Asymptomatic SARS-CoV-2 Infections Among Persons Entering China From April 16 to October 12, 2020.
TL;DR: In this paper, a population epidemiology study characterizes trends in the prevalence of asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among international entrants testing positive for SARS at Chinese border checkpoints between mid-April and mid-October 2020.
Abstract: This population epidemiology study characterizes trends in the prevalence of asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among international entrants testing positive for SARS-CoV-2 at Chinese border checkpoints between mid-April and mid-October 2020.
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TL;DR: In this paper, the authors search PubMed, Embase, Web of Science, and World Health Organization Global Research Database on COVID-19 between January 1, 2020 and April 2, 2021 to identify studies that reported silent infections at the time of testing.
Abstract: Quantification of asymptomatic infections is fundamental for effective public health responses to the COVID-19 pandemic. Discrepancies regarding the extent of asymptomaticity have arisen from inconsistent terminology as well as conflation of index and secondary cases which biases toward lower asymptomaticity. We searched PubMed, Embase, Web of Science, and World Health Organization Global Research Database on COVID-19 between January 1, 2020 and April 2, 2021 to identify studies that reported silent infections at the time of testing, whether presymptomatic or asymptomatic. Index cases were removed to minimize representational bias that would result in overestimation of symptomaticity. By analyzing over 350 studies, we estimate that the percentage of infections that never developed clinical symptoms, and thus were truly asymptomatic, was 35.1% (95% CI: 30.7 to 39.9%). At the time of testing, 42.8% (95% prediction interval: 5.2 to 91.1%) of cases exhibited no symptoms, a group comprising both asymptomatic and presymptomatic infections. Asymptomaticity was significantly lower among the elderly, at 19.7% (95% CI: 12.7 to 29.4%) compared with children at 46.7% (95% CI: 32.0 to 62.0%). We also found that cases with comorbidities had significantly lower asymptomaticity compared to cases with no underlying medical conditions. Without proactive policies to detect asymptomatic infections, such as rapid contact tracing, prolonged efforts for pandemic control may be needed even in the presence of vaccination.
269 citations
TL;DR: Based on studies published up to July 2021, most SARS-CoV-2 infections were not persistently asymptomatic, and asymPTomatic infections were less infectious than symptomatic infections.
Abstract: Background Debate about the level of asymptomatic Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection continues. The amount of evidence is increasing and study designs have changed over time. We updated a living systematic review to address 3 questions: (1) Among people who become infected with SARS-CoV-2, what proportion does not experience symptoms at all during their infection? (2) What is the infectiousness of asymptomatic and presymptomatic, compared with symptomatic, SARS-CoV-2 infection? (3) What proportion of SARS-CoV-2 transmission in a population is accounted for by people who are asymptomatic or presymptomatic? Methods and findings The protocol was first published on 1 April 2020 and last updated on 18 June 2021. We searched PubMed, Embase, bioRxiv, and medRxiv, aggregated in a database of SARS-CoV-2 literature, most recently on 6 July 2021. Studies of people with PCR-diagnosed SARS-CoV-2, which documented symptom status at the beginning and end of follow-up, or mathematical modelling studies were included. Studies restricted to people already diagnosed, of single individuals or families, or without sufficient follow-up were excluded. One reviewer extracted data and a second verified the extraction, with disagreement resolved by discussion or a third reviewer. Risk of bias in empirical studies was assessed with a bespoke checklist and modelling studies with a published checklist. All data syntheses were done using random effects models. Review question (1): We included 130 studies. Heterogeneity was high so we did not estimate a mean proportion of asymptomatic infections overall (interquartile range (IQR) 14% to 50%, prediction interval 2% to 90%), or in 84 studies based on screening of defined populations (IQR 20% to 65%, prediction interval 4% to 94%). In 46 studies based on contact or outbreak investigations, the summary proportion asymptomatic was 19% (95% confidence interval (CI) 15% to 25%, prediction interval 2% to 70%). (2) The secondary attack rate in contacts of people with asymptomatic infection compared with symptomatic infection was 0.32 (95% CI 0.16 to 0.64, prediction interval 0.11 to 0.95, 8 studies). (3) In 13 modelling studies fit to data, the proportion of all SARS-CoV-2 transmission from presymptomatic individuals was higher than from asymptomatic individuals. Limitations of the evidence include high heterogeneity and high risks of selection and information bias in studies that were not designed to measure persistently asymptomatic infection, and limited information about variants of concern or in people who have been vaccinated. Conclusions Based on studies published up to July 2021, most SARS-CoV-2 infections were not persistently asymptomatic, and asymptomatic infections were less infectious than symptomatic infections. Summary estimates from meta-analysis may be misleading when variability between studies is extreme and prediction intervals should be presented. Future studies should determine the asymptomatic proportion of SARS-CoV-2 infections caused by variants of concern and in people with immunity following vaccination or previous infection. Without prospective longitudinal studies with methods that minimise selection and measurement biases, further updates with the study types included in this living systematic review are unlikely to be able to provide a reliable summary estimate of the proportion of asymptomatic infections caused by SARS-CoV-2. Review protocol Open Science Framework (https://osf.io/9ewys/)
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TL;DR: In this article, a combination of early, strict, and consistently implemented interventions is crucial to control COVID-19 incidence in low-middle income countries with limited capacity using non-pharmaceutical interventions.
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TL;DR: In this paper , a linear B cell epitope prediction model based on T-B reciprocity was developed, which explicitly included the enrichment of putative CD4+ T cell epitopes (predicted HLA class II epitopes) in the model.
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TL;DR: Evidence is provided that the NPIs measures taken to control COVID-19 were effective in improving air quality and reducing the spread of RIDs, however, a direct causal relationship has not been established.
Abstract: The Yangtze River Delta is one of the top five Chinese regions affected by COVID-19, as it is adjacent to Hubei Province, where COVID-19 first emerged. We investigated the impact of COVID-19 non-pharmaceutical interventions (NPIs) on changes in respiratory infectious diseases (RIDs) incidence and air quality in the Yangtze River Delta by constructing two proportional tests and fitting ARIMA and linear regression models. Compared with the pre-COVID-19 period, the average monthly incidence of seven RIDs decreased by 37.80% (p < 0.001) and 37.11% (p < 0.001) during the COVID-19 period and the post-vaccination period, respectively, in Shanghai, and decreased by 20.39% (p < 0.001) and 22.86% (p < 0.001), respectively, in Zhejiang. Similarly, compared with the pre-COVID-19 period, the monthly overall concentrations of six air pollutants decreased by 12.7% (p = 0.003) and 18.79% (p < 0.001) during the COVID-19 period and the post-vaccination period, respectively, in Shanghai, and decreased by 12.85% (p = 0.008) and 15.26% (p = 0.001), respectively, in Zhejiang. Interestingly, no significant difference in overall incidence of RIDs and concentrations of air quality was shown between the COVID-19 period and the post-vaccination period in either Shanghai or Zhejiang. This study provides additional evidence that the NPIs measures taken to control COVID-19 were effective in improving air quality and reducing the spread of RIDs. However, a direct causal relationship has not been established.
7 citations
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TL;DR: It is found that interventions aimed at children might have a relatively small impact on reducing SARS-CoV-2 transmission, particularly if the transmissibility of subclinical infections is low.
Abstract: The COVID-19 pandemic has shown a markedly low proportion of cases among children1–4. Age disparities in observed cases could be explained by children having lower susceptibility to infection, lower propensity to show clinical symptoms or both. We evaluate these possibilities by fitting an age-structured mathematical model to epidemic data from China, Italy, Japan, Singapore, Canada and South Korea. We estimate that susceptibility to infection in individuals under 20 years of age is approximately half that of adults aged over 20 years, and that clinical symptoms manifest in 21% (95% credible interval: 12–31%) of infections in 10- to 19-year-olds, rising to 69% (57–82%) of infections in people aged over 70 years. Accordingly, we find that interventions aimed at children might have a relatively small impact on reducing SARS-CoV-2 transmission, particularly if the transmissibility of subclinical infections is low. Our age-specific clinical fraction and susceptibility estimates have implications for the expected global burden of COVID-19, as a result of demographic differences across settings. In countries with younger population structures—such as many low-income countries—the expected per capita incidence of clinical cases would be lower than in countries with older population structures, although it is likely that comorbidities in low-income countries will also influence disease severity. Without effective control measures, regions with relatively older populations could see disproportionally more cases of COVID-19, particularly in the later stages of an unmitigated epidemic. A new epidemiological study shows reduced susceptibility to SARS-CoV-2 and decreased risk of developing severe symptoms in people aged younger than 20 years, suggesting that children have limited contribution to spread of COVID-19.
1,281 citations
TL;DR: The COVID-19 pandemic continues to be severe, particularly in certain population groups, and the need to build on current efforts to collect and analyze case data, especially among those with underlying health conditions is underscored.
Abstract: The coronavirus disease 2019 (COVID-19) pandemic resulted in 5,817,385 reported cases and 362,705 deaths worldwide through May, 30, 2020,† including 1,761,503 aggregated reported cases and 103,700 deaths in the United States.§ Previous analyses during February-early April 2020 indicated that age ≥65 years and underlying health conditions were associated with a higher risk for severe outcomes, which were less common among children aged <18 years (1-3). This report describes demographic characteristics, underlying health conditions, symptoms, and outcomes among 1,320,488 laboratory-confirmed COVID-19 cases individually reported to CDC during January 22-May 30, 2020. Cumulative incidence, 403.6 cases per 100,000 persons,¶ was similar among males (401.1) and females (406.0) and highest among persons aged ≥80 years (902.0). Among 599,636 (45%) cases with known information, 33% of persons were Hispanic or Latino of any race (Hispanic), 22% were non-Hispanic black (black), and 1.3% were non-Hispanic American Indian or Alaska Native (AI/AN). Among 287,320 (22%) cases with sufficient data on underlying health conditions, the most common were cardiovascular disease (32%), diabetes (30%), and chronic lung disease (18%). Overall, 184,673 (14%) patients were hospitalized, 29,837 (2%) were admitted to an intensive care unit (ICU), and 71,116 (5%) died. Hospitalizations were six times higher among patients with a reported underlying condition (45.4%) than those without reported underlying conditions (7.6%). Deaths were 12 times higher among patients with reported underlying conditions (19.5%) compared with those without reported underlying conditions (1.6%). The COVID-19 pandemic continues to be severe, particularly in certain population groups. These preliminary findings underscore the need to build on current efforts to collect and analyze case data, especially among those with underlying health conditions. These data are used to monitor trends in COVID-19 illness, identify and respond to localized incidence increase, and inform policies and practices designed to reduce transmission in the United States.
1,111 citations
TL;DR: This Editorial aims to describe how asymptomatic cases contribute to transmission and what the implications are for control strategies.
Abstract: As the novel coronavirus disease 2019 (COVID-19) pandemic spreads rapidly across the globe many unanswered questions about the basic biology and epidemiology of the disease hamper our response strategies and limit our ability to achieve control and prevent a rebound or so-called “second wave”. One such crucial question is: To what degree do asymptomatic cases contribute to transmission? Early, small studies on this subject have found wide ranging estimates of the prevalence of asymptomatic carriers, and just a handful of studies so far have documented viral shedding by asymptomatic cases [1]. We recently re-examined China’s COVID-19 case report data to investigate this question [2]. This Editorial aims to describe how asymptomatic cases contribute to transmission and what the implications are for control strategies. Asymptomatic COVID-19 cases are those having positive results from either viral nucleic acid or antibody testing yet not having classical symptoms (i.e., fever, dry cough, fatigue). In a report of the first 72,314 COVID-19 cases in China, the proportion of such asymptomatic cases was 1% — only 889 cases had been documented [3, 4]. However, these researchers underscored the high likelihood of this being an understatement of the true prevalence of asymptomatic infection because of the inherent difficulty of finding these cases [3, 4]. Also, it should be noted that community transmission in China was limited primarily to Wuhan City, and to a lesser extent in Hubei Province, while the 30 other provinces/municipalities/autonomous regions only had clusters of cases. The prevalence of asymptomatic cases may differ in areas with versus without community transmission. Indeed, until recently asymptomatic cases were only being found through rapid screening of close contacts of symptomatic cases, intensive investigation of case clusters, and active testing campaigns [5]. Not surprisingly, one important finding that has come to light over the past two months is that only a portion of cases in China originally categorized as asymptomatic are “true” asymptomatic cases. Even after an extended period of close medical observation, these individuals never become ill with COVID-19 symptoms, yet they eventually produce detectable levels of specific antibodies. Other individuals who have been identified as asymptomatic at their initial RT-PCR screening, were likely in the virus incubation period. Thus, they were not asymptomatic, but pre-symptomatic, and they eventually experienced the onset of symptoms, which meant that they were reclassified into one of the other case definitions (i.e., mild, moderate, severe, critical) [5]. As of April 7, 2020, a total of 81 802 COVID-19 cases had been reported in China. This total included 1190 asymptomatic cases that had been confirmed as asymptomatic after extended close follow-up. It also included a further 1095 cases that had been tentatively categorized as asymptomatic cases but were still under medical observation [6]. These findings place the prevalence of “true” asymptomatic infection in the range of 1.5 to 2.8%. Nevertheless, this is clearly still an underestimate since testing has primarily occurred among individuals who have symptoms. Interestingly, the new widespread
31 citations