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The epidemiological characteristics of cluster transmission of coronavirus disease 2019 (COVID-19): a multi-center study in Jiangsu Province.

ABSTRACT: Coronavirus Disease 2019 (COVID-19) pandemic has rapidly spread across the globe while little multi-center research about the epidemiological characteristics of cluster transmission is conducted. To provide a more comprehensive description of the epidemiological characteristics of cluster transmission and the virulence of SARS-CoV-2 carried by asymptomatic carriers, we studied the epidemiological characteristics of 70 clusters. 70 clusters including 311 consecutive subjects from January 20, 2020, to March 10, 2020, were enrolled. Of 70 clusters, 5 were infected by asymptomatic or presymptomatic carriers. We gathered and analyzed information about their demographic, epidemiological, clinical, diagnostic classification, and cluster characteristics. Among the 66 asymptomatic carriers in Jiangsu Province, 49 asymptomatic were observed in 311 subjects distributed in 70 clusters. We demonstrated that there is a significance between the severity of cases infected by asymptomatic carriers and cases infected by symptomatic patients (P=0.033) and the former usually presented with milder symptoms. A significant difference was shown regarding the level distribution of age (P=0.006) and the frequency distribution of gender (P=0.014) and disease severity of COVID-19 (P=0.008) among the seven groups classified by the relationship with the index cases. The average age of infected medical staff was the youngest and the majority of infected medical are females while the infected patients were generally oldest and usually accompanied by severest symptoms. We concluded that asymptomatic carriers are mainly screened out of clusters and the patients infected by asymptomatic carriers present with milder symptoms than those infected by symptomatic patients, which indicated that the SARS-CoV-2 shares decreased virulence among asymptomatic carriers. Effective measures should be taken to prevent transmission in hospitals to protect doctors, nurses, and patients.

SUBMITTER: Han T

PROVIDER: S-EPMC7653592 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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The epidemiological characteristics of cluster transmission of coronavirus disease 2019 (COVID-19): a multi-center study in Jiangsu Province.

Han Tao T Hua Lei L He Shu S Zhou Yaqing Y Hou Can C Chen Jiaxin J Yuan Jinxia J Guo Yi Y Zhang Sheng S Jia Qiaowei Q Zhao Chenhui C Zhang Jing J Cao Quan Q Jia Enzhi E

American journal of translational research 20201015 10

Coronavirus Disease 2019 (COVID-19) pandemic has rapidly spread across the globe while little multi-center research about the epidemiological characteristics of cluster transmission is conducted. To provide a more comprehensive description of the epidemiological characteristics of cluster transmission and the virulence of SARS-CoV-2 carried by asymptomatic carriers, we studied the epidemiological characteristics of 70 clusters. 70 clusters including 311 consecutive subjects from January 20, 2020 ...[more]

PMID: 33194041

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Project description:BackgroundWith the continuous progress of the epidemic of coronavirus disease 2019 (COVID-19) infection and the constant mutation of the virus strain, reinfection occurred in previously infected individuals and caused waves of the epidemic in many countries. Therefore, we aimed to explore the characteristics of COVID-19 reinfection during the epidemic period in Yangzhou and provide a scientific basis for assessing the COVID-19 situation and optimizing the allocation of medical resources.MethodsWe chose previously infected individuals of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reported locally in Yangzhou city from January 2020 to November 30, 2022. A telephone follow-up of cases was conducted from February to March 2023 to collect the COVID-19 reinfection information. We conducted a face-to-face survey on that who met the definition of reinfection to collect information on clinical symptoms, vaccination status of COVID-19, and so on. Data were analyzed using SPSS 19.0.ResultsAmong the 999 eligible respondents (92.24% of all the participants), consisting of 42.28% males and 57.72% females, the reinfection incidence of females was significantly higher than that of male cases (χ2 = 5.197, P < 0.05); the ages of the respondents ranged from 1 to 91 years, with the mean age of 42.28 (standard deviation 22.73) years; the most of the sufferers were infected initially with Delta variant (56.88%), followed by the Omicron subvariants BA.1/BA.2 (39.52%). Among all the eligible respondents, 126 (12.61%) reported COVID-19 reinfection appearing during the epidemic period, and the intervals between infections were from 73 to 1,082 days. The earlier the initial infection occurred, the higher the reinfection incidence and the reinfection incidence was significantly increased when the interval was beyond 1 year (P < 0.01) .119 reinfection cases (94.4%) were symptomatic when the most common symptoms included fever (65.54%) and cough (61.34%); compared with the initial infection cases, the proportion of clinical symptoms in the reinfected cases was significantly higher (P < 0.01). The reinfection incidence of COVID-19 vaccination groups with different doses was statistically significant (P < 0.01). Fewer reinfections were observed among the respondents with three doses of COVID-19 vaccination compared to the respondents with two doses (χ2 = 14.595, P < 0.001) or without COVID-19 vaccination (χ2 =4.263, P = 0.039).ConclusionAfter the epidemic period of COVID-19, the reinfection incidence varied with different types of SARS-CoV-2 strains. The reinfection incidence was influenced by various factors such as virus characteristics, vaccination, epidemic prevention policies, and individual variations. As the SARS-CoV-2 continues to mutate, vaccination and appropriate personal protection have practical significance in reducing the risk of reinfection.

Project description:BackgroundZhejiang Province is one of the five provinces in China that had the highest incidence of novel coronavirus disease (COVID-19). Zhejiang, ranked fourth highest in COVID-19 incidence, is located in the Yangtze River Delta region of southeast China. This study was undertaken to identify the space-time characteristics of COVID-19 in Zhejiang.MethodsData on COVID-19 cases in Zhejiang Province from January to July 2020 were obtained from this network system. Individual information on cases and deaths was imported, and surveillance information, including demographic characteristics and geographic and temporal distributions, was computed by the system. The Knox test was used to identify possible space-time interactions to test whether cases that are close in distance were also close in time. Network analysis was performed to determine the relationship among the cases in a transmission community and to try to identify the key nodes.ResultsIn total, 1475 COVID-19 cases and 1 fatal case were reported from January to July 2020 in Zhejiang Province, China. Most of the cases occurred before February 15th, which accounted for 90.10%. The imported cases increased and became the main risk in Zhejiang Province after February 2020. The risk areas showed strong heterogeneity according to the Knox test. The areas at short distances within 1 kilometer and at brief periods within 5 days presented relatively high risk. The numbers of subcommunities for the four clusters were 12, 9, 6 and 4. There was obvious heterogeneity in the modularity of subcommunities. The maximum values of the node centrality for the four clusters were 2.9474, 4.3706, 4.1080 and 2.7500.ConclusionsCOVID-19 was brought under control over a short period in Zhejiang Province. Imported infections from outside of mainland China then became a new challenge. The effects of spatiotemporal interaction exhibited interval heterogeneity. The characteristics of transmission showed short range and short term risks. The importance to the cluster of each case was detected, and the key patients were identified. It is suggested that we should focus on key patients in complex conditions and in situations with limited control resources.

Dataset Information

The epidemiological characteristics of cluster transmission of coronavirus disease 2019 (COVID-19): a multi-center study in Jiangsu Province.

Publications

The epidemiological characteristics of cluster transmission of coronavirus disease 2019 (COVID-19): a multi-center study in Jiangsu Province.

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