| Tuberculosis is a chronic infectious disease caused by mycobacterium tuberculosis,which is a serious disease endangering human health.At present,China is still one of the countries with high burden of tuberculosis in the world.In the occupational distribution of tuberculosis patients in China,farmers account for a large proportion,and there is less research on the spatial-temporal characteristics of tuberculosis in county and district areas.This study selected a county in Liaoning as the target population,with farmers as the main population.Through descriptive analysis of the incidence of pulmonary tuberculosis in the county from 2011 to 2021,the general epidemic characteristics of pulmonary tuberculosis patients in this area in terms of age,gender,region,occupation,etc.are obtained.Further,spatial epidemiological analysis method is used to analyze the aggregation region and spatial-temporal aggregation characteristics of pulmonary tuberculosis in this area,providing a theoretical basis for the prevention and control of pulmonary tuberculosis in this area,It can also provide assistance for tuberculosis monitoring in areas dominated by farmers.MethodsData on confirmed cases of pulmonary tuberculosis from 2011 to 2021 were obtained through the disease prevention and control center of the county.The population data was obtained from the population served by the village clinic project subsidy distribution table in the county.The fourth level coordinate boundary map of the county was obtained from the municipal government’s official website,and other relevant information was obtained from the county government’s official website.The following studies were conducted based on the data obtained above.1.Calculate the incidence rate of tuberculosis,distribution of tuberculosis incidence population and other indicators in the county from 2011 to 2021 through case data and demography data,and conduct descriptive analysis;2.Use ArcGIS10.2 software to draw an excess hazard ratio map;Study the incidence and changes of pulmonary tuberculosis in various townships of the county from 2011 to 2021;3.Establish a global auto-correlation model using ArcGIS10.2 software to study the global spatial-temporal aggregation of pulmonary tuberculosis in the county from2011 to 2021;4.Establish a local auto-correlation model using ArcGIS10.2 software to study the local spatial-temporal aggregation of pulmonary tuberculosis in the county from2011 to 2021;5.Use Sa TSCAN9.6 spatial-temporal scanning to analyze the time,clustering area,and scope of tuberculosis incidence in the county from 2011 to 2021.Results1.From 2011 to 2021,there were 2101 reported cases of pulmonary tuberculosis in the county,1650 men and 451 women.The sex ratio of men and women was 3.66:1.The number of patients aged 50 to 60 is the highest,reaching 572,accounting for27.23% of the total cases.Farmers account for the largest proportion of occupations,reaching 1876 cases,accounting for 89.29% of the total cases,with the highest age of onset being 83 years old and the lowest being 24 years old.2.From 2011 to 2021,the incidence of tuberculosis in the county showed great fluctuations,forming a bimodal state.It peaked in 2017,fell back to the level of2011-2015 in 2018-2020,and reached a peak again in 2021,with the incidence far above the average level.The etiological positive cases were mostly concentrated from 2011 to 2013.Most of the etiological negative cases were concentrated from 2014 to2017.3.The incidence rate in the county varies greatly from year to year,with Dayushupu Town having the highest incidence rate(87.77 per 100,000)and Liulonggou Town having the lowest incidence rate(42.53 per 100,000).From 2011 to 2021,the incidence rate of Liulongtai Town was 1.75 times higher than that of the county for 6years,that of Dizangsi Manzu Township was 0.75 times lower than that of the county for 6 years,and that of the Manzu Township was 1.25 times higher than that of the county in 2016 and 2017,accounting for more than half of the county.The average annual incidence in Liulongtai Town,Dadingpu Manchu Town,Jiudaoling Town and Dyushupu Town was higher than that in the county.4.In the past 11 years,only 2015 saw significant spatial clustering of tuberculosis incidence in the county,while in the remaining years,there was no spatial auto-correlation.In 2015 and 2020,there was a situation where hot spots were clustered adjacent to each other,namely,Dayushupu Town and Waziyu Town,Dadingpu Manchu Township and Qianyang Town.Liulongtai Town has been a hot spot gathering area for5 years,followed by Jiudaoling Town,3 years as a hot spot gathering area,and 2townships have been a hot spot gathering area for 1 year,namely Qianyang Town and Toutai Manchu Town.There are only two towns with cold spots of disease,namely,Dizangsi Manchu Township in 2012 and Toutai Manchu Township in 2018.5.From 2014 to 2017,Waziyu Town,Shaohuyingzi Town,Gaotaizi Town,and Dayushupu Town formed First-order spatial-temporal aggregation;In 2016,Toutai Manchu Town and Jiudaoling Town formed Second-order spatial-temporal aggregation.Conclusions1.From 2011 to 2021,the incidence of tuberculosis in the county showed great fluctuations,forming a bimodal state.2.The risk of tuberculosis in the county is higher for males than females,and the proportion of patients between 40 and 60 years old is the largest,and the proportion of farmers is the largest.Therefore,special attention should be paid to TB prevention among male,middle-aged and peasant groups in the county.3.Dayushupu Town is a high incidence township of tuberculosis in the county,while Dizangsi Manchu Township is a low incidence township of tuberculosis.Identify the differences between the two towns to develop better tuberculosis prevention and control strategies.4.The average annual incidence in Liulongtai Town,Ddingpu Manchu Town,Jiudaoling Town and Dyushupu Town was higher than that in the county;From 2011 to2017,although the average annual incidence of tuberculosis in Liulongtai Town was not the highest in the county,it became the hot spot of tuberculosis incidence in the county for many times.There are spatial-temporal clusters in Waziyu Town,Shaohuyingzi Town,Gaotaizi Town,and Toutai Manchu Town;We should strengthen monitoring in these areas. |
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