TY - JOUR
T1 - Hubei's Core Response Policies in the Early Stage of COVID-19
AU - Zhang, Yuyao
AU - Shi, Leiyu
AU - Chen, Haiqian
AU - Wang, Xiaohan
AU - Sun, Gang
N1 - Publisher Copyright:
© 2021 Yuyao Zhang et al.
PY - 2021
Y1 - 2021
N2 - Background. This study is aimed at confirming the effectiveness of nonpharmaceutical interventions during the COVID-19 outbreak in Hubei, China. Methods. The data are all from the epidemic information released by the National Health Commission of the People's Republic of China and the Health Commission of Hubei Province. We used the multivariable linear regression by the SPSS 19.0 software: the cumulative number of confirmed cases, the cumulative number of cured cases, and the number of daily severe cases were taken as dependent variables, and the six policies, including the Joint Prevention and Control Mechanism of the State Council, lockdown Wuhan city, the first-level response to public health emergencies, the expansion of medical insurance coverage to suspected patients, mobile cabin hospitals, and counterpart assistance in Hubei province, were gradually entered into multiple linear regression models as independent variables. Results. The factors influencing the cumulative number of diagnosed cases ranged from large to small: mobile cabin hospitals and the expansion of medical insurance coverage to suspected patients. The factors influencing the cumulative number of cured cases ranged from large to small: counterpart support medical teams in Hubei province and mobile cabin hospitals. The factors influencing the number of daily severe cases ranged from large to small: mobile cabin hospitals and the expansion of medical insurance coverage to suspected patients. Conclusion. The mobile cabin hospital is a major reason for the successfully defeating COVID-19 in China. As COVID-19 pandemic spreads globally, the mobile cabin hospital is a successful experience in formulating policies to defeat COVID-19 for other countries in the outbreak phase.
AB - Background. This study is aimed at confirming the effectiveness of nonpharmaceutical interventions during the COVID-19 outbreak in Hubei, China. Methods. The data are all from the epidemic information released by the National Health Commission of the People's Republic of China and the Health Commission of Hubei Province. We used the multivariable linear regression by the SPSS 19.0 software: the cumulative number of confirmed cases, the cumulative number of cured cases, and the number of daily severe cases were taken as dependent variables, and the six policies, including the Joint Prevention and Control Mechanism of the State Council, lockdown Wuhan city, the first-level response to public health emergencies, the expansion of medical insurance coverage to suspected patients, mobile cabin hospitals, and counterpart assistance in Hubei province, were gradually entered into multiple linear regression models as independent variables. Results. The factors influencing the cumulative number of diagnosed cases ranged from large to small: mobile cabin hospitals and the expansion of medical insurance coverage to suspected patients. The factors influencing the cumulative number of cured cases ranged from large to small: counterpart support medical teams in Hubei province and mobile cabin hospitals. The factors influencing the number of daily severe cases ranged from large to small: mobile cabin hospitals and the expansion of medical insurance coverage to suspected patients. Conclusion. The mobile cabin hospital is a major reason for the successfully defeating COVID-19 in China. As COVID-19 pandemic spreads globally, the mobile cabin hospital is a successful experience in formulating policies to defeat COVID-19 for other countries in the outbreak phase.
UR - http://www.scopus.com/inward/record.url?scp=85107636497&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85107636497&partnerID=8YFLogxK
U2 - 10.1155/2021/6610045
DO - 10.1155/2021/6610045
M3 - Article
C2 - 34159196
AN - SCOPUS:85107636497
SN - 2314-6133
VL - 2021
JO - BioMed research international
JF - BioMed research international
M1 - 6610045
ER -