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COVID-19 distributes socially in China: A Bayesian spatial analysis
Di Peng1,2, Jian Qian2, Luyi Wei2
1The First People's Hospital of Shuangliu District, Chengdu, Sichuan, China.
Plos One
|April 20, 2022
Summary
High-risk areas for coronavirus disease 2019 (COVID-19) in China were linked to economic development and population movement. Controlling these factors can help prevent local transmission.
Area of Science:
- Epidemiology
- Public Health
- Spatial Analysis
Background:
- The coronavirus disease 2019 (COVID-19) pandemic poses a significant global public health threat.
- Understanding the spatial distribution of COVID-19 and its associated socioeconomic factors is crucial for effective epidemic control.
Purpose of the Study:
- To identify high-risk areas for COVID-19 in China.
- To investigate the association between socioeconomic factors and the spatial distribution of COVID-19.
- To provide insights for epidemic control strategies in China and globally.
Main Methods:
- Analysis of COVID-19 case data from 30 mainland Chinese provinces (excluding Hubei) between January 16 and March 31, 2020.
- Inclusion of demographic, economic, health, and transportation factors in the analysis.
- Application of Global Autocorrelation analysis and Bayesian spatial models to identify spatial patterns and risk factors.
Main Results:
- COVID-19 incidence exhibited significant spatial autocorrelation (Global Moran's I = 0.31, P<0.05).
- High-risk areas were concentrated around Hubei province and in economically developed regions.
- Per capita household consumption expenditure (RR=1.887) and the proportion of migrants from Hubei (RR=1.099) were significant socioeconomic risk factors, explaining substantial spatial variation.
Conclusions:
- COVID-19 risk is positively associated with economic development and population mobility.
- Strategies to block population movement and reduce local exposure are effective in curbing local COVID-19 transmission.
- Findings offer valuable guidance for public health interventions during the COVID-19 pandemic.
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