Using secondary cases to characterize the severity of an emerging or re-emerging infection

Author:

Tsang Tim K.ORCID,Wang Can,Yang Bingyi,Cauchemez SimonORCID,Cowling Benjamin J.ORCID

Abstract

AbstractThe methods to ascertain cases of an emerging infectious disease are typically biased toward cases with more severe disease, which can bias the average infection-severity profile. Here, we conducted a systematic review to extract information on disease severity among index cases and secondary cases identified by contact tracing of index cases for COVID-19. We identified 38 studies to extract information on measures of clinical severity. The proportion of index cases with fever was 43% higher than for secondary cases. The proportion of symptomatic, hospitalized, and fatal illnesses among index cases were 12%, 126%, and 179% higher than for secondary cases, respectively. We developed a statistical model to utilize the severity difference, and estimate 55% of index cases were missed in Wuhan, China. Information on disease severity in secondary cases should be less susceptible to ascertainment bias and could inform estimates of disease severity and the proportion of missed index cases.

Funder

Food and Health Bureau of the Government of the Hong Kong Special Administrative Region | Health and Medical Research Fund

Research Grants Council, University Grants Committee

Publisher

Springer Science and Business Media LLC

Subject

General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry

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