Acute asthma epidemics, weather and pollen in England, 1987-1994.
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.
Newson
R
R
Dept of Public Health Sciences, St George's Hospital Medical School, London, UK.
Strachan
D
D
Archibald
E
E
Emberlin
J
J
Hardaker
P
P
Collier
C
C
D000293:Adolescent; D000328:Adult; D000393:Air Pollutants / Q000009:adverse effects / Q000032:analysis; D001249:Asthma / Q000453:epidemiology* / Q000209:etiology*; D016022:Case-Control Studies; D002648:Child; D002675:Child, Preschool; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D004739:England / Q000453:epidemiology; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D007223:Infant; D016014:Linear Models; D008685:Meteorological Concepts; D006109:Poaceae; D011058:Pollen / Q000009:adverse effects; D012189:Retrospective Studies; D012307:Risk Factors; D014197:Trees; D014887:Weather
D000393:Air Pollutants