The Study On The Pattern Of SARS Spread, Prevention And Control

Severe acute respiratory syndrome (SARS) is a new and emerging infectious disease. To clarify the pattern and dynamics of spread of its causal agent is the base of its effective prevention and control. Although some epidemiolgoical research on this subject has been done, there are still many aspects pending further clarification. Our study tries to further reveal the pattern of spread, transmission dynamics, molecular mechanism, and the prevention and control of SARS from five aspects: the accurate estimation of the incubation period of SARS and its influential factors, the effects of the meteorological condition and air pollution on the epidemic of SARS, the evaluation of intervention measures implemented in the SARS outbreak, the transmission dynamics of SARS, the molecular mechanism of transmission of SARS. Our findings in the study have provided the scientific basis for the prevention and control of SARS.1 Data and MethodsIn the study of the incubation period of SARS, 209 probable cases with definite contact history were selected as the research objects. By telephone investigation, their contact history and five possible factors influencing the incubation period, that is contact pattern, age, sex, profession, and region, were obtained. Of the 209 observation data of the incubation period, 161 data belonged to interval data, which came from multiple contact days. There was no ready-made method for the estimation of the incubation period with interval data. Our study has set up a maximum likelihood estimation method based on EM algorithm, which was applied in estimating the distribution parameter of the incubation period. Then we obtained the estimation of the mean of the incubation period. As well as the estimation of the mean, no ready-made method was found in the study on the influencing factors of the incubation period with interval data. We developed a generalized linear model based on EM algorithm to do univariate and multivariate analysis.In the second part of the dissertation, our aim was to find whether the meteorological elements and air pollution could affect the secondary attack rate of SARS. The data of SARS probable cases came from the nationwide case study database of SARS. The data of close contact history came from the nationwide survey data of people with close contact. The State Meteorology Bureau provided the meteorological data and the State Environment Protection Bureau provided the Air Pollution Index (API) data.The third part of the dissertation aims at the evaluation of the major intervention measures implemented in the SARS outbreak in China mainland and Beijing. The daily incidence of SARS came from nationwide SARS case study database. SARS incubation period distribution data came from the first part of the paper. Descriptive data of control measures were obtained through review of official documents and discussions with officials in MOH. In order to overcome the defects of the traditional evaluation methods based on report cases and incidence cases, we used a non-parameter maximum likelihood estimation method to reconstruct the SARS infectious curve of China mainland and Beijing, linking with the major control measures and the meteorological condition during the period of the spread of SARS in Beijing. By this means, we succeeded to explain and evaluate the effects of all sorts of control measures taken by China mainland and Beijing.In the fourth part of the paper, we studied the pattern of spread of causal agent of SARS and its transmission dynamics, and evaluated the major intervention measures implemented in Beijing quantitatively by establishing the transmission dynamics model of SARS. The model structure was founded on the basis of the latest research results about transmission dynamics and the knowledge of the epidemiological determinants of spread of casual agent of SARS. Genetic algorithm was employed to parameter estimation. Modeling epidemic process of SARS in Beijing was fulfilled in Markov chain model of transmission dynamics of SARS by using Vanguard Deci...