Applying Big Data To Analyze The Dynamics Of Tuberculosis Epidemics In China

BackgroundAlong with the rapid development of informatization in public health,there have been large relevant data resources after years of accumulation and it conforms to features of big data.There is no doubt that big data will bring great influence on the public health area and promote people to learn more about causes of diseases and health risk factors and improve the capacity of disease control,prediction and early warning to help people keep health.However the application of big data in public health is still in the stage of exploration and the value of public health data is far from being mined.Thus it's necessary to study appropriate data analysis methods and tools to mine useful knowledge from big data resources in public health.Although enormous progress has been made in tuberculosis(TB)prevention and control,the epidemic situation of TB in china is still serious and it remains an important public health problem for government to pay attention to.In the background of big data development,it may be useful to apply big data thought and method to the study of epidemic traits and risk factors of TB,in order to find more effective measures and strategies for TB control.ObjectiveTo explore the application of big data analysis methods to TB data from 2005 to 2014 in China,describing spatial cluster and cases flow situation.To analyze dynamic rules of TB broadcast and spread in spatial and provide new analysis thought and methods for data mining in public health surveillance system.MethodsCollecting reported cases data of TB in China between 2005 and 2014 and shape files of China map.To estimate kernel density of spatial point distribution of TB cases and then test with statistical method of local spatial autocorrelation.To plot spatial hotspots map todescribe spatial cluster distribution and change of TB cases.To analyze cases flow situation of TB according to the geocode of resident and reported places,showing direction and amount of cases flow.To describeand visualize cases output-input-hospital degree situation of every province for cases flowing across province.ResultsThe incidence of TB in China decreased from 2005 to 2014,but the speed of descending was slow after 2011.There is a seasonal trend in temporal distribution.There are much more male patients than female patients.TB mostly happens in population between 20 and 30 years old and farmers.In the distribution of spatial clusterof TB cases,most hotspots are in the southeast of China and several hotspots in southeast and XinJiang province.The spatial hotspots have expanded and enhancedin south of Guangdong,northwest of Xinjiang and north-central of Hunan.There are 79 percent of the cases reported in their own town in average.Others went to hospitals in other towns,cities or provinces,and its proportion increased from 2005 to 2014.The direction of cases flow is mainly to provincial capital in province,and from mid-western china to eastern big cities between provinces.Cases flow is mostly among neighboring province and toward grade ?,class A hospitals.The consecutive distribution of spatial hotspots of TB was analyzed with spatial cluster model,providing references for finding spatial hotspot areas.The direction and amount of cases flow was analyzed with cases flow model,reflecting the situation of dynamic spatial flow of TB cases better than traditional methods and showing the regional broadcast rules of TB.ConclusionThe epidemic situation of TB in China is still serious and the decrease of cases became slow,more effective control measures and strategies should be developed to deal with drug resistance and cases flow problems.Spatial hotspot regions should put forward specific prevention and control measures to resolve TB cluster problem.Targeted measures on local or flow cases respectively should be adopted based on the situation of cases flow in different areas.The areas between which cases flow occurred frequently should promote share of information,communication and cooperationto enforce the monitor and regulation of cases.Grade ?,class A hospitalsshould improve the treatment and regulation of TB cases.The analysis results of spatial cluster and cases flow models can reflect the distribution of spatial hotspots and cases flow more effectively than traditional methods.These models can be applied to others diseases study.