Toward better allergy management in the digital era: empirical essays

The prevalence of pollen-induced allergies stagnates on a high level, ranging from 15% to 25% worldwide. Since allergy is a chronic health condition, it requires long-term therapy. The efficiency of every pharmacological treatment or supporting health behavior is limited by the patient’s cooperation, especially, if it requires self-administration and is performed outside of healthcare institutions. It is well-known, that most noncompliance is intentional. Thus, interventions focusing on improvement of health behavior of allergic individuals, should address the root causes of inappropriate health behavior. Anti-allergic medications are symptomatic and have to be taken as needed. Allergen avoidance strategies make sense only if performed at the moment, when airborne pollen concentration is high. Pollen information provided to allergic individuals via a pollen application, might become an important aid in avoiding exposure to allergenic pollen, as well as planning medication and outdoor activities. However, little is known about factors motivating sustained pollen application use. Depending on the phenological and meteorological factors, airborne pollen concentration shows considerable fluctuation in its amount during the main pollen season. Robust forecasting techniques providing prediction of airborne pollen levels on a diurnal scale are of paramount importance to support a proper allergy management. The doctoral thesis contains four contributions to scientific literature. Contribution 1 examines the current situation regarding the impairment caused by allergic symptoms and frequently performed health behavior. Contribution 2 investigates the influencing factors explaining the health behavior of allergic individuals. Contribution 3 focuses on influencing factors facilitating the acceptance and utilization of pollen applications as a supporting tool in allergy management. Contribution 4 is devoted to development of predictive models of airborne pollen concentrations on a 3-hourly scales of pollen data using time series analysis and machine learning techniques. The contribution 1 explores health behavior of allergic individuals by means of a cross-sectional study. It confirms that pollen allergy remains a serious health-related problem with a profound effect on the health-related quality of life of allergic individuals, with negative implications in social life, everyday activities, and significant decline of work productivity. Despite perceived symptoms, a considerably small proportion of the allergic individuals seek medical support or undergo specific immunotherapy. Allergen avoidance strategies and pollen information services are moderately used by allergic individuals. The biggest share of allergic individuals self-manages allergic symptoms using over-the-counter medication. The contribution 2 investigates the determinants of utilization of various allergy management measures using Protection Motivation Theory. It shows that the threat appraisal, consisting of perceived severity of the symptoms and perceived seriousness of allergy, is the most relevant motivator of allergy management efforts performed by allergic individuals. However, educational interventions aiming at promoting appropriate allergy management and raising awareness of health risks associated with inadequate allergy management should be accompanied by measures increasing self-efficacy of allergic individuals. The contribution 3 explores motivational factors facilitating the acceptance and utilization of pollen applications by allergic individuals. Empirical data collected in the course of an online experiment shows that the IT-driven factors have substantially greater influence on the acceptance of pollen applications, than allergy characteristics. Therefore, to assure sustained use, pollen applications have to focus on providing high quality health content and pollen information in order to be perceived as a useful supporting tool in allergy management. The contribution 4 tests ability of four forecasting techniques, namely ARIMA, dynamic regression, artificial neural network and neural network autoregression to accurately predict airborne pollen concentrations of Betula and Poaceae on a 3-hourly scale of data. In general, forecasting techniques explicitly using autoregression and considering external meteorological variables performed well in forecasting airborne pollen levels. However, seasonal ARIMA, being the simplest among tested forecasting methods, was superior in predicting Poaceae airborne pollen concentration. A possible extension of the present scientific work, is to test the utility of the provided recommendation using experimental and longitudinal study designs. These research questions are especially interesting in context of the third contribution presenting a pollen application as a supporting tool in allergy management

Airborne Fungal Spore Review, New Advances and Automatisation

Fungal spores make up a significant portion of Primary Biological Aerosol Particles (PBAPs) with large quantities of such particles noted in the air. Fungal particles are of interest because of their potential to affect the health of both plants and humans. They are omnipresent in the atmosphere year-round, with concentrations varying due to meteorological parameters and location. Equally, differences between indoor and outdoor fungal spore concentrations and dispersal play an important role in occupational health. This review attempts to summarise the different spore sampling methods, identify the most important spore types in terms of negative effects on crops and the public, the factors affecting their growth/dispersal, and different methods of predicting fungal spore concentrations currently in use

Status and Trend of the Main Allergenic Pollen Grains and Alternaria Spores in the City of Rome (2003-2019)

Today a large part of the European population is exposed to levels of air pollution exceeding the standards recommended by the World Health Organization. Moreover, air pollution and the seasonal emission of allergenic pollen are progressively affecting human health and can cause severe allergic reactions, particularly when air pollution combines with pollen allergen peaks. Unlike atmospheric pollutants of anthropogenic origin, pollen sources have a pulsating trend that leads to high values in the flowering period and values close to, or equal to, zero in the rest of the year. This aspect makes essential the definition of data coverage standards for the main allergenic taxa. For air quality assessment detailed classification criteria for monitoring stations are defined by international standards, not the same from the European Standards for the Sampling and analysis of airborne pollen grains and fungal spores. This paper describes the status and the air concentration trends of the main allergenic pollen and the Alternaria spore measured in Rome from 2003 to 2019 by the Aerobiological Monitoring Center of Tor Vergata (Rome) and calculated by the Seasonal Kendall test with the open-source OpenAir R package. The analysis was carried out on the daily concentrations of the most widespread allergenic taxa in Italy: Asteraceae, Betulaceae, Corylaceae, Cupressaceae/Taxaceae, Poaceae, Oleaceae, Urticaceae and the Alternaria spores

Outdoor airborne allergens: Characterization, behavior and monitoring in Europe

Aeroallergens or inhalant allergens, are proteins dispersed through the air and have the potential to induce allergic conditions such as rhinitis, conjunctivitis, and asthma. Outdoor aeroallergens are found predominantly in pollen grains and fungal spores, which are allergen carriers. Aeroallergens from pollen and fungi have seasonal emission patterns that correlate with plant pollination and fungal sporulation and are strongly associated with atmospheric weather conditions. They are released when allergen carriers come in contact with the respiratory system, e.g. the nasal mucosa. In addition, due to the rupture of allergen carriers, airborne allergen molecules may be released directly into the air in the form of micronic and submicronic particles (cytoplasmic debris, cell wall fragments, droplets etc.) or adhered onto other airborne particulate matter. Therefore, aeroallergen detection strategies must consider, in addition to the allergen carriers, the allergen molecules themselves. This review article aims to present the current knowledge on inhalant allergens in the outdoor environment, their structure, localization, and factors affecting their production, transformation, release or degradation. In addition, methods for collecting and quantifying aeroallergens are listed and thoroughly discussed. Finally, the knowledge gaps, challenges and implications associated with aeroallergen analysis are describe

Forecasting of Corylus, Alnus, and Betula pollen concentration in the air in Poland

Wydział Nauk Geograficznych i Geologicznych: Instytut Geoekologii i GeoinformacjiZrozumienie dynamiki przebiegu pylenia i występowania pyłku w powietrzu, a także stworzenie modeli predykcyjnych, może istotnie pomóc alergikom. Głównymi celami pracy było (i) określenie charakterystyk czasowej i czasoprzestrzennej autokorelacji dobowych stężeń pyłku leszczyny, olszy i brzozy w Polsce, (ii) stworzenie i ocena prognoz poziomów stężeń pyłku leszczyny, olszy i brzozy zbudowanych w oparciu o przeszłe dane pyłkowe z badanych stacji, oraz (iii) zbudowanie czasoprzestrzennych modeli prognozujących poziomy stężeń pyłku leszczyny, olszy i brzozy w oparciu o dane meteorologiczne. Monitoring dobowych stężeń pyłku badanych taksonów w powietrzu atmosferycznym był przeprowadzony w 11 miastach w Polsce. Dodatkowo użyto danych w regularnej siatce pochodzących z reanaliz meteorologicznych. Do zbadania wzorców zmienności czasowej stężeń pyłku zostały użyte funkcje autokorelacji, natomiast do analizy zróżnicowania przestrzennego - funkcje kroskorelacji. Wysokie poziomy stężeń pyłku leszczyny, olszy i brzozy prognozowano wykorzystując metodykę losowych lasów. Zaprezentowane wyniki pozwoliły na lepsze zrozumienie czasowych i czasoprzestrzennych charakterystyk stężeń pyłku leszczyny, olszy i brzozy w powietrzu atmosferycznym. Badanie pokazało także możliwości prognozowania wysokich stężeń tych taksonów na całym obszarze Polski, a nie tylko punktowo dla poszczególnych stanowisk.Understanding of the behavior of atmospheric pollen concentration, as well as developing predictive models, can greatly help allergic sufferers. The aims of this study were (i) to determine mean multi-year characteristics of temporal and space–time autocorrelation of the pollen counts of Corylus, Alnus, and Betula in Poland, (ii) to create and evaluate Corylus, Alnus, and Betula pollen concentration levels predictions based on previous pollen count values from given sites, and (ii) to develop spatiotemporal predictive models of Corylus, Alnus, and Betula pollen concentration levels, using preprocessed gridded meteorological data. The monitoring of the concentrations of Corylus, Alnus, and Betula pollen in the air was conducted in 11 cities in Poland. Additionally, AGRI4CAST Interpolated Meteorological Data were used as predictor variables. The autocorrelation and cross-correlation functions were used to investigate temporal and spatial patterns. Random forest method was used to predict the high pollen concentration level of Corylus, Alnus, and Betula. The study provided an understanding of the temporal and spatiotemporal autocorrelation of Corylus, Alnus, and Betula pollen counts. The final models also proved to be capable of pollen levels predicting in continuous areas rather than in a single location

Isolating the species element in grass pollen allergy: A review

Grass pollen is a leading cause of allergy in many countries, particularly Europe. Although many elements of grass pollen production and dispersal are quite well researched, gaps still remain around the grass species that are predominant in the air and which of those are most likely to trigger allergy. In this comprehensive review we isolate the species aspect in grass pollen allergy by exploring the interdisciplinary interdependencies between plant ecology, public health, aerobiology, reproductive phenology and molecular ecology. We further identify current research gaps and provide open ended questions and recommendations for future research in an effort to focus the research community to develop novel strategies to combat grass pollen allergy. We emphasise the role of separating temperate and subtropical grasses, identified through divergence in evolutionary history, climate adaptations and flowering times. However, allergen cross-reactivity and the degree of IgE connectivity in sufferers between the two groups remains an area of active research. The importance of future research to identify allergen homology through biomolecular similarity and the connection to species taxonomy and practical implications of this to allergenicity is further emphasised. We also discuss the relevance of eDNA and molecular ecological techniques (DNA metabarcoding, qPCR and ELISA) as important tools in quantifying the connection between the biosphere with the atmosphere. By gaining more understanding of the connection between species-specific atmospheric eDNA and flowering phenology we will further elucidate the importance of species in releasing grass pollen and allergens to the atmosphere and their individual role in grass pollen allergy

Development and Characterization of an Inexpensive Single-Particle Fluorescence Spectrometer for Detection and Classification of Pollen and Other Bioaerosols

Atmospheric aerosols are ubiquitous throughout the Earth’s atmosphere and can be important with respect to environmental systems and human health. Pollen particles are a class of primary biological aerosol particles (PBAPs) that cost the United States billions of dollars a year in loss of productivity and healthcare costs due to allergy and respiratory effects. Traditional methods of pollen detection rely on collection and subsequent identification by visual microscopy, yet few measurement stations exist in the United States. As such, current pollen forecasting models have relatively high prediction uncertainty, especially in regions without sampling stations. Recently, laser-induced fluorescence instrumentation has been applied as one method to bridge gaps in bioaerosol detection and classification, though this instrumentation suffers from prohibitively high cost or analysis barriers. This thesis describes the development, characterization, and preliminary application of a new single-particle fluorescence spectrometer geared towards bioaerosol, particularly pollen, analysis. A sequence of four laser or LED sources are used to excite the particles, which emit fluorescent light that is magnified then diffracted through a transmission grating into a simple digital camera. This instrument operates similar to a traditional spectroscope, though is able to collect spectral light from several small particles simultaneously. This process allows for spectroscopic analysis of many particles at the same time. The instrument went through several phases of both development and characterization. Development included the addition of several new excitation sources (two light-emitting diodes and one laser) to expand the number of fluorophores probed. A monochrome camera was also added to the system to circumvent issues caused by inexpensive point-and-shoot cameras. Methods to size the particles, as well as calibrations for camera parameters and systemic defects were also implemented. For defects in the optical surface and differences in source intensity, a spatial interpolation map was developed that reduces the error of identical particles depending on their location on the CCD from 17% to 3%. Utilizing these techniques, four clustering and classification methods were examined with 8 species of commercial pollen in Chapter 4. The random forest (RF) and gradient boosting algorithms performed exceptionally well, both classifying above 95% accuracy. The RF technique was examined further due to computational advantages. Testing on source reduction revealed that the 405 and 450 nm sources were less important in classification models, with the latter having particularly low (3%) importance. The classification techniques were utilized on freshly collected pollen standards in Chapter 5. 34 types of pollen were collected and classified to 90% accuracy at the species level. Pollen was also classified by species, allergenicity, as well as by plant type depending on their collection months, with one scenario being classified at 98% accuracy. A proof-of-concept was also provided for the prediction of new, ambient pollen samples to a developed random forest classification model from standard collections, in which several particles collected in a central location of the Botanic Gardens were classified as a type of tree that was seen to be pollinating on the same day

The interaction of pollution, meteorology and bioaerosols: implications on human health

The global incidence of allergic reaction has been rising for years, especially within westernised urban areas. There is evidence that the interaction between pollen grains, environmental pollution and meteorological change is increasing the allergenicity of the pollen grain and consequently, increasing the misery of hay fever sufferers. Laboratory experiments have shown that the interaction of pollen with atmospheric oxidants such as ozone and nitrogen dioxide ($NO_2$) can alter protein molecules that are present within the pollen grains via post-translational modification of the protein. Within the laboratory, birch pollen was exposed to atmospherically relevant exposures of gas phase $NO_2$ and ozone under a range of environmentally relevant conditions (temperature and relative humidity RH). The effects of the exposures on the biochemistry of the pollen grains were probed using proteomic approach. The morphological changes of unexposed and exposed pollen samples to RH, rainwater and $NO_2$, where observed under fluorescence microscopy and scanning electron microscope. The discoveries suggest that interaction between gas pollutants and pollen do exist and cause protein specific modifications; nitration. Detailed analysis of London Ambulance data compared to London temperature data is presented. The relationships established will allow for prediction of likely changes in ambulance demand (and illness types) that will be caused by seasonal temperature changes, increased frequency and intensity of extreme weather events, due to climate change, in the future. The study applied statistical analyses to examine short-term associations between birch pollen count with allergic related illnesses recorded in the London Ambulance data, temperature and $NO_2$

Microscale pollen release and dispersal patterns in flowering grass populations

Characterizing pollen release and dispersion processes is fundamental for knowledge advancement in ecological, agricultural and public health disciplines. Understanding pollen dispersion from grass communities is especially relevant due to their high species-specific allergenicity and heterogeneously distributed source areas. Here, we aimed to address questions concerning fine level heterogeneity in grass pollen release and dispersion processes, with a focus on characterizing the taxonomic composition of airborne grass pollen over the grass flowering season using eDNA and molecular ecology methods. High resolution grass pollen concentrations were compared between three microscale sites (<300 m apart) in a rural area in Worcestershire, UK. The grass pollen was modelled with local meteorology in a MANOVA (Multivariate ANOVA) approach to investigate factors relevant to pollen release and dispersion. Simultaneously, airborne pollen was sequenced using Illumina MySeq for metabarcoding, analysed against a reference database with all UK grasses using the R packages DADA2 and phyloseq to calculate Shannon's Diversity Index (α-diversity). The flowering phenology of a local Festuca rubra population was observed. We found that grass pollen concentrations varied on a microscale level, likely attributed to local topography and the dispersion distance of pollen from flowering grasses in local source areas. Six genera (Agrostis, Alopecurus, Arrhenatherum, Holcus, Lolium and Poa) dominated the pollen season, comprising on average 77 % of the relative abundance of grass species reads. Temperature, solar radiation, relative humidity, turbulence and wind speeds were found to be relevant for grass pollen release and dispersion processes. An isolated flowering Festuca rubra population contributed almost 40 % of the relative pollen abundance adjacent to the nearby sampler, but only contributed 1 % to samplers situated 300 m away. This suggests that most emitted grass pollen has limited dispersion distance and our results show substantial variation in airborne grass species composition over short geographical scales