Scoping review and meta-analysis of COVID-19 epidemiological parameters for modeling from early Asian studies

Retrospective epidemiological models are powerful tools to understand its transmission dynamics and to assess the efficacy of different control measures. This study summarises key epidemiological parameters of COVID-19 for retrospective mathematical and clinical modeling. A review of scientific papers and preprints published in English between 1 January and 15 April 2020 in PubMed, MedRxiv and BioRxiv was performed to obtain epidemiological parameters of the initial stage of COVID-19 pandemic in Asia. After excluding articles with unacceptable risks of bias and those that remained as preprints as of 15 November 2021, meta-analyses were performed to derive summary effect estimates from the data collected using the statistical software R. Out of 4,893 articles identified, 88 provided data for 22 parameters for the overall population and 7 specifically for children. Meta-analyses were conducted considering time period as a categorical moderator when it was statistically significant. The results obtained are essential for building more reliable models to help clinicians and policymakers improve their knowledge on COVID-19 and apply it in future decisions. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by the University of Alicante [grant number COVID-19 2020-41.30.6P.0016] and the Conselleria de Agricultura, Desarrollo Rural, Emergencia Climatica y Transicion Ecologica de Generalitat Valenciana, Ajuntament de Denia and University of Alicante through the Montgo-Denia-UA Research Station Agreement [grant number 20202-41.30.6O.00.01]. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All data produced in the present work are contained in the manuscript and the references cited in the text.