Asymptomatic and Human-to-Human Transmission of SARS-CoV-2 in a 2-Family Cluster, Xuzhou, China

Li, Chunyang; Ji, Fang; Wang, Liang; Wang, Liping; Hao, Jungui; Dai, Mingjia; Liu, Yan; Pan, Xiucheng; Fu, Juanjuan; Li, Li; Yang, Guang-de; Yang, Jianye; Yan, Xuebing; Gu, Bing

doi:10.3201/eid2607.200718

Cited by 201 publications

(178 citation statements)

References 7 publications

(8 reference statements)

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“…Ultimately, an optimal view is asymptomatic cases may account for 60% of infections. However, recent research and case reports have confirmed that asymptomatic or pre-symptomatic cases can shed enough quantify of virus to be infectious [5][6][7][8]10]. Furthermore, if the infectivity of asymptomatic cases is similar to that of symptomatic cases, a faster epidemic will occur.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Modeling Return of the Epidemic: Impact of Population Structure, Asymptomatic Infection, Case Importation and Personal Contacts

2020

Preprint

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Background: Proactive interventions have halted the pandemic of coronavirus infected disease in some regions. However, without reaching herd immunity, the return of epidemic is possible.We investigate the impact of population structure, case importation, asymptomatic cases, and the number of contacts on a possible second wave of epidemic through mathematical modelling.Methods: we built a modified Susceptible-exposed-Infectious-Removed (SEIR) model with parameters mirroring those of the COVID-19 pandemic and reported simulated characteristics of epidemics for incidence, hospitalizations and deaths under different scenarios. Results:A larger percent of old people leads to higher number of hospitalizations, while a large percent of prior infection will effectively curb the epidemic. The number of imported cases and the speed of importation have small impact on the epidemic progression. However, a higher percent of asymptomatic cases slows the epidemic down and reduces the number of hospitalizations and deaths at the epidemic peak. Finally, reducing the number of contacts among young people alone has moderate effects on themselves, but little effects on the old population.However, reducing the number of contacts among old people alone can mitigate the epidemic significantly in both groups, even though young people remain active within themselves.

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Section: Discussionmentioning

confidence: 99%

“…Two important factors may contribute a second wave of epidemic. First, unlike the 2003 SARS epidemic in which mainly symptomatic cases are infectious [4], asymptomatic infection of the SARS-CoV2 can transmit disease [5][6][7][8][9]. Studies have detected virus shedding in nasopharyngeal swap samples among asymptomatic cases [10].…”

Section: Introductionmentioning

confidence: 99%

Modeling Return of the Epidemic: Impact of Population Structure, Asymptomatic Infection, Case Importation and Personal Contacts

2020

Preprint

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“…In summary, we inoculated young and aged cynomolgus macaques with a low passage clinical isolate of SARS-CoV-2, which resulted in productive infection in the absence of overt clinical signs. Recent studies in human cases have shown that presymptomatic and asymptomatic cases can also shed virus (14,15). Increased age did not affect disease outcome, but there was prolonged viral shedding in the upper respiratory tract of aged animals.…”

mentioning

confidence: 89%

Comparative pathogenesis of COVID-19, MERS, and SARS in a nonhuman primate model

Rockx

Kuiken

Herfst

et al. 2020

Science

872

927

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The current pandemic coronavirus, severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2), was recently identified in patients with an acute respiratory syndrome, coronavirus disease 2019 (COVID-19). To compare its pathogenesis with that of previously emerging coronaviruses, we inoculated cynomolgus macaques with SARS-CoV-2 or Middle East respiratory syndrome (MERS)–CoV and compared the pathology and virology with historical reports of SARS-CoV infections. In SARS-CoV-2–infected macaques, virus was excreted from nose and throat in the absence of clinical signs and detected in type I and II pneumocytes in foci of diffuse alveolar damage and in ciliated epithelial cells of nasal, bronchial, and bronchiolar mucosae. In SARS-CoV infection, lung lesions were typically more severe, whereas they were milder in MERS-CoV infection, where virus was detected mainly in type II pneumocytes. These data show that SARS-CoV-2 causes COVID-19–like disease in macaques and provides a new model to test preventive and therapeutic strategies.

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“…In view of the simulation by mathematical model, the initial number of the susceptible cases might be difficult to be determined. This might be demonstrated by the report that 60% of active cases might have no symptoms but could infect other healthy people [17][18][19]. And it is reported that the infected cases are of strong infection when they appeared to have no symptoms [24].…”

Section: 2mentioning

confidence: 96%

“…Similar to the simulation in China, the increase rate in simulation is not as large as that in the actual data. As it has been reported that the susceptible cases might be very inexplicit [17][18][19], the initial number of the susceptible cases S(t 0 ) is not accurate. It would be shown in the section of discussion.…”

mentioning

confidence: 99%

Evaluating the different control policies for COVID-19 between mainland China and European countries by a mathematical model in the confirmed cases

Lin

Huang

Zhang

et al. 2020

Preprint

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This study focuses on evaluating the different policies of controlling the outbreak of COVID-19 in mainland China and in some European countries. The study is based on mathematical model which is a modified susceptible-infected-recovered (SIR) model. The model takes death and recovery into consideration which in convenience is called the susceptible-infected-recovered-death (SIRD) model. The criterion for the recovered patients is assumed by COVID-19 nucleic acid testing negative. The mathematical model is constructed by retrospective study. Determination of the parameters in the model is based on the epidemic bulletin supplied by the Chinese Center for Disease Control and Prevention (CDC) and National Health Commission of the People's Republic of China (NHC) from Jan 16 2020 to Mar 5 2020. The data cover the date when the epidemic situation is reported and the data showed that the epidemic situation is almost under control in China. The mathematical model mainly simulates the active cases and the deaths during the outbreak of COVID-19. Then apply the mathematical model to simulate the epidemic situations in Italy and Spain, which are suffering the outbreak of COVID-19 in Europe. The determination of the parameters for the 2 European countries is based on the data supplied by Worldometers. By comparing the difference of the parameters based on the same mathematical model, it is possible to evaluate the different policies in different countries. It turns out that the relatively easing control policies might lead to rapid spread of the disease.

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Asymptomatic and Human-to-Human Transmission of SARS-CoV-2 in a 2-Family Cluster, Xuzhou, China

Cited by 201 publications

References 7 publications

Modeling Return of the Epidemic: Impact of Population Structure, Asymptomatic Infection, Case Importation and Personal Contacts

Modeling Return of the Epidemic: Impact of Population Structure, Asymptomatic Infection, Case Importation and Personal Contacts

Comparative pathogenesis of COVID-19, MERS, and SARS in a nonhuman primate model

Evaluating the different control policies for COVID-19 between mainland China and European countries by a mathematical model in the confirmed cases

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