合肥市疟疾发病预测数学模型应用及发病现况的流行病学研究

发布时间：2019-02-20 10:07

【摘要】：目的探讨ARIMA模型及Markov模型预测合肥市疟疾发病率的可行性，预测疟疾发病趋势，为全市的疟疾防治工作提供科学依据。方法采用SPSS13.0软件对合肥市1991-2010年疟疾逐月发病率建立ARIMA模型，利用2011年疟疾月发病率对模型参数进行校正，从而预测2012年疟疾月发病率；用Excel软件对合肥市1990-2011年疟疾发病率建立Markov模型，预测合肥市2012-2013年的疟疾发病率。结果模型ARIMA(1,1,1)(1,1,0)_12是合肥市疟疾拟合的较优模型，预测值与实际值基本吻合，且实际值均在预测值95%可信区间范围内，其外推预测的平均相对误差为2.57%；利用建成的Markov模型预测合肥市2012-2013年疟疾发病率均在1/10万-3.5/10万之间，而2012年实际发病率为0/10万，，预测结果与实际情况不符。结论用时间序列模型对疟疾发病情况的拟合结果满意，预测效果良好，可用于预测未来疟疾的变动趋势，为疟疾预防控制措施的制定提供重要依据；而本研究中模拟的Markov模型不适合预测合肥市疟疾的发病情况。目的了解2005-2009年安徽省合肥市疟疾的流行特点，为制定防控策略提供依据。方法借助中国疾病预防控制信息系统收集疟疾发病统计数据，对合肥市2005-2009年发病资料进行描述性分析,借助合肥市统计信息公众网收集气象资料进行多元相关和多元逐步回归分析合肥市本地发病与各种气象因素之间的关系。结果合肥市2005-2009年共报告疟疾414例，年平均报告发病率为1.57/10万，发病高峰为2007年，发病率为2.05/10万；发病季节性特点显著，时间主要集中在7-10月份，占66.91%；414例报告病例中男性293人，女性121人，男女年均发病率分别为2.39/10万人和1.08/10万人，其差异具有统计学意义（χ2=11.504,P=0.001）；发病以21-40岁人群病例数最多，占总病例数的37.68%；职业分布以农民为主（23.9%）；月均气温与疟疾发病数呈强正相关，相关系数为0.734（P=0.000），相对湿度与疟疾月均发病数呈正相关，相关系数为0.384（P=0.002），2个月之前的降雨量与疟疾发病相关，其相关系数为0.559（P=0.000）。结论合肥市疟疾的发生存在明显的季节性和性别差异。在流行季节应大力开展疟疾防治知识宣传，减少感染机会，控制疟疾的发生和流行。
[Abstract]:Objective To study the feasibility of ARIMA model and Markov model to predict the incidence of malaria in Hefei. Methods The incidence of malaria in Hefei from 1991 to 2010 was established by using the SPSS13.0 software. The model parameters were corrected by the incidence of malaria in 2011, and the incidence of malaria in 2012 was predicted. The Markov model was established for the incidence of malaria in Hefei from 1990 to 2011 with Excel software. Model and prediction of the incidence of malaria in Hefei in 2012-2013 The result model ARIMA (1, 1, 1) (1, 1, 0) _ 12 is the better model of the malarial fitting in Hefei. The predicted value is in agreement with the actual value, and the actual value is within the 95% confidence interval of the predicted value, and the average relative error of the extrapolated prediction is 2. According to the established Markov model, the incidence of malaria in Hefei in 2012-2013 was between 1/ 10 and 3. 5/ 10, and the actual incidence in 2012 was 0/ 100,000, the results of the forecast and the actual situation Conclusion The time series model can be used to predict the change trend of malaria in the future and to develop the control measures for malaria prevention. The Markov model simulated in this study is not suitable for predicting the malaria in Hefei Objective To study the epidemic characteristics of malaria in Hefei, Anhui, from 2005 to 2009, and to develop the anti-malaria control system. The method provides the basis for the control strategy. According to the method, the disease incidence statistics of malaria are collected by means of the Chinese disease prevention and control information system, and the incidence of the disease in Hefei, 2005-2009 The data was analyzed by means of multi-correlation and multiple stepwise regression analysis of the meteorological data collected by the public network of Hefei Statistical Information. The results showed that 414 cases of malaria were reported in Hefei from 2005 to 2009. The annual average incidence of malaria was 1. 57/ 100 000. The incidence peak was 2007. The incidence rate was 2.05/ 1 million. The seasonal characteristics of the disease were significant, the time was mainly in July to October, accounting for 66. 91%, and 414 cases of the reported cases were male There were 293 people and 121 women. The average annual incidence of male and female was 2.39/ 100,000 and 1.08/ 100,000 respectively. The difference was of statistical significance (Sup2 = 11. 504, P = 0.001); the number of cases in the 21-40 year-old group was the largest, accounting for 37. 68% of the total number of cases; the occupational distribution was dominated by the farmers (23. 9%); the monthly average temperature The correlation coefficient was 0.734 (P = 0.000), and the relative correlation coefficient was 0.384 (P = 0.002). The correlation coefficient was 0. 5. 59 (P = 0.000). Conclusion The occurrence of malaria in Hefei There are obvious seasonal and gender differences. In the epidemic season, the prevention and control knowledge of malaria should be carried out to reduce the infection.
【学位授予单位】：安徽医科大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：R531.3

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