Correlation Engine 2.0
Clear Search sequence regions

  • allergens (2)
  • asthma (6)
  • australia (1)
  • disease outbreaks (1)
  • humans (1)
  • outbreaks (2)
  • particles (6)
  • patient (1)
  • pollen (10)
  • pollen (2)
  • Sizes of these terms reflect their relevance to your search.

    When exposed to convective thunderstorm conditions, pollen grains can rupture and release large numbers of allergenic sub-pollen particles (SPPs). These sub-pollen particles easily enter deep into human lungs, causing an asthmatic response named thunderstorm asthma (TA). Up to now, efforts to numerically predict the airborne SPP process and to forecast the occurrence of TAs are unsatisfactory. To overcome this problem, we have developed a physically-based pollen model (DREAM-POLL) with parameterized formation of airborne SPPs caused by convective atmospheric conditions. We ran the model over the Southern Australian grass fields for 2010 and 2016 pollen seasons when four largest decadal TA epidemics happened in Melbourne. One of these TA events (in November 2016) was the worldwide most extreme one which resulted to nine deaths and hundreds of hospital patient presentations. By executing the model on a day-by-day basis in a hindcast real-time mode we predicted SPP peaks exclusively only when the four major TA outbreaks happened, thus achieving a high forecasting success rate. The proposed modelling system can be easily implemented for other geographical domains and for different pollen types. Copyright © 2022 Elsevier B.V. All rights reserved.


    Slobodan Nickovic, Slavko Petković, Luka Ilić, Goran Pejanović, Zoran Mijić, Alfredo Huete, Guy Marks. Prediction of airborne pollen and sub-pollen particles for thunderstorm asthma outbreaks assessment. The Science of the total environment. 2023 Mar 15;864:160879

    Expand section icon Mesh Tags

    Expand section icon Substances

    PMID: 36521601

    View Full Text