, we treat the lag as a random variable, whose parameters we determine empirically by fitting our infections sequence to the sequence of deaths. Our approach allows us to narrow our estimation to smaller time intervals in order to observe how the IFR changes over time. We analyze a 250 day period starting on March 1, 2020. We estimate that the IFR in the U.S. decreases from a high of $0.68\%$ down to $0.24\%$ over the course of this time period. We also provide IFR and lag estimates for Italy, Denmark, and the Netherlands, all of which also exhibit decreasing IFRs but to different degrees.

翻译：COVID-19的传染性死亡率(IFR)很难估算,因为感染人数不详,而且每种感染和可能随后的死亡之间存在差距。我们采用了一种新的方法,通过首先估计每日感染的全序来估计IFR。与以前的方法不同,我们把关于每日COVID-19测试数量的现有数据纳入我们的估计;我们了解测试率帮助我们估计病例数量与感染数量的比率。同样,与以前的方法不同,我们不确定从研究一组病人的一贯滞后期,而是将滞后期作为一个随机变量处理,我们通过将感染顺序与死亡顺序相匹配,从经验上确定其参数。我们的方法使我们能够缩短估计IFR的估计数,以便观察IFR随时间变化的情况。我们从2020年3月1日起分析250天的时间段。我们估计,美国境内的IFR从高0.68 美元下降到0.24 美元。我们还提供了意大利、丹麦和荷兰的IFR和滞后期估计数,所有这些都显示IFRs下降,但程度不同。