Study On The Factors Of SARS Epidemic

Background & Objectives Severe acute respiratory Syndromes (SARS) is anacute respiratory infectious disease, caused by a novel coronavirus which mainlyleaded to lung infection. SARS has spread among many countries. This disease ishighly contagious with its mortality highly and spreads quickly. SARS mainly spreadin big cities and resulted in serious influence to those regions. It has the value ofmedical and social to study the factors involved in SARS epidemic. This study aimedto explore potential factors and estimated the effects of the intervention measures ofSARS epidemic in the particular crowd of Hong Kong and in the population in HongKong and Beijing. We also predicted the daily number of SARS case in short term inHong Kong.Methods After collecting the daily incidence of confirmed SARS patients andintervention measures in Hong Kong and Beijing, and meteorology data of HongKong during the outbreak, the SARS database was established. A structuredmultiphase regression analysis, factor analysis-regression analysis were performed toidentify the relative factors involved in the emergence, prevention and elimination ofSARS. A structured logistic regression model was also used to estimate the potentialrisk [i.e. odds ratio (OR)] of the occurrence of a larger SARS epidemic with thesefactors. Curve fitting, Gamma Model, Time Series and Grey Model (1, 1) wereperformed to predict the daily number of SARS case in Hong Kong. The study itemsare as follows. The potential factors of SARS epidemic and their effects in theparticular crowd in Hong Kong (i.e. in the hospitals staff, the residents of AmoyGardens' estate and the community at large excluding Amoy Gardens) wererespectively estimated. In Hong Kong, the effects of the provision of protective gearfor hospital staff, quarantine of Block E in Amoy Gardens and multiple interventionmeasures were also evaluated. In addition, the potential factors of SARS transmissionand their effects were explored in the population in Hong Kong and Beijing, respectively. Finally, the daily number of SARS patients in short term in Hong Kongwas forecasted. The accuracy of number of daily SARS case predicted by statistic wasalso compared with that by grey systems.Result1. Factors of SARS spread in the particular crowdAdjusted the factors mentioned above, the reinforce of defense equipment to thefront line healthcare staff might reduce by an average of 5.4 cases occurred in hospitalstaff daily. The daily new cases in healthcare staff might increased by 3 when SARSpatients in ICU increased 100. The estimated risk of a larger SARS epidemic inhospital staff was 15.87-fold higher before strengthening the defense equipment to thefront line healthcare staff.The quarantine measure might reduce by an average of 9.2 cases occurred inAmoy Gardens daily. Before taking the quarantine measure, the estimated risk of alarger SARS epidemic in Amoy Gardens was 13.7-fold higher.The proportion of patients in ICUs increased 10％, the daily new cases in thecommunity increased 7.6 after adjusting the factors mentioned above. A 200increased in the multiplicative effect of the number of SARS infected patients in ICUsand the daily incidence of the infected hospital staff was related to 1.0 additional casein the community in a day. The daily new cases in the community might decrease byan average of 0.27 with epidemic day lapsed. When the air temperature was lowerthan 24.6℃, the estimated risk of a larger SARS epidemic in the community was12.82-fold higher than that over 24.6℃.2. Factors of SARS spread in the populationThe results of factor analysis-structured multiphase regression model and Logisticregression analysis showed that there were 3 common factors associated with SARSepidemic in Hong Kong, i.e. "Measure and Time Factor", "Daily Case Factor" and"Hospital Infection Factor". Among those factors, "Daily Case Factor" representingthe daily incidence might have the biggest influence to SARS epidemic in Hong Kong.The risk of a larger SARS epidemic in Hong Kong might increase by 35.3-fold forevery increase of one unit of "Daily Case Factor" after the longest incubation periodof 10 days. In Beijing SARS epidemic, we also found 3 common factors—"Hospital Infection Factor", "Measure and Time Factor" and "Hospitalization and DischargeFactor". The first one might be a very important factor in SARS epidemic in Beijing.The estimated risk of a larger SARS epidemic in Beijing might increase by 39.4-foldfor every increase of one unit of "Hospital Infection Factor".3. Prediction effect of daily number of SARS patients in Hong KongTime Series with the predicted error 0.29％was the optimal prediction method ofdaily accumulative cases during the SARS epidemic fastigium in Hong Kong. Whileγmodel with the predicted error 0.02％had the best predicted effect of dailyaccumulative cases during the descent stage, dynamic Grey Model (1, 1) was theoptimal predicted technology of the cases during the end and whole of epidemic, withthe error 0.03％and less than 2.0％, individually. In addition, Gamma model (with thepredicted error less than 3.0％) and Time Series (with the error less than 11.0％) werebetter predicted technologies of the incidence during SARS epidemic in Hong Kong.Conclusion1. Factors of SARS spread in the particular crowdThe air temperature, the reinforce of defense equipment, the epidemic time andthe SARS patients in ICUs are potential factors on SARS epidemic in hospital staff inHong Kong. The quarantine measure may stop SARS epidemic in Amoy Gardens'estate. The air temperature, the proportion of patients in ICUs, the epidemic day, andthe multiplicative effect of the number of SARS infected patients in ICUs and thedaily incidence of SARS infected hospital staff are potential factors on SARSepidemic in the community at large in Hong Kong.2. Factors of SARS spread in the populationIntervention measures and epidemic time were very important factors of SARStransmission. The main reason resulted in SARS outbreak was the number of SARSinfection source increased sharply. The amplified and doubling effect of hospitalinfection source greatly accelerated SARS spread.3. Prediction effect of daily number of SARS patients in Hong KongTime Series,γmodel and dynamic Grey Model (1, 1) were suitable to predictSARS epidemic in short-term in Hong Kong.