Potential Biases in Estimating Absolute and Relative Case-Fatality Risks during Outbreaks

Abstract

Estimating the case-fatality risk (CFR)—the probability that a person dies from an infection given that they are a case—is a high priority in epidemiologic investigation of newly emerging infectious diseases and sometimes in new outbreaks of known infectious diseases. The data available to estimate the overall CFR are often gathered for other purposes (e.g., surveillance) in challenging circumstances. We describe two forms of bias that may affect the estimation of the overall CFR—preferential ascertainment of severe cases and bias from reporting delays—and review solutions that have been proposed and implemented in past epidemics. Also of interest is the estimation of the causal impact of specific interventions (e.g., hospitalization, or hospitalization at a particular hospital) on survival, which can be estimated as a relative CFR for two or more groups. When observational data are used for this purpose, three more sources of bias may arise: confounding, survivorship bias, and selection due to preferential inclusion in surveillance datasets of those who are hospitalized and/or die. We illustrate these biases and caution against causal interpretation of differential CFR among those receiving different interventions in observational datasets. Again, we discuss ways to reduce these biases, particularly by estimating outcomes in smaller but more systematically defined cohorts ascertained before the onset of symptoms, such as those identified by forward contact tracing. Finally, we discuss the circumstances in which these biases may affect non-causal interpretation of risk factors for death among cases.

Novel Coronavirus Outbreak in Wuhan, China, 2020: Intense Surveillance Is Vital for Preventing Sustained Transmission in New Locations

“…The infectious agent driving the ongoing pneumonia outbreak (the 2019-nCoV) appears to have transitioned from animals into humans, with the Huanan seafood wholesale market in Wuhan, China, representing the most likely source [1][2][3][4][5]. Since then, cases have been recorded in other countries, and initial estimates suggest a hospital fatality risk of around 14% [6], although estimates of disease severity early in an outbreak are often imprecise [7][8][9]. Even countries without confirmed cases have been on high alert.…”

Estimation of SARS-CoV-2 mortality during the early stages of an epidemic: a modeling study in Hubei, China, and six regions in Europe

“…Other reported measures such as the confirmed, symptomatic or hospitalized CFR, based on different denominators, are sometimes used, adding confusion. The crude CFR can be misleading if used to assess the overall mortality because of two opposing biases [9,10]. First, because of the delay of several weeks between disease onset and death, the number of confirmed and reported Covid-19 deaths at a certain time point does not consider the total number of deaths that will occur among already infected individuals (right-censoring).…”

Letalidad de la COVID-19: ausencia de patrón epidemiológico

“…Este estudio se ha desarrollado cuando todavía se está en la fase inicial de la epidemia en muchos países, y además, el número de países incluidos es limitado, lo cual puede haber afectado a los resultados. Por otra parte, el uso de criterios epidemiológicos y el análisis de datos poblacionales pueden ayudar a comprender las nuevas epidemias, incluso considerando los posibles sesgos y las limitaciones de estos estudios 14 .…”