Objective To describe the space hotspots and explore clustering of coronavirus disease (COVID-19) in Shandong Province during the beginning of 2020, which can provide a basis for the development of regional COVID-19 prevention and control strategies.
Methods Geographical information system(GIS)was used to manage the COVID-19 cases reported by the health commissions of all cities in Shandong Province. The global empirical Bayesian smoothing, spatial empirical Bayes smoothing, spatial autocorrelation and spatial scan statistic were used for further analysis.
Results Totally 548 cases of COVID-19 were reported in Shandong Province, from January 21 to February 20, 2020;77.19% of cases were between 15 and 59 years old, and 56.02% of them were males. The number of reported cases showed clearly the spatial differences. More cases were reported in the cities in Qingdao, Weihai and Jinan, and there were 45 counties with excess risk (ER) more than 1. The global spatial autocorrelation analyses implied that distribution of COVID-19 was no spatially auto-correlated in Shandong Province (Moran's I=-0.027, P > 0.05). Local autocorrelation analysis found 1 high-risk area(HH area), 7 cold-spot areas(LL area), and 4 spatial abnormal points(HL or LH area). Spatial scanning analysis revealed 9 statistically significant clustering areas, of which the first three clustering areas appeared in Shizhong District of Jinan (RR=8.65, P < 0.01), Kuiwen District of Weifang (RR=9.02, P < 0.01), and Taishan District of Tai'an (RR=6.41, P < 0.01).
Conclusions The overall distribution of COVID-19 cases in Shandong Province during January 21 to February 20, 2020 was discrete. One third of the counties had the excess risk and local aggregation.
DownLoad: