期刊文献+

Logistic模型在甲型H1N1流感大流行模拟中的应用 被引量:7

Application of Logistic model in simulating influenza A( H1N1) pandemic
原文传递
导出
摘要 目的 采用Logistic模型模拟甲型H1N1流感大流行过程. 方法 使用Logistic模型对长沙市甲型H1N1流感大流行疫情进行拟合,确定模型的参数;推导模型的3个关键点,对大流行疫情进行定量分期. 结果 长沙市甲型H1N1流感疫情可以分为“输入期”、“本地扩散期”、“大流行期”三个时期.“大流行期”的Logistic模型方程为:n=6878/1+e-(0.1166t-8.3859).模型模拟结果显示,“大流行期”分为三个阶段:①渐增期(第105~166 d),在该时期,疫情发展缓慢,是采取防控措施的最佳时期;②快增期(第167~ 188 d),此时期的防控难度较大,付出的防控成本可能收不到预期的效果;③缓增期(第189~244 d),在该时期,免疫屏障已逐步建立,采取防控措施效果将不明显. 结论 Logistic模型能较好地模拟城市甲型H1N1流感大流行过程. Objective To simulate the spreading process of influenza A (H1NI) pandemic with Logistic model. Methods Data about influenza A (H1N1) pandemic in Changsha were employed for simulating and confirming the parameters of the mod- al. 3 critical points of the model were deduced for dividing the pandemic into different stages. Results The influenza A (H1 N1 ) pandemic in Changsha could be divided into three phases, including "case - import phase", "local - case - spread phase" and "pandemic phase". Logistic model equation of "pandemic phase" was n=6878/1+e-(0.1166t-8.3859) The predictive results of the model showed that the pandemic was expected to experience three phrases: (1) increasingly growing stage (105th- 166th d), in which the epidemic developed slowly and could be intervened relatively easilyl (2) rapidly growing stage (167th- 188th d), in which it was difficult to take preventive measures and might pot receive expected effectiveness at greater cast; (3) relaxedly growing stage (189th- 244tb d), in which immunological barrier had been built up and the efficacy of the preventive measures was not significant. Conclusions Influenza A (H1N1) pandemic can be simulated perfectly by Logistic model.
出处 《实用预防医学》 CAS 2014年第9期1052-1055,共4页 Practical Preventive Medicine
基金 湖南省卫生厅科研项目(B2012-138) 长沙市科技局科研项目(K1205028-31)
关键词 LOGISTIC模型 甲型H1N1流感 大流行 Logistic model Influenza A (H1N1) Pandemic
  • 相关文献

参考文献20

  • 1Russell CJ, Webster RG. The genesis of a pandemic influenza virus [J]. Cell, 2005, 123(3):368 371.
  • 2Belser JA, Bridges CB, Katz JM. Past, present, and possible future human infection with influenza virus A subtype H7[J]. Emerg Infect Dis, 2009, 15(6):859 -865.
  • 3World Health Organization. Pandemic (H1N1) 2009- update 112 [EB/OL]. Available from: http://www, who. int/csr/don/2010-08-06/ en/index, html.
  • 4徐付霞,李秀敏,徐红梅,董永权.传染病的logistic模型研究[J].中国卫生统计,2007,24(2):168-170. 被引量:9
  • 5张良,时书丽.SARS传播的Logistic模型及其推广[J].数理医药学杂志,2004,17(2):97-98. 被引量:3
  • 6李雄.细菌性痢疾季节性分布数学模型[J].数理医药学杂志,2000,13(3):199-199. 被引量:2
  • 7中华人民共和国卫生部.甲型HINl流感诊疗方案(2009年第一至三版)[Z],2009.
  • 8Malthus TR. An essay on the principle of population[M]. J. Johnson. London, 1798.
  • 9崔党群.Logistic曲线方程的解析与拟合优度测验[J].数理统计与管理,2005,24(1):112-115. 被引量:214
  • 10Pearl R, Reed LJ. On the rate of growth of the population of the United States since 1790 and its mathematical representation[J]. Proc Nat Acad Sci, 1920, 6:275 288.

二级参考文献16

  • 1何文章,张宪彬.利用Logistic模型预测耐用消费品社会拥有量[J].数理统计与管理,1994,13(1):21-25. 被引量:22
  • 2阙少聪,潘宝骏,游明基.圆形分布构成比法计算疾病季节高峰月日的探讨[J].中国公共卫生,1994,10(5):217-219. 被引量:12
  • 3李应光,程琮,赵月英.细菌性痢疾发病季节特征统计分析[J].中国医院统计,1997,4(1):18-19. 被引量:1
  • 4王振中.逻辑斯谛曲线K值的四点式平均值估计法[J].生态学报,1987,7(3):193-198.
  • 5崔党群.生物统计学[M].北京:中国科学技术出版社,1994..
  • 6Press,S. J. &.S. Wilson. Choosing between logistic regression and discriminant analysis. Journal of the American Statistical Association, 1978, Vol. 73:699-705.
  • 7Pregibon,D. Logistic regression diagnostics. Annals of Statistics,1981,Vol. 8:705-724.
  • 8Berkson. Application of the logistic function to bio-assay. Journal of the American Statistical Association,1994,Vol. 39:357-365.
  • 9Press,S.J.&S.Wilson. Choosing between logistic regression and discriminant analysis. Journal of the American Statistical Association, 1978, Vol.73:699-705.
  • 10Pregibon,D. Logistic regression diagnostics. Annals of Statistics, 1981,Vol.8: 705-724.

共引文献222

同被引文献76

  • 1王义康,刘学艺.复合Logistic模型对SARS区域疫情的动态描述[J].中国计量学院学报,2005,16(2):159-162. 被引量:4
  • 2易静,杜昌廷,王润华,刘琍.应用灰色预测模型GM(1,1)对结核病发病率进行预测[J].重庆医科大学学报,2007,32(3):275-278. 被引量:16
  • 3徐付霞,李秀敏,徐红梅,董永权.传染病的logistic模型研究[J].中国卫生统计,2007,24(2):168-170. 被引量:9
  • 4吴家兵,张新平,张琴,马龙飞.基于人工神经网络方法对流感分级的判别[J].中国预防医学杂志,2007,8(5):655-656. 被引量:6
  • 5Huang X,Wei H,Wu S,et al.Epidemiological and etiological characteristics of hand,foot,and mouth disease in henan,china,2008-2013[J].Sci Rep,2015,5:8904.
  • 6Zhao YY,Jin H,Zhang XF,et al.Case-fatality of hand,foot and mouth disease associated with EV71:a systematic review and meta-analysis[J].Epidemiol Infect,2015,27:1-9.[Epub ahead of print].
  • 7Liu SL,Pan H,Liu P,et al.Comparative epidemiology and virology of fatal and nonfatal cases of hand,foot and mouth disease in China's Mainland from 2008 to 2014[J].Rev Med Virol,2015,25(2):115-128.
  • 8Song Y,Wang F,Wang B,et al.Time series analyses of hand,foot and mouth disease integrating weather variables[J].PLoS One,2015,10(3):0117296.
  • 9Verhulst P.F.Recherches mathématiques sur la loi d'accroissement de la population[J].Nouveaux mémoires de l'Academie Royale des Science et Belles-Lettres de Bruxelles,1845,18:1-41.
  • 10Heydari J,Lawless C,Lydall DA,et al.Fast Bayesian parameter estimation for stochastic logistic growth models[J].Biosystems,2014,122:55-72.

引证文献7

二级引证文献18

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部