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Basic Reproduction Number of the 2019 Novel Coronavirus Disease in the Major Endemic Areas of China: A Latent Profile Analysis.
Xu, Honglv; Zhang, Yi; Yuan, Min; Ma, Liya; Liu, Meng; Gan, Hong; Liu, Wenwen; Lum, Gillian Gianna Anne; Tao, Fangbiao.
  • Xu H; School of Medicine, Kunming University, Kunming, China.
  • Zhang Y; Key Laboratory of Population Health Across Life Cycle, Ministry of Education of the People's Republic of China, Anhui Medical University, Hefei, China.
  • Yuan M; Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.
  • Ma L; School of Health Service Management, Center for Big Data Science in Health, Anhui Medical University, Hefei, China.
  • Liu M; Key Laboratory of Population Health Across Life Cycle, Ministry of Education of the People's Republic of China, Anhui Medical University, Hefei, China.
  • Gan H; Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.
  • Liu W; Key Laboratory of Population Health Across Life Cycle, Ministry of Education of the People's Republic of China, Anhui Medical University, Hefei, China.
  • Lum GGA; Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.
  • Tao F; Key Laboratory of Population Health Across Life Cycle, Ministry of Education of the People's Republic of China, Anhui Medical University, Hefei, China.
Front Public Health ; 9: 575315, 2021.
Article in English | MEDLINE | ID: covidwho-1448817
ABSTRACT

Objective:

The aim of this study is to analyze the latent class of basic reproduction number (R0) trends of the 2019 novel coronavirus disease (COVID-19) in the major endemic areas of China.

Methods:

The provinces that reported more than 500 cases of COVID-19 till February 18, 2020 were selected as the major endemic areas. The Verhulst model was used to fit the growth rate of cumulative confirmed cases. The R0 of COVID-19 was calculated using the parameters of severe acute respiratory syndrome (SARS) and COVID-19. The latent class of R0 was analyzed using the latent profile analysis (LPA) model.

Results:

The median R0 calculated from the SARS and COVID-19 parameters were 1.84-3.18 and 1.74-2.91, respectively. The R0 calculated from the SARS parameters was greater than that calculated from the COVID-19 parameters (Z = -4.782 to -4.623, p < 0.01). Both R0 can be divided into three latent classes. The initial value of R0 in class 1 (Shandong Province, Sichuan Province, and Chongqing Municipality) was relatively low and decreased slowly. The initial value of R0 in class 2 (Anhui Province, Hunan Province, Jiangxi Province, Henan Province, Zhejiang Province, Guangdong Province, and Jiangsu Province) was relatively high and decreased rapidly. Moreover, the initial R0 value of class 3 (Hubei Province) was in the range between that of classes 1 and 2, but the higher R0 level lasted longer and decreased slowly.

Conclusion:

The results indicated that the overall R0 trend is decreased with the strengthening of comprehensive prevention and control measures of China for COVID-19, however, there are regional differences.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: Front Public Health Year: 2021 Document Type: Article Affiliation country: Fpubh.2021.575315

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: Front Public Health Year: 2021 Document Type: Article Affiliation country: Fpubh.2021.575315