Application Of Three Mathematical Models In Predicting And Fitting Infectious Disease

ObjectiveAlthough the infectious disease control and prevention has been high up in the pictures, actually it presented the tendency of global epidemic and extension in recent years. This prompts us that infectious disease control and prevention will be still the key point of disease control and prevention for quite a long time. Moreover, it is hard for us to find the effectively academic support about the preventing and controlling measure. Therefore, theoretical researches for the epidemical law and forecast it before its outbreak and epidemic is provided with the important theoretical value. Also, it is a big significance of taking effective measure and having a definite object in view.The mathematical model of epidemiology has provided the research method for infectious disease prevention. And it is based on the epidemical process of the disease and the influence of correlative factors. With the mathematical expression which can quantificationally expatiate the epidemical process of disease , it can reflect the restriction relations of the quantity about disease ecology. At the same time, pestiferous process can also be reflected by this model . The mathematical model of epidemiology widely applies in each domain of epidemiology research. The model has the vital role at the research of diseases epidemic characteristic, the effect appraisal and forecast.This research attempts to take Z - D Phenomenon and autoregressive integrated moving average ( ARIMA) model as the essential method. And besides, taking the epidemic situation of Liaoning province from 1950 to 2002 as the basic data, it qualitatively and quantificationally describes the epidemical law of infectious disease control and prevention. This research appraises the epidemicsituation and effect of disease control measure. Moreover, to qualitatively and quantificationally predict and forecast the epidemic situation about diseased occurrence and development, it establishes the dynamic model. Furthermore, the research provides the theory basis for the scientific and effective measure by the family's gathering characteristic which analyses the outbreak of infectious disease , and also it fits the actual distribution by applying the Negative - binomial distribution.Methods1. Z - D Phenomenon was employed in studying the time series of the disease, and prediction was based on the extrapolation model.2. Annual incidence were analyzed over the period 1950 -2002 by the au-toregressive integrated moving average (ARIMA) model.3. Negative - binomial distribution are employed in studying the distribution of the-disease.Results1. Correlation analysis, which was conducted between monthly cumulative percentage and predictive ratio of increase to decrease in incidence rate at the best cut - off point, showed that the coefficient was negative ( R < 0). The effect of prediction by Z - D Phenomenon was satisfied.2. We defined ARIMA (1,1,1) converted by natural logarithm ,and the effect is shown that incidence is ascending slowly after 2003.3. The effect of application by Negative - binomial distribution is satisfied.Conclusion1. This research completely uses the infectious disease material about the epidemic situation of Liaoning provine from 1950 to 2002, which has integrity and continuity. In the practice, qualitatively and quantificationally forecast a-...