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Citing this Article

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Published on 06.11.17 in Vol 3, No 4 (2017): Oct-Dec

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

Works citing "Health Information–Seeking Patterns of the General Public and Indications for Disease Surveillance: Register-Based Study Using Lyme Disease"

According to Crossref, the following articles are citing this article (DOI 10.2196/publichealth.8306):

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

  1. Tana JC, Kettunen J, Eirola E, Paakkonen H. Diurnal Variations of Depression-Related Health Information Seeking: Case Study in Finland Using Google Trends Data. JMIR Mental Health 2018;5(2):e43
    CrossRef
  2. Kapitány‐Fövény M, Ferenci T, Sulyok Z, Kegele J, Richter H, Vályi‐Nagy I, Sulyok M. Can Google Trends data improve forecasting of Lyme disease incidence?. Zoonoses and Public Health 2019;66(1):101
    CrossRef
  3. Mavragani A, Sampri A, Sypsa K, Tsagarakis KP. Integrating Smart Health in the US Health Care System: Infodemiology Study of Asthma Monitoring in the Google Era. JMIR Public Health and Surveillance 2018;4(1):e24
    CrossRef
  4. Pesälä S, Virtanen MJ, Mukka M, Ylilammi K, Mustonen P, Kaila M, Helve O. Healthcare professionals’ queries on oseltamivir and influenza in Finland 2011‐2016—Can we detect influenza epidemics with specific online searches?. Influenza and Other Respiratory Viruses 2019;13(4):364
    CrossRef
  5. Basch CH, MacLean SA, Romero R, Ethan D. Health Information Seeking Behavior Among College Students. Journal of Community Health 2018;43(6):1094
    CrossRef
  6. Johnson AK, Bhaumik R, Tabidze I, Mehta SD. Nowcasting Sexually Transmitted Infections in Chicago: Predictive Modeling and Evaluation Study Using Google Trends. JMIR Public Health and Surveillance 2020;6(4):e20588
    CrossRef
  7. Zhou C, Xiu H, Wang Y, Yu X. Characterizing the dissemination of misinformation on social media in health emergencies: An empirical study based on COVID-19. Information Processing & Management 2021;58(4):102554
    CrossRef
  8. Simonart T, Lam Hoai X, de Maertelaer V. Worldwide Evolution of Vaccinable and Nonvaccinable Viral Skin Infections: Google Trends Analysis. JMIR Dermatology 2022;5(4):e35034
    CrossRef
  9. Mukka M, Pesälä S, Hammer C, Mustonen P, Jormanainen V, Pelttari H, Kaila M, Helve O. Analyzing Citizens’ and Health Care Professionals’ Searches for Smell/Taste Disorders and Coronavirus in Finland During the COVID-19 Pandemic: Infodemiological Approach Using Database Logs. JMIR Public Health and Surveillance 2021;7(12):e31961
    CrossRef
  10. Simonart T, Lam Hoai X, De Maertelaer V. Epidemiologic evolution of common cutaneous infestations and arthropod bites: A Google Trends analysis. JAAD International 2021;5:69
    CrossRef
  11. 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
    CrossRef
  12. Brinkman JC, Christopher ZK, Moore ML, Pollock JR, Haglin JM, Bingham JS. Patient Interest in Robotic Total Joint Arthroplasty Is Exponential: A 10-Year Google Trends Analysis. Arthroplasty Today 2022;15:13
    CrossRef
  13. Longanga Diese E, Baker E, Akpan I, Acharya R, Raines-Milenkov A, Felini M, Hussain A, Donlan J. Health information-seeking behavior among Congolese refugees. PLOS ONE 2022;17(9):e0273650
    CrossRef
  14. Zhang L, Wang X, Wang J, Yang P, Zhou P, Liao G. A study on predicting crisis information dissemination in epidemic-level public health events. Journal of Safety Science and Resilience 2023;4(3):253
    CrossRef
  15. . Tick-Bite “Meteo”-Prevention: An Evaluation of Public Responsiveness to Tick Activity Forecasts Available Online. Life 2023;13(9):1908
    CrossRef
  16. Maxwell SP, Brooks C, Kim D, McNeely CL, Cho S, Thomas KC. Improving Surveillance of Human Tick-Borne Disease Risks: Spatial Analysis Using Multimodal Databases. JMIR Public Health and Surveillance 2023;9:e43790
    CrossRef
  17. Boligarla S, Laison EKE, Li J, Mahadevan R, Ng A, Lin Y, Thioub MY, Huang B, Ibrahim MH, Nasri B. Leveraging machine learning approaches for predicting potential Lyme disease cases and incidence rates in the United States using Twitter. BMC Medical Informatics and Decision Making 2023;23(1)
    CrossRef
  18. Kopsco HL, Krell RK, Mather TN, Connally NP. Identifying Trusted Sources of Lyme Disease Prevention Information Among Internet Users Connected to Academic Public Health Resources: Internet-Based Survey Study. JMIR Formative Research 2023;7:e43516
    CrossRef
  19. Brinkman JC, McQuivey KS, Hassebrock JD, Moore ML, Pollock JR, Tokish JM. Public Interest in Shoulder Platelet-Rich Plasma Injections Is Increasing: A 10-Year Google Trends Analysis. Arthroscopy, Sports Medicine, and Rehabilitation 2023;5(4):100744
    CrossRef
  20. Hadley M, Patil U, Colvin KF, Sentell T, Massey PM, Gallant M, Manganello JA. Exploring the impact of digital health literacy on COVID-19 behaviors in New York state college students during the COVID-19 pandemic. Computer Methods and Programs in Biomedicine Update 2023;4:100126
    CrossRef
  21. Mukka M, Pesälä S, Mustonen P, Kaila M, Helve O, Aslam MS. Detecting epinephrine auto-injector shortages in Finland 2016–2022: Log-data analysis of online information seeking. PLOS ONE 2024;19(4):e0299092
    CrossRef
  22. Brinkman JC, Moore ML, Lai C, Tummala SV, Pollock JR, McQuivey KS, Hassebrock JD, Thompson AB, Chhabra A. Patient Interest in Quadriceps Autograft ACL Reconstruction is Increasing Over Other Autograft Options: A 12-year Google Trends Analysis. Arthroscopy, Sports Medicine, and Rehabilitation 2024;:100942
    CrossRef