ArticleJournal of medical Internet research2017
Evaluation of Pollen Apps Forecasts: The Need for Quality Control in an eHealth Service.
Article in Journal of medical Internet research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 44 citations in OpenAlex.
- Clinical Benefits of a Randomized Allergy App Intervention in Grass Pollen Sufferers: A Controlled Trial.Allergy · 2025Trial
- Evaluating the concordance of pollen forecasting apps against automated pollen monitoring: A single-site experience.The journal of allergy and clinical immunology. Global · 2026Article
- Digital health in allergy care: current practices, evidence, and future prospects.Frontiers in allergy · 2026Review
- Efficient and scalable training set generation for automated pollen monitoring with Hirst-type samplers.Scientific reports · 2025Article
- The present and future of digital health, digital medicine, and digital therapeutics for allergic diseases.Clinical and translational allergy · 2025Review
- Conception and pilot testing of a self-management health application for patients with pollen-related allergic rhinitis and allergic asthma-the APOLLO app.Scientific reports · 2023Article
- Real-life evidence in allergen immunotherapy: Moving forward with mHealth apps.Allergologie select · 2023Review
- Real-world data using mHealth apps in rhinitis, rhinosinusitis and their multimorbidities.Clinical and translational allergy · 2022Article
- mHealth and telemedicine utility in the monitoring of allergic diseases.Frontiers in allergy · 2022Review
- The applications of eHealth technologies in the management of asthma and allergic diseases.Clinical and translational allergy · 2021Review
- Turkish Guideline for Diagnosis and Treatment of Allergic Rhinitis (ART).Turkish archives of otorhinolaryngology · 2021Article
- Precise automatic classification of 46 different pollen types with convolutional neural networks.PloS one · 2020Article
- Causal Relationships Among Pollen Counts, Tweet Numbers, and Patient Numbers for Seasonal Allergic Rhinitis Surveillance: Retrospective Analysis.Journal of medical Internet research · 2019Article
- Next-generation ARIA care pathways for rhinitis and asthma: a model for multimorbid chronic diseases.Clinical and translational allergy · 2019Review
- How to do a clinical trial? Recommendations from the aerobiological point of view.The World Allergy Organization journal · 2019Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPollen forecasts are highly valuable for allergen avoidance and thus raising the quality of life of persons concerned by pollen allergies. They are considered as valuable free services for the public. Careful scientific evaluation of pollen forecasts in terms of accurateness and reliability has not been available till date.
objectiveThe aim of this study was to analyze 9 mobile apps, which deliver pollen information and pollen forecasts, with a focus on their accurateness regarding the prediction of the pollen load in the grass pollen season 2016 to assess their usefulness for pollen allergy sufferers.
methodsThe following number of apps was evaluated for each location: 3 apps for Vienna (Austria), 4 apps for Berlin (Germany), and 1 app each for Basel (Switzerland) and London (United Kingdom). All mobile apps were freely available. Today's grass pollen forecast was compared throughout the defined grass pollen season at each respective location with measured grass pollen concentrations. Hit rates were calculated for the exact performance and for a tolerance in a range of ±2 and ±4 pollen per cubic meter.
resultsIn general, for most apps, hit rates score around 50% (6 apps). It was found that 1 app showed better results, whereas 3 apps performed less well. Hit rates increased when calculated with tolerances for most apps. In contrast, the forecast for the "readiness to flower" for grasses was performed at a sufficiently accurate level, although only two apps provided such a forecast. The last of those forecasts coincided with the first moderate grass pollen load on the predicted day or 3 days after and performed even from about a month before well within the range of 3 days. Advertisement was present in 3 of the 9 analyzed apps, whereas an imprint mentioning institutions with experience in pollen forecasting was present in only three other apps.
conclusionsThe quality of pollen forecasts is in need of improvement, and quality control for pollen forecasts is recommended to avoid potential harm to pollen allergy sufferers due to inadequate forecasts. The inclusion of information on reliability of provided forecasts and a similar handling regarding probabilistic weather forecasts should be considered.
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