This paper is in the following e-collection/theme issue:

Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1481) Data Science (223) Infodemiology and Infoveillance (1269) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1010) JMIR Theme Issue: COVID-19 Special Issue (2388)

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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18828, first published .
Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study

Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study

Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study

Authors of this article:

Seyed Mohammad Ayyoubzadeh1 Author Orcid Image ;   Seyed Mehdi Ayyoubzadeh2 Author Orcid Image ;   Hoda Zahedi3 Author Orcid Image ;   Mahnaz Ahmadi4 Author Orcid Image ;   Sharareh R Niakan Kalhori1 Author Orcid Image
Article Authors Cited by (239) Tweetations (6) Metrics

Journals

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  122. Ayala‐Cantu L, Frattini F, Morando B. Setting an example: Political leaders' cues and compliance with health policies in the early stages of the Covid‐19 pandemic in Mexico. Latin American Policy 2021;12(2):276 View
  123. Hu J, Lv S, Zhou T, Chen H, Xiao L, Huang X, Wang L, Wu P. Identification of Pulmonary Hypertension Animal Models Using a New Evolutionary Machine Learning Framework Based on Blood Routine Indicators. Journal of Bionic Engineering 2023;20(2):762 View
  124. Martínez V, García A, Moraleda I. 360 Video Trend on YouTube Before and During the COVID-19 Pandemic. Journal of Creative Communications 2022;17(1):22 View
  125. Husnayain A, Shim E, Fuad A, Su E. Predicting New Daily COVID-19 Cases and Deaths Using Search Engine Query Data in South Korea From 2020 to 2021: Infodemiology Study. Journal of Medical Internet Research 2021;23(12):e34178 View
  126. Basu S, Sen S. COVID 19 Pandemic, Socio-Economic Behaviour and Infection Characteristics: An Inter-Country Predictive Study Using Deep Learning. Computational Economics 2023;61(2):645 View
  127. Bitar H, Babour A, Nafa F, Alzamzami O, Alismail S. Increasing Women’s Knowledge about HPV Using BERT Text Summarization: An Online Randomized Study. International Journal of Environmental Research and Public Health 2022;19(13):8100 View
  128. Bağcı N, Peker I. Interest in dentistry in early months of the COVID‐19 global pandemic: A Google Trends approach. Health Information & Libraries Journal 2022;39(3):284 View
  129. Wang B, Liang B, Chen Q, Wang S, Wang S, Huang Z, Long Y, Wu Q, Xu S, Jinna P, Yang F, Ming W, Liu Q. COVID-19 Related Early Google Search Behavior and Health Communication in the United States: Panel Data Analysis on Health Measures. International Journal of Environmental Research and Public Health 2023;20(4):3007 View
  130. Lin C, Yousefi S, Kahoro E, Karisani P, Liang D, Sarnat J, Agichtein E. Detecting Elevated Air Pollution Levels by Monitoring Web Search Queries: Algorithm Development and Validation. JMIR Formative Research 2022;6(12):e23422 View
  131. 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
  132. Li J, Huang W, Sia C, Chen Z, Wu T, Wang Q. Enhancing COVID-19 Epidemic Forecasting Accuracy by Combining Real-time and Historical Data From Multiple Internet-Based Sources: Analysis of Social Media Data, Online News Articles, and Search Queries. JMIR Public Health and Surveillance 2022;8(6):e35266 View
  133. Li H, Hai M, Tang W. Prior Knowledge-Based Causal Inference Algorithms and Their Applications for China COVID-19 Analysis. Mathematics 2022;10(19):3568 View
  134. Widyasari V, Putra K, Wang J. Community Curiosity on COVID-19 Based on Google Trends in Indonesia: An Infodemic Study. Journal of Consumer Health on the Internet 2022;26(1):48 View
  135. Safaie N, Kaveie M, Mardanian S, Mohammadi M, Abdol Mohamadi R, Nasri S, Ijaz M. Investigation of Factors Affecting COVID-19 and Sixth Wave Management Using a System Dynamics Approach. Journal of Healthcare Engineering 2022;2022:1 View
  136. Abbasi S, Erdebilli B. Green Closed-Loop Supply Chain Networks’ Response to Various Carbon Policies during COVID-19. Sustainability 2023;15(4):3677 View
  137. Nabarrette M, Carneiro D, Santos P, Araujo C, Carvalho A, Meneghim M, Vedovello S. On-line Searches for Terms Related to Hand Hygiene During the COVID-19 Pandemic Worldwide. Pesquisa Brasileira em Odontopediatria e Clínica Integrada 2021;21 View
  138. Shafay M, Ahmad R, Salah K, Yaqoob I, Jayaraman R, Omar M. Blockchain for deep learning: review and open challenges. Cluster Computing 2023;26(1):197 View
  139. Khuhawar U, Siddiqui I, Arain Q, Siddiqui M, Qureshi N, Khattak H. On-Ground Distributed COVID-19 Variant Intelligent Data Analytics for a Regional Territory. Wireless Communications and Mobile Computing 2021;2021:1 View
  140. Amusa L, Twinomurinzi H, Okonkwo C. Modeling COVID-19 incidence with Google Trends. Frontiers in Research Metrics and Analytics 2022;7 View
  141. Mohammadi E, Azmin M, Fattahi N, Ghasemi E, Azadnajafabad S, Rezaei N, Rashidi M, Keykhaei M, Zokaei H, Rezaei N, Haghshenas R, Kaveh F, Pakatchian E, Jamshidi H, Farzadfar F. A pilot study using financial transactions’ spatial information to define high-risk neighborhoods and distribution pattern of COVID-19. DIGITAL HEALTH 2022;8:205520762210762 View
  142. Shukla A, Seth T, Muhuri P. Artificial intelligence centric scientific research on COVID-19: an analysis based on scientometrics data. Multimedia Tools and Applications 2023;82(21):32755 View
  143. Ali W, Zuo W, Ali R, Zuo X, Rahman G. Causality Mining in Natural Languages Using Machine and Deep Learning Techniques: A Survey. Applied Sciences 2021;11(21):10064 View
  144. KHAN R, SYAMIMI N, MAMBANG C, THOMAS I, WEE T. Visualisation System of COVID-19 Data in Malaysia. Trends in Undergraduate Research 2021;4(1):e8 View
  145. Ma M. COVID-19 concerns in cyberspace predict human reduced dispersal in the real world: Meta-regression analysis of time series relationships across American states and 115 countries/territories. Computers in Human Behavior 2022;127:107059 View
  146. Nikolić V, Subotić N, Subotić J, Marković-Denić L. Google trends as an aid in predicting the course of the COVID-19 epidemic in Serbia. Medicinski casopis 2021;55(2):59 View
  147. Yan H, Feng J, Chen X, Nilashi M. Prediction of the Normalized COVID-19 Epidemic Prevention Costs of Construction Projects Based on an Optimized Neural Network. Mathematical Problems in Engineering 2022;2022:1 View
  148. Obiała K, Obiała J, Mańczak M, Owoc J, Olszewski R. Type and reliability of information about coronavirus most frequently shared by social media users. Health Policy and Technology 2022;11(3):100626 View
  149. Wang M, Tang N. The correlation between Google trends and salmonellosis. BMC Public Health 2021;21(1) View
  150. Khoroshun D, Momynaliev K, Voronin E, Akimkin V. Analysis of Yandex search queries related to COVID‑19 in Russian Federation. Medical alphabet 2022;(14):14 View
  151. Ma S, Yang S. COVID-19 forecasts using Internet search information in the United States. Scientific Reports 2022;12(1) View
  152. Cai O, Sousa-Pinto B. United States Influenza Search Patterns Since the Emergence of COVID-19: Infodemiology Study. JMIR Public Health and Surveillance 2022;8(3):e32364 View
  153. Wang W, Cai J, Xu J, Wang Y, Zou Y. Prediction of the COVID-19 infectivity and the sustainable impact on public health under deep learning algorithm. Soft Computing 2023;27(5):2695 View
  154. Šušteršič T, Blagojević A, Cvetković D, Cvetković A, Lorencin I, Šegota S, Milovanović D, Baskić D, Car Z, Filipović N. Epidemiological Predictive Modeling of COVID-19 Infection: Development, Testing, and Implementation on the Population of the Benelux Union. Frontiers in Public Health 2021;9 View
  155. Gupta S, Shabaz M, Vyas S. Artificial intelligence and IoT based prediction of Covid-19 using chest X-ray images. Smart Health 2022;25:100299 View
  156. Hermosilla M, Ni J, Wang H, Zhang J. Unmet Needs: Healthcare Crowd-out During the COVID-19 Pandemic. SSRN Electronic Journal 2020 View
  157. Tan L, Tan Y, Qin J, Tang H, Xiang X, Xie D, N. Xiong N. Risk Prediction of Aortic Dissection Operation Based on Boosting Trees. Computers, Materials & Continua 2021;69(2):2583 View
  158. Ito T. Global monitoring of public interest in preventive measures against COVID-19 via analysis of Google Trends: an infodemiology and infoveillance study. BMJ Open 2022;12(8):e060715 View
  159. Feng Y, Shah C. Unifying telescope and microscope: A multi-lens framework with open data for modeling emerging events. Information Processing & Management 2022;59(2):102811 View
  160. Loola Bokonda P, Sidibe M, Souissi N, Ouazzani-Touhami K. Machine Learning Model for Predicting Epidemics. Computers 2023;12(3):54 View
  161. Feng Y, Cui X, Lv J, Yan B, Meng X, Zhang L, Guo Y, Peng L. Deep learning models for hepatitis E incidence prediction leveraging meteorological factors. PLOS ONE 2023;18(3):e0282928 View
  162. Król K, Zdonek D. Cultural Heritage Topics in Online Queries: A Comparison between English- and Polish-Speaking Internet Users. Sustainability 2023;15(6):5119 View
  163. Khaleel A, Abu Dayyih W, AlTamimi L, Dalaeen L, Zakaraya Z, Ahmad A, Albadareen B, Elbakkoush A. Predicting infection with COVID-19 disease using logistic regression model in Karak City, Jordan. F1000Research 2023;12:126 View
  164. 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
  165. Uzun Ozsahin D, Precious Onakpojeruo E, Bartholomew Duwa B, Usman A, Isah Abba S, Uzun B. COVID-19 Prediction Using Black-Box Based Pearson Correlation Approach. Diagnostics 2023;13(7):1264 View
  166. Kellner D, Lowin M, Hinz O. Improved healthcare disaster decision-making utilizing information extraction from complementary social media data during the COVID-19 pandemic. Decision Support Systems 2023;172:113983 View
  167. Li J, He Z, Zhang M, Ma W, Jin Y, Zhang L, Zhang S, Liu Y, Ma S. Estimating Rare Disease Incidences With Large-scale Internet Search Data: Development and Evaluation of a Two-step Machine Learning Method. JMIR Infodemiology 2023;3:e42721 View
  168. Tai C, Wang W, Huang Y. Using Time-Series Generative Adversarial Networks to Synthesize Sensing Data for Pest Incidence Forecasting on Sustainable Agriculture. Sustainability 2023;15(10):7834 View
  169. Porcu G, Chen Y, Bonaugurio A, Villa S, Riva L, Messina V, Bagarella G, Maistrello M, Leoni O, Cereda D, Matone F, Gori A, Corrao G. Web-based surveillance of respiratory infection outbreaks: retrospective analysis of Italian COVID-19 epidemic waves using Google Trends. Frontiers in Public Health 2023;11 View
  170. Yang X, Li S. Prediction of COVID-19 Using a WOA-BILSTM Model. Bioengineering 2023;10(8):883 View
  171. Wakabayashi T, Mansour H, Abishek R, Sridhar J, Cohen M, Xu D, Deaner J, Yonekawa Y, Hsu J, Kuriyan A, Bayoumi N. Google Search Trends to assess public interest in and concern about Vuity for treating presbyopia. PLOS ONE 2023;18(10):e0293066 View
  172. Chew N, Chong B, Kuo S, Jayabaskaran J, Cai M, Zheng H, Goh R, Kong G, Chin Y, Imran S, Liang M, Lim P, Yong T, Liew B, Chia P, Ho H, Foo D, Khoo D, Huang Z, Chua T, Tan J, Yeo K, Hausenloy D, Sim H, Kua J, Chan K, Loh P, Lim T, Low A, Chai P, Lee C, Yeo T, Yip J, Tan H, Mamas M, Nicholls S, Chan M. Trends and predictions of metabolic risk factors for acute myocardial infarction: findings from a multiethnic nationwide cohort. The Lancet Regional Health - Western Pacific 2023;37:100803 View
  173. Liu Y, Wolff K, Lo T. Big data in crime statistics: Using Google Trends to measure victimization in designated market areas across the United States. Methodological Innovations 2023;16(3):341 View
  174. Orojo O, Tepper J, McGinnity T, Mahmud M. The Multi-Recurrent Neural Network for State-Of-The-Art Time-Series Processing. Procedia Computer Science 2023;222:488 View
  175. Lösch L, Zuiderent-Jerak T, Kunneman F, Syurina E, Bongers M, Stein M, Chan M, Willems W, Timen A. Capturing Emerging Experiential Knowledge for Vaccination Guidelines Through Natural Language Processing: Proof-of-Concept Study. Journal of Medical Internet Research 2023;25:e44461 View
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  177. USTA G. Google Trend Özelinde Kullanıcıların Afetlere Yönelik İlgi Düzeylerinin Belirlenmesi. IBAD Sosyal Bilimler Dergisi 2022;(13):96 View
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  179. Hermosilla M, Ni J, Wang H, Zhang J. Leveraging the E-commerce footprint for the surveillance of healthcare utilization. Health Care Management Science 2023;26(4):604 View
  180. Haleem S, Albar N, Al fahad M, AlWasem H. Knowledge, Awareness, and Perception of COVID-19 and Artificial Intelligence: A Cross-Sectional Study Among the Population in Saudi Arabia. Cureus 2023 View
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  182. Mahdi H. Blockchain and Machine Learning as Deep Reinforcement. Wasit Journal of Computer and Mathematics Science 2023;2(1):46 View
  183. Rayan R, Suruliandi A, Raja S, David H. A Survey on an Analysis of Big Data Open Source Datasets, Techniques and Tools for the Prediction of Coronavirus Disease. Journal of Circuits, Systems and Computers 2023;32(12) View
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  185. Ge Y, Wang H, Cao J, Zhang Y, Jiang X. Privacy-preserving data publishing: an information-driven distributed genetic algorithm. World Wide Web 2024;27(1) View
  186. Kaur M, Cargill T, Hui K, Vu M, Bragazzi N, Kong J. A Novel Approach for the Early Detection of Medical Resource Demand Surges During Health Care Emergencies: Infodemiology Study of Tweets. JMIR Formative Research 2024;8:e46087 View
  187. Shoeibi A, Khodatars M, Jafari M, Ghassemi N, Sadeghi D, Moridian P, Khadem A, Alizadehsani R, Hussain S, Zare A, Sani Z, Khozeimeh F, Nahavandi S, Acharya U, Gorriz J. Automated detection and forecasting of COVID-19 using deep learning techniques: A review. Neurocomputing 2024;577:127317 View
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Books/Policy Documents

  1. Soliman M, Darwish A, Hassanien A. Digital Transformation and Emerging Technologies for Fighting COVID-19 Pandemic: Innovative Approaches. View
  2. Rekha H, Behera H, Nayak J, Naik B. Intelligent Computing in Control and Communication. View
  3. Saire J, Cruz J. Information Management and Big Data. View
  4. Folorunso S, Awotunde J, Adeboye N, Matiluko O. Advances in Data Science and Intelligent Data Communication Technologies for COVID-19. View
  5. Orojo O, Tepper J, McGinnity T, Mahmud M. Applied Intelligence and Informatics. View
  6. Erol Genevois M, Cedolin M. New Perspectives in Operations Research and Management Science. View
  7. Khemani B, Sabhani J, Goplani M. Proceedings of Third International Conference on Computing, Communications, and Cyber-Security. View
  8. Lefèvre T, Colineaux H, Morgand C, Tournois L, Delpierre C. Artificial Intelligence in Covid-19. View
  9. Ge Y, Wang H, Cao J, Zhang Y. Web Information Systems Engineering – WISE 2022. View
  10. Goyal A, Puri K, Jain R, Nagrath P. International Conference on Innovative Computing and Communications. View
  11. Pham H, Nguyen Q. Artificial Intelligence in Data and Big Data Processing. View
  12. Muhammad L, Algehyne E, Usman S, Mohammed I, Abdulkadir A, Jibrin M, Malgwi Y. Trends and Advancements of Image Processing and Its Applications. View
  13. Gracia D, Martínez V. Communication and Smart Technologies. View
  14. Sah S, Kamerkar A, Surendiran B, Dhanalakshmi R. Intelligent Data Engineering and Analytics. View
  15. Wiwanittkit V, Wayalun S. Emerging Technologies During the Era of COVID-19 Pandemic. View
  16. Lukman A, Benedicta A, Awotunde J, Okon C, Oludoun O, Oluwakemi A, Ayinde O, Alabi O, Adeniyi A. Modeling, Control and Drug Development for COVID-19 Outbreak Prevention. View
  17. Fatima M, Rextin A, Nasim M, Yusuf O. Disinformation in Open Online Media. View
  18. Ojokoh B, Sarumi O, Salako K, Gabriel A, Taiwo A, Johnson O, Adegun I, Babalola O. Data Science for COVID-19. View
  19. da Silva A, de Lima C, da Silva C, Moreno G, Silva E, Marques G, de Araújo L, Júnior L, de Souza S, de Santana M, Gomes J, de Freitas Barbosa V, Musah A, Kostkova P, da Silva Filho A, dos Santos W. Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis. View
  20. Lozano M, Orts Ò, Piñol E, Rebollo M, Polotskaya K, Garcia-March M, Conejero J, Escolano F, Oliver N. Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track. View
  21. Raman V, Aravinth N, Joy P, Kowsalya . Proceedings of the International Conference on Emerging Trends in Business & Management (ICETBM 2023). View
  22. Atighehchian A, Alidadi T, Mohammadi R, Lotfi F, Ajami S. Advances in Computer Science for Engineering and Education VI. View
  23. Hussain A, Basak R, Mandal S. AGC 2023. View
  24. Butt Z. Artificial Intelligence, Big Data, Blockchain and 5G for the Digital Transformation of the Healthcare Industry. View
  25. Dhoot A, Deva R, Shukla V. Cryptology and Network Security with Machine Learning. View
  26. Hazimze H, Gaou S, Akhlil K. Advancements in Climate and Smart Environment Technology. View
  27. Chumachenko D. Data-Centric Business and Applications. View