%0 Journal Article
%T A Model for the Determination of Pollen Count Using Google Search Queries for Patients Suffering from Allergic Rhinitis
%A Volker K£¿nig
%A Ralph M£¿sges
%J Journal of Allergy
%D 2014
%I Hindawi Publishing Corporation
%R 10.1155/2014/381983
%X Background. The transregional increase in pollen-associated allergies and their diversity have been scientifically proven. However, patchy pollen count measurement in many regions is a worldwide problem with few exceptions. Methods. This paper used data gathered from pollen count stations in Germany, Google queries using relevant allergological/biological keywords, and patient data from three German study centres collected in a prospective, double-blind, randomised, placebo-controlled, multicentre immunotherapy study to analyse a possible correlation between these data pools. Results. Overall, correlations between the patient-based, combined symptom medication score and Google data were stronger than those with the regionally measured pollen count data. The correlation of the Google data was especially strong in the groups of severe allergy sufferers. The results of the three-centre analyses show moderate to strong correlations with the Google keywords (up to >0.8 cross-correlation coefficient, ) in 10 out of 11 groups (three averaged patient cohorts and eight subgroups of severe allergy sufferers: high IgE class, high combined symptom medication score, and asthma). Conclusion. For countries with a good Internet infrastructure but no dense network of pollen traps, this could represent an alternative for determining pollen levels and, forecasting the pollen count for the next day. 1. Introduction Allergic rhinitis (AR), together with the comorbidity of asthma, ranks among the most frequent chronic diseases of our time [1, 2]. Its prevalence rates continue to rise and are thereby defining it as a global health problem. In several countries, the prevalence rate of AR in young adults is over 40% [2]. In the therapeutic ranking the avoidance of the allergen exposure comes first. An already established measurement supporting the avoidance of pollen exposure of affected persons suffering from seasonal AR is the measurement of the pollen count on the basis of pollen traps [3, 4]. This is especially drawing attention to the strength of the pollen count. Forecasting and providing the patients suffering from AR with these forecasts allow them to take measures to specifically avoid either strong or any pollen exposure. Possible measures could be an airing according to the time of the day and a postponement of outdoor activities. The warning of a high pollen count furthermore enables the patients to prepare themselves these days by taking along symptomatic medication especially for asthmatics. Data from clinical trials on AR must be interpreted in the context of
%U http://www.hindawi.com/journals/ja/2014/381983/