Transmission roles of symptomatic and asymptomatic COVID-19 cases: a modeling study (preprint)

ObjectiveAge-dependent asymptomatic and symptomatic transmission dynamics of COVID-19 have not been well quantified due to limited data. MethodsThrough a population-based surveillance network, we collected data on 1342 confirmed cases with a 90-days follow-up for all asymptomatic cases. ResultsThe difference in transmissibility of a symptomatic and asymptomatic case depended on age and was most distinct for the middle-age groups. The asymptomatic cases had a 66.72% lower transmissibility rate than symptomatic cases, and 74.10% (95%CI: 65.85% - 80.72%) of all asymptomatic cases were missed in detection. The average proportion of asymptomatic cases was 28.22% (95%CI: 22.97% - 34.56%). Simulation showed that the burden of asymptomatic transmission increased as the epidemic continued and could potentially dominate the spreading. ConclusionAsymptomatic COVID-19 cases play a significant role in transmission. Vaccine Strategies prioritizing the population between 30-60 years old are likely to have the most population-level benefits.

The timing and effectiveness of implementing mild interventions of COVID-19 in large industrial cities (preprint)

Background The outbreak of novel coronavirus disease (COVID-19) has spread around the world since it was detected in December 2019. As the starting place of COVID-19 pandemic, the Chinese government executed a series of interventions to curb the pandemic. The "battle" against COVID-19 in Shenzhen, China is valuable because populated industrial cities are the epic centers of COVID-19 in many regions. Methods We used synthetic control methods to compare the spread of COVID-19 between Shenzhen and its counterpart regions that didn't implement interventions for the total duration of 16 days starting from the day of the first reported case in compared locations. The hypothetical epidemic situations in Shenzhen were inferred by using time-varying reproduction numbers, assuming the interventions were delayed by 0 day to 5 days. Results The expected cumulative confirmed cases would be 1307, is which 4.86 times of 269 observed cumulative confirmed cases in Shenzhen on February 3, 2020, based on the data from the counterpart counties (mainly from Broward, New York, Santa Clara, Westchester and Orange) in the United States. If the interventions were delayed 5 days from the day when the interventions started, the expected cumulative confirmed cases of COVID-19 in Shenzhen on February 3, 2020 would be 676 with 95% CI (303,1959). Conclusions Early implementation of mild interventions can subdue the epidemic of COVID-19. The later the interventions were implemented, the more severe the epidemic was in the hard-hit areas. Mild interventions are less damaging to the society but can be effective when implemented early.

Data-driven analysis on the simulations of the spread of COVID-19 under different interventions of China (preprint)

Since February 2020, COVID-19 has spread rapidly to more than 200 countries in the world. During the pandemic, local governments in China have implemented different interventions to efficiently control the spread of the epidemic. Characterizing transmission of COVID-19 under some typical interventions is essential to help countries develop appropriate interventions. Based on the pre-symptomatic transmission patterns of COVID-19, we established a novel compartmental model: Baysian SIHR model with latent Markov structure, which treated the numbers of infected and infectious individuals without isolation to be the latent variables and allowed the effective reproduction number to change over time, thus the effects of policies could be reasonably estimated. By using the epidemic data of Wuhan, Wenzhou and Shenzhen, we migrated the corresponding estimated policy modes to South Korea, Italy, and the United States and simulated the potential outcomes for these countries when they adopted similar policy strategies of three cities in China. We found that the mild interventions implemented in Shenzhen were effective to control the epidemic in the early stage, while more stringent policies which were issued in Wuhan and Wenzhou were necessary if the epidemic was more severe and needed to be controlled in a short time.

Evaluate the timing of resumption of business for the states of New York, New Jersey and California via a pre-symptomatic and asymptomatic transmission model of COVID-19 (preprint)

Background The United States has the highest numbers of confirmed cases of COVID-19, where they took up nearly half in the hot spot states of New York, New Jersey, Connecticut, and California. The workforce in these states was required to work from home except for essential services. It is necessary to evaluate an appropriate date for resumption of business since premature reopening of economy will lead to broader spread of COVID-19, while the opposite situation would cause greater loss of economy. Methods To consider pre-symptomatic and asymptomatic transmission of COIVD-19, it is crucial to evaluate the unobserved numbers of unidentified infectious individuals but not the observed number of confirmed cases, which reflect the real-time risks of different stage of infectious disease. We proposed an epidemic model in considering the pre-symptomatic transmission and asymptomatic transmission of COVID-19 to evaluate the real-time risk of epidemic for the states of New York, New Jersey and Connecticut, and compared with California state (where it effectively phased reopened on May 8) for assessments of the appropriate Monday for resumption of business. Results The predicted numbers of unidentified infectious individuals per 100,000 for states of New York, New Jersey and Connecticut which are close to those in California state are 12.23 with 95% CI (10.68, 13.57) on June 1, 25.65 with 95% CI (20.04, 30.43) on June 15, 28.49 with 95% CI (19.10, 38.65) on June 22, respectively, which may cause 11.23%, 15.64% and 17.32% higher than the estimated number of cumulative confirmed cases on July 11, if the second wave of the infection would happen after people return to work. Conclusions It may be feasible for states of New York, New Jersey and Connecticut to reopen business on June 1 (or even May 18), June 15 and June 22. For the period after resumption of work, if the number of unidentified infectious individuals is still non-zero, the risks for the second wave of the infection would never vanish.