Using Secondary Cases to Characterize the Severity of an Emerging or Re-Emerging Infection
نویسندگان
چکیده
Background: The methods to ascertain cases of an emerging infectious disease are typically biased toward with more severe disease, which can affect estimates the average infection-severity profile. We examine potential for using data from secondary cases, identified through transmission studies or contact tracing index characterize severity. Methods: extracted information on reported symptoms, severity and fatality risk among previous reviews pandemic influenza A(H1N1)pdm09, Middle East Respiratory Syndrome (MERS) Coronavirus Disease 2019 (COVID-19). compared profiles between inferred ascertainment bias in confirmed cases.Findings. Overall, had illness than each disease. For COVID-19 proportions fever cough were 1.3-fold 1.6-fold higher cases. COVID-19, proportion asymptomatic infection, severe/critical death 54% lower, 39% 82% respectively. MERS, was 73% China, we estimated that 68% (95% Credible interval (CrI): 43%, 85%) 56% CrI: 42%, 68%) missed due bias, Guangzhou Wuhan, respectively. Interpretation: Information should be less susceptible could inform cases. Funding: This project supported by Health Medical Research Fund, Food and Health Bureau, Government Hong Kong Special Administrative Region (grant no. COVID190118) Collaborative Fund (Project No. C7123-20G) Grants Council SAR Government.BJC is AIR@innoHK program Innovation Technology Commission Government. Declaration Interest: BJC reports honoraria Sanofi Pasteur, GSK, Moderna Roche. The authors report no other conflicts interest.
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ژورنال
عنوان ژورنال: Social Science Research Network
سال: 2021
ISSN: ['1556-5068']
DOI: https://doi.org/10.2139/ssrn.3854641