AirRater is now available to users in all states across Australia

In the current bushfire and air quality crisis, AirRater has been made available to users in all states across Australia. This has increased our user base to over 50,000. From the feedback we have received, AirRater has been able to assist many people with planning their activities and managing their health.

AirRater app

Please find our just published paper in Environmental Research, which uses AirRater symptom data to show a strong association between PM2.5 and respiratory symptoms in Tasmania. This association is present in both winter and summer, suggesting both wood smoke and landscape fire related smoke are associated with symptoms. We also find associations between symptoms and several pollen types, including grass, birch, cypresses, the Eucalypt family (Myrtaceae), and the native hop bush, Dodonaea.

Many thanks to our funders, stakeholders and all of the AirRater team, including the pollen counters, for their support and assistance with this research.

Abstract

Grass pollen, one of the pollen types linked with respiratory symptoms in Tasmania.

Asthma and allergic rhinitis (or hay fever) are ubiquitous, chronic health conditions that seasonally affect a sizeable proportion of the population. Both are commonly triggered or exacerbated by environmental conditions including aeroallergens, air quality and weather. Smartphone technology offers new opportunities to identify environmental drivers by allowing large-scale, real-time collection of day-to-day symptoms. As yet, however, few studies have explored the potential of this technology to provide useful epidemiological data on environment-symptom relationships. Here, we use data from the smartphone app ‘AirRater’ to examine relationships between asthma and allergic rhinitis symptoms and weather, air quality and pollen loads in Hobart, Tasmania, Australia. We draw on symptom data logged by app users over a three-year period and use time-series analysis to assess the relationship between symptoms and environmental co-variates. Symptoms are associated with particulate matter (IRR 1.06, 95% CI: 1.04–1.08), maximum temperature (IRR 1.28, 95% CI: 1.13–1.44) and pollen taxa including Betula (IRR 1.04, 95% CI: 1.02–1.07), Cupressaceae (IRR 1.02, 95% CI: 1.01–1.04), Myrtaceae (IRR 1.06, 95% CI: 1.02–1.10) and Poaceae (IRR 1.05, 95% CI: 1.01–1.09). The importance of these pollen taxa varies seasonally and more taxa are associated with allergic rhinitis (eye/nose) than asthma (lung) symptoms. Our results are congruent with established epidemiological evidence, while providing important local insights including the association between symptoms and Myrtaceae pollen. We conclude that smartphone-sourced data can be a useful tool in environmental epidemiology.

Corresponding author

  Fay Johnston

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