Thunderstorm asthma in seasonal allergic rhinitis: The TAISAR study.

BACKGROUND: Asthma epidemics associated with thunderstorms have had catastrophic effects on individuals and emergency services. Seasonal allergic rhinitis (SAR) is present in the vast majority of people who develop thunderstorm asthma (TA), but there is little evidence regarding risk factors for TA among the SAR population. OBJECTIVE: We sought to identify risk factors for a history of TA and hospital presentation in a cohort of individuals with SAR. METHODS: This multicenter study recruited adults from Melbourne, Australia, with a past diagnosis of TA and/or self-reported SAR. Clinical information, spirometry results, white blood cell count, ryegrass pollen-specific (RGP-sp) IgE concentration, and fractional exhaled nitric oxide were measured to identify risk factors for a history of TA in individuals with SAR. RESULTS: From a total of 228 individuals with SAR, 35% (80 of 228) reported SAR only (the I-SAR group), 37% (84 of 228) reported TA symptoms but had not attended hospital for treatment (the O-TA group), and 28% (64 of 228) had presented to the hospital for TA (the H-TA group). All patients in the H-TA group reported a previous asthma diagnosis. Logistic regression analysis of factors associated with O-TA and H-TA indicated that lower FEV1 value and an Asthma Control Questionnaire score higher than 1.5 were associated with H-TA. Higher blood RGP-sp IgE concentration, eosinophil counts, and fractional exhaled nitric oxide level were significantly associated with both O-TA and H-TA. Receiver operating curve analysis showed an RGP-sp IgE concentration higher than 10.1 kU/L and a prebronchodilator FEV1 value of 90% or lower to be biomarkers of increased H-TA risk. CONCLUSION: Clinical tests can identify risk of a history of TA in individuals with SAR and thereby inform patient-specific treatment recommendations.

Atmospheric modelling of grass pollen rupturing mechanisms for thunderstorm asthma prediction.

The world's most severe thunderstorm asthma event occurred in Melbourne, Australia on 21 November 2016, coinciding with the peak of the grass pollen season. The aetiological role of thunderstorms in these events is thought to cause pollen to rupture in high humidity conditions, releasing large numbers of sub-pollen particles (SPPs) with sizes very easily inhaled deep into the lungs. The humidity hypothesis was implemented into a three-dimensional atmospheric model and driven by inputs from three meteorological models. However, the mechanism could not explain how the Melbourne event occurred as relative humidity was very low throughout the atmosphere, and most available grass pollen remained within 40 m of the surface. Our tests showed humidity induced rupturing occurred frequently at other times and would likely lead to recurrent false alarms if used in a predictive capacity. We used the model to investigate a range of other possible pollen rupturing mechanisms which could have produced high concentrations of SPPs in the atmosphere during the storm. The mechanisms studied involve mechanical friction from wind gusts, electrical build up and discharge incurred during conditions of low relative humidity, and lightning strikes. Our results suggest that these mechanisms likely operated in tandem with one another, but the lightning method was the only mechanism to generate a pattern in SPPs following the path of the storm. If humidity induced rupturing cannot explain the 2016 Melbourne event, then new targeted laboratory studies of alternative pollen rupture mechanisms would be of considerable value to help constrain the parameterisation of the pollen rupturing process.

Is short-term exposure to grass pollen adversely associated with lung function and airway inflammation in the community?

BACKGROUND: The association between grass pollen exposure and early markers of asthma exacerbations such as lung function changes and increase in airway inflammation is limited. We investigated the associations between short-term grass pollen exposure and lung function and airway inflammation in a community-based sample, and whether any such associations were modified by current asthma, current hay fever, pollen sensitization, age, and other environmental factors. METHODS: Cross-sectional and short-term analyses of data from the Melbourne Atopy Cohort Study (MACS) participants (n = 936). Lung function was assessed using spirometry. Airway inflammation was assessed by fractional exhaled nitric oxide (FeNO) and exhaled breath condensate pH and nitrogen oxides (NOx). Daily pollen counts were collected using a volumetric spore trap. The associations were examined by linear regression. RESULTS: Higher ambient levels of grass pollen 2 days before (lag 2) were associated with lower mid-forced expiratory flow (FEF25%-75% ) and FEV1 /FVC ratio (Coef. [95% CI] = -119 [-226, -11] mL/s and -1.0 [-3.0, -0.03] %, respectively) and also 3 days before (lag 3). Increased levels of grass pollen a day before (lag 1) were associated with increased FeNO (4.35 [-0.1, 8.7] ppb) and also at lag 2. Adverse associations between pollen and multiple outcomes were greater in adults with current asthma, hay fever, and pollen sensitization. CONCLUSION: Grass pollen exposure was associated with eosinophilic airway inflammation 1-2 days after exposure and airway obstruction 2-3 days after exposure. Adults and individuals with asthma, hay fever, and pollen sensitization may be at higher risk.

Using crowd-sourced allergic rhinitis symptom data to improve grass pollen forecasts and predict individual symptoms.

Seasonal allergic rhinitis (AR), also known as hay fever, is a common respiratory condition brought on by a range of environmental triggers. Previous work has characterised the relationships between community-level AR symptoms collected using mobile apps in two Australian cities, Canberra and Melbourne, and various environmental covariates including pollen. Here, we build on these relationships by assessing the skill of models that provide a next-day forecast of an individual's risk of developing AR and that nowcast ambient grass pollen concentrations using crowd-sourced AR symptoms as a predictor. Categorical grass pollen forecasts (low/moderate/high) were made based on binning mean daily symptom scores by corresponding categories. Models for an individual's risk were constructed by forward variable selection, considering environmental, demographic, behaviour and health-related inputs, with non-linear responses permitted. Proportional-odds logistic regression was then applied with the variables selected, modelling the symptom scores on their original five-point scale. AR symptom-based estimates of today's average grass pollen concentration were more accurate than those provided by two benchmark forecasting methods using various metrics for assessing accuracy. Predictions of an individual's next-day AR symptoms rated on a five-point scale were correct in 36% of cases and within one point on this scale in 82% of cases. Both outcomes were significantly better than chance. This large-scale AR symptoms measurement program shows that crowd-sourced symptom scores can be used to predict the daily average grass pollen concentration, as well as provide a personalised AR forecast.

Crowd-sourced allergic rhinitis symptom data: The influence of environmental and demographic factors.

Allergic Rhinitis (AR) affects over half a billion people worldwide with an estimated prevalence of 1 in 5 individuals in developed countries. Although ambient pollen exposure is a causal factor in AR, the symptom-exposure relationship is typically not studied in the broader community but in small, well-characterised cohorts drawn from clinical populations. To identify relationships between AR symptoms in the community and a range of environmental factors, we used a database containing over 96,000 symptom score reports collected over a 3-year period (2014-2016) through freely available smartphone apps released in two Australian cities, Melbourne and Canberra. Ambient pollen levels and symptom scores were strongly related, with grass pollen explaining most of the symptom variation. Other factors correlated with higher symptom scores included temperature (R > 0.73) and wind speed (R > 0.75). In general, worse symptom scores were reported by younger participants, women, and those who had taken medication for AR in the preceding 24 h. The strength of this relationship varied between the two cities. Smartphone-based symptom surveys offer a cost-effective means of studying real-world risk factors for AR in a broader 'extra-clinical' population.

Seasonal asthma in Melbourne, Australia, and some observations on the occurrence of thunderstorm asthma and its predictability.

We examine the seasonality of asthma-related hospital admissions in Melbourne, Australia, in particular the contribution and predictability of episodic thunderstorm asthma. Using a time-series ecological approach based on asthma admissions to Melbourne metropolitan hospitals, we identified seasonal peaks in asthma admissions that were centred in late February, June and mid-November. These peaks were most likely due to the return to school, winter viral infections and seasonal allergies, respectively. We performed non-linear statistical regression to predict daily admission rates as functions of the seasonal cycle, weather conditions, reported thunderstorms, pollen counts and air quality. Important predictor variables were the seasonal cycle and mean relative humidity in the preceding two weeks, with higher humidity associated with higher asthma admissions. Although various attempts were made to model asthma admissions, none of the models explained substantially more variation above that associated with the annual cycle. We also identified a list of high asthma admissions days (HAADs). Most HAADs fell in the late-February return-to-school peak and the November allergy peak, with the latter containing the greatest number of daily admissions. Many HAADs in the spring allergy peak may represent episodes of thunderstorm asthma, as they were associated with rainfall, thunderstorms, high ambient grass pollen levels and high humidity, a finding that suggests thunderstorm asthma is a recurrent phenomenon in Melbourne that occurs roughly once per five years. The rarity of thunderstorm asthma events makes prediction challenging, underscoring the importance of maintaining high standards of asthma management, both for patients and health professionals, especially during late spring and early summer.

Trans-disciplinary research in synthesis of grass pollen aerobiology and its importance for respiratory health in Australasia.

Grass pollen is a major trigger for allergic rhinitis and asthma, yet little is known about the timing and levels of human exposure to airborne grass pollen across Australasian urban environments. The relationships between environmental aeroallergen exposure and allergic respiratory disease bridge the fields of ecology, aerobiology, geospatial science and public health. The Australian Aerobiology Working Group comprised of experts in botany, palynology, biogeography, climate change science, plant genetics, biostatistics, ecology, pollen allergy, public and environmental health, and medicine, was established to systematically source, collate and analyse atmospheric pollen concentration data from 11 Australian and six New Zealand sites. Following two week-long workshops, post-workshop evaluations were conducted to reflect upon the utility of this analysis and synthesis approach to address complex multidisciplinary questions. This Working Group described i) a biogeographically dependent variation in airborne pollen diversity, ii) a latitudinal gradient in the timing, duration and number of peaks of the grass pollen season, and iii) the emergence of new methodologies based on trans-disciplinary synthesis of aerobiology and remote sensing data. Challenges included resolving methodological variations between pollen monitoring sites and temporal variations in pollen datasets. Other challenges included "marrying" ecosystem and health sciences and reconciling divergent expert opinion. The Australian Aerobiology Working Group facilitated knowledge transfer between diverse scientific disciplines, mentored students and early career scientists, and provided an uninterrupted collaborative opportunity to focus on a unifying problem globally. The Working Group provided a platform to optimise the value of large existing ecological datasets that have importance for human respiratory health and ecosystems research. Compilation of current knowledge of Australasian pollen aerobiology is a critical first step towards the management of exposure to pollen in patients with allergic disease and provides a basis from which the future impacts of climate change on pollen distribution can be assessed and monitored.