Published on in Vol 5 , No 2 (2003) :

SARS and Population Health Technology

SARS and Population Health Technology

SARS and Population Health Technology

Authors of this article:

Gunther Eysenbach


  1. Ishizaki T, Imanaka Y, Hirose M, Hayashida K, Kizu M, Inoue A, Sugie S. Estimation of the impact of providing outpatients with information about SARS infection control on their intention of outpatient visit. Health Policy 2004;69(3):293 View
  2. Higgins T, Wu A, Sharma D, Illing E, Rubel K, Ting J. Correlations of Online Search Engine Trends With Coronavirus Disease (COVID-19) Incidence: Infodemiology Study. JMIR Public Health and Surveillance 2020;6(2):e19702 View
  3. Lee G, Warner M. The Consequences of the SARS Epidemic for China's Employment and Human Resources. The Journal of Comparative Asian Development 2005;4(1):9 View
  4. Ramaprasad A, Papagari S. Ontological Design. SSRN Electronic Journal 2009 View
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  7. Rovetta A, Bhagavathula A. COVID-19-Related Web Search Behaviors and Infodemic Attitudes in Italy: Infodemiological Study. JMIR Public Health and Surveillance 2020;6(2):e19374 View
  8. Ripberger J. Capturing Curiosity: Using Internet Search Trends to Measure Public Attentiveness. Policy Studies Journal 2011;39(2):239 View
  9. Sousa-Pinto B, Anto A, Czarlewski W, Anto J, Fonseca J, Bousquet J. Assessment of the Impact of Media Coverage on COVID-19–Related Google Trends Data: Infodemiology Study. Journal of Medical Internet Research 2020;22(8):e19611 View
  10. Lee G, Warner M. Human Resources, Labour Markets and Unemployment: The Impact of the SARS Epidemic on the Service Sector in Singapore. Asia Pacific Business Review 2006;12(4):507 View
  11. Mohr O, Velasco E, Fell G, Burckhardt F, Poggensee G, Eckmanns T. Die telefonische infektionsepidemiologische Bund-Länder-Lagekonferenz in Deutschland. Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz 2010;53(9):903 View
  12. Ye J. The Role of Health Technology and Informatics in a Global Public Health Emergency: Practices and Implications From the COVID-19 Pandemic. JMIR Medical Informatics 2020;8(7):e19866 View
  13. Mahbubul Islam Y, Doyle K. Distance Education via SMS Technology in Rural Bangladesh. American Behavioral Scientist 2008;52(1):87 View
  14. Whitten P, Kreps G, Eastin M. Creating a Framework for Online Cancer Services Research to Facilitate Timely and Interdisciplinary Applications. Journal of Medical Internet Research 2005;7(3):e34 View
  15. Eysenbach G. Infodemiology and Infoveillance: Framework for an Emerging Set of Public Health Informatics Methods to Analyze Search, Communication and Publication Behavior on the Internet. Journal of Medical Internet Research 2009;11(1):e11 View
  16. Bernard R, Bowsher G, Milner C, Boyle P, Patel P, Sullivan R. Intelligence and global health: assessing the role of open source and social media intelligence analysis in infectious disease outbreaks. Journal of Public Health 2018;26(5):509 View
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  18. Rizo C, Lupea D, Baybourdy H, Anderson M, Closson T, Jadad A. What Internet Services Would Patients Like From Hospitals During an Epidemic? Lessons From the SARS Outbreak in Toronto. Journal of Medical Internet Research 2005;7(4):e46 View
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  21. Caputi T, Ayers J, Dredze M, Suplina N, Burd-Sharps S. Collateral Crises of Gun Preparation and the COVID-19 Pandemic: Infodemiology Study. JMIR Public Health and Surveillance 2020;6(2):e19369 View
  22. Leal Neto O, Dimech G, Libel M, de Souza W, Cesse E, Smolinski M, Oliveira W, Albuquerque J. Saúde na Copa: The World’s First Application of Participatory Surveillance for a Mass Gathering at FIFA World Cup 2014, Brazil. JMIR Public Health and Surveillance 2017;3(2):e26 View
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  25. Yellowlees P, Mackenzie J. Telehealth responses to bio-terrorism and emerging infections. Journal of Telemedicine and Telecare 2003;9(2_suppl):80 View
  26. 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
  27. Mavragani A, Gkillas K. COVID-19 predictability in the United States using Google Trends time series. Scientific Reports 2020;10(1) View
  28. Salehinejad S, Niakan Kalhori S, Hajesmaeel Gohari S, Bahaadinbeigy K, Fatehi F. A review and content analysis of national apps for COVID-19 management using Mobile Application Rating Scale (MARS). Informatics for Health and Social Care 2021;46(1):42 View
  29. Perlman A, Vodonos Zilberg A, Bak P, Dreyfuss M, Leventer-Roberts M, Vurembrand Y, Jeffries H, Fisher E, Steuerman Y, Namir Y, Goldschmidt Y, Souroujon D. Characteristics and Symptoms of App Users Seeking COVID-19–Related Digital Health Information and Remote Services: Retrospective Cohort Study. Journal of Medical Internet Research 2020;22(10):e23197 View
  30. 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
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Books/Policy Documents

  1. Pletneva N, Cruchet S, Simonet M, Kajiwara M, Boyer C. Systèmes d’information pour l’amélioration de la qualité en santé. View
  2. Webster R, Fedson D. Severe Acute Respiratory Syndrome. View
  3. Apolinario-Arzube Ó, García-Díaz J, Luna-Aveiga H, Medina-Moreira J, Valencia-García R. Technologies and Innovation. View
  4. Betancourt-Cravioto M, Falcón-Lezama J, Rojas-Estrella F, Saucedo-Martínez R, Tapia-Conyer R. Viral Outbreaks [Working Title]. View