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WELCOME ON THE SEVENTH MINISTERIAL CONFERENCE ON ENVIRONMENT AND HEALTH

5-7 JULY 2023, BUDAPEST, HUNGARY

In Hungary, ragweed pollen is the most important biological allergen affecting approximately 15-20% of the population. Based on the surveys carried out by the National Public Health Center (NPHC), the number of allergic people is considerably increasing. As it is not possible to significantly reduce the concentration of ragweed pollen in a short period of time, pollen concentration forecast is essential to support allergic people during the pollen season.  Furthermore, information on the onset of the season is also needed to indicate the start of the preventive medication which takes preferably two weeks ahead of the appearance of symptoms. Different methods exist for predicting the onset of the ragweed pollen season such as the calendar-based method. Our investigations revealed that the by National Food Chain Safety Office provides the best input for the forecast of the onset.

During the ragweed pollen season the short-term (i.e. 3 days) ragweed pollen forecast is crucial. For this type of prediction in the main pollen season the Ragweed Pollen Alarm System (R-PAS) was developed. R-PAS is a joint collaboration among universities, public institutes and research centers to supply pollen information for different target groups (i.e. public, stakeholders) in the Pannonian biogeographical region, the hot spot of ragweed infestation in Europe. R-PAS was initiated by the National Public Health Institute in 2014. Recently, R-PAS provides daily ragweed pollen concentration forecast on a high resolution map. Categories based on symptom threshold values are depicted on the maps, in order to achieve a clear, simple and informative way of risk communication. The forecast maps are generated three times a week (Monday, Wednesday and Friday).

In addition, high resolution ragweed pollen concentration forecast maps are produced daily for Hungary. Besides the daily ragweed pollen concentration forecast, hourly forecast maps are also generated; thus, people can follow the daily patterns.

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