Regional infectious risk prediction of COVID-19 based on geo-spatial data

PeerJ

article

Xuewei Cheng¹  Zhaozhou Han²  Badamasi Abba¹  Hong Wang¹ 

[1] School of Mathematics and Statistics, Central South University;School of Economics, Jinan University

关键词: Risk prediction;    Migration index;    Geography-economy matrix;    Geo-spatial data;   

DOI  :  10.7717/peerj.10139

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

After the first confirmed case of the novel coronavirus disease (COVID-19) was found, it is of considerable significance to divide the risk levels of various provinces or provincial municipalities in Mainland China and predict the spatial distribution characteristics of infectious diseases. In this paper, we predict the epidemic risk of each province based on geographical proximity information, spatial inverse distance information, economic distance and Baidu migration index. A simulation study revealed that the information based on geographical economy matrix and migration index could well predict the spatial spread of the epidemic. The results reveal that the accuracy rate of the prediction is over 87.10% with a rank difference of 3.1. The results based on prior information will guide government agencies and medical and health institutions to implement responses to major public health emergencies when facing the epidemic situation.

【 授权许可】

CC BY