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Ｍａｒｋｏｖ 模型是用于描述时间和状态都是离散的随机过程的数学模型，应用其理论可以对疾病发病率随时间序列变化规律进行分析和研究，预测发病率变化趋势，为预防和控制疾病提供依据。将伤寒的发病率划分为若干状态，计算各状态间的转移次数，确定转移概率矩阵，根据矩阵中最大转移概率作出预报。１９９８ 年的预测结果与实际完全吻合；预测结果显示在今后５ 年中徐州市伤寒发病率将由１／１０ 万～２／１０ 万上升到２／１０ 万～３／１０ 万的水平。用Ｍａｒｋｏｖ 模型进行预测，过程简明、容易操作，尤其在短期预测中准确度很高。
Markov model is a mathematical model used to describe the stochastic processes whose time and state are discrete. By applying the theory, the variation of disease morbidity with time series can be analyzed and studied, the trend of the incidence can be predicted, and the basis for prevention and control of diseases can be provided . The incidence of typhoid fever is divided into several states, the number of transitions between states is calculated, the transition probability matrix is determined, and the forecast is made based on the maximum transition probability in the matrix. The forecast results in 1998 are completely consistent with the actual ones. The forecast results show that the incidence rate of typhoid fever in Xuzhou will rise from 1/10 million to 2/10 million to 2/10 to 3/10 million over the next five years. Predicting with Markov model is concise and easy to operate, especially in the short-term prediction.