Newson R, Strachan D, Archibald E, Emberlin J, Hardaker P, Collier C
Dept of Public Health Sciences, St George's Hospital Medical School, London, UK.
Eur Respir J. 1998 Mar;11(3):694-701.
Recent epidemics of acute asthma have caused speculation that, if their causes were known, early warnings might be feasible. In particular, some epidemics seemed to be associated with thunderstorms. We wondered what risk factors predicting epidemics could be identified. Daily asthma admissions counts during 1987-1994, for two age groups (0-14 yrs and > or = 15 yrs), were measured using the Hospital Episodes System (HES). Epidemics were defined as combinations of date, age group and English Regional Health Authority (RHA) with exceptionally high asthma admission counts compared to the predictions of a log-linear autoregression model. They were compared with control days 1 week before and afterwards, regarding seven meteorological variables and 5 day average pollen counts for four species. Fifty six asthma epidemics were identified. The mean density of sferics (lightning flashes), temperature and rainfall on epidemic days were greater than those on control days. High sferics densities were overrepresented in epidemics. Simultaneously high sferics and grass pollen further increased the probability of an epidemic, but only to 15% (95% confidence interval 2-45%). Two thirds of epidemics were not preceded by thunderstorms. Thunderstorms and high grass pollen levels precede asthma epidemics more often than expected by chance. However, most epidemics are not associated with thunderstorms or unusual weather conditions, and most thunderstorms, even following high grass pollen levels, do not precede epidemics. An early warning system based on the indicators examined here would, therefore, detect few epidemics and generate an unacceptably high rate of false alarms.
如果其病因已知,那么早期预警或许可行。尤其是,一些流行似乎与雷暴有关。我们想知道能够识别出哪些预测流行的风险因素。1987年至1994年期间,使用医院事件系统(HES)对两个年龄组(0至14岁以及≥15岁)的每日哮喘住院人数进行了统计。流行被定义为日期、年龄组和英国地区卫生局(RHA)的组合,其哮喘住院人数相较于对数线性自回归模型的预测异常高。将它们与前后各1周的对照日进行比较,涉及7个气象变量以及4种花粉的5天平均花粉计数。共识别出56次哮喘流行。流行日的天电(闪电)平均密度、温度和降雨量高于对照日。天电高密度在流行中占比过高。同时出现高天电密度和草花粉会进一步增加流行的可能性,但仅增至15%(95%置信区间为2%至45%)。三分之二的流行之前没有雷暴。雷暴和高草花粉水平先于哮喘流行出现的情况比偶然预期的更为频繁。然而,大多数流行与雷暴或异常天气状况无关,而且大多数雷暴,即使在高草花粉水平之后,也不会先于流行出现。因此,基于此处所研究指标的早期预警系统只能检测到少数流行,并且会产生高得令人无法接受的误报率。