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Citing this Article

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Published on 30.06.03 in Vol 5, No 2 (2003)

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

Works citing "SARS and Population Health Technology"

Gunther Eysenbach

J Med Internet Res 2003 (Jun 30); 5(2):e14 

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.5.2.e14):

(note that this is only a small subset of citations)

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    CrossRef
  3. Lee GOM, 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
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  12. . 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
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  22. Leal Neto O, Dimech GS, Libel M, de Souza WV, 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
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  29. Perlman A, Vodonos Zilberg A, Bak P, Dreyfuss M, Leventer-Roberts M, Vurembrand Y, Jeffries HE, 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
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  30. Wong MYZ, Gunasekeran DV, Nusinovici S, Sabanayagam C, Yeo KK, 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
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  31. Alamoodi A, Zaidan B, Zaidan A, Albahri O, Mohammed K, Malik R, Almahdi E, Chyad M, Tareq Z, Albahri A, Hameed H, Alaa M. Sentiment analysis and its applications in fighting COVID-19 and infectious diseases: A systematic review. Expert Systems with Applications 2021;167:114155
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  32. Datta P, Nwankpa JK. Digital transformation and the COVID-19 crisis continuity planning. Journal of Information Technology Teaching Cases 2021;11(2):81
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  33. Mills K, Peterson A, McNair M, Abe T, Igwe J, Sobukonla T, Surapaneni P, Ajose T, Yan F, Chang E, Volcy J. Virtually Serving the Underserved: Resident Perceptions of Telemedicine Use While Training During Coronavirus Disease 2019. Telemedicine and e-Health 2022;28(3):391
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  34. Kishore K, Jaswal V, Verma M, Koushal V. Exploring the Utility of Google Mobility Data During the COVID-19 Pandemic in India: Digital Epidemiological Analysis. JMIR Public Health and Surveillance 2021;7(8):e29957
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  35. Guo N, Zhao SZ, Weng X, Wu Y, Luk TT, Wong JYH, Lam TH, Wang MP. Associations of COVID-19 online information sources and information overload with psychological distress symptoms: a population-based study. Translational Behavioral Medicine 2021;11(7):1330
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  36. Gómez-Salgado J, Palomino-Baldeón JC, Ortega-Moreno M, Fagundo-Rivera J, Allande-Cussó R, Ruiz-Frutos C. COVID-19 information received by the Peruvian population, during the first phase of the pandemic, and its association with developing psychological distress. Medicine 2022;101(5):e28625
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  37. Bui LV, Ha ST, Nguyen HN, Nguyen TT, Nguyen TP, Tran K, Tran TV, Nguyen TH, Tran TH, Pham ND, Bui HM. The Contribution of Digital Health in the Response to Covid-19 in Vietnam. Frontiers in Public Health 2021;9
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  38. 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
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  39. Mukka M, Pesälä S, Juutinen A, Virtanen MJ, Mustonen P, Kaila M, Helve O, Khanijahani A. Online searches of children’s oseltamivir in public primary and specialized care: Detecting influenza outbreaks in Finland using dedicated databases for health care professionals. PLOS ONE 2022;17(8):e0272040
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  40. Jiang LC, Chu TH, Sun M. Characterization of Vaccine Tweets During the Early Stage of the COVID-19 Outbreak in the United States: Topic Modeling Analysis. JMIR Infodemiology 2021;1(1):e25636
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  41. 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
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  42. Izhar TAT, Torabi T. Online searching trend on Covid-19 using Google trend: infodemiological study in Malaysia. International Journal of Information Technology 2022;14(2):675
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  43. Poongodi M, Malviya M, Hamdi M, Rauf HT, Kadry S, Thinnukool O. The Recent Technologies to Curb the Second-Wave of COVID-19 Pandemic. IEEE Access 2021;9:97906
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  44. Liu Z, Jiang Z, Kip G, Snigdha K, Xu J, Wu X, Khan N, Schultz T. An infodemiological framework for tracking the spread of SARS-CoV-2 using integrated public data. Pattern Recognition Letters 2022;158:133
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  45. 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
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  46. Iyamu I, Gómez-Ramírez O, Xu AX, Chang H, Watt S, Mckee G, Gilbert M. Challenges in the development of digital public health interventions and mapped solutions: Findings from a scoping review. DIGITAL HEALTH 2022;8:205520762211022
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  47. Mremi IR, George J, Rumisha SF, Sindato C, Kimera SI, Mboera LEG. Twenty years of integrated disease surveillance and response in Sub-Saharan Africa: challenges and opportunities for effective management of infectious disease epidemics. One Health Outlook 2021;3(1)
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  48. Porcu G, Chen YX, Bonaugurio AS, 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
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  49. Saeidnia HR, Kozak M, Ausloos M, Lund BD, Ghorbi A, Mohammadzadeh Z. Evaluation of COVID-19 m-Health apps: An analysis of the methods of app usability testing during a global pandemic. Informatics in Medicine Unlocked 2023;41:101310
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  50. Aizaz M, Khan F, Ali B, Ahmad S, Naseem K, Mishra S, Abbas FA, Yang G. Significance of Digital Health Technologies (DHTs) to manage communicable and non-communicable diseases in Low and Middle-Income Countries (LMICs). Health and Technology 2023;13(6):883
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  51. Perez AJ, Zeadally S, Tan DK. Detecting Mobile Malware Associated With Global Pandemics. IEEE Pervasive Computing 2023;22(4):45
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.5.2.e14):

  1. Pletneva N, Cruchet S, Simonet M, Kajiwara M, Boyer C. Systèmes d’information pour l’amélioration de la qualité en santé. 2011. Chapter 31:353
    CrossRef
  2. Webster RG, Fedson DS. Severe Acute Respiratory Syndrome. 2005. :239
    CrossRef
  3. Apolinario-Arzube , García-Díaz JA, Luna-Aveiga H, Medina-Moreira J, Valencia-García R. Technologies and Innovation. 2020. Chapter 4:43
    CrossRef
  4. Betancourt-Cravioto M, Falcón-Lezama J, Rojas-Estrella F, Saucedo-Martínez R, Tapia-Conyer R. Current Perspectives on Viral Disease Outbreaks - Epidemiology, Detection and Control. 2022. Chapter 9
    CrossRef
  5. Al-Emran M, Arpaci I. Emerging Technologies During the Era of COVID-19 Pandemic. 2021. Chapter 5:59
    CrossRef
  6. . Proceedings of the 2022 International Conference on Business and Policy Studies. 2022. Chapter 92:932
    CrossRef
  7. Cuyvers J, Passanante A, Pertwee E, Paterson P, Lin L, J. Larson H. Modernizing Global Health Security to Prevent, Detect, and Respond. 2024. :375
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