Published on in Vol 6, No 2 (2020): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19702, first published .
Correlations of Online Search Engine Trends With Coronavirus Disease (COVID-19) Incidence: Infodemiology Study

Correlations of Online Search Engine Trends With Coronavirus Disease (COVID-19) Incidence: Infodemiology Study

Correlations of Online Search Engine Trends With Coronavirus Disease (COVID-19) Incidence: Infodemiology Study

Journals

  1. Qu H, Cheng Z, Duan Z, Tian L, Hakonarson H. The Infection Rate of COVID-19 in Wuhan, China: Combined Analysis of Population Samples. Journal of Medical Internet Research 2020;22(8):e20914 View
  2. Rajan A, Sharaf R, Brown R, Sharaiha R, Lebwohl B, Mahadev S. Association of Search Query Interest in Gastrointestinal Symptoms With COVID-19 Diagnosis in the United States: Infodemiology Study. JMIR Public Health and Surveillance 2020;6(3):e19354 View
  3. Gong X, Han Y, Hou M, Guo R. Online Public Attention During the Early Days of the COVID-19 Pandemic: Infoveillance Study Based on Baidu Index. JMIR Public Health and Surveillance 2020;6(4):e23098 View
  4. Senecal C, Gulati R, Lerman A. Google Trends Insights Into Reduced Acute Coronary Syndrome Admissions During the COVID-19 Pandemic: Infodemiology Study. JMIR Cardio 2020;4(1):e20426 View
  5. Arshad Ali S, Bin Arif T, Maab H, Baloch M, Manazir S, Jawed F, Ochani R. Global Interest in Telehealth During COVID-19 Pandemic: An Analysis of Google Trends™. Cureus 2020 View
  6. Paguio J, Yao J, Dee E. Silver lining of COVID-19: Heightened global interest in pneumococcal and influenza vaccines, an infodemiology study. Vaccine 2020;38(34):5430 View
  7. Dai Y, Wang J, Samy A. Identifying the outbreak signal of COVID-19 before the response of the traditional disease monitoring system. PLOS Neglected Tropical Diseases 2020;14(10):e0008758 View
  8. Álvarez-Mon M, Rodríguez-Quiroga A, de Anta L, Quintero J. Aplicaciones médicas de las redes sociales. Aspectos específicos de la pandemia de la COVID-19. Medicine - Programa de Formación Médica Continuada Acreditado 2020;13(23):1305 View
  9. Cleverley P, Cousins F, Burnett S. Impact of COVID-19 on search in an organisation. Journal of Information Science 2023;49(1):43 View
  10. Momynaliev K, Khoperskay L, Pshenichnaya N, Abuova G, Akimkin V. Infodemiological study of coronavirus epidemic using Google Trends in Central Asian Republics of Kazakhstan, Kyrgyzstan, Uzbekistan, Tajikistan. Medical alphabet 2021;(34):47 View
  11. Schnoell J, Besser G, Jank B, Bartosik T, Parzefall T, Riss D, Mueller C, Liu D. The association between COVID-19 cases and deaths and web-based public inquiries. Infectious Diseases 2021;53(3):176 View
  12. Wu A, Higgins T, Ting J, Illing E. Use of Google Trends to investigate anosmia: power and pitfalls of infodemiology. International Forum of Allergy & Rhinology 2021;11(5):957 View
  13. Jimenez A, Estevez-Reboredo R, Santed M, Ramos V. COVID-19 Symptom-Related Google Searches and Local COVID-19 Incidence in Spain: Correlational Study. Journal of Medical Internet Research 2020;22(12):e23518 View
  14. Rubel K, Sharma D, Campiti V, Yedlicka G, Burgin S, Illing E, Kroenke K, Ting J. COVID‐19 Status Differentially Affects Olfaction: A Prospective Case‐Control Study. OTO Open 2020;4(4) View
  15. Cui H, Kertész J. Attention dynamics on the Chinese social media Sina Weibo during the COVID-19 pandemic. EPJ Data Science 2021;10(1) View
  16. Badell-Grau R, Cuff J, Kelly B, Waller-Evans H, Lloyd-Evans E. Investigating the Prevalence of Reactive Online Searching in the COVID-19 Pandemic: Infoveillance Study. Journal of Medical Internet Research 2020;22(10):e19791 View
  17. Sousa-Pinto B, Heffler E, Antó A, Czarlewski W, Bedbrook A, Gemicioglu B, Canonica G, Antó J, Fonseca J, Bousquet J. Anomalous asthma and chronic obstructive pulmonary disease Google Trends patterns during the COVID-19 pandemic. Clinical and Translational Allergy 2020;10(1) View
  18. Englund T, Kinlaw A, Sheikh S. Rise and Fall: Hydroxychloroquine and COVID‐19 Global Trends: Interest, Political Influence, and Potential Implications. ACR Open Rheumatology 2020;2(12):760 View
  19. ESEN M. COVID-19 salgınıyla ilişkili semptomların Türkiye’den gerçekleştirilen internet arama motoru sorgularının incelenmesi. Journal of Medicine and Palliative Care 2021;2(1):7 View
  20. Wong M, Gunasekeran D, Nusinovici S, Sabanayagam C, Yeo K, Cheng C, Tham Y. Telehealth Demand Trends During the COVID-19 Pandemic in the Top 50 Most Affected Countries: Infodemiological Evaluation. JMIR Public Health and Surveillance 2021;7(2):e24445 View
  21. Worrall A, Kelly C, O'Neill A, O'Doherty M, Kelleher E, Cushen A, McNally C, McConkey S, Glavey S, Lavin M, de Barra E. Online Search Trends Influencing Anticoagulation in Patients With COVID-19: Observational Study. JMIR Formative Research 2021;5(8):e21817 View
  22. Ortega J, Bernabé-Moreno J. Modelling the Degree of Emotional Concern: COVID-19 Response in Social Media. Applied Sciences 2021;11(9):3872 View
  23. Steiger E, Mussgnug T, Kroll L, Lim S. Causal graph analysis of COVID-19 observational data in German districts reveals effects of determining factors on reported case numbers. PLOS ONE 2021;16(5):e0237277 View
  24. Peng Y, Li C, Rong Y, Pang C, Chen X, Chen H. Real-time Prediction of the Daily Incidence of COVID-19 in 215 Countries and Territories Using Machine Learning: Model Development and Validation. Journal of Medical Internet Research 2021;23(6):e24285 View
  25. Paramita M, Orphanou K, Christoforou E, Otterbacher J, Hopfgartner F. Do you see what I see? Images of the COVID-19 pandemic through the lens of Google. Information Processing & Management 2021;58(5):102654 View
  26. Tseng P, Tsai F, Hsu J, Chang Y, Wang K, Wu M, Chen M, Su C, Shia B, Miser J. Public Awareness as a Line of Defense Against COVID-19 in Taiwan. Asia Pacific Journal of Public Health 2021;33(8):981 View
  27. SeyyedHosseini S, BasirianJahromi R. COVID-19 pandemic in the Middle East countries: coronavirus-seeking behavior versus coronavirus-related publications. Scientometrics 2021;126(9):7503 View
  28. Riswantini D, Nugraheni E, Arisal A, Khotimah P, Munandar D, Suwarningsih W. Big Data Research in Fighting COVID-19: Contributions and Techniques. Big Data and Cognitive Computing 2021;5(3):30 View
  29. Cinarka H, Uysal M, Cifter A, Niksarlioglu E, Çarkoğlu A. The relationship between Google search interest for pulmonary symptoms and COVID-19 cases using dynamic conditional correlation analysis. Scientific Reports 2021;11(1) View
  30. Sato K, Mano T, Iwata A, Toda T. Need of care in interpreting Google Trends-based COVID-19 infodemiological study results: potential risk of false-positivity. BMC Medical Research Methodology 2021;21(1) View
  31. Satpathy P, Kumar S, Prasad P. Suitability of Google Trends™ for Digital Surveillance During Ongoing COVID-19 Epidemic: A Case Study from India. Disaster Medicine and Public Health Preparedness 2023;17 View
  32. Shee V, Louis C. Language Barriers to Online Search Interest for COVID-19: A Global Infodemiological Study. Cureus 2022 View
  33. Zhang Q, Yu Y, He J, Yao X, He Y, Wu J, Xu C, Ye C. Did the COVID-19 pandemic impact urticaria information-seeking behavior in China? A retrospective longitudinal study. Frontiers in Public Health 2023;11 View
  34. Pulido-Polo M, Jiménez-Marín G, Pérez Curiel C, Vázquez-González J. Twitter como herramienta de comunicación institucional: la Casa Real Británica y la Casa Real Española en el contexto postpandémico. Revista de Comunicación 2022;21(2):225 View
  35. Aragón-Ayala C, Copa-Uscamayta J, Herrera L, Zela-Coila F, Quispe-Juli C. Interest in COVID-19 in Latin America and the Caribbean: an infodemiological study using Google Trends. Cadernos de Saúde Pública 2021;37(10) View
  36. Rochford B, Pendse S, Kumar N, De Choudhury M. Leveraging Symptom Search Data to Understand Disparities in US Mental Health Care: Demographic Analysis of Search Engine Trace Data. JMIR Mental Health 2023;10:e43253 View
  37. TİRGİL M, ÇULHA E, DEMİRCİ Ş. Google arama motoru Türkiye’de Covid-19 salgınının yayılımının izlenmesinde ve tahmininde kullanılabilir mi?. Mersin Üniversitesi Sağlık Bilimleri Dergisi 2021;14(3):520 View
  38. Quach H, Pham T, Hoang N, Phung D, Nguyen V, Le S, Le T, Bui T, Le D, Dang A, Tran D, Ngu N, Vogt F, Nguyen C, Sung W. Using ‘infodemics’ to understand public awareness and perception of SARS-CoV-2: A longitudinal analysis of online information about COVID-19 incidence and mortality during a major outbreak in Vietnam, July—September 2020. PLOS ONE 2022;17(4):e0266299 View
  39. Madden K, Feldman B. Anosmia-related internet search and the course of the first wave of the COVID-19 pandemic in the United States. Heliyon 2021;7(12):e08499 View
  40. Niu Q, Liu J, Zhao Z, Onishi M, Kawaguchi A, Bandara A, Harada K, Aoyama T, Nagai-Tanima M. Explanation of hand, foot, and mouth disease cases in Japan using Google Trends before and during the COVID-19: infodemiology study. BMC Infectious Diseases 2022;22(1) View
  41. ÇİMKE S, YILDIRIM GÜRKAN D. Determining the Global Corona Agenda via Google Trends. Black Sea Journal of Public and Social Science 2022;5(1):17 View
  42. Htay M, Parial L, Tolabing M, Dadaczynski K, Okan O, Leung A, Su T, Padhi B. Digital health literacy, online information-seeking behaviour, and satisfaction of Covid-19 information among the university students of East and South-East Asia. PLOS ONE 2022;17(4):e0266276 View
  43. Coro G, Bove P. A High-resolution Global-scale Model for COVID-19 Infection Rate. ACM Transactions on Spatial Algorithms and Systems 2022;8(3):1 View
  44. Ho M, Tadrous M, Iacono A, Suda K, Gomes T. Outpatient purchasing patterns of hydroxychloroquine and ivermectin in the USA and Canada during the COVID-19 pandemic: an interrupted time series analysis from 2016 to 2021. Journal of Antimicrobial Chemotherapy 2023;78(1):242 View
  45. Trevino J, Malik S, Schmidt M. Integrating Google Trends Search Engine Query Data Into Adult Emergency Department Volume Forecasting: Infodemiology Study. JMIR Infodemiology 2022;2(1):e32386 View
  46. Samadbeik M, Garavand A, Aslani N, Ebrahimzadeh F, Fatehi F, Kardeş S. Assessing the online search behavior for COVID-19 outbreak: Evidence from Iran. PLOS ONE 2022;17(7):e0267818 View
  47. An L, Russell D, Mihalcea R, Bacon E, Huffman S, Resnicow K. Online Search Behavior Related to COVID-19 Vaccines: Infodemiology Study. JMIR Infodemiology 2021;1(1):e32127 View
  48. Chen J, Mi H, Fu J, Zheng H, Zhao H, Yuan R, Guo H, Zhu K, Zhang Y, Lyu H, Zhang Y, She N, Ren X. Construction and validation of a COVID-19 pandemic trend forecast model based on Google Trends data for smell and taste loss. Frontiers in Public Health 2022;10 View
  49. Lamba J, Jain E. A review on unprecedented influence of COVID-19 on stock market: what communities should know?. Journal of Enterprising Communities: People and Places in the Global Economy 2023;17(6):1088 View
  50. Saegner T, Austys D. Forecasting and Surveillance of COVID-19 Spread Using Google Trends: Literature Review. International Journal of Environmental Research and Public Health 2022;19(19):12394 View
  51. Chen Y, Liu Y, Yan Y. Revealing the spatiotemporal characteristics of the general public's panic levels during the pandemic crisis in China. Transactions in GIS 2023;27(1):176 View
  52. Pulido Polo M, Sánchez González M, Mesa Göbel J, Vázquez-González J. La Moncloa en Twitter: un análisis cuantitativo en la era post COVID. Revista Latina de Comunicación Social 2023;(81) View
  53. Locatelli M, Cunha E, Guiginski J, Franco R, Bernardes T, Alzamora P, Silva D, Ganem M, Santos T, Carvalho A, Souza L, Paixão G, Chaves E, Santos G, Santos R, Freitas A, Flores M, Biezuner R, Cardoso R, Fonseca R, Silva A, Meira Jr W. Correlations between Web Searches and COVID-19 Epidemiological Indicators in Brazil. Brazilian Archives of Biology and Technology 2022;65 View
  54. Momynaliev K, Khoroshun D, Akimkin V. Online queries as a criterion for evaluating epidemiological status and effectiveness of COVID-19 control measures in Russia: results from Yandex.Wordstat analysis. BMJ Open 2022;12(7):e056716 View
  55. Ming W, Huang F, Chen Q, Liang B, Jiao A, Liu T, Wu H, Akinwunmi B, Li J, Liu G, Zhang C, Huang J, Liu Q. Understanding Health Communication Through Google Trends and News Coverage for COVID-19: Multinational Study in Eight Countries. JMIR Public Health and Surveillance 2021;7(12):e26644 View
  56. Zayed B, Talaia A, Gaaboobah M, Amer S, Mansour F. Google Trends as a predictive tool in the era of COVID-19: a scoping review. Postgraduate Medical Journal 2023;99(1175):962 View
  57. Amzat J, Kanmodi K, Egbedina E. Infoveillance and bibliometric analysis of COVID‐19 in Nigeria. Public Health Challenges 2023;2(1) View
  58. García-García S, Rodríguez-Díaz R. Official Information on Twitter during the Pandemic in Spain. Societies 2023;13(4):91 View
  59. Li X, Tang K. Effects of Online Health Information-Seeking Behavior on Sexually Transmitted Disease in China: An Infodemiology Study Based on the Baidu Index. SSRN Electronic Journal 2022 View
  60. Li X, Tang K. The Effects of Online Health Information–Seeking Behavior on Sexually Transmitted Disease in China: Infodemiology Study of the Internet Search Queries. Journal of Medical Internet Research 2023;25:e43046 View
  61. Melián-Fleitas L, Franco-Pérez Á, Sanz-Valero J, Wanden-Berghe C. Population Interest in Information on Obesity, Nutrition, and Occupational Health and Its Relationship with the Prevalence of Obesity: An Infodemiological Study. Nutrients 2023;15(17):3773 View
  62. Costa I, Nisa M, Ferreira L. Online Search Patterns about Vaccination: A National Study. Portuguese Journal of Public Health 2022;40(3):134 View
  63. Latorre A, Nakamura K, Seino K, Hasegawa T. Vector Autoregression for Forecasting the Number of COVID-19 Cases and Analyzing Behavioral Indicators in the Philippines: Ecologic Time-Trend Study. JMIR Formative Research 2023;7:e46357 View
  64. Ishizuka K, Miyagami T, Tsuchida T, Saita M, Ohira Y, Naito T, Santangelo O. Online search interest in long-term symptoms of coronavirus disease 2019 during the COVID-19 pandemic in Japan: Infodemiology study using the most visited search engine in Japan. PLOS ONE 2023;18(11):e0294261 View
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  66. Kanamori R, Umemura F, Uemura K, Miyagami T, Valenti S, Fukui N, Yuda M, Saita M, Mori H, Naito T. Web-Based Search Volume for HIV Tests and HIV-Testing Preferences During the COVID-19 Pandemic in Japan: Infodemiology Study. JMIR Formative Research 2024;8:e52306 View
  67. Lyu S, Adegboye O, Adhinugraha K, Emeto T, Taniar D. Analysing the impact of comorbid conditions and media coverage on online symptom search data: a novel AI-based approach for COVID-19 tracking. Infectious Diseases 2024;56(5):348 View
  68. Comer L, Donelle L, Hiebert B, Smith M, Kothari A, Stranges S, Gilliland J, Long J, Burkell J, Shelley J, Hall J, Shelley J, Cooke T, Ngole Dione M, Facca D. Short- and Long-Term Predicted and Witnessed Consequences of Digital Surveillance During the COVID-19 Pandemic: Scoping Review. JMIR Public Health and Surveillance 2024;10:e47154 View
  69. Wecker H, Ziehfreund S, Sitaru S, Johansson E, Elberling J, Doll A, Nicolaidou E, Scala E, Boffa M, Schmidt L, Sikora M, Torres T, Chernyshov P, Zink A. Burden of atopic dermatitis in Europe: A population‐centred approach leveraging web search data in 21 European countries. Journal of the European Academy of Dermatology and Venereology 2024 View
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  71. Alfano V. Unravelling the Web: The Internet’s Double-Edged Impact on COVID-19 Dynamics. Italian Economic Journal 2024 View
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Books/Policy Documents

  1. Nassi M, Riza E, Bouziani E. SDGs in the European Region. View
  2. Galido A, Ecleo J. Novel & Intelligent Digital Systems: Proceedings of the 2nd International Conference (NiDS 2022). View
  3. Champagne-Poirier O, Carignan M, David M, O’Sullivan T, Marcotte G. Infodemic Disorder. View
  4. Butt Z. Accelerating Strategic Changes for Digital Transformation in the Healthcare Industry. View
  5. Nassi M, Riza E, Bouziani E. SDGs in the European Region. View