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Abstract
Assessing the infection fatality rate (IFR) of SARS-CoV-2 is one of the most controversial issues during the pandemic. Due to asymptomatic or mild courses of COVID-19, many infections remain undetected. Reported case fatality rates - COVID-19-associated deaths divided by number of detected infections - are therefore poor estimates of the IFR. Endogenous changes of the population at risk of a SARS-CoV-2 infection, changing test practices and an improved understanding of the pathogenesis of COVID-19 further exacerbate the estimation of the IFR. Here, we propose a strategy to estimate the IFR of SARS-CoV-2 in Germany that combines official data on reported cases and fatalities supplied by the Robert Koch Institute (RKI) with data from seroepidemiological studies in two infection hotspots, the Austrian town Ischgl and the German municipality Gangelt, respectively. For this purpose, we use the law of total probability to derive an approximate formula for the IFR that is based on a set of assumptions regarding data quality and test specificity and sensitivity. The resulting estimate of the IFR in Germany of 0.83% (95% CI: [0.69%; 0.98%]) that is based on a combination of the RKI and Ischgl data is notably higher than the IFR estimate reported in the Gangelt study (0.36% [0.29%; 0.45%]). It is closer to the consolidated estimate based on a meta-analysis (0.68% [0.53%; 0.82%]), where the difference can be explained by Germany's disadvantageous age structure. As a result of virus mutations, vaccination strategies, and improved therapy, a re-estimation of the IFR will eventually be mandated; the proposed method is able to account for such developments.
Highlights
Estimating the infection fatality rate (IFR) of SARS-CoV-2 as it applies to the population of a country by using official data on detected infections and case fatalities is hampered for two main reasons
A robustness check varies the end date from April 1 to June 1. This time period is selected for the following considerations: First, it implies that the estimation of the case fatality rate (CFR) can be based on a sufficient number of cases (161,880 PCR-positive individuals by May 1, 2020) and fatalities (8,059 COVID-19-associated deaths by May 1, 2020)
In Germany, comprehensive data on detected SARS-CoV-2 infections and COVID-19-associated fatalities are publicly reported by the Robert Koch Institute (RKI)
Summary
Estimating the infection fatality rate (IFR) of SARS-CoV-2 as it applies to the population of a country (here: Germany) by using official data on detected infections and case fatalities (here: data provided by the Robert Koch Institute, RKI) is hampered for two main reasons. Younger individuals without pre-existing conditions who become infected are often asymptomatic or show mild courses of COVID-19.6,7 For this subpopulation, a much smaller or even negligible IFR applies, and they will be initially underrepresented in the subpopulation of those who tested positive for a SARS-CoV-2 infection. As the pandemic evolves, members of high-risk subpopulations (elderly and individuals with pre-existing conditions) will try to protect themselves from a SARS-CoV-2 infection, either by voluntary self-isolation and social distancing or receiving vaccination. They will benefit from lockdown measures, and may be offered special protection (e.g., in nursery homes).[9]. As members of the high-risk subpopulations effectively avoid a SARS-CoV-2 infection, the composition of the infected subpopulation and that of the reported cases change, too
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