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OBJECTIVE To stud y the s patial distribution and spatial aggregation of pharmacist resources at provincial level in China from 2010 to 2020，and to provide reference for the optimal configuration of pharmacist resources. METHODS Taking the 2011 China Health Statistics Yearbook ，2016 China Health and Family Planning Statistics Yearbook ，2021 China Health Statistics Yearbook and China Statistical Yearbook as data sources ，the spatial distribution of the number of pharmacists per capita in each province in China was described ，and the current situation of pharmacist resource spatial aggregation were analyzed by using global spatial autocorrelation and local spatial autocorrelation methods. RESULTS In 2020，the number of pharmacists per capita in China had certain differences among provinces ，with the highest in Beijing reaching 6.9 people/10 000 people，and the lowest in Hebei at 2.7 people/10 000 people. From 2010 to 2020，the number of pharmacists per capita in all provinces had increased ，with the largest increase in Guizhou （50.6％）and the smallest increase in Liaoning （3.1％）. Results of the global spatial autocorrelation showed that the clustering degree of pharmacist resource allocation per capita decreased gradually from 2010 to 2014. Spatial aggregation of pharmacist resource allocation per capita increased to certain extent from 2016 to 2019，and remained stable in 2020. Results of local spatial autocorrelation showed that Sichuan ，Yunnan and Guizhou presented a low-low aggregation pattern in 2010，while Tianjin presented a high-high aggregation pattern ；in 2015，Sichuan and Yunnan presented a low-low aggregation pattern ，while Tianjin presented a high-high aggregation pattern ；in 2020，Shandong presented a low-low aggregation pattern ，while Tianjin presented a high-high aggregation pattern. CONCLUSIONS From 2010 to 2020，there was a spatial clustering phenomenon in the allocation of pharmacist source per capita at the provincial level in China ，and pharmacist resources are correspondingly concentrated in the Beijing ，Shanghai，Guangzhou and Shenzhen and the economically developed Yangtze River Delta region.
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Objective To analyze the spatial and temporal characteristics of hand, foot and mouth disease (HFMD) in Hunan Province from 2016 to 2020. Methods The data of HFMD in Hunan Province from 2016 to 2020 were collected from China's Disease Prevention and Control Information System. HFMD spatial autocorrelation analysis was conducted by ArcGIS 10.2 software at county level, and spatial-temporal scan statistical analysis was performed by SaTScan 9.7 software. Results A total of 714 157 cases was reported in Hunan Province during 2016-2020, with an average annual incidence rate of 208.36/100 000. Global spatial autocorrelation showed that HFMD had a positive spatial correlation on the county scale in Hunan Province during this period. Local spatial autocorrelation indicated that the hot spots were mainly concentrated in the north of central Hunan, the east of central Hunan and the west of Hunan. Spatial-temporal scanning analysis revealed the first class clusters (RR = 6.65, P< 0.001) covering 34 counties in northern and central Hunan, mainly distributed in Yueyang City, Changsha City, Zhuzhou City, Yiyang City and Xiangtan City from May 2018 to June, and the second class clusters (RR = 3.02, P < 0.001) covering 40 counties in western Hunan and central and southwest Hunan from April 2016 to June 2016. Conclusion HFMD incidence exhibits seasonal and regional characteristics in Hunan Province. The prevention and control of HFMD should be guided by combining the characteristics of spatial-temporal clustering.
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Objective To explore the epidemic characteristics and spatial clustering of pulmonary tuberculosis in Wuhan from 2011 to 2019, and to provide a scientific basis for formulating intervention strategies and measures. Methods Descriptive statistical analysis was conducted on the epidemic characteristics of tuberculosis data in Wuhan registered in the national tuberculosis information management system in the last 9 years, and spatial autocorrelation analysis was performed on the incidence of tuberculosis in 155 communities or in the city using Arcgis10.5 software. Results From 2011 to 2019, there were 56,432 cases of tuberculosis reported in Wuhan, and the annual average reported incidence rate of tuberculosis was 59.24/100 000. The overall incidence rate showed a fluctuating downward trend, with an average annual decline rate of 1.99%. The ratio of the number of cases between men and women was 2.35:1, and the incidence rate in males was higher than that in females (χ2=285.36，P0,P<0.001), and the high-high aggregation areas of tuberculosis were mainly distributed in Erqi community, Baibuting community, Liujiaoting community, Yijiadun community, Heping Street, Changqian Street, Tonghu farm, Yuxian Town, Zhifang Town, Wulijie Town, Fenghuang Street, Liji Street, and Daoguanhe Street. Conclusion The overall epidemic situation of pulmonary tuberculosis in Wuhan showed a slow downward trend. The main population and the clustering time of cases were relatively fixed, and the overall epidemic showed a certain spatial clustering. Active screening should be carried out for high-risk populations and high-aggregation areas, and effective prevention and control strategies should be developed based on time and location classification.
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Objective @#To understand the spatial distribution of iodine in drinking water in Wenzhou,and to provide reference for preventing iodine deficiency disorders.@*Methods @#Drinking water was sampled from 182 townships of all 11 counties under the jurisdiction of Wenzhou according to different ways of water supply. The iodine in water was detected by cerium sulfate catalytic spectrophotometry. The water iodine data was matched with the electronic map by ArcGIS10.2 to construct a spatial database; spatial autocorrelation analysis by GeoDa1.10 and spatial scanning analysis by SaTScan 9.4 were conducted to obtain the water iodine concentration range in Wenzhou. @*Results @#The contents of iodine in 998 out of 1 008 drinking water samples were less than 10 μg/L,accounting for 99.01%. The median of water iodine in all townships of Wenzhou was 1.8 μg/L. The results of geospatial distribution analysis demonstrated that the iodine distribution in drinking water had positive spatial autocorrelation in Wenzhou（Moran's I= 0.40,Z=15.65,P< 0.05）; there were four kinds of local aggregation models for water iodine in 78 townships（P< 0.01）. Three cluster areas of the water iodine were detected by space scanning,with three townships in Dongtou as the first high cluster areas,seven coastal townships in Cangnan as the second high cluster areas and 49 mountainous townships in Yongjia,Yueqing and Lucheng as the low cluster areas.@*Conclusion @#The iodine in drinking water in Wenzhou was low and exists spatial aggregation.