Ragweed as an Example of Worldwide Allergen Expansion

<p/> <p>Multiple factors are contributing to the expansion of ragweed on a worldwide scale. This review seeks to examine factors that may contribute to allergen expansion with reference to ragweed as a well-studied example. It is our hope that increased surveillance for new pollens in areas not previously affected and awareness of the influence the changing environment plays in allergic disease will lead to better outcomes in susceptible patients.</p

Adaptation to Impacts of Climate Change on Aeroallergens and Allergic Respiratory Diseases

Climate change has the potential to have many significant impacts on aeroallergens such as pollen and mould spores, and therefore related diseases such as asthma and allergic rhinitis. This paper critically reviews this topic, with a focus on the potential adaptation measures that have been identified to date. These are aeroallergen monitoring; aeroallergen forecasting; allergenic plant management; planting practices and policies; urban/settlement planning; building design and heating, ventilating, and air-conditioning (HVAC); access to health care and medications; education; and research

Impact of meteorological variation on hospital visits of patients with tree pollen allergy

<p>Abstract</p> <p>Background</p> <p>Climate change could affect allergic diseases, especially due to pollen. However, there has been no epidemiologic study to demonstrate the relationship between meteorological factors, pollen, and allergic patients. We aimed to investigate the association between meteorological variations and hospital visits of patients with tree pollen allergy.</p> <p>Methods</p> <p>The study subjects were adult patients who received skin prick tests between April and July from 1999 to 2008. We reviewed the medical records for the test results of 4,715 patients. Patients with tree pollen allergy were defined as those sensitized to more than 1 of 12 tree pollen allergens. We used monthly means of airborne tree pollen counts and meteorological factors: maximum/average/minimum temperature, relative humidity, and precipitation. We analyzed the correlations between meteorological variations, tree pollen counts, and the patient numbers. Multivariable logistic regression analyses were used to investigate the associations between meteorological factors and hospital visits of patients.</p> <p>Results</p> <p>The minimum temperature in March was significantly and positively correlated with tree pollen counts in March/April and patient numbers from April through July. Pollen counts in March/April were also correlated with patient numbers from April through July. After adjusting for confounders, including air pollutants, there was a positive association between the minimum temperature in March and hospital visits of patients with tree pollen allergy from April to July(odds ratio, 1.14; 95% CI 1.03 to 1.25).</p> <p>Conclusions</p> <p>Higher temperatures could increase tree pollen counts, affecting the symptoms of patients with tree pollen allergy, thereby increasing the number of patients visiting hospitals.</p

Predicting tree pollen season start dates using thermal conditions

Thermal conditions at the beginning of the year determine the timing of pollen seasons of early flowering trees. The aims of this study were to quantify the relationship between the tree pollen season start dates and the thermal conditions just before the beginning of the season and to construct models predicting the start of the pollen season in a given year. The study was performed in Krakow (Southern Poland); the pollen data of Alnus, Corylus and Betula were obtained in 1991–2012 using a volumetric method. The relationship between the tree pollen season start, calculated by the cumulated pollen grain sum method, and a 5-day running means of maximum (for Alnus and Corylus) and mean (for Betula) daily temperature was found and used in the logistic regression models. The estimation of model parameters indicated their statistically significance for all studied taxa; the odds ratio was higher in models for Betula, comparing to Alnus and Corylus. The proposed model makes the accuracy of prediction in 83.58 % of cases for Alnus, in 84.29 % of cases for Corylus and in 90.41 % of cases for Betula. In years of model verification (2011 and 2012), the season start of Alnus and Corylus was predicted more precisely in 2011, while in case of Betula, the model predictions achieved 100 % of accuracy in both years. The correctness of prediction indicated that the data used for the model arrangement fitted the models well and stressed the high efficacy of model prediction estimated using the pollen data in 1991–2010

Threat of allergenic airborne grass pollen in Szczecin, NW Poland: the dynamics of pollen seasons, effect of meteorological variables and air pollution

The dynamics of Poaceae pollen season, in particularly that of the Secale genus, in Szczecin (western Poland) 2004–2008 was analysed to establish a relationship between the meteorological variables, air pollution and the pollen count of the taxa studied. Consecutive phases during the pollen season were defined for each taxon (1, 2.5, 5, 25, 50, 75, 95, 97.5, 99% of annual total), and duration of the season was determined using the 98% method. On the basis of this analysis, the temporary differences in the dynamics of the seasons were most evident for Secale in 2005 and 2006 with the longest main pollen season (90% total pollen). The pollen season of Poaceae started the earliest in 2007, when thermal conditions were the most favourable. Correlation analysis with meteorological factors demonstrated that the relative humidity, mean and maximum air temperature, and rainfall were the factors influencing the average daily pollen concentrations in the atmosphere; also, the presence of air pollutants such as ozone, PM10 and SO2 was statistically related to the pollen count in the air. However, multiple regression models explained little part of the total variance. Atmospheric pollution induces aggravation of symptoms of grass pollen allergy