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Analysis Of AIDS Epidemic Characteristics And Prediction Of Monthly Incidence Rate In China From 2004 To 2016

Posted on:2020-03-15Degree:MasterType:Thesis
Country:ChinaCandidate:Y X GuoFull Text:PDF
GTID:2404330575987610Subject:Social Medicine and Health Management
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Objectives : Understand the current epidemic situation and general epidemiological characteristics of AIDS epidemic in China from 2004 to 2016,establish a predictive model of AIDS epidemic trend,and predict the epidemic trend of AIDS in China in the next few years,and visualize the results of predictive analysis.This study can provide a reference for the departments concerned in HIV/AIDS epidemic monitoring,prevention and control measures formulation and resource allocation,as well as provide ideas and methods for the data analysis of other infectious diseases.Method:Based on the AIDS epidemic data of the statutory report infectious disease database of the Public Health Science Data Center of the Chinese Center for Disease Control and Prevention.Descriptive epidemiological methods were used to describe and analyze the distribution characteristics of AIDS in China from 2004 to 2016.The indicators used incidence rate,incidence number,composition ratio,development speed,growth rate,etc.The gray GM(1,1)model and AutoRegressive Integrated Moving Average(ARIMA)were established based on the monthly incidence data of AIDS in China from 2004 to 2015,using the monthly incidence data of 2016.Verification and forecasting the incidence of AIDS in China from 2017 to 2020.The prediction effect evaluation uses the squared error of prediction(SSE),mean square error(MSE),mean absolute error(MAE),mean absolute percentage error(MAPE),and mean square error(MSPE).Result : From 2004 to 2016,318,895 AIDS cases were reported in China,with an average annual incidence of 24,530 cases.The annual incidence rate was0.2349/100,000-3.9314/100,000.Among them,236,327 cases were male,accounting for74.11%.And 82,568 cases were women,the proportion was 25.89%.The male incidence increased from 0.1546/100,000 in 2004 to 3.0687/100,000 in 2016.The incidence rate of women increased from 0.0804/100,000 in 2004 to 0.8627/100,000 in2016.AIDS occurred in all age groups,with the highest number of cases in the 25-49 age group,a total of 199077 cases,accounting for 62.43%.Among them,the number of male cases was 147,742,accounting for 46.33% of all reported cases,and the number of female cases was 51,335,accounting for 16.10% of all reported cases.The occupation is dominated by farmers,domestic chores,unemployed workers and workers,with a total of 228,115 cases,accounting for 71.54% of the total population.In the regional distribution,the number of cases in the western region was 174,576,accounting for54.74%,which was higher than that in the east,middle and regions.In the prediction of the epidemic situation,the GM(1,1)model and the ARIMA model were established based on the monthly incidence of AIDS.By comparing the accuracy prediction indicators,the final selected optimal model was the ARIMA model,and its SSE=0.0088,MSE=0.0078,MAE=0.0224,MAPE=0.0677,MSPE=0.0066.The predicted result is that the monthly incidence rate from 2017 to 2020 is generally on the rise.Conclusions:The trend of AIDS epidemic in China is on the rise.The age of onset is mainly young and middle-aged from 25 to 49 years old.The number of cases and the incidence rate of males in each age group are higher than those in women.The occupational population is concentrated in farmers,domestic chores,and unemployed workers.The western region has the highest number of cases and the highest incidence rate.The provinces with high incidence are mainly in Guangxi,Yunnan and Sichuan provinces.Compared with the GM(1,1)model,the ARIMA model has higher prediction accuracy and is more suitable for the prediction of AIDS incidence in China.The forecast results show that the incidence of AIDS in China will continue to rise in the future,and the task of prevention and control will be more arduous.Relevant departments should strengthen prevention and control of AIDS.
Keywords/Search Tags:AIDS, Epidemic characteristics, Incidence prediction, Recommended measures
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