Background A local coronavirus disease 2019 (COVID-19) case confirmed on June 11, 2020 triggered an outbreak in Beijing, China after 56 consecutive days without a newly confirmed case. Non-pharmaceutical interventions (NPIs) were used to contain the source in Xinfadi (XFD) market. To rapidly control the outbreak, both traditional and newly introduced NPIs including large-scale management of high-risk populations and expanded severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR-based screening in the general population were conducted in Beijing. We aimed to assess the effectiveness of the response to the COVID-19 outbreak in Beijing’s XFD market and inform future response efforts of resurgence across regions. Methods A modified susceptible–exposed–infectious–recovered (SEIR) model was developed and applied to evaluate a range of different scenarios from the public health perspective. Two outcomes were measured: magnitude of transmission (i.e., number of cases in the outbreak) and endpoint of transmission (i.e., date of containment). The outcomes of scenario evaluations were presented relative to the reality case (i.e., 368 cases in 34 days) with 95% Confidence Interval (CI). Results Our results indicated that a 3 to 14 day delay in the identification of XFD as the infection source and initiation of NPIs would have caused a 3 to 28-fold increase in total case number (31–77 day delay in containment). A failure to implement the quarantine scheme employed in the XFD outbreak for defined key population would have caused a fivefold greater number of cases (73 day delay in containment). Similarly, failure to implement the quarantine plan executed in the XFD outbreak for close contacts would have caused twofold greater transmission (44 day delay in containment). Finally, failure to implement expanded nucleic acid screening in the general population would have yielded 1.6-fold greater transmission and a 32 day delay to containment. Conclusions This study informs new evidence that in form the selection of NPI to use as countermeasures in response to a COVID-19 outbreak and optimal timing of their implementation. The evidence provided by this study should inform responses to future outbreaks of COVID-19 and future infectious disease outbreak preparedness efforts in China and elsewhere. Graphical abstract

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Awareness of epidemics can influence people’s behavior and further trigger changes in epidemic spreading. Previous studies concentrating on the coupled awareness-epidemic dynamics usually ignore the multi-type information and the heterogeneity of individuals. However, the real-world cases can be more complicated, and the interaction between information diffusion and epidemic spreading needs further study. In this article, we propose an individual-based epidemics and multi-type information spreading (IEMIS) model on two-layered multiplex networks considering positive and negative preventive information and two types of heterogeneity: 1) heterogeneity of aware individual’s state which leads to differences in aware transmission capacity and 2) heterogeneity of individual’s node degree which affects the epidemic infection rate. Based on Micro-Markov Chain approach (MMCA), we derive the theoretical epidemic threshold for the proposed model and validate the results by those obtained with Monto Carlo (MC) simulations. Through extensive simulations, we demonstrate that for epidemics with low infectivity, promoting the diffusion of positive preventive information, enhancing the importance ratio of neighbors who are aware of positive information, and increasing social distance among individuals can effectively suppress epidemic spreading. However, for highly infectious diseases, the influence of these factors becomes limited.