| BACKGROUNDThe COVID-19 epidemic is one of the most serious public health emergencies since the SARS epidemic in 2003.As of October 2020,there were more than 40 million cases of infection worldwide.The COVID-19 pandemic has caused severe damage all over the world and has placed a huge burden on the socio-economic and health systems.As a new infectious disease,all populations were susceptible to the disease,and the diversity of its transmission routes increases the difficulty of prevention and control.At present,since the local transmission of COVID-19 in Wuhan was interrupted,the epidemic intensity of COVID-19 in China has gradually weakened.And the subsequent waves of epidemics were mainly localized and small-scale clustered epidemics,and were related to overseas imports.Since the first case of infection was reported in Shandong Province on January 22,2020,the epidemic has been increasing in intensity and affecting more and more areas.Based on the epidemic data of COVID-19 in Shandong Province,this study explored the spatio-temporal distribution characteristics of COVID-19 during the epidemic period and the socio-economic factors affecting the prevalence of COVID-19 in Shandong Province,so as to provide a basis for the development of prevention and control strategies of COVID-19.OBJECTIVE1.The temporal,human and spatial distribution of COVID-19 in Shandong Province was analyzed by descriptive epidemiological methods.2.To investigate the population characteristics of severe and critical cases of COVID-19 in Shandong Province and to explore the related factors of severe cases.3.Using spatial epidemiology methods to explore the spatial relationship,temporal and spatial clustering characteristics of the distribution of new coronavirus pneumonia in the county in Shandong Province,and relevant socioeconomic factors that may affect the distribution of the disease,and provide for the formulation of prevention and control measures for the disease Scientific basisMATERIALS and METHODSThe cases data of COVID-19 in Shandong Province were collected through the Chinese Disease Control and Prevention Information System,and the relevant population and socio-economic indicators data of each county in Shandong Province were collected by Statistical Yearbook of Shandong Province,and the following studies were carried out:1.SPSS24.0 software was used to describe the demographic characteristics,temporal and regional distribution characteristics.2.The influencing factors of severe and critical cases were analyzed by binary Logistic regression using SPSS24.0 software.3.Use ArcGIS 10.6 and Geoda software to perform spatial autocorrelation analysis,and use SatScan spatio-temporal scanning analysis software to analyze the spatial and spatiotemporal clustering characteristics of new coronary pneumonia at the county level in Shandong.4.Geographically weighted regression model was used to analyze the spatial connection between the incidence of Covid-19 and socio-economic factors in counties of Shandong Province,and to reveal the variation characteristics of its parameter estimates in spatial locations.RESULTS1.Three-dimension distribution featuresThis study analyzed a total of 725 cases of COVID-19 in Shandong Province as of June 13,with a cumulative incidence of 0.93/100,000.Seven cases died,and the case fatality rate was 0.97%.The median age of patients was 40 years(31,54 years),and the male-to-female ratio was 1.2:1.The occupational composition of the cases is mostly farmers/workers(235/725,32.4%).The peak of case reports was in January and February,with a total of 670 cases reported,accounting for 92.41%of the total cases.There are 15 cities in this province that have reported cases,and most of the reported incidences in counties were low(＜2/100,000).In general,the distribution of cases in Shandong province showed a trend of low in the west and high in the east,and an inverted "U" shaped trend of increasing first and then decreasing from south to north.2.Analysis of severe casesShandong Province reported 67 critical cases,accounting for 9.24%(67/725)of the total number of cases.Multivariate analysis showed that the proportion of severe cases was higher in the≥60 age group than in the ≤29 age group(OR=6.284,95%CI:1.582～24.969).Compared with cadres,staff members,teachers and workers,the proportion of severe cases in retired personnel was higher(OR=3.078,95%CI:1.062～8.926).And compared with patients whose onset to diagnosis time is ≤3 days,patients with≥7 days(OR=2.819,95%CI:1.478～5.374)had a higher proportion of severe illness.3.Spatial autocorrelation and spatio-temporal scanning analysisThe global spatial autocorrelation analysis after Bayesian smoothing for the incidence of each county in Shandong Province showed that Moran’s I was 0.195,E(I)-0.007,Z=3.24,P=0.003,suggesting that the incidence of Covid-19 was positively correlated at the county level,and there was spatial aggregation.Local spatial autocorrelation showed four high-high clusters,which were visualized by LISA map and located in Qingdao city and Tai’an City.A simple spatial scanning analysis of the cumulative number of cases during the study period showed that the largest possible cluster area covers 13 counties in the eastern coastal area(RR=2.03,LLR=20.14,P<0.001).Time-space scanning analysis shows that the maximum possible gathering time and region of imported cases from other places are from January 12 to February 8,2020,covering 22 counties in Weihai,Yantai and Qingdao(RR=32.14,LLR=150.55,P<0.001).The maximum possible gathering time and region of local cases were from January 19 to February 19,covering 20 counties in the central and southwestern regions(RR=6.15,LLR=98.57,P＜0.001).4.Geographically weighted regression analysisThe analysis of geographically weighted regression model showed that the local regression coefficients of the number of health technicians per thousand people were positively correlated in most regions except the east,and the distribution of the coefficients increased from northwest to southeast.The local regression coefficients of population density have both positive and negative directions,and the areas south of the central area are negatively correlated,but the value is small and the explanatory power is weak.The other regions are all positively correlated,and the regression coefficients of the central part to the east and north gradually increase.The local regression coefficient of per capita GDP is negatively correlated,and its absolute value is larger in the economically developed eastern coastal areas.The local regression coefficients of the urbanization rate are all positive,and the spatial distribution map shows a gradually downward trend from west to east.The local regression coefficient of government public budget revenue is positive,and the coefficient distribution is increasing from the central to the west.CONCLUSIONS1.The epidemic trend of Covid-19 in Shandong Province was similar to the national epidemic trend.Severe cases and fatality rates are lower than the national average during the same period.The infected population is diverse,and the age of the cases is concentrated in 20～40 years old.The epidemic has affected a wide range of areas in Shandong Province.Elderly persons and delayed visits in cases are risk factors for the development of severe and critical cases.The prevention and control of the disease should be strengthened in the elderly.2.The incidence of COVID-19 in Shandong Province is not randomly distributed in space and time,and has a clear tendency to cluster.Among them,imported cases are distribute mainly in the eastern coastal areas.Local cases are mainly in central Shandong and southwestern Shandong.3.The GWR model can effectively establish the relationship between the number of health technicians per thousand people,population density,per capita gross regional product,urbanization rate and government public financial revenue and the incidence of COVID-19 at the county scale. |
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