ABSTRACT
Some asymptomatic individuals carrying SARS-CoV-2 can transmit the virus and contribute to outbreaks of COVID-19. Here, we use detailed surveillance data gathered during COVID-19 resurgences in six cities of China at the beginning of 2021 to investigate the relationship between asymptomatic proportion and age. Epidemiological data obtained before mass vaccination provide valuable insights into the nature of pathogenicity of SARS-CoV-2. The data were collected by multiple rounds of city-wide PCR testing with contact tracing, where each patient was monitored for symptoms through the whole course of infection. The clinical endpoint (asymptomatic or symptomatic) for each patient was recorded (the pre-symptomatic patients were classified as symptomatic). We find that the proportion of infections that are asymptomatic declines with age (coefficient = -0.006, 95% CI: -0.008 to -0.003, p < 0.01), falling from 42% (95% CI: 6-78%) in age group 0-9 years to 11% (95% CI: 0-25%) in age group greater than 60 years. Using an age-stratified compartment model, we show that this age-dependent asymptomatic pattern, together with the distribution of cases by age, can explain most of the reported variation in asymptomatic proportions among cities. Our analysis suggests that SARS-CoV-2 surveillance strategies should take account of the variation in asymptomatic proportion with age.
ABSTRACT
The SARS-CoV-2 Omicron variant is rampant in Europe and the United States, and the Delta variant has caused several small-scale outbreaks in China. It is particularly important to simulate the transmission risk of novel coronavirus pneumonia (COVID-19) during large-scale events, so as to ensure a good preparation of personnel, materials, isolation sites and other support work in advance. Taking the Beijing 2022 Winter Olympic Games as an example, this study introduces the use of mathematical models to simulate the entry risks, closed-loop risks and prevention and control measures of athletes, officials and other stakeholders of the Olympic Games. In the simulation results on January 19, 2022, the estimated number of Olympic Games-related infections who were identified at borders was 357 (95%CI: 153-568) and the observed number was 323. The estimated number of "seed" cases that entered the closed-loop of Olympics Games was 195 (95%CI: 43-335), and the observed number of cases in the closed-loop was 212. This study demonstrates the important role of mathematical models of infectious diseases in the pragmatic application of preventive medicine and public health.
Subject(s)
COVID-19 , Communicable Diseases , Anniversaries and Special Events , Humans , Mass Gatherings , Models, Theoretical , SARS-CoV-2 , United StatesABSTRACT
The outbreak of pneumonia caused by the novel coronavirus 2019-nCoV in Wuhan, Hubei province of China, at the end of 2019 shaped tremendous challenges to China's public health and clinical treatment. The virus belongs to the ß genus Coronavirus in the family Corornaviridae, and is closely related to SARS-CoV and MERS-CoV, causing severe symptoms of pneumonia. The virus is transmitted through droplets, close contact, and other means, and patients in the incubation period could potentially transmit the virus to other persons. According to current observations, 2019-nCoV is weaker than SARS in pathogenesis, but has stronger transmission competence; it's mechanism of cross-species spread might be related with angiotensin-converting enzyme â ¡ (ACE2), which is consistent with the receptor SARS-CoV. After the outbreak of this disease, Chinese scientists invested a lot of energy to carry out research by developing rapid diagnostic reagents, identifying the characters of the pathogen, screening out clinical drugs that may inhibit the virus, and are rapidly developing vaccines. The emergence of 2019-nCoV reminds us once again of the importance of establishing a systematic coronavirus surveillance network. It also poses new challenges to prevention and control of the emerging epidemic and rapidly responses on scientific research.