| Hand, foot and mouth disease（HFMD） is a common infectious disease inchildren under the age of five. In recent years,it has several outbreaks in Asia.HFMDmay lead to irreversible nerve damage and even death. It’s the serious threat to publichealth. At present, neither vaccine no effects drugs can prevent hand, foot and mouthdisease. Therefore, epidemiological surveillance, and take positive and effectivepublic health interventions to prevent its outbreak is very meaningful.Early warningcan effectively improve the effectiveness of control measures. because we can takeearly intervention measures and by early warning, reducing the incidence andmortality of disease.Thus, it can reduce the disease’s impact on health.Objective:In order to understanding the incidence and its distribution characteristics of timeand space of foot and mouth disease inchangchun city. Analysis of the affectingfactors,such as geography, humanities and climate factors. We will select themeaningful factors into the seasonal model. To explore the difference of compositemodel and single model. In addition, combining with laboratory studies, we will havea comprehensive understanding of the virus types and main viral gene subtypecharacteristics in changchun area.All of above,it can provide theoretical basis forthe prevention and control.of hand, foot and mouth disease.Methods:①All the cases were stratified according to age,gender and area. Spss16.0was used to analyze the prevalence of hand, foot and mouth disease and populationdistribution. ArcGIS9.3softwarehe was used to show the incidence map in2008-2011, describing the spatial distribution characteristics of hand, foot and mouth disease.Time distribution characteristics were described by time sequence diagram.We used space-time clustering analysis by ArcGis9.3software to find hot aeras ofHFMD.②Poisson regression was used to explore, potential influencing factors offoot and mouth disease. All data was from geographic information sharing platformsystem. The cumulative number of HFMD cases in children under5years old in eachtownship was set as the outcome variable, and the number of children under5yearsold in each county was included as the offset. Potential environmental andsocio-economic factors, such as population density, children population density, typeof township, distance to the nearest national highway and to the nearest freeway, GDP,density of medical facilities and density of kindergartens for each township wereincluded as co-variables in the analysis. Cross correlation analysis was used to explorethe relationship between climate factors and HFMD and its lagging effect.③Asingle SARIMA model was created to forecast he number of hand-foot-mouth diseasecases. Then we discussed weather the model effectiveness was enhanced byimputing positive Influencing factors, Comparing the prediction and fitting effectbetween two models. Root mean square error (RMSE) was used to measure thedeviation of predicted value and actual value. Root mean square error (RMSE) wasused to evaluate the effectiveness of the model.④RT-PCR was used to detectenucleic acid of hand, foot and mouth disease samples. We separated EV71virus,by RD cells,getting16virus isolated strains for VP1gene amplification andsequencing.Then, homology comparison and the analysis of evolutionaryrelationships. was adopted to compare with standard strains.Result:①There was different incidence in different age groups,with86.8%of totalreported cases in children under5years old. There was highest incidence of a diseaseat the age of2,about4.63%. Scattered children accounted for65.4%of the totalnumber of reported cases. Boys had higher incidence than girls(χ2=130.03, P <0.001). Severe cases of children were younger than common cases of children(t=5.4, P<0.001). Every year, the reported of cases increased from about16weeks (at the end of April),at the peak of26to30weeks (July and August).The peaks forwardedyear by year in2008to2010. As digital map displayed,city hadthe highest incidence,and spreaded along the way to neighboring towns. Theincidence of hand, foot and mouth disease was highest at the road intersection parts.The results were that there were11Ⅰclass gathered areas according to space-timeclustering analysis. they were Shuangde township, Xinlicheng township,Yutantownship,Shengling township,Xingfu township, Xixin township,Yingjuntownship,Sandao township,Xinhu township,Fufeng township,Quannongshan township.The outbreak continued from April to June. There were3Ⅰ class gatheredareas,including Xinglongshan township,Luxiang township and Kalun township. Theoutbreak continued from April to September.The two aeras connected closely.②Multi-Poisson regression analysis results showed that the incidence of hand, foot andmouth disease had the relationship with the type of towns, the distance tothehighway and the GDP. City,close to highway,and high GDP had the highestincidence. Results showed that rainfall, the average air temperature, wind speed,sunshine time and vapor pressure was closely related to the weekly number of hand,foot and mouth disease with0-2weeks lagging time by cross correlation analysis.Thecorrelation coefficients were0.382,0.615,-0.256,0.316,0.683, respectively.The laggingtime were1week,2weeks,0week,0week,0week, respectively. The incidence of hand,foot and mouth disease had negatively relationship with wind speed and positivecorrelation with others.③Multivariate model SARIMA(2,1,2)(1,1,1)12had a largernumber of Smooth R2, smaller number of BIC and RMSE than a univariate model..Extrapolation forecast showed that multivariate model had the smaller average errorthan a univariate model, especially at the peak time.It was proved that Multivariatemodel SARIMA(2,1,2)(1,1,1)12l had better prediction effect.④952specimens weredetected during2008-2011. Positive rate of Pharyngeal swab, feces, anal swabwas，Sputum and herpes liquid were70.3%,67.8%,87.0%,66.7%respectively. The mainpathogens of HFMD was EV71during2008-2011.we choosed60specimens fromEV71positive samples randomly,and16strains were separated from the selected specimens. The separation rate was26.67%.16strains VP1region was for genesequencing. The results showed that there were high nucleotide and amino acidhomology between16strains of EV71isolates,96.2%～100.0%and98.7%～100%respectively.16isolated strains, had close genetic relationship except for JL/CC/10-2, JL/CC/10-3, JL/CC/09-413,with Nucleotide homology and amino acidhomology98.7~100%and100.0%, respectively. We Searched in the NCBIGenBank for the EV71virus subtype standard strains. Then,16strains VP1regionsequence were compared with the above standard strains.The results showed thatthey had the highest nucleotide sequence and amino acid sequence homology.withC4a subtype, with nucleotide sequence homology was96.0%~99.8%, the amino acidsequence homology was98.0%~100%;Evolutionary tree analysis showed that therewere three clades in16isolated strains. Of13strains formed Clade1in theevolutionary tree which had the shortest evolution distance. JL/CC/10-2、JL/CC/10-3formed clade2had father evolutionary distance than clade1. JL/CC/09-4formed clade3,had the furthest evolutionary distance.Conclusions:①There was different incidence in different age groups.There was highestincidence of a disease at the age of2. Boys had higher incidence than girls. Severecases of children were younger than common cases of children. As digital mapdisplayed,city had the highest incidence,and spreaded along the way toneighboring towns. The incidence of hand, foot and mouth disease was highest at theroad intersection parts.②The results were that there were11Ⅰclass gathered areasaccording to space-time clustering analysis. The outbreak continued from April toJune.Also there were3Ⅱclass gathered areas.The outbreak continued from April toSeptember.The two aeras connected closely.③Multi-Poisson regression analysisresults showed that the incidence of hand, foot and mouth disease had therelationship with the type of towns, the distance to the highway and the GDP.City,close to highway,and high GDP had the highest incidence. Results showed thatrainfall, the average air temperature, wind speed, sunshine time and vapor pressure was closely related to the weekly number of hand, foot and mouth disease with0-2weeks lagging time by cross correlation analysis. The incidence of hand, foot andmouth disease had negatively relationship with wind speed and positive correlationwith others.④Multivariate model SARIMA(2,1,2)(1,1,1)12had better predictioneffect after adding the meaningful influencing factors.⑤The main pathogens ofHFMD was EV71during2008-2011. Anal swabwas had the highest positive rate.There were high nucleotide and amino acid homology between16strains of EV71isolates. They had the highest nucleotide sequence and amino acid sequencehomology with C4a subtype. Evolutionary tree analysis showed that there were threeclades in16isolated strains. |
PDF Full Text Request