The epidemiological analysis and spatial analysis based on big data of 120 pre-hospital first aid as an example of Dalian
Urban public health emergency management is closely related to the life safety of residents,and with the accelerated aging of the population in Dalian,the disease spectrum has become more complex,and the demand for emergency care among residents is increasing day by day.This paper u-ses historical big data of 120 pre-hospital emergency patients in Dalian from September 2020 to Au-gust 2021,screens and analyses the epidemiological characteristics of pre-hospital emergency patients to establish a database.It uses nearest neighbour distance index,kernel density and buffer zone anal-ysis to study the types and characteristics of the spatial pattern distribution of 120 pre-hospital emer-gency patients in Dalian.After screening 40 551 cases that met the criteria,epidemiological analysis was performed on the case pre-hospital emergency patients to obtain the epidemiological characteris-tics of 120 pre-hospital emergency patients in Dalian:the ratio of men to women was 1.13∶1,the peak age group of diseases was the elderly group(age of onset 60 years),unclear diagnosis was excluded,and the top three diseases in terms of type were injury and poisoning(24.727%),cardio-vascular system(10.219%),and respiratory system(9.928%),and all of these diseases occurred mainly in the elderly group.The pre-hospital 120 emergency patients were mostly spatially clustered,mainly around Cang Shan Road,near Friendship Square,around the intersection of Dong Lian Road and Hua Bei Road,Xiang Fu Reef Street,both sides of Union Road,near Zhongshan Square,Renmin Road,around Er Qi Square,around Maban North Street,near Xishan District,and around Taishan Street.It is expected to be of reference significance in guiding the rational allocation of hospi-tal emergency resources and the development of effective pre-hospital emergency prevention and con-trol measures.
epidemiology120 pre-hospital first aidbig data of emergency patientsGIS spatial analy-sis