https://www.socictopen.socict.org/files/original/7eaa71d518433119a90b4b4693b32f2e.pdf 0368f0d9a2eae4b42227b7f3aad6c5fd Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Estimating the Serial Interval of the Novel Coronavirus Disease (COVID-19): A Statistical Analysis Using the Public Data in Hong Kong From January 16 to February 15, 2020 Creator An entity primarily responsible for making the resource Jinjun Ran, Yijun Lou, Daozhou Gao, Lin Yang, Weiming Wang, Daihai He, Zian Zhuang, Shi Zhao, Shi Zhao, Marc K. C. Chong, Marc K. C. Chong, Yongli Cai, Peihua Cao, Kai Wang, Maggie H. Wang, Maggie H. Wang Description An account of the resource Background: The emerging virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a large outbreak of novel coronavirus disease (COVID-19) since the end of 2019. As of February 15, there were 56 COVID-19 cases confirmed in Hong Kong since the first case with symptom onset on January 23, 2020.Methods: Based on the publicly available surveillance data in Hong Kong, we identified 21 transmission events as of February 15, 2020. An interval censored likelihood framework is adopted to fit three different distributions including Gamma, Weibull, and lognormal, that govern the serial interval (SI) of COVID-19. We selected the distribution according to the Akaike information criterion corrected for small sample size (AICc).Findings: We found the lognormal distribution performed slightly better than the other two distributions in terms of the AICc. Assuming a lognormal distribution model, we estimated the mean of SI at 4.9 days (95% CI: 3.6–6.2) and SD of SI at 4.4 days (95% CI: 2.9–8.3) by using the information of all 21 transmission events.Conclusion: The SI of COVID-19 may be shorter than the preliminary estimates in previous works. Given the likelihood that SI could be shorter than the incubation period, pre-symptomatic transmission may occur, and extra efforts on timely contact tracing and quarantine are crucially needed in combating the COVID-19 outbreak. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource Hong Kong, covid-19, contact-tracing, Statistical analysis, serial interval Identifier An unambiguous reference to the resource within a given context 10.3389/fphy.2020.00347 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Physics