Comprehensive Risk Assessment and Spatial Pattern Analysis of COVID-19 of China

Man Xie, Xiling Wu, Xiling Wu, Chiping Yuan, Chiping Yuan

2022

Abstract

The outbreak of COVID-19 has a certain impact on China, an objective assessment of COVID-19 risk is of great significance for epidemic preparedness and public health management. In this paper, the spatial distribution pattern and spatial aggregation pattern of comprehensive risk of COVID-19 are studied by constructing an index system of COVID-19 with using an exploratory spatial data analysis method. The results show that the overall Moran’s I index of comprehensive risk is 0.2417, indicating that there is a positive spatial correlation and a significant spatial clustering feature. The comprehensive risk distribution of COVID-19 in some regions follows the characteristics of geographical proximity, and there is a risk of transmission between regions. Tianjin, Hubei, Sichuan, Liaoning, Shanghai and Hainan are the areas with high comprehensive risk of COVID-19, while the low risk areas are Guangdong, Yunnan, Tibet, Shanxi, Qinghai, Ningxia and Xinjiang. There are 13 regions with low-low clustering pattern (LL), there are 5 regions with high-high clustering pattern (HH). According to the distribution of comprehensive risk, we should formulate prevention, control and emergency response strategies, strengthen the construction of public health facilities and training of medical professional and technical personnel, and reduce the level of epidemic risk.

Paper Citation

in Harvard Style

Xie M., Wu X. and Yuan C. (2022). Comprehensive Risk Assessment and Spatial Pattern Analysis of COVID-19 of China. In Proceedings of the 1st International Conference on Health Big Data and Intelligent Healthcare - Volume 1: ICHIH, ISBN 978-989-758-596-8, pages 107-114. DOI: 10.5220/0011233000003438

in Bibtex Style

@conference{ichih22,
author={Man Xie and Xiling Wu and Chiping Yuan},
title={Comprehensive Risk Assessment and Spatial Pattern Analysis of COVID-19 of China},
booktitle={Proceedings of the 1st International Conference on Health Big Data and Intelligent Healthcare - Volume 1: ICHIH,},
year={2022},
pages={107-114},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011233000003438},
isbn={978-989-758-596-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Health Big Data and Intelligent Healthcare - Volume 1: ICHIH,
TI - Comprehensive Risk Assessment and Spatial Pattern Analysis of COVID-19 of China
SN - 978-989-758-596-8
AU - Xie M.
AU - Wu X.
AU - Yuan C.
PY - 2022
SP - 107
EP - 114
DO - 10.5220/0011233000003438