手足口病流行与暴发的气象因素预警界值研究
|
摘要
目的探讨气象因素与手足口病(hand foot and mouth disease,HFMD)流行和暴发的相关性,并提出预警界值。方法选取广州市为研究现场,分别以2010-2017年HFMD流行和暴发情况为结局变量,以平均气温、总和降雨量和相对湿度为解释变量,经交叉相关分析后应用分类和回归树(classification and regression trees,CART)模型进行预警界值分析。结果 2010-2017年广州市共报告494 359例HFMD病例,平均每年报告(61 795±15 232)例,其中24个月疫情呈现暴发状态。月平均气温滞后0期(0.64,P<0.05)和月平均相对湿度滞后1期(0.59,P<0.05)与月发病数的相关系数最高。月发病例数的气象预警界值回归树分析中,月平均气温滞后0期≥22.3℃且月平均相对湿度滞后1期≥82.37%时RR值最大,为2.06(95%CI:1.99～2.13)。月度暴发的气象预警界值分类树分析中,月平均气温滞后0期≥24.6℃且月平均相对湿度滞后1期≥83.92%时RR值最大,为3.54(95%CI:3.03～4.03)。结论基于CART模型分析HFMD流行与暴发的气象因素预警界值,可有效提升监测和预警的质量。
Objective To explore the correlation of climate variables with the epidemic and outbreak of hand-foot-mouth disease(HFMD), and to propose early-warning thresholds of meteorological parameters. Methods This study was conducted in Guangzhou.The epidemic and outbreak of HFMD between 2010 and 2017 were taken as the outcome variables with average temperature, total rainfall and relative humidity as explanatory variables.The classification and regression trees(CART) model was applied for early-warning thresholds value determination after the cross-correlation analysis. Results During the study period, a total of 494 359 cases with HFMD were reported in Guangzhou, with an average annual report of 61 795±15 232 cases, and HFMD outbreaks were recorded in 24 months.The monthly average temperature at phase lag 0(0.64, P<0.05) and the monthly average relative humidity at phase lag 1(0.59, P<0.05) were closely correlated with the monthly case numbers of HFMD with the highest correlation coefficients.CART analysis for the early-warning thresholds of climate parameters with the monthly number of cases showed that the RR value reached its highest of 2.06(95% CI: 1.99-2.13) when the monthly average temperature in phase lag 0 ≥22.3 ℃ and the monthly average relative humidity at phase lag 1 ≥82.37%. CART analysis for the early-warning thresholds of climate parameters with the monthly number of HFMD outbreaks showed that the RR value reached its highest of 3.54(95% CI: 3.03-4.03) when the average monthly temperature at phase lag 0 ≥24.6 ℃ and the relative humidity at phase lag 1 ≥83.92%. Conclusions The early warning thresholds of meteorological parameters based on the CART model analysis for the epidemic and outbreak of HFMD can effectively improve the quality of disease monitoring and early warning.
Objective To explore the correlation of climate variables with the epidemic and outbreak of hand-foot-mouth disease(HFMD), and to propose early-warning thresholds of meteorological parameters. Methods This study was conducted in Guangzhou.The epidemic and outbreak of HFMD between 2010 and 2017 were taken as the outcome variables with average temperature, total rainfall and relative humidity as explanatory variables.The classification and regression trees(CART) model was applied for early-warning thresholds value determination after the cross-correlation analysis. Results During the study period, a total of 494 359 cases with HFMD were reported in Guangzhou, with an average annual report of 61 795±15 232 cases, and HFMD outbreaks were recorded in 24 months.The monthly average temperature at phase lag 0(0.64, P<0.05) and the monthly average relative humidity at phase lag 1(0.59, P<0.05) were closely correlated with the monthly case numbers of HFMD with the highest correlation coefficients.CART analysis for the early-warning thresholds of climate parameters with the monthly number of cases showed that the RR value reached its highest of 2.06(95% CI: 1.99-2.13) when the monthly average temperature in phase lag 0 ≥22.3 ℃ and the monthly average relative humidity at phase lag 1 ≥82.37%. CART analysis for the early-warning thresholds of climate parameters with the monthly number of HFMD outbreaks showed that the RR value reached its highest of 3.54(95% CI: 3.03-4.03) when the average monthly temperature at phase lag 0 ≥24.6 ℃ and the relative humidity at phase lag 1 ≥83.92%. Conclusions The early warning thresholds of meteorological parameters based on the CART model analysis for the epidemic and outbreak of HFMD can effectively improve the quality of disease monitoring and early warning.
引文
[1] 杨芳,于石成,张菊英,等.2008—2011年我国大陆地区重症手足口病流行特征分析 [J].疾病监测,2013,28(11):888-893.
[2] An Q,Wu J,Fan X,et al.Using a negative binomial regression model for early warning at the start of a hand foot Mouth disease epidemic in dalian,Liaoning Province,China [J].PloS One,2016,11(6):e0157815.
[3] 蔡春燕,王娟,王忠敏,等.2011-2012年杭州市儿童手足口病流行病学特征及重症病例危险因素分析 [J].中国预防医学杂志,2016,17(6):419-423.
[4] 姚一泓,霍达,贾蕾,等.手足口病预警模型及其应用现状 [J].国际病毒学杂志,2018,29(2):1366-1139.
[5] Liu S,Chen J,Wang J,et al.Predicting the outbreak of hand,foot,and mouth disease in Nanjing,China:a time-series model based on weather variability [J].Int J Biometeorol,2018,62(4):565-574.
[6] 姜璎慈,李颖.气象条件与手足口病发病情况的反向传播神经网络模型构建 [J].疾病监测,2018,33(12):1026-1031.
[7] 曹磊,闫云,张义,等.决策树模型在手足口病重症预测中的应用 [J].中国热带医学,2018,18(1):57-62.
[8] 陈纯,肖新才,谢华萍,等.2008-2013年广州市手足口病流行病学特征研究 [J].疾病监测,2014,29(12):964-968.
[9] 杜志成,张王剑,于石成,等.广东省手足口病气象危险因素阈值效应的研究 [J].现代预防医学,2015,42(19):3457-3460.
[10] 景钦隆,罗雷,李晓宁,等.布雷图指数、输入病例、气象因子与登革热本地流行的关系研究 [J].华南预防医学,2015,41(5):401-406.
[11] Hutwagner L,Thompson W,Seeman GM,et al.The bioterrorism preparedness and response Early Aberration Reporting System (EARS) [J].J Urban Health,2003,80(2 Suppl 1):i89-96.
[12] 李中杰,廖一兰,赖圣杰,等.传染病暴发探测时间模型和时空模型的应用效果比较 [J].中华流行病学杂志,2011,32(5):436-441.
[13] Onozuka D,Hashizume M.The influence of temperature and humidity on the incidence of hand,foot,and mouth disease in Japan [J].Sci Tobal Environ,2011,410-411:119-125.
[14] Dowell SF.Seasonal variation in host susceptibility and cycles of certain infectious diseases [J].Emerg Infect Dis,2001,7(3):369-374.
[15] 刘云霞,董承红,王丽春,等.不同温度培养的3株EV71毒株的增殖动力学分析 [J].中国生物制品学杂志,2010,23(9):974-977.
[16] 赵佳楠,薛超,仲连发,等.重庆市手足口病接触率及感染力分析 [J].科学通报,2016,61(22):2475-2482.
[17] 李月,郭芳,黄晓敏.随州市手足口病流行特征与气象因素的关系研究 [J].中国预防医学杂志,2016,17(7):557-558.
[18] Greene SK,Peterson ER,Kapell D,et al.Daily reportable disease spatiotemporal cluster detection,New York City,New York,USA,2014-2015 [J].Emerg Infect Dis,2016,22(10):1808-1812.
[19] Urashima M,Shindo NN.Seasonal models of hepangina and hand-foot-mouth disease to simulate annual fluctuations in urban warming in Tokyo [J].Jpn J Infect Dis,2003,56(2):48-53.
[20] 韦懿芸.向量自回归模型在手足口病发病与气象因素的动态分析中的应用 [J].中国卫生统计,2013,30(6):794-797.
[21] Takahashi S,Liao Q,Van Boeckel TP,et al.Hand,foot,and mouth disease in China:modeling epidemic dynamics of enterovirus serotypes and implications for vaccination [J].PLoS Med,2016,13(2):e1001958.
[2] An Q,Wu J,Fan X,et al.Using a negative binomial regression model for early warning at the start of a hand foot Mouth disease epidemic in dalian,Liaoning Province,China [J].PloS One,2016,11(6):e0157815.
[3] 蔡春燕,王娟,王忠敏,等.2011-2012年杭州市儿童手足口病流行病学特征及重症病例危险因素分析 [J].中国预防医学杂志,2016,17(6):419-423.
[4] 姚一泓,霍达,贾蕾,等.手足口病预警模型及其应用现状 [J].国际病毒学杂志,2018,29(2):1366-1139.
[5] Liu S,Chen J,Wang J,et al.Predicting the outbreak of hand,foot,and mouth disease in Nanjing,China:a time-series model based on weather variability [J].Int J Biometeorol,2018,62(4):565-574.
[6] 姜璎慈,李颖.气象条件与手足口病发病情况的反向传播神经网络模型构建 [J].疾病监测,2018,33(12):1026-1031.
[7] 曹磊,闫云,张义,等.决策树模型在手足口病重症预测中的应用 [J].中国热带医学,2018,18(1):57-62.
[8] 陈纯,肖新才,谢华萍,等.2008-2013年广州市手足口病流行病学特征研究 [J].疾病监测,2014,29(12):964-968.
[9] 杜志成,张王剑,于石成,等.广东省手足口病气象危险因素阈值效应的研究 [J].现代预防医学,2015,42(19):3457-3460.
[10] 景钦隆,罗雷,李晓宁,等.布雷图指数、输入病例、气象因子与登革热本地流行的关系研究 [J].华南预防医学,2015,41(5):401-406.
[11] Hutwagner L,Thompson W,Seeman GM,et al.The bioterrorism preparedness and response Early Aberration Reporting System (EARS) [J].J Urban Health,2003,80(2 Suppl 1):i89-96.
[12] 李中杰,廖一兰,赖圣杰,等.传染病暴发探测时间模型和时空模型的应用效果比较 [J].中华流行病学杂志,2011,32(5):436-441.
[13] Onozuka D,Hashizume M.The influence of temperature and humidity on the incidence of hand,foot,and mouth disease in Japan [J].Sci Tobal Environ,2011,410-411:119-125.
[14] Dowell SF.Seasonal variation in host susceptibility and cycles of certain infectious diseases [J].Emerg Infect Dis,2001,7(3):369-374.
[15] 刘云霞,董承红,王丽春,等.不同温度培养的3株EV71毒株的增殖动力学分析 [J].中国生物制品学杂志,2010,23(9):974-977.
[16] 赵佳楠,薛超,仲连发,等.重庆市手足口病接触率及感染力分析 [J].科学通报,2016,61(22):2475-2482.
[17] 李月,郭芳,黄晓敏.随州市手足口病流行特征与气象因素的关系研究 [J].中国预防医学杂志,2016,17(7):557-558.
[18] Greene SK,Peterson ER,Kapell D,et al.Daily reportable disease spatiotemporal cluster detection,New York City,New York,USA,2014-2015 [J].Emerg Infect Dis,2016,22(10):1808-1812.
[19] Urashima M,Shindo NN.Seasonal models of hepangina and hand-foot-mouth disease to simulate annual fluctuations in urban warming in Tokyo [J].Jpn J Infect Dis,2003,56(2):48-53.
[20] 韦懿芸.向量自回归模型在手足口病发病与气象因素的动态分析中的应用 [J].中国卫生统计,2013,30(6):794-797.
[21] Takahashi S,Liao Q,Van Boeckel TP,et al.Hand,foot,and mouth disease in China:modeling epidemic dynamics of enterovirus serotypes and implications for vaccination [J].PLoS Med,2016,13(2):e1001958.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |