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

Key PointsO_ST_ABSQuestionC_ST_ABSWhat is the transmissibility of COVID-19 asymptomatic and symptomatic cases, respectively? To date, they have not been well quantified in existing literature. FindingsThe transmissibility of asymptomatic and symptomatic COVID-19 increases with patient age. The asymptomatic cases had a 66.72% lower transmissibility rate than symptomatic cases. MeaningThe transmissibility of asymptomatic COVID-19 cases is not low. Asymptomatic cases are harder to detect compared to symptomatic cases. Consequently, the burden of asymptomatic transmission could potentially dominate the spreading in certain scenarios.

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

The outbreak of novel coronavirus disease (COVID-19) has spread around the world since it was detected in December 2019. 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 centres of COVID-19 in many regions. We made use of synthetic control methods to create a reference population matching specific characteristics of Shenzhen. With both the synthetic and observed data, we introduced an epidemic compartmental model to compare the spread of COVID-19 between Shenzhen and its counterpart regions in the United States that didnt implement interventions for policy evaluation. Once the effects of policy interventions adopted in Shenzhen were estimated, the delay effects of those interventions were referred to provide the further control degree of interventions. Thus, the hypothetical epidemic situations in Shenzhen were inferred by using time-varying reproduction numbers in the proposed SIHR (Susceptible, Infectious, Hospitalized, Removed) model and considering if the interventions were delayed by 0 day to 5 days. The expected cumulative confirmed cases would be 1546, which is 5.75 times of the observed cumulative confirmed cases of 269 in Shenzhen on February 3, 2020, based on the data from the counterpart counties (mainly from Broward, New York, Santa Clara, Pinellas, and Westchester) in the United States. If the interventions were delayed by 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% credible interval (303,1959). 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. AMS 2000 O_SCPLOWSUBJECTC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWCLASSIFICATIONSC_SCPLOW: Primary 00K00, 00K01; secondary 00K02.

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

The United States has the highest numbers of confirmed cases of COVID-19 in the world. The early hot spot states were New York, New Jersey, and Connecticut. The workforce in these states was required to work from home except for essential services. It was necessary to evaluate an appropriate date for resumption of business since the premature reopening of the economy would lead to a broader spread of COVID-19, while the opposite situation would cause greater loss of economy. To reflect the real-time risk of the spread of COVID-19, it was crucial to evaluate the population of infected individuals before or never being confirmed due to the pre-symptomatic and asymptomatic transmissions of COVID-19. To this end, we proposed an epidemic model and applied it to evaluate the real-time risk of epidemic for the states of New York, New Jersey, and Connecticut. We used California as the benchmark state because California began a phased reopening on May 8, 2020. The dates on which the estimated numbers of unidentified infectious individuals per 100,000 for states of New York, New Jersey, and Connecticut were close to those in California on May 8, 2020, were June 1, 22, and 22, 2020, respectively. By the practice in California, New York, New Jersey, and Connecticut might consider reopening their business. Meanwhile, according to our simulation models, to prevent resurgence of infections after reopening the economy, it would be crucial to maintain sufficient measures to limit the social distance after the resumption of businesses. This precaution turned out to be critical as the situation in California quickly deteriorated after our analysis was completed and its interventions after the reopening of business were not as effective as those in New York, New Jersey, and Connecticut.

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

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.