ABSTRACT
Prior to the emergence of the Omicron variant, many cities in China had been able to maintain a "Zero-COVID" policy. They were able to achieve this without blanket city-wide lockdown and through widespread testing and an extensive set of nonpharmaceutical interventions (NPIs), such as mask wearing, contact tracing, and social distancing. We wanted to examine the effectiveness of such a policy in containing SARS-CoV-2 in the early stage of the pandemic. Therefore, we developed a fully stochastic, spatially structured, agent-based model of SARS-CoV-2 ancestral strain and reconstructed the Beijing Xinfadi outbreak through computational simulations. We found that screening for symptoms and among high-risk populations served as methods to discover cryptic community transmission in the early stage of the outbreak. Effective contact tracing could greatly reduce transmission. Targeted community lockdown and temporal mobility restriction could slow down the spatial spread of the virus, with much less of the population being affected. Population-wide mass testing could further improve the speed at which the outbreak is contained. Our analysis suggests that the containment of SARS-CoV-2 ancestral strains was certainly possible. Outbreak suppression and containment at the beginning of the pandemic, before the virus had the opportunity to undergo extensive adaptive evolution with increasing fitness in the human population, could be much more cost-effective in averting the overall pandemic disease burden and socioeconomic cost.
ABSTRACT
BackgroundSeveral parameters driving the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain unclear, including age-specific differences in infectivity and susceptibility, and the contribution of inapparent infections to transmission. Robust estimates of key time-to-event distributions remain scarce as well. MethodsWe collected individual records for 1,178 SARS-CoV-2 infected individuals and their 15,648 contacts identified by contact tracing and monitoring over the period from January 13 to April 02, 2020 in Hunan Province, China. We provide descriptive statistics of the characteristics of cases and their close contacts; we fitted distributions to time-to-key-events distributions and infectiousness profile over time; and we used generalized linear mixed model to estimate risk factors for susceptibility and transmissibility of SARS-CoV-2. ResultsWe estimated the mean serial interval at 5.5 days (95%CI -5.0, 19.9) and the mean generation time at 5.5 days (95%CI 1.7, 11.6). The infectiousness was estimated to peak 1.8 days before symptom onset, with 95% of transmission events occurring between 7.6 days before and 7.3 days after the date of symptom onset. The proportion of pre-symptomatic transmission was estimated to be 62.5%. We estimated that at least 3.5% of cases were generated asymptomatic individuals. SARS-CoV-2 transmissibility was not significantly different between working-age adults (15-59 years old) and other age groups (0-14 years old: p-value=0.16; 60 years and over: p-value=0.33), whilst susceptibility to SARS-CoV-2 infection was estimated to increase with age (p-value=0.03). In addition, transmission risk was higher for household contacts (p-value<0.001), decreased for higher generations within a cluster (second generation: odds ratio=0.13, p-value<0.001; generations 3-4: odds ratio=0.05, p-value<0.001, relative to generation 1), and decreased for infectors with a larger number of contacts (p-value=0.04). InterpretationOur findings warn of the possible relevant contribution of children to SARS-CoV-2 transmission. When lockdown interventions are in place, we found that odds of transmission are highest in the household setting but, with the relaxation of interventions, other settings (including schools) could bear a higher risk of transmission. Moreover, the estimated relevant fraction of pre-symptomatic and asymptomatic transmission highlight the importance of large-scale testing, contact tracing activities, and the use of personnel protective equipment during the COVID-19 pandemic.