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Markov模型是用于描述某种复杂系统状态转移概率的数学模型。应用其理论和方法,可以对疾病随时间序列的变化规律分析研究,预测疾病发展变化的趋势据疫情资料记载:本市自1974年首次发现肾综合征出血热(EHF)病例,至1980年以前,EHF的病例呈零星散发,发病率均在1/10万以下。但80年代始,该病的发病率迅速增长,以致成为我市近几年来发病率最高的传染病之一。为摸清该病发展变化趋势,制定合理有效的防病策略,本文应用Markov模型对本市1980~1995年EHF的发病串进行了分析预测。一、方法根据本市1980~1995年EHF疫情报告资料,按时间序列将年发病率排表(表1)。确定各状态取值范围,并求出各状态的频数及初始概率(表2)。按各状态相互转移出现的频率,确定一阶转移概率的矩阵,然后根据矩阵乘法原则,求出k阶转移矩阵。并按各阶概率矩阵中最大转移概率作出预报。
The Markov model is a mathematical model used to describe the state transition probability of a complex system. According to the epidemiological data, the city has first discovered the cases of hemorrhagic fever with renal syndrome (EHF) since 1974. Until 1980 EHF cases were scattered sporadic, the incidence rates are less than 1/100000. However, since the 1980s, the incidence of the disease has rapidly increased, making it one of the most infectious diseases in our city in recent years. To find out the trend of the development of the disease and to develop a reasonable and effective disease prevention strategy, this paper uses Markov model to analyze the incidence of EHF from 1980 to 1995 in our city. First, the method According to the city from 1980 to 1995 EHF outbreak report data, the annual incidence of the time series of the schedule (Table 1). Determine the value range of each state, and find the frequency of each state and the initial probability (Table 2). According to the frequency of each state transition, determine the first-order transition probability matrix, and then calculate the k-th transition matrix according to the principle of matrix multiplication. And according to the maximum probability of transition matrix probability forecast.