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Epidemiological Characteristics and Factors Associated with Critical Time Intervals of COVID-19 in Eighteen Provinces, China: A Retrospective Study.
Zhou, Feng; You, Chong; Zhang, Xiaoyu; Qian, Kaihuan; Hou, Yan; Gao, Yanhui; Zhou, Xiao-Hua.
  • Zhou F; Department of Biostatistics, School of Public Health, Peking University, Beijing, China.
  • You C; Beijing International Center for Mathematical Research, Peking University, Beijing, China.
  • Zhang X; School of Medicine, Macau University of Science and Technology, Macau, China.
  • Qian K; Department of Biostatistics, School of Public Health, Peking University, Beijing, China.
  • Hou Y; Department of Biostatistics, School of Public Health, Peking University, Beijing, China.
  • Gao Y; Department of Epidemiology and Medical statistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China.
  • Zhou XH; Department of Biostatistics, School of Public Health, Peking University, Beijing, China; Beijing International Center for Mathematical Research, Peking University, Beijing, China; School of Mathematical Sciences, Peking University, Beijing, China. Electronic address: azhou@math.pku.edu.cn.
Int J Infect Dis ; 102: 123-131, 2021 Jan.
Article in English | MEDLINE | ID: covidwho-1059590
ABSTRACT

BACKGROUND:

As COVID-19 ravages continuously around the world, more information on the epidemiological characteristics and factors associated with time interval between critical events is needed to contain the pandemic and to assess the effectiveness of interventions.

METHODS:

Individual information on confirmed cases from January 21 to March 2 was collected from provincial or municipal health commissions. We identified the difference between imported and local cases in the epidemiological characteristics. Two models were established to estimate the factors associated with time interval from symptom onset to hospitalization (TOH) and length of hospital stay (LOS) respectively.

RESULTS:

Among 7,042 cases, 3392 (48.17%) were local cases and 3304 (46.92%) were imported cases. Since the first intervention was adopted in Hubei on January 23, the daily reported imported cases reached a peak on January 28 and gradually decreased since then. Imported cases were on average younger (41 vs. 48), and had more male (58.66% vs. 47.53%) compared to local cases. Furthermore, imported cases had more contacts with other confirmed cases (2.80 ± 2.33 vs. 2.17 ± 2.10), which were mainly within family members (2.26 ± 2.18 vs. 1.57 ± 2.06). The TOH and LOS were 2.67 ± 3.69 and 18.96 ± 7.63 days respectively, and a longer TOH was observed in elderly living in the provincial capital cities that were higher migration intensity with Hubei.

CONCLUSIONS:

Measures to restrict traffic can effectively reduce imported spread. However, household transmission is still not controlled, particularly for the infection of imported cases to elderly women. It is still essential to surveil and educate patients about the early admission or isolation.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Experimental Studies / Observational study Topics: Long Covid Limits: Adolescent / Adult / Aged / Female / Humans / Male / Middle aged / Young adult Country/Region as subject: Asia Language: English Journal: Int J Infect Dis Journal subject: Communicable Diseases Year: 2021 Document Type: Article Affiliation country: J.ijid.2020.09.1487

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Experimental Studies / Observational study Topics: Long Covid Limits: Adolescent / Adult / Aged / Female / Humans / Male / Middle aged / Young adult Country/Region as subject: Asia Language: English Journal: Int J Infect Dis Journal subject: Communicable Diseases Year: 2021 Document Type: Article Affiliation country: J.ijid.2020.09.1487