Predicting the grass pollen count from meteorological data with regard to estimating the severity of hayfever symptoms in Melbourne (Australia)

In Melbourne, Australia, grass pollen is the predominant cause of hayfever in late spring and summer. The grass pollen season has been monitored in Melbourne, using a Burkard spore trap, for 13 years (1975–1981, 1985 and 1991–1997). Total counts for grass pollen were highly variable from one season to the next (approximately 1000 to >8000 grains/m³). The daily grass pollen counts also showed a high variability (0 to approximately 400 grains/m³). In this study, the grass pollen counts of the 13 years (12 grass pollen seasons, extending from October to January) have been compared with meteorological data in order to identify the conditions that can determine the daily amounts of grass pollen in the air. It was found that the seasonal total of grass pollen was directly correlated with the rainfall sum of the preceding 12 months (1 September–31 August): seasonal total of grass pollen (counts/m³)=18.161 × rainfall sum of the preceding 12 months (mm) −8541.5 (r _s=0.74,P<0.005,n=12). The daily amounts of grass pollen in the air were positively correlated with the corresponding daily average ambient temperatures (P<0.001). The daily amount of grass pollen which was to be expected with a certain daily average temperature was linked to the seasonal total of grass pollen: in years with high total grass pollen counts, a lower daily average temperature was required for a high daily pollen count than in years with low total grass pollen counts. As the concentration of airborne grass pollen determines the severity of hayfever in sensitive patients, an estimation of daily grass pollen counts can provide an indication of potential pollinosis symptoms. We compared daily grass pollen counts with the reported symptomatic responses of hayfever sufferers in November 1985 and found that hayfever symptoms were significantly correlated to the grass pollen counts (P<0.001 for nasal,P<0.005 for eye symptoms). Thus, a combination of meteorological information (i.e. rainfall and temperature) allows for an estimation of the potential daily pollinosis symptoms during the grass pollen season. Here we propose a symptom estimation chart, allowing a quick prediction of eye and nasal symptoms that are likely to occur as a result of variations in meteorological conditions, thus enabling both physicians and patients to take appropriate avoidance measures or therapy.