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Impacts of socio-economic determinants, spatial distance and climate factors on the confirmed cases and deaths of COVID-19 in China.
Yang, Xiao-Dong; Su, Xin-Yi; Li, Hong-Li; Ma, Ren-Feng; Qi, Fang-Jie; Cao, Yue-E.
  • Yang XD; Department of Geography and Spatial Information Techniques/Center for Land and Marine Spatial Utilization and Governance Research, Ningbo University, Ningbo, China.
  • Su XY; Ningbo Universities Collaborative Innovation Center for Land and Marine Spatial Utilization and Governance Research at Ningbo University, Ningbo, China.
  • Li HL; Department of Geography and Spatial Information Techniques/Center for Land and Marine Spatial Utilization and Governance Research, Ningbo University, Ningbo, China.
  • Ma RF; Department of Geography and Spatial Information Techniques/Center for Land and Marine Spatial Utilization and Governance Research, Ningbo University, Ningbo, China.
  • Qi FJ; Ningbo Universities Collaborative Innovation Center for Land and Marine Spatial Utilization and Governance Research at Ningbo University, Ningbo, China.
  • Cao YE; Institute of East China Sea, Ningbo University, Ningbo, China.
PLoS One ; 16(7): e0255229, 2021.
Article in English | MEDLINE | ID: covidwho-1327982
ABSTRACT
This study is to assess the influences of climate, socio-economic determinants, and spatial distance on the confirmed cases and deaths in the raise phase of COVID-19 in China. The positive confirmed cases and deaths of COVID-19 over the population size of 100,000 over every 5 consecutive days (the CCOPSPTT and DOPSPTT for short, respectively) covered from 25th January to 29th February, 2020 in five city types (i.e., small-, medium-, large-, very large- and super large-sized cities), along with the data of climate, socio-economic determinants, spatial distance of the target city to Wuhan city (DW, for short), and spatial distance between the target city and their local province capital city (DLPC, for short) were collected from the official websites of China. Then the above-mentioned influencing factors on CCOPSPTT and DOPSPTT were analyzed separately in Hubei and other provinces. The results showed that CCOPSPTT and DOPSPTT were significantly different among five city types outside Hubei province (p < 0.05), but not obviously different in Hubei province (p > 0.05). The CCOPSPTT had significant correlation with socio-economic determinants (GDP and population), DW, climate and time after the outbreak of COVID-19 outside Hubei province (p < 0.05), while was only significantly related with GDP in Hubei province (p < 0.05). The DOPSPTT showed significant correlation with socio-economic determinants, DW, time and CCOPSPTT outside Hubei province (p < 0.05), while was significantly correlated with GDP and CCOPSPTT in Hubei province (p < 0.05). Compared with other factors, socio-economic determinants have the largest relative contribution to variance of CCOPSPTT in all studied cities (> 78%). The difference of DOPSPTT among cities was mainly affected by CCOPSPTT. Our results showed that influences of city types on the confirmed cases and death differed between Hubei and other provinces. Socio-economic determinants, especially GDP, have higher impact on the change of COVID-19 transmission compared with other factors.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Socioeconomic Factors / Climate / COVID-19 Type of study: Health economic evaluation Limits: Humans Country/Region as subject: Asia Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2021 Document Type: Article Affiliation country: Journal.pone.0255229

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Socioeconomic Factors / Climate / COVID-19 Type of study: Health economic evaluation Limits: Humans Country/Region as subject: Asia Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2021 Document Type: Article Affiliation country: Journal.pone.0255229