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BACKGROUND: The complexity, high prevalence, and substantial personal and socioeconomic burden collectively render atopic dermatitis (AD) a major public health concern. Using crowdsourced Internet data has the potential to provide unique insights into this concern, as demonstrated by several previous studies. However, a comprehensive comparison across European countries remains lacking. OBJECTIVES: The study aimed to investigate AD-related web searches across Europe to assess spatiotemporal variations and associations between disease-related and external factors. METHODS: AD-related web search data were extracted for 21 European countries between February 2019 and January 2023. Descriptive analysis and autocorrelation functions were performed to examine spatiotemporal patterns. Correlations (r) were used to evaluate the associations between web searches and disease-related, socioeconomic and meteorological data. RESULTS: Over 241 million AD-related web searches were identified, with search volume varying substantially among European countries (p < 0.001) and correlating with AD prevalence and disease burden (both r = 0.51, p = 0.019). Search volume increased between 2019 and 2023 in all countries and seasonally peaked in January and March. Negative correlations with median population age (r = -0.46, p = 0.039), number of general practitioners (r = -0.29, p = 0.226) and specialists (r = -0.27, p = 0.270) were observed. Moderate to strong correlations were found between search volume and cold, humid and windy weather with fewer sunshine hours, while higher online interest typically occurred 1-3 months after such weather conditions. CONCLUSION: The study highlights the great potential of online crowdsourced data analysis, for example, to investigate the impact of climate change or to identify unmet needs at a population level. Furthermore, the growing online interest in AD and the corresponding seasonal peaks emphasize the necessity of adapting treatment plans, intensifying public health campaigns, and disseminating reliable online information by governments and healthcare providers, especially during these periods.
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Background: Asthma is a chronic inflammatory disorder of the airways and one of the most important non-communicable diseases worldwide. Analyzing crowdsourced data can help understand public interest and unmet needs as well as potential factors influencing search behavior. Objective: The study aimed to investigate asthma-related web search data in Europe to identify possible regional and seasonal variations and to assess public interest. Methods: Google Ads Keyword Planner was used to measure search volume for search terms related to asthma, allergic asthma, and bronchial asthma in 21 European countries between January 2018 and December 2021. The top 10 keywords of each country were categorized qualitatively. Search volume per 100 000 inhabitants was descriptively assessed in terms of regional and seasonal trends. Spearman correlations between search volume and pollen concentration as well as coronavirus disease (COVID-19) cases were investigated. Results: The median search volume per 100 000 inhabitants for asthma and allergic asthma was highest in Northern and Western Europe, while the highest search volume for bronchial asthma was observed in Western and Eastern regions. A seasonal trend was identified for all search terms and in all regions. Correlations were found between search frequency and pollen load and search behavior and COVID-19 cases. Overall, Europeans were most interested in the diseases in general, their treatment options, and symptoms. Conclusion: These results highlighted the need for reliable and region-specific information about the disease and for public campaigns to improve asthma control. The study also emphasizes the importance of using crowdsourced data for a more encompassing overview beyond conventional healthcare data.
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Highly effective targeted therapies are available to treat noncommunicable chronic inflammatory skin diseases. In contrast, the exact diagnosis of noncommunicable chronic inflammatory skin diseases is complicated by its complex pathogenesis and clinical and histological overlap. Particularly, the differential diagnosis of psoriasis and eczema can be challenging in some cases, and molecular diagnostic tools need to be developed to support a gold standard diagnosis. The aim of this work was to develop a real-time PCR-based molecular classifier to distinguish psoriasis from eczema in formalin-fixed and paraffin-embedded-fixed skin samples and to evaluate the use of minimally invasive microbiopsies and tape strips for molecular diagnosis. In this study, we present a formalin-fixed and paraffin-embedded-based molecular classifier that determines the probability for psoriasis with a sensitivity/specificity of 92%/100%, respectively, and an area under the curve of 0.97, delivering comparable results to our previous published RNAprotect-based molecular classifier. The psoriasis probability, as well as levels of NOS2 expression, positively correlated with the disease hallmarks of psoriasis and negatively with eczema hallmarks. Furthermore, minimally invasive tape strips and microbiopsies were effectively used to differentiate psoriasis from eczema. In summary, the molecular classifier offers broad usage in pathology laboratories as well as outpatient settings and can support the differential diagnosis of noncommunicable chronic inflammatory skin diseases on a molecular level using formalin-fixed and paraffin-embedded tissue, microbiopsies, and tape strips.
