COVID-19 Pandemisi Döneminde Romatizmal Hastalıklara Halkın İlgisi: Google Trends Verilerinin Analizi

Amaç: Çalışmanın amacı Koronavirüs Hastalığı-2019 (COVID-19) pandemisi sırasında romatizmal hastalıklara halkın ilgisini Google Trends verilerinin analizi ile değerlendirmektir. Gereç ve Yöntemler: Çalışmanın tüm verileri Google arama sayılarının ve ilişkilerinin paylaşıldığı, https://trends.google.com/trends/ aracılığıyla Google Trends veri tabanından elde edildi. Bu çalışma Mart 2019-Mart 2020 (pandemi öncesi dönem) ve Mart 2020-Mart 2021 (pandemi dönemi) arasında yapılan aramaları içermektedir. Google Trends arama terimleri gut, fibromiyalji, ailevi Akdeniz ateşi, Behçet hastalığı, sistemik lupus eritematosus, ankilozan spondilit, romatoid artrit, osteoartrit, sjögren sendromu ve skleroderma olarak belirlendi. Türkiye seçimiyle arama yoğunlaşmaları tüm kategorilerde incelendi. Bulgular: Çalışmamızda Türkiye’de romatizmal hastalıklara olan dijital ilginin GT verileri karşılaştırıldı. Pandemi öncesi dönem ve pandemi döneminde göreli arama hacmi en fazla olan ilk beş romatizmal hastalığın gut, fibromiyalji, ailevi Akdeniz ateşi, Behçet hastalığı ve sistemik lupus eritematozus olduğu tespit edildi. On arama terimi için ilgili arama hacmi incelendiğinde pandemi döneminde ailesel Akdeniz ateşi, ankilozan spondilit, romatoid artrit ve sjögren sendromu istatistiksel olarak anlamlı derecede azalırken Behçet hastalığı arama terimi anlamlı ölçüde arttı. Sonuç: COVID-19 gibi pandemilerde çevrim içi internet arama sonuçlarının değerlendirilmesi hem halkın hastalıklara olan ilgisini ve eğilimlerini belirleme hem de toplumsal farkındalığın oluşturulabilmesi açısından önemlidir. Farkındalık günlerinin hastalıkların tanınmasında potansiyel faydalar sağlaması nedeniyle daha fazla vurgulanması gerektiğini düşünmekteyiz.

Public Interest in Rheumatic Diseases during the COVID-19 Pandemic: Analysis of Google Trends Data

Aim: The aim of the study is to evaluate the public interest in rheumatic diseases during the Coronavirus Disease-2019 (COVID-19) pandemic by using Google Trends data. Material and methods: All data of the study were obtained from the Google Trends database via https://trends.google.com/trends/, where Google search numbers and relationships are shared. This study contains the searches made between March 2019-March 2020 (pre-pandemic period) and March 2020-March 2021 (pandemic period). Google Trends search terms were determined as gout, fibromyalgia, familial Mediterranean fever, Behçet's disease, systemic lupus erythematosus, ankylosing spondylitis, rheumatoid arthritis, osteoarthritis, Sjogren's syndrome, and scleroderma. All categories was chosen as subject and Turkey was chosen as the country. Results: In our study, GT data of digital interest in rheumatic diseases in Turkey were compared. It was determined that the first five rheumatic diseases with the highest relative search volume in the pre-pandemic and pandemic periods were gout, fibromyalgia, familial Mediterranean fever, Behçet's disease and systemic lupus erythematosus. When the relevant search volume for 10 search terms was examined, familial Mediterranean fever, ankylosing spondylitis, rheumatoid arthritis and Sjögren's syndrome decreased statistically during the pandemic period, while the search term for Behçet's disease increased significantly. Conclusion: Evaluation of online internet search results in pandemics such as COVID-19 is important both in terms of determining the public's interest and tendencies towards diseases and creating social awareness. We think that awareness days should be emphasized more, because it provides potential benefits in the recognition of diseases.

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  • Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. A novel corona virüs from patients with pneumonia in China, 2019. N Engl J Med. 2020; 382(8): 727-33.
  • World Health Organization announces COVID-19 outbreak a pandemic. https://www.euro.who.int/en/health-topics/healthemergencies/ coronavirus-covid-19/news/news/2020/3/whoannounces-covid-19-outbreak-a-pandemic/.Accessed 25 October 2021.
  • Demirbilek Y, Pehlivantürk G, Özgüler ZÖ, Alp Meşe E. COVID-19 outbreak control, example of ministry of health of Turkey. Turk J Med Sci. 2020; 50(SI-1): 489-94.
  • Sultanoğlu H, Boğan M, Erdem Sultanoğlu T, Altınsoy HB. Examination of physiological changes seen in workers using breathing masks during COVID-19 Pandemic. Hospital Practices and Research. 2021; 6(3): 93-7.
  • Ladani AP, Loganathan M, Danve A. Managing rheumatic diseases during COVID-19. Clin Rheumatol. 2020; 39(11): 3245-54.
  • Kastritis E, Kitas GD, Vassilopoulos D, Giannopoulos G, Dimopoulos MA, Sfikakis PP. Systemic autoimmune diseases, anti-rheumatic therapies, COVID-19 infection risk and patient outcomes. Rheumatology international. 2020; 40(9): 1353-60.
  • Sultanoğlu TE, Ataoğlu S. Düzce University Faculty of Medicine Department of Physical Medicine and Rehabilitation in the COVID-19 pandemic process. Konuralp Medical Journal. 2000;12(S1):386-7.
  • Datareportal.org [Internet]. Singapore: Digital 2021 Turkey; 2021 March 11 [ Updated: 2021 March 11; Cited: 2021 October 10]. Available from: https://datareportal.com/reports/digital-2021-turkey.
  • Statcounter Globalstats [Internet]. Ireland: Search-Engine-Market-Share Turkey; 2021 September 30[Updated: 2021 September 30; Cited: 2021 October 10].Available from: https://gs.statcounter.com/search-engine-market-share/all/turkey.
  • Brownstein JS, Freifeld CC, Madoff LC. Digital disease detection harnessing the Web for public health surveillance. The New England journal of medicine. 2009; 360(21): 2153-57.
  • Salathe M, Bengtsson L, Bodnar TJ, Brewer DD, Brownstein JS, Buckee C, et al. Digital epidemiology. PLoS computational biology. 2012; 8(7): e1002616.
  • Carneiro HA, Mylonakis E. Google trends: a web-based tool for real-time surveillance of disease outbreaks. Clin Infect Dis. 2009; 49(10): 1557-64.
  • Lu FS, Hou S, Baltrusaitis K, Shah M, Leskovec J, Hawkins J, Santillana M. Accurate influenza monitoring and forecasting using novel internet data streams: a case study in the Boston Metropolis. JMIR public health and surveillance. 2018; 4(1): e4.
  • Teng Y, Bi D, Xie G, Jin Y, Huang Y, Lin B, Tong Y. Dynamic forecasting of Zika epidemicusing Google Trends. PloSone. 2017; 12(1): e0165085.
  • Guzman AK, Barbieri JS. Analysis of dermatology-related search engine trends during the COVID-19 pandemic: Implications for patient demand for outpatient services and telehealth. J Am Acad Dermatol. 2020; 83(3): 963-5.
  • Dhanda AK, Leverant E, Leshchuk K, Paskhover B. A Google Trends analysis of facial plastic surgery interest during the COVID-19 pandemic. Aesthetic Plast Surg 2020; 44(4): 1378-80.
  • Bhambhvani HP, Tijerina JD, Parham MJ, Greenberg DR, Eisenberg ML. Public interest in elective urologic procedures in the COVID-19 pandemic: A Google Trends analysis. Urology Practice. 2020; 7(6): 496-501.
  • Kardeş S, Kuzu AS, Raiker R, Pakhchanian H, Karagülle M. Public interest in rheumatic diseases and rheumatologist in the United States during the COVID-19 pandemic: evidence from Google Trends. Rheumatology International. 2021; 41(2): 329-34.
  • Mavragani A, Ochoa G. Google Trends in infodemiology and infoveillance: methodology framework. JMIR public health and surveillance. 2019; 5(2): e13439.
  • Misitzis A, Weinstock MA. Increased interest in sunless tanning versus tanning beds in the United States: A Google Trends analysis. Journal of the American Academy of Dermatology. 2019; 81(6): 1438-9.
  • Landy DC, Chalmers BP, Utset-Ward TJ, Ast MP. Public interest in knee replacement fell during the onset of the COVID-19 pandemic: a Google Trends analysis. HSS Journal. 2020; 16(1): 24-8.
  • Pier MM, Pasick LJ, Benito DA, Alnouri G, Sataloff RT. Otolaryngology-related Google Search trends during the COVID-19 pandemic. Am J Otolaryngol. 2020; 41(6): 102615.
  • Google: Google Trends. Erişim: https://trends.google.com.tr/ Erişim tarihi: 01.10.2021
  • Yıldız MS. Google Arama Trendleri: Türkiye’de Sağlık Hizmetleri ile İlişkili Aramalar için Bir Uygulama. Uluslararası Sağlık Yönetimi Ve Stratejileri Araştırma Dergisi. 2018; 4(2): 168-79.
  • Akkoç N. Türkiye'de romatizmal hastalıkların epidemiyolojisi ve diğer ülkelerle karşılaştırılması. J Turk Soc Rheumatol. 2010; 2(2): 1-8.
  • Ciaffi J, Meliconi R, Landini MP, Ursini F. Google trends and COVID-19 in Italy: could we brace for impact? Internal and Emergency Medicine. 2020; 15(1): 1555-9.
  • Çölgeçen E, Özyurt K, Ferahbaş A, Borlu M, Kulluk P, Öztürk A, et al. The prevalence of Behçet's disease in a city in Central Anatolia in Turkey. International Journal of Dermatology. 2015; 54(3): 286-9.
  • Pinto AJ, Dunstan DW, Owen N, Bonfá E, Gualano B. Combating physical inactivity during the COVID-19 pandemic. Nature Reviews Rheumatology. 2020; 16(7): 347-8.
Sağlık Bilimlerinde Değer-Cover
  • Yayın Aralığı: Yılda 3 Sayı
  • Başlangıç: 2022
  • Yayıncı: Düzce Üniversitesi