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Epidemic Characteristics Of Hand-Foot-Mouth Disease In The Three Gorges Region From 2009 To 2016 And The Construction Of ARIMA Model

Posted on:2021-03-27Degree:MasterType:Thesis
Country:ChinaCandidate:H LiFull Text:PDF
GTID:2404330632950939Subject:Public health
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ObjectiveThrough the comprehensive analysis of HFMD epidemic situation in reservoir areas andnon-reservoir areas in the three gorges area from 2009 to 2016,To understand the epidemic characteristics and changing trend of HFMD in the three gorges area.The comparison of the characteristics of HFMD between the three gorges reservoir area and non-reservoir areas provides a scientific basis for the formulation of disease-related prevention and control strategies.Moreover,ARIMA epidemic early warning model of HFMD was constructed by time series analysis in reservoir areas and non-reservoir areas.Make a scientific prediction of the incidence of HFMD in non-reservoir areas of the three gorges region.It provides reference for the future monitoring and early warning in this region.MethodAccording to this study,the regions include Chongqing City and Yichang City in Hubei Province in the three gorges region.Chongqing and Yichang are divided into 25 reservoir areas and 26 non-reservoir areas according to whether they are in the distribution area of the three gorges reservoir.Data of hand-foot-mouth disease cases and laboratory testing in Chongqing and Yichang were collected from 2009 to 2016 in the infectious disease report information management system.Excel2010 and SPSS 17.0 were used for data analysis.Descriptive analysis and statistical comparison of the epidemic characteristics of HFMD in reservoir area and non-reservoir area were conducted respectively.With Autoregressive moving average model(ARIMA model),the monthly incidence of HFMD in reservoir counties and non-reservoir counties from January 2009 to December 2016 was modeled,and the monthly incidence of HFMD in reservoir counties from January to December 2017 was predicted.Results(1)A total of 310,111 cases of HFMD were reported in the three gorges region from 2009 to 2016,including 223,795 cases in the reservoir area and 86316 cases in the non-reservoir area.There were 662 severe cases,including 416 cases in the reservoir area and 246 cases in the non-reservoir area.A total of 146 deaths were reported,including 101 in the reservoir area and 46 in the non-reservoir area.The average annual reported morbidity in the three gorges area was 117.59/100,000,with 145.66/100,000 in the reservoir area and 78.42/100,000 in the non-reservoir area.There were two obvious seasonal peaks in the reservoir area and non-reservoir area every year,which were from April to June and October to December respectively.The reported age morbidity was highest in the 1-year-old group,followed by 3-year-old group in the reservoir area and non-reservoir area.(2)From 2009 to 2016,children under 5 years old were the main age group of HFMD reported in the three gorges region,accounting for 98.26%of the total number of cases.The incidence of HFMD in both the reservoir area and non-reservoir area was the highest in the 1 year old group,followed by the 3 year old group,which decreased significantly after 5 years old.The occupational distribution was dominated by scattered children and preschool children,accounting for 61.5%and 34.8%of the total incidence,respectively.(3)From 2009 to 2016,a total of 16,902 laboratory-confirmed cases were reported in the three gorges area,including 16,481 cases of mild diseases and 421 cases of severe diseases(including 88 deaths).EV71,CoxA16 and other enteroviruses accounted for 36.34%,27.99%and 35.67%of laboratory-confirmed cases,respectively.Other enteroviruses predominate in mild HFMD in the three gorges area and reservoir area.The EV71 serotype predominated in non-reservoir mild disease.Severe cases and death cases in the reservoir area and non-reservoir area were the dominant EV71 serotype.(4)The incidence of the disease in the reservoir area was higher than that in the non-reservoir area.The proportion of severe cases reported in the reservoir area was 0.19%,and that of non-severe cases was 0.28%,with statistically significant difference(χ2=28.73,P<0.01).The CFR of the reservoir area was 0.053%and that of the non-reservoir area was 0.045%,with no statistical significance(χ2=0.876,P=0.349).Severe cases in the reservoir area were dominated by EV71(79.17%),while non-severe cases were dominated by EV71(47.37%)and other enteroviruses(35.34%).The composition of other enteroviruses(37.83%)in reservoir areas and EV71(41.19%)were higher in mild cases than in non-reservoir areas.(5)Prediction effect:ARIMA(2,0,0)(0,1,2)12 was used as the prediction model in the reservoir area.The prediction results were basically consistent with the actual incidence,and the fitting effect was moderate.The non-reservoir prediction model ARIMA(1,0,0)(0,1,2)12 was consistent with the actual incidence.Non-reservoir prediction model ARIMA(1,0,0)(0,1,2)12,the prediction results were consistent with the actual incidence,and the fitting effect was good.The use of ARIMA model to predict HFMD incidence in reservoir areas and non-reservoir areas can provide scientific basis for policy formulation,monitoring and early warning.ConclusionFrom 2009 to 2016,the incidence of HFMD in three gorges was on the rise.The incidence of hand,foot and mouth in non-reservoir areas is lower than that in reservoir areas,but the proportion of severe cases is higher.There were differences in the pathogen composition of HFMD in non-reservoir areas,but EV71 was dominant in both severe and fatal cases,while the composition of other enteroviruses increased.The main cities in the reservoir area and children under 3 years old are the key areas for prevention and control of HFMD.To strengthen the surveillance of foot and mouth disease etiology in the three gorges reservoir area and non-reservoir area,and further classify other enteroviruses,so as to provide the basis for epidemic risk assessment.
Keywords/Search Tags:Three gorges area, HFMD, Analysis of epidemic characteristics, Etiological characteristics, Time series analysis
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