If you don't remember your password, you can reset it by entering your email address and clicking the Reset Password button. You will then receive an email that contains a secure link for resetting your password
If the address matches a valid account an email will be sent to __email__ with instructions for resetting your password
University Hospital, Montpellier, FranceMACVIA-France, Fondation Partenariale FMC VIA-LR, Montpellier, FranceVIMA. INSERM U 1168, VIMA: Ageing and Chronic Diseases, Epidemiological and Public Health Approaches, Villejuif, FranceUniversité Versailles St-Quentin-en-Yvelines, UMR-S 1168, Montigny le Bretonneux, FranceEuforea, Brussels, Belgium
Grass pollen allergy is an important trigger for the development of respiratory disorders. Defining the grass pollen season onset is critical for correct allergy diagnosis and personalized therapy. The development of a pan-European sentinel network for allergic diseases has raised the problem of translating the Google search terms into different European languages as well as defining specific pollen season characteristics in different regions. Grass pollen allergy was investigated due to high allergenicity and wide expansion of grass pollen in Europe.
The aim of this study was to examine which translations of “hay fever”, “grass”, and “rhinitis” could be used in the native Cyrillic languages, especially in Ukrainian and Russian, and to compare the seasonality of allergic respiratory queries in Ukraine with the grass pollen counts.
Google Trends (GT) was used to search Google queries concerning grass pollen allergy: “allergy”, “hay fever”, “runny nose”, “grass”, “asthma”, and “pollen”. The Cyrillic terms in Ukrainian and Russian were used. The search was done for the period from 2013 to 2017. Pollen collection from 2013 to 2016 was conducted using volumetric methods. Average daily temperatures were obtained from http://gismeteo.ua. Correlations were assessed by Spearman (R) test.
The Ukrainian Google users searched the Cyrillic equivalents for “runny nose”, “grass”, and “asthma”. Due to the GT queries profile, Ukraine had a “D” pattern according to the classification, developed by Bousquet J et al (2017). In Ukraine, the Poaceae pollen season generally occurred between the second ten-day period of May and the last ten-day period of July. The Poaceae pollen season started with a concentration of pollen grains of 8.0 m−3. This concentration provoked the growth of GT “grass”, “allergy”, “hay fever”, and “asthma” queries.
The terms “grass”, “allergy”, “hay fever”, and “asthma” (in their Cyrillic equivalents) are required in Ukraine to account for the grass pollen exposure by GT. The study of GT may be a useful tool to make an assessment of the grass pollen season for the prevention and minimization of exposure to significant grass pollen concentrations.
Pollen exposure is a major cause of respiratory allergies worldwide. However, it is unclear how everyday exposure is related to symptoms and how exactly allergic patients may be affected spatially and temporally.
A precise definition of the grass pollen season onset is crucial for the confirmation of a pollen allergy diagnosis and personalized treatment of patients with allergic rhinitis and asthma. The high costs of the instruments and procedures required for pollen counting limit the capacity to constitute a comprehensive pollen network covering all planes. The possibility was shown to use a geographically customized search option of Google and further fine-tuned analysis techniques to extract local query data about the regional patient concern from the Internet with possible complement pollen measurements.
For further development of this approach, Google search profiles were assessed for allergic rhinitis and related topics for grass (Poaceae) pollen allergy. Grass pollen allergy was investigated due to the high prevalence in Europe.
There are also difficulties in the choice of the correct translation for “hay fever” and “rhinitis” in the Cyrillic-based languages.
The aim of this study was to examine which GT translations of “hay fever”, “grass”, and “rhinitis” could be used in the native Cyrillic languages, especially in Ukrainian and Russian, and to compare the seasonality of queries in Ukraine with the grass pollen counts.
Google Trends terms and analyses
GT terms, a public web facility of Google Inc., based on Google Search, shows how often a particular search term is entered in relation to the total search volume across various regions of the world and in various languages (http://en.wikipedia.org/wiki/Google_Trends). The following terms were used: “allergy”, “hay fever”, “runny nose”, “grass”, “asthma”, and “pollen”. The Cyrillic terms in Ukrainian and Russian were used. In GT, data are normalized to the highest number of searches for each topic. The score of 100 means that a certain query was entered on that day for the highest number of times for the entire search period in Ukraine. For further comparison of Ukrainian data with the data from other countries, the country patterns were assessed as was proposed previously. In pattern A countries, “allergy” queries were reported at a lower level than “hay fever” and did not show any clear seasonal pattern. In pattern B, C and D countries, “allergy” queries were higher than the other terms and showed a seasonal pattern. When all countries with a seasonal pattern were examined, the peak of queries was the same for “allergy” and “hay fever” (pattern B) or D, the seasonal patterns were similar between countries for the five years.
The 5-year GT graphs were used to examine GT queries from January 1, 2013 through January 1, 2018 in Ukraine to determine the pattern of inquiries. The grass pollen counts were compared with GT queries during the 2013 through 2016 pollen seasons.
Grass pollen count
Pollen collection for 2013–2015 2016 was conducted using volumetric methods, applying a Burkard trap of a Hurst type. The pollen count was performed by the twelve vertical transects method. Pollen grains were identified by using the pollen reference slides of Ukraine, The Pollen Identification Key Program and The Pollen Atlas edited by the American National Aerobiology Bureau.
Correlations were studied by Spearman (R) test. A probability of <0.05 was considered statistically significant.
The five-year GT queries graph for “hay fever”, “allergy”, “asthma”, and “pollen” using manually translated terms is shown in Fig. 1. The query statistics for “hay fever” were assessed by the Cyrillic equivalent of “runny nose”.
Moreover, this seasonality was similar over the period of 5 years. The analysis of GT graphs revealed 2 major peaks of “allergy” queries – the first one (early summer), characteristic for grass pollen allergy, and the second one (late summer – early autumn), representative of the weed pollen season.
There was a strong positive correlation between the pairs “hay fever – asthma” (R = 0.46; p = 0.01), “pollen – allergy” (R = 0.54; p = 0.01), and “pollen – asthma” (R = 0.46; p = 0.01).
Further validation of “hay fever” and “grass” terms was provided by the comparison of these GT terms queries with the average daily temperature (Fig. 2). A strong positive correlation between the “grass” queries and the average daily temperature was observed (R = 0.67; p = 0.01). Analysis of the five-year graphs revealed that the peak of the “grass” queries came before the maximum of the average daily temperature.
The frequency of GT queries was compared with the average daily temperature and Poaceae pollen count (Fig. 3). Firstly, the time periods of the pollen exposure times were defined.
In 2013, the season of Poaceae pollination started on May 12, 2013 and ended on July 28, 2013. In 2014, the Poaceae pollen season lasted from May 11, 2014 until July 13, 2014. In 2015, the Poaceae pollen season lasted from May 17, 2015 until July 19, 2015. In 2016, the Poaceae pollen season lasted from June 3, 2016 until August 21, 2016.
To detect the grass peak high pollen seasons, unfortunately, when the concentration of Poaceae pollen ≥50 pollen/m3 was used as a criterion, it was not possible to recognize the peak of the high grass pollen seasons. During the Poaceae pollen seasons, the highest pollen concentration in 2013 was 25.9 pollen m−3 (June 07); in 2014 was 48.7 pollen m3 (June 06); in 2015 was 16.0 pollen/m3 (June 21) and in 2016 was 11.1 grains/m3 (July 10). Generally, the growth of allergy symptoms determined as increasing of GT queries was observed with pollen counts of more than 8 pollen/m3.
There was a strong positive correlation between Poaceae pollen counts and “grass” (R = 0.42; p = 0.01) and “allergy” queries (R = 0.47; p = 0.01), and average daily temperature (R = 0.72; p = 0.01), and also between “allergy” and “grass” queries (R = 0.55; p = 0.01), and the average daily temperature (R = 0.55; p = 0.01).
In this study, the GT queries were examined, which could be used as Cyrillic equivalent terms to describe the grass pollen seasons in Ukraine. Using these terms, the GT queries were compared with Poaceae pollen counts and the meteorological parameter of the average daily temperature.
Our previous study showed that Ukrainian Google users apply the GT query “runny nose” (“nasmork” in Cyrillic) as “hay fever”.
Recent investigations showed that Ukrainian users apply the GT query “travy” (in Cyrillic) as “grass”. Thus, in further analysis, this Cyrillic equivalent was used.
In Ukraine, we needed to use “grass” (“travy” in Cyrillic) in addition to “allergy” and “hay fever” (“nasmork” in Cyrillic) to account for the pollen seasons. According to the GT queries profile, Ukraine had the “D” pattern in compliance with the classification by Bousquet J et al (2017).
Analysis of GT graphs revealed the peak of “allergy” queries in early summer, characteristic for grass pollen allergy. There was a strong positive correlation between the “pollen”, “allergy”, and “asthma” queries.
The comparison of GT queries with average daily temperature revealed a peak of “grass” queries before the maximum of average daily temperature. The number of “grass” queries correlated with the average daily temperature.
We analyzed the four-year Poaceae pollination, which revealed that Poaceae pollen seasons in Ukraine were similar to those in the Berlin and Brandenburg areas. Nevertheless, it was not possible to recognize the peak high pollen seasons using a concentration ≥50 pollen m−3 as a criterion as recommended by the EAACI definition.
According to our data, the allergy symptoms were associated with pollen counts of more than 8 pollen/m3 in the Ukrainian population. Thus, the correlation between regional pollen counts and Google searches for pollen allergy related terms might be a useful approach to determine pollen level induced allergy symptoms.
where grass pollen counts of 4.8 pollen/m3 were significantly associated with asthma exacerbations. A significant increase in asthma hospitalizations was observed for an interquartile range increase in grass pollen concentrations (5.9%, 95% CI:0.0, 12.0) in the Brussels region.
Three categories of Poaceae pollen daily concentration were recognized: 1–10 pollen/m3 – symptoms in individual patients; 11–50 pollen/m3 – symptoms in about 25% of patients, and >50 pollen/m3 – symptoms in all patients.
We compared the four-year Poaceae pollination and GT queries, concluding that to account for grass pollen exposure by GT, 3 terms are required in Ukraine: “allergy”, “grass”, and “asthma” (in Cyrillic equivalents). The combination of GT tools with Poaceae pollen counts may also be used in large-scale epidemiological studies. For an accurate description of the Poaceae pollen season, average daily temperature is an important factor. The results of our study may be used in further development of the MACVIA-ARIA sentinel network,
especially for countries where the Cyrillic alphabet is used.
Our data can also be used for computation of grass pollen seasons and as a successful tool for allergy patients to prevent or minimize exposure to elevated pollen concentrations. This approach may also assist researchers, providing insight into various factors driving the pollen season. Moreover, thee data may improve the definition of the grass pollen season, which mirrors the symptom load for grass-pollen induced allergy. Allergen immunotherapy specialists can monitor GT query profiles in a specific geographic location to determinatie the ideal time to begin allergen immunotherapy.
Consent for publication, and availability of data and materials
All authors consent to the publication of this work. Contact the corresponding author for questions regarding data and materials.
Statement of ethics
The authors have no ethical conflicts to disclose.
The authors declare that no competing interests exist.
I. Kaidashev conducted and supervised the manuscript development; H. Morokhovets provided the Google Trends search and statistical processing of the results; V. Rodinkova managed the process of pollen count; L. Dubuske and J. Bousquet designed the conceptual framework of the present research.
Declaration of competing interest
The authors have no conflicts of interest to declare.
We thank Yuliia Lysanets for her help in preparing this manuscript and in the submission process.
Human exposure to airborne pollen and relationships with symptoms and immune responses: indoors versus outdoors, circadian patterns and meteorological effects in alpine and urban environments.