Author: Gallo, Luciana Guerra; Oliveira, Ana Flávia de Morais; Abrahão, Amanda Amaral; Sandoval, Leticia Assad Maia; Martins, Yure Rodrigues Araújo; Almirón, Maria; dos Santos, Fabiana Sherine Ganem; Araújo, Wildo Navegantes; de Oliveira, Maria Regina Fernandes; Peixoto, Henry Maia
Title: Ten Epidemiological Parameters of COVID-19: Use of Rapid Literature Review to Inform Predictive Models During the Pandemic Cord-id: vktx1e0a Document date: 2020_12_1
ID: vktx1e0a
Snippet: Objective: To describe the methods used in a rapid review of the literature and to present the main epidemiological parameters that describe the transmission of SARS-Cov-2 and the illness caused by this virus, coronavirus disease 2019 (COVID-19). Methods: This is a methodological protocol that enabled a rapid review of COVID-19 epidemiological parameters. Findings: The protocol consisted of the following steps: definition of scope; eligibility criteria; information sources; search strategies; se
Document: Objective: To describe the methods used in a rapid review of the literature and to present the main epidemiological parameters that describe the transmission of SARS-Cov-2 and the illness caused by this virus, coronavirus disease 2019 (COVID-19). Methods: This is a methodological protocol that enabled a rapid review of COVID-19 epidemiological parameters. Findings: The protocol consisted of the following steps: definition of scope; eligibility criteria; information sources; search strategies; selection of studies; and data extraction. Four reviewers and three supervisors conducted this review in 40 days. Of the 1,266 studies found, 65 were included, mostly observational and descriptive in content, indicating relative homogeneity as to the quality of the evidence. The variation in the basic reproduction number, between 0.48 and 14.8; and the median of the hospitalization period, between 7.5 and 20.5 days stand out as key findings. Conclusion: We identified and synthesized 10 epidemiological parameters that may support predictive models and other rapid reviews to inform modeling of this and other future public health emergencies.
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