CAMS outreach to health professionals European pollen forecasts

Transcription

1 CAMS outreach to health professionals European pollen forecasts Mikhail Sofiev, Uwe Berger, Marje Prank, Julius Vira, Joaquim Arteta, Jordina Belmonte, Karl-Christian Bergmann, Françoise Chéroux, Hendrik Elbern, Elmar Friese, Carmen Galan, Regula Gehrig, Dmitry Khvorostyanov, Richard Kranenburg, Virginie Marécal, Frederik Meleux, Laurent Menut, Anna-Mari Pessi, Lennart Robertson, Olga Ritenberga, Viktoria Rodinkova, Annika Saarto, Arjo Segers, Elena Severova, Ingrida Sauliene, Pilvi Siljamo, Birthe Marie Steensen, Erik Teinemaa, Michel Thibaudon, Vincent-Henri Peuch

2 He inhaled a breath of humid morning breeze and let in nitrogen, oxygen, argon, xenon & radon, steam, carbon monoxide, nitrogen dioxide, tetra-ethyl lead, benzene, some mould spores, a bacteria fleet, anonymous body hair, a pigeon ectoparasite, anemophilous pollen, a drop of sulphur dioxide flown from a distant factory, and a particle of dust carried by the night sirocco. In other words he breathed air of the city (Stefano Benni "Achille piè veloce", Mondadori, Italy, 2003) Courtesy of G.D Amato

3 Outlook Introduction Pollen: an air pollutant causing human allergy CAMS pollen forecasts birch: done olive: ACPD grass: in progress Next steps hybrid model + expert forecasting symptom forecasting

4 Prevalence of allergenic rhinitis in Europe Mean prevalence 24,5% 33.6 Prevalence of respiratory allergy disorders (% of population) Austria Denmark Finland Germany Italy Netherlands Norw ay Spain Sw eden UK Adapted from Dahl, de Monchy, Chivato, Valovirta et al. Respir Med 2004; 98: Flags courtesy of used with permission

5 European Parliament Allergy Declaration (2015) During discussion and voting, EAACI offered sensitization testing for passers-by in the EP s building 350 tests made for most-common allergies 47% tested positive 178 MPs voted for the Declaration second strongest EP vote on environmental topics, ever

6 Timely proper medication reduces symptoms Mean medication score

7 CAMS approach: models + measurements Pollen modelling since mid-2000s developed into reliable forecasting and analysis tool in combination with measurements, shows good results in operational use 7-models-strong CAMS European ensemble (+3 coming) European Aeroallergen Network: started in 1970s well-organized, coordinated and standardized observations throughout Europe manual microscopic analysis: slow, expensive, long delays limited number of sites daily standard resolution (bi-hourly in some countries) Link to patients: load thresholds COST EUPOL unified approach: medical data, observations and modelling for clinically-relevant threshold of pollen concentrations

8 Season 2013: CAMS, 7 models CAMS regional ensemble for birch pollen standard CAMS domain, forecast parameters similar to chemical AQF birch, grass, olive pollen source terms of FMI daily forecasts available during the season 2017: extension to operational grass, olive Evaluation against European Aeroallergen Network (EAN) world-wide unique pollen network, >160 stations over Europe: voluntary unfunded contribution state of the art (manual microscopic analysis of pollen slides) sofar did not allow for NRT comparison and data assimilation no public funding: complicated arrangements to ensure sustainability Sofiev et al, ACP, 2015

9 Birch: seasonal pollen index & model scores Sofiev et al, ACP, 2015

10 Olive: 2014 season evaluation, ACPD

11 Grass: 2014 season, on-going Mean : Season start Season start error Season shape Observations: EAN

12 How / whom to deliver the forecasts? Pollen forecast maps: available Unverified model forecasts straight to allergy sufferers: cold welcome from medical community Existing downstream services based on CAMS-type forecasts involve expert assessment step Personalised automated services: under development

13 Norkko-pollen forecasts for Finland: University of Turku and FMI CAMS / Europe Helsinki / FMI High-resolution SILAM pollen forecasts FMI production machine DATA Pollen concentrations Rain T2m V10m DATA* Turku / Aerobiolgy Unit SmartMet editor Smart Met Pollen cnc* Checked/Corrected SILAM data

14 Pollen forecast at norkko.fi: Birch flowering started in the Southern Finland May 3, 2016 Former pollen forecasts New Norkko-pollen forecasts

15 Pollen forecast at norkko.fi: Birch flowering started in the Southern Finland May 3, 2016 Former pollen forecasts New Norkko-pollen forecasts

16 Next frontiers Improvement of the forecast quality and reliability Close interaction with EAN, support of the vital network Extension towards grass, olive, and ragweed: 2017 Interaction with chemical pollution Proceed towards personalized forecasting service Feasibility study by MUW, Charite, AUTH, and FMI

17 Feasibility and challenge Doable but same amount of data, similar average symptoms -> different performance LS-SVR Model, Cit.#80 Overall Symptoms Predicted Observed d: 0.79 ± 0.12 r: 0.68 ± 0.21 rmse: 3.83 ± 1.20 LS-SVR Model, Cit.#85 Overall Symptoms Predicted Observed d: 0.95 ± 0.03 r: 0.93 ± 0.05 rmse: 2.34 ± Day of Year More: Voukantis et al, IJB, 2014

18 Personalised Allergy SYmptom FOrecasting: PASYFO Downstream of CAMS, started Testbed in Lithuania and Latvia replicable all over Europe

19 Thank you for your attention!