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A Large-Scale Dataset of Search Interests Related to Disease X Originating from Different Geographic Regions. (2023). Duggal, Yuvraj Nihal ; Cui, Shuqi ; Thakur, Nirmalya ; Patel, Kesha A ; Hall, Isabella.
In: Data.
RePEc:gam:jdataj:v:8:y:2023:i:11:p:163-:d:1268303.

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  95. Thakur, N.; Hall, I.; Han, C.Y. A Comprehensive Study to Analyze Trends in Web Search Interests Related to Fall Detection before and after COVID-19. In Proceedings of the 2022 5th International Conference on Computer Science and Software Engineering (CSSE 2022), New York, NY, USA, 21–23 October 2022.
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  96. Thakur, N.; Han, C. An Exploratory Study of Tweets about the SARS-CoV-2 Omicron Variant: Insights from Sentiment Analysis, Language Interpretation, Source Tracking, Type Classification, and Embedded URL Detection. COVID 2022, 2, 1026–1049. [CrossRef]
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  97. Thakur, N.; Han, C.Y. A Framework for Prediction of Cramps during Activities of Daily Living in Elderly. In Proceedings of the 2020 International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE), Fuzhou, China, 12–14 June 2020.
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  98. Thakur, N.; Han, C.Y. A Human-Human Interaction-Driven Framework to Address Societal Issues. In Human Interaction, Emerging Technologies and Future Systems V; Springer International Publishing: Cham, Switzerland, 2022; pp. 563–571, ISBN 9783030855390.
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  99. Thakur, N.; Han, C.Y. A Multimodal Approach for Early Detection of Cognitive Impairment from Tweets. In Human Interaction, Emerging Technologies and Future Systems V; Springer International Publishing: Cham, Switzerland, 2022; pp. 11–19, ISBN 9783030855390.
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  100. Thakur, N.; Han, C.Y. An Approach for Detection of Walking Related Falls during Activities of Daily Living. In Proceedings of the 2020 International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE), Fuzhou, China, 12–14 June 2020.
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  101. Thakur, N.; Han, C.Y. An Intelligent Ubiquitous Activity Aware Framework for Smart Home. In Human Interaction, Emerging Technologies and Future Applications III; Springer International Publishing: Cham, Switzerland, 2021; pp. 296–302, ISBN 9783030553067.
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  102. Thakur, N.; Han, C.Y. Country-Specific Interests towards Fall Detection from 2004–2021: An Open Access Dataset and Research Questions. Data 2021, 6, 92. [CrossRef]

  103. Thakur, N.; Han, C.Y. Google Trends to Investigate the Degree of Global Interest Related to Indoor Location Detection. In Human Interaction, Emerging Technologies and Future Systems V; Springer International Publishing: Cham, Switzerland, 2022; pp. 580–588, ISBN 9783030855390.
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  104. Thakur, N.; Han, C.Y. Indoor Localization for Personalized Ambient Assisted Living of Multiple Users in Multi-Floor Smart Environments. Big Data Cogn. Comput. 2021, 5, 42. [CrossRef]
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  105. Thakur, N.; Han, C.Y. Pervasive Activity Logging for Indoor Localization in Smart Homes. In Proceedings of the 2021 4th International Conference on Data Science and Information Technology, Shanghai, China, 23–25 July 2021.
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  106. Tijerina, J.D.; Morrison, S.D.; Nolan, I.T.; Parham, M.J.; Richardson, M.T.; Nazerali, R. Celebrity Influence Affecting Public Interest in Plastic Surgery Procedures: Google Trends Analysis. Aesthetic Plast. Surg. 2019, 43, 1669–1680. [CrossRef] [PubMed]
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  107. Tkachenko, N.; Chotvijit, S.; Gupta, N.; Bradley, E.; Gilks, C.; Guo, W.; Crosby, H.; Shore, E.; Thiarai, M.; Procter, R.; et al. Google Trends Can Improve Surveillance of Type 2 Diabetes. Sci. Rep. 2017, 7, 4993. [CrossRef] [PubMed]
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  108. Tran, U.S.; Andel, R.; Niederkrotenthaler, T.; Till, B.; Ajdacic-Gross, V.; Voracek, M. Low Validity of Google Trends for Behavioral Forecasting of National Suicide Rates. PLoS ONE 2017, 12, e0183149. [CrossRef] [PubMed]
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  109. Urban, M.; Cuzick, A.; Seager, J.; Wood, V.; Rutherford, K.; Venkatesh, S.Y.; De Silva, N.; Martinez, M.C.; Pedro, H.; Yates, A.D.; et al. PHI-Base: The Pathogen–Host Interactions Database. Nucleic Acids Res. 2019, 48, D613–D620. [CrossRef]
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  110. Van Kerkhove, M.D.; Ryan, M.J.; Ghebreyesus, T.A. Preparing for “Disease X”. Science 2021, 374, 377. [CrossRef]
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  111. Vasconcellos-Silva, P.R.; Carvalho, D.B.F.; Trajano, V.; de La Rocque, L.R.; Sawada, A.C.M.B.; Juvanhol, L.L. Using Google Trends Data to Study Public Interest in Breast Cancer Screening in Brazil: Why Not a Pink February? JMIR Public Health Surveill. 2017, 3, e17. [CrossRef]
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  112. Vats, V. What Is Disease X? It Could Bring the next Pandemic, Says Expert. Available online: https://www.ndtv.com/health/ what-is-disease-x-it-could-bring-the-next-pandemic-deadlier-than-covid-19-says-expert-4424840 (accessed on 3 October 2023). Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
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  113. Vaughan, L.; Chen, Y. Data Mining from Web Search Queries: A Comparison of Google Trends and Baidu Index: Data Mining from Web Search Queries: A Comparison of Google Trends and Baidu Index. J. Assoc. Inf. Sci. Technol. 2015, 66, 13–22. [CrossRef]
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  114. Verma, M.; Kishore, K.; Kumar, M.; Sondh, A.R.; Aggarwal, G.; Kathirvel, S. Google Search Trends Predicting Disease Outbreaks: An Analysis from India. Healthc. Inform. Res. 2018, 24, 300. [CrossRef] [PubMed]
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  115. Wang, D.; Guerra, A.; Wittke, F.; Lang, J.C.; Bakker, K.; Lee, A.W.; Finelli, L.; Chen, Y.-H. Real-Time Monitoring of Infectious Disease Outbreaks with a Combination of Google Trends Search Results and the Moving Epidemic Method: A Respiratory Syncytial Virus Case Study. Trop. Med. Infect. Dis. 2023, 8, 75. [CrossRef] [PubMed]
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  116. Wilkinson, M.D.; Dumontier, M.; Aalbersberg, I.J.; Appleton, G.; Axton, M.; Baak, A.; Blomberg, N.; Boiten, J.-W.; da Silva Santos, L.B.; Bourne, P.E.; et al. The FAIR Guiding Principles for Scientific Data Management and Stewardship. Sci. Data 2016, 3, 160018. [CrossRef]
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Cocites

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  2. How COVID-19 illness perceptions and individual shocks are associated with trust during the COVID-19 pandemic in Australia, France, Germany, and South Africa. (2025). Plotkina, Daria ; Broihanne, Marie-Hlne ; Gritz, Anja S ; Kleimeier, Stefanie.
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  3. Trust during troubled times: Evidence from Sierra Leones Ebola epidemic. (2025). Burke, Monica Galloway ; Cannonier, Colin.
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  18. Risk culture as a blessing in tourism development: Long-run effects of epidemic disasters. (2023). Mao, Zhenxing ; Yang, Yang ; Fu, Tong ; Zhang, Hongru.
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  19. Epidemics and pandemics: from the Justinianic Plague to the Spanish Flu. (2023). Alfani, Guido.
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  20. Public Infrastructure and Regional Resilience: Evidence from the 1918 Spanish Flu in Germany. (2023). Roesel, Felix ; Foertsch, Mona.
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  21. Crises and Political Polarization: Towards a Better Understanding of the Timing and Impact of Shocks and Media. (2023). Grignani, Maddalena ; Briscese, Guglielmo ; Stapleton, Stephen.
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  22. Preferences matter! Political Responses to the COVID-19 and Population’s Preferences. (2022). Pourieux, Matthieu ; Dagorn, Etienne ; Dattilo, Martina.
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  26. Do Pandemics Change Healthcare? Evidence from the Great Influenza. (2022). Thomasson, Melissa ; Esteves, Rui ; Nencka, Peter ; Mitchener, Kris James.
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  27. The Great Influenza Pandemic in Japan: Policy Responses and Socioeconomic Consequences. (2022). Shizume, Masato.
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  28. COVID-19 Point Blank: Language, Migration, and the Pandemic as a Political Issue. (2022). Veikou, Mariangela.
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  31. Do Pandemics Change Healthcare? Evidence from the Great Influenza. (2022). Esteves, Rui ; Nencka, Peter ; Thomasson, Melissa A ; Mitchener, Kris James.
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  32. Economic consequences of pre-COVID-19 epidemics: A literature review. (2021). Noy, Ilan ; Uher, Tom.
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  33. Employees’ Work-Related Well-Being during COVID-19 Pandemic: An Integrated Perspective of Technology Acceptance Model and JD-R Theory. (2021). Iakovleva, Tatiana ; Bagozzi, Richard P ; Shamsi, Marjan ; Olsen, Espen.
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  34. The demographic drivers of grief and memory after genocide in Guatemala. (2021). Alburez-Gutierrez, Diego.
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  35. Correlates and Consequences of the 1918 Influenza in South Africa. (2021). Murard, Elie ; Fourie, Johan ; Norling, Johannes ; Greyling, Jan ; de Kadt, Daniel.
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  36. Survival of the city: Living and thriving in an age of isolation By Edward Glaeser and David Cutler, Penguin Press, 2021. 480 pages. $14.99 (Kindle). ISBN 0593297687. (2021). Caragliu, Andrea.
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  37. Evaluation of Critical Infrastructure Essential Businesses Amidst Covid -19 Using Network Optimization Models. (2021). Madapat, Richard Job ; Williams, Quintin ; Cailas, Michael ; Liotine, Matthew ; Novotny, Jim.
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  38. The medium-term impact of non-pharmaceutical interventions. The case of the 1918 influenza in US cities. (2020). de la Chapelle, Guillaume Flamerie.
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