Literature DB >> 32447904

[Epidemiological characteristics of infection in COVID-19 close contacts in Ningbo city].

Y Chen1, A H Wang1, B Yi1, K Q Ding1, H B Wang1, J M Wang1, H B Shi1, S J Wang1, G Z Xu1.   

Abstract

Objective: To estimate the infection rate of close contacts of COVID-19 cases, and to evaluate the risk of COVID-19 under different exposure conditions.
Methods: A prospective study was used to conduct continuous quarantine medical observations of close contacts of people infected with COVID-19, collect epidemiological, clinical manifestations, and laboratory test data to estimate the infection rate of close contacts under different exposures.
Results: The epidemiological curve of COVID-19 in Ningbo showed persistent human-to-human characteristics. A total of 2 147 close contacts were tracked and investigated. The total infection rate was 6.15%. The infection rates of confirmed cases and positive contacts were 6.30% and 4.11%, respectively. The difference was not statistically significant (P>0.05). Among close contacts of different relationships, friends/pilgrims (22.31%), family members (18.01%), and relatives (4.73%) have a higher infection rate, and close contacts of medical staff were not infected. Differences in infection rates among the close contacts were statistically significant (P<0.005). Living with the case (13.26%), taking the same transportation (11.91%), and dining together (7.18%) are high risk factors for infection. Cross-infection in the hospital should not be ignored (1.94%). The median of incubation period is 5 days.
Conclusion: The infection rate of close contacts of COVID-19 cases is high, and isolation medical observation measures should be implemented in strict accordance with the close contact management plan.

Entities:  

Keywords:  COVID-19; Close contacts; Epidemiological characteristics; Infection rate

Mesh:

Year:  2020        PMID: 32447904     DOI: 10.3760/cma.j.cn112338-20200304-00251

Source DB:  PubMed          Journal:  Zhonghua Liu Xing Bing Xue Za Zhi        ISSN: 0254-6450


  52 in total

1.  Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of SARS-CoV-2 in different settings: a mathematical modelling study.

Authors:  Adam J Kucharski; Petra Klepac; Andrew J K Conlan; Stephen M Kissler; Maria L Tang; Hannah Fry; Julia R Gog; W John Edmunds
Journal:  Lancet Infect Dis       Date:  2020-06-16       Impact factor: 25.071

2.  Knowledge about the COVID-19 pandemic among undergraduate medical and dental students in Lalitpur, Nepal.

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3.  Role of Asymptomatic COVID-19 Cases in Viral Transmission: Findings From a Hierarchical Community Contact Network Model.

Authors:  Tianyi Luo; Zhidong Cao; Yuejiao Wang; Daniel Zeng; Qingpeng Zhang
Journal:  IEEE Trans Autom Sci Eng       Date:  2021-09-03       Impact factor: 6.636

Review 4.  Asymptomatic and pre-symptomatic infection in Coronavirus Disease 2019 pandemic.

Authors:  Yutong Wang; Ke Zheng; Wenjing Gao; Jun Lv; Canqing Yu; Lan Wang; Zijun Wang; Bo Wang; Chunxiao Liao; Liming Li
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Journal:  Clin Epidemiol Glob Health       Date:  2021-05-16

Review 6.  Coronavirus's (SARS-CoV-2) airborne transmission.

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Journal:  SAGE Open Med       Date:  2022-04-21

Review 7.  Mask use during COVID-19: A risk adjusted strategy.

Authors:  Jiao Wang; Lijun Pan; Song Tang; John S Ji; Xiaoming Shi
Journal:  Environ Pollut       Date:  2020-06-25       Impact factor: 8.071

8.  Cost effective reproduction number based strategies for reducing deaths from COVID-19.

Authors:  Christopher Thron; Vianney Mbazumutima; Luis V Tamayo; Léonard Todjihounde
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9.  Exploring secondary SARS-CoV-2 transmission from asymptomatic cases using contact tracing data.

Authors:  Ko Nakajo; Hiroshi Nishiura
Journal:  Theor Biol Med Model       Date:  2021-07-16       Impact factor: 2.432

10.  Modeling the Prevalence of Asymptomatic COVID-19 Infections in the Chinese Mainland.

Authors:  Xiaoqian Jia; Junxi Chen; Liangjing Li; Na Jia; Bahabaike Jiangtulu; Tao Xue; Le Zhang; Zhiwen Li; Rongwei Ye; Bin Wang
Journal:  Innovation (Camb)       Date:  2020-08-04
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