Department of Disease Control, Center for Disease Control and Prevention in Northern Theater Command, Shenyang, China.
China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, No. 119, South 4th Ring Road West, Fengtai District, Beijing, China.
Sci Rep. 2021 Mar 18;11(1):6251. doi: 10.1038/s41598-021-84893-4.
We established an individual-based computer model to simulate the occurrence, infection, discovery, quarantine, and quarantine release (recovery) of asymptomatic SARS-CoV-2 infected individuals or patients within the community. The model was used to explore the effects of control measures, such as active tracing, laboratory testing, active treatment, and home quarantine on the epidemic. Considering the condition that R = 1.2, when a case of an imported asymptomatic infected individual (AII) was reported in the community, the implementation of control measures reduced the number of AIIs and patients by 62.2% and 62.4%, respectively. The number of undetected AIIs and patients peaked at 302 days of the epidemic, reaching 53 and 20 individuals, respectively. The implementation of sustained active tracing, laboratory testing, active treatment, and home quarantine can significantly reduce the probability of disease outbreaks and block the spread of the COVID-19 epidemic caused by AIIs in the community.
我们建立了一个基于个体的计算机模型，以模拟社区中无症状 SARS-CoV-2 感染个体或患者的发生、感染、发现、隔离和隔离释放（康复）。该模型用于探索控制措施（如主动追踪、实验室检测、主动治疗和家庭隔离）对疫情的影响。考虑到 R = 1.2 的情况，当社区报告一例输入性无症状感染个体（AII）时，实施控制措施可分别减少 AII 和患者的数量 62.2%和 62.4%。未检出的 AII 和患者数量在疫情爆发的第 302 天达到峰值，分别为 53 人和 20 人。持续实施主动追踪、实验室检测、主动治疗和家庭隔离可以显著降低疫情爆发的概率，并阻断社区中由 AII 引起的 COVID-19 疫情的传播。
