A Study On The Course And The Forecast Method Of Daily Incidence Of Severe Acute Respiratory Syndrome

Objective In order to find out some features and regular patterns during the period of SARS, we analyzed the incubation period, the onset time, and some important factors in the course of diease. Corresponding to those features and regular patterns, countermeasures and forecast method would be carried out to prevent the prevalence of SARS.Methods Analyze the incubation, the onset time, some important clinical factors in clincal period, of all SARS patients by descriptive analysis. Use the ARIMA model to fit the daily incidence during the prevalence of SARS in main China.Results Through the study on patients with the exact history of exposure to SARS-Cov, we find the median of incubation is 4 days, and its P95 is 14 days. From October 1, 2002 to January 7, 2004, the first case of SARS disease to the last case. About February 4, 2003, the first peak of onset came out and then the second peak came out on April 23, 2003. Since then, the daily incidence has appeared a sharp decline. In the first three onset days, there were 96.87% patients suffered fever and 82.80% patients had differential X-rays. The temperature became normal in the first two weeks. The count of WBC declined to the lowest level in the first week and recoverd to normal gradually till the third week. After three weeks, the incidence rate of chest distress began to decline. Respiratory frequency raise slowly, but not recovered to normal. The ARIMA mode l (1, 1, 0) can successfully fit the sequence of daily incidence. Conclusion The P95 of incubation of SARS is 14 days. We could consider that it is reasonable to institute 14 days for the quarantine or medical observation period in the prevention and control of SARS; In the prevalence of SARS, the daily incidence had a sharp decline after the second peak. The national policies maybe play an important role; Fever and differential X-rays are typical symptoms. With the decline of the count of WBC, we can distinguish SARS from other bacterial infectious diseases; The slow decline of respiratory frequency and the rate of chest distress indicates that the lung damage can not be recovered in a short period. The model ARIMA(1, 1, 0) can fit the sequence of daily incidence. We can conclude that the method of time series can be used in the infectious diseases.