The Transmission Dynamics Of SARS

Since the SARS outbreak in 2003, many studies have been published on the mathematical modeling of its transmission and control. These researches used different modeling techniques and were mainly focused on estimating key epidemiological parameters of the outbreak and predicting the effect of control measures. Our study gives an overview of the SARS models developed so far. We integrated these models into a new mathematical model of SARS using the currently available more extensive and detailed data. We used the model to assess the impact of different diagnostic standards during the epidemic. The results can be helpful in the case of a new emerging infectious disease in general or a next emergence of a SARS-like disease in particular.The major research and achievements are as follows:1. We identified a total of published mathematical models on the SARS epidemic in the international and Chinese literatures. We classified the models according to their types, structures, underlying assumptions, definition and value of parameters, as well as their main predictions.2. Using the existing models and the epidemiological data currently available, an integrative model was developed that showed a good agreement between simulated and observed epidemiological patterns of the SARS outbreak. The model could be used to assess the efficacy of implemented intervention measures, thereby assuming different diagnostic standards in the epidemic process of the disease. It is showed that the disease can be effectively prevented and controlled by making use of certain diagnostic standards early in the epidemic and by conducting enough public health interventions.3. Using the same methodology, the transmission dynamics of West Nile virus was modeled. We determined the main characteristics of the infectious disease and calculated the formula of the basic reproductive number. To validate the model, actual epidemic data are required.Our analyses of the SARS transmission bring the theoretical basis for prevention and control of the next emergence of a SARS-like disease. The same method can be also used for other infectious diseases.