https://socictopen.socict.org/files/original/2f4ccefe125a36392e5fa1d636bccb55.pdf 7301c94780770dd42d83e264fe79aeb1 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 Nonpharmaceutical interventions contribute to the control of COVID-19 in China based on a pairwise model. Creator An entity primarily responsible for making the resource Xiao-Feng Luo, Shanshan Feng, Meiping Yao, Huaiping Zhu, Michael Y. Li, Hao Wang, Junyuan Yang, Xiao-Long Peng, Xiaochun Cao, Juping Zhang, Zhen Jin Description An account of the resource Nonpharmaceutical interventions (NPIs), particularly contact tracing isolation and household quarantine, play a vital role in effectively bringing the Coronavirus Disease 2019 (COVID-19) under control in China. The pairwise model, has an inherent advantage in characterizing those two NPIs than the classical well-mixed models. Therefore, in this paper, we devised a pairwise epidemic model with NPIs to analyze COVID-19 outbreak in China by using confirmed cases during February 3rd-22nd, 2020. By explicitly incorporating contact tracing isolation and family clusters caused by household quarantine, our model provided a good fit to the trajectory of COVID-19 infections. We calculated the reproduction number R = 1.345 (95% CI: 1.230 - 1.460) for Hubei province and R = 1.217 (95% CI: 1.207 - 1.227) for China (except Hubei). We also estimated the peak time of infections, the epidemic duration and the final size, which are basically consistent with real observation. We indicated by simulation that the traced high-risk contacts from incubated to susceptible decrease under NPIs, regardless of infected cases. The sensitivity analysis showed that reducing the exposure of the susceptible and increasing the clustering coefficient bolster COVID-19 control. With the enforcement of household quarantine, the reproduction number R and the epidemic prevalence declined effectively. Furthermore, we obtained the resumption time of work and production in China (except Hubei) on 10th March and in Hubei at the end of April 2020, respectively, which is broadly in line with the actual time. Our results may provide some potential lessons from China on the control of COVID-19 for other parts of the world. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource covid-19, Clustering coefficient, household quarantine, Pairwise epidemic model, High-risk contacts Identifier An unambiguous reference to the resource within a given context 10.1016/j.idm.2021.04.001 Source A related resource from which the described resource is derived Infectious Disease Modelling