Published on in Vol 5, No 1 (2019): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13142, first published .
Google Trends Predicts Present and Future Plague Cases During the Plague Outbreak in Madagascar: Infodemiological Study

Google Trends Predicts Present and Future Plague Cases During the Plague Outbreak in Madagascar: Infodemiological Study

Google Trends Predicts Present and Future Plague Cases During the Plague Outbreak in Madagascar: Infodemiological Study

Authors of this article:

Nicola Luigi Bragazzi1 Author Orcid Image ;   Naim Mahroum2 Author Orcid Image

Journals

  1. Pinter G, Felde I, Mosavi A, Ghamisi P, Gloaguen R. COVID-19 Pandemic Prediction for Hungary; A Hybrid Machine Learning Approach. SSRN Electronic Journal 2020 View
  2. Cossin S, Thiébaut R. Public Health and Epidemiology Informatics: Recent Research Trends Moving toward Public Health Data Science. Yearbook of Medical Informatics 2020;29(01):231 View
  3. Pinter G, Felde I, Mosavi A, Ghamisi P, Gloaguen R. COVID-19 Pandemic Prediction for Hungary; A Hybrid Machine Learning Approach. Mathematics 2020;8(6):890 View
  4. Mavragani A, Ochoa G. Google Trends in Infodemiology and Infoveillance: Methodology Framework. JMIR Public Health and Surveillance 2019;5(2):e13439 View
  5. Strzelecki A. Google Medical Update: Why Is the Search Engine Decreasing Visibility of Health and Medical Information Websites?. International Journal of Environmental Research and Public Health 2020;17(4):1160 View
  6. Aiello A, Renson A, Zivich P. Social Media– and Internet-Based Disease Surveillance for Public Health. Annual Review of Public Health 2020;41(1):101 View
  7. Frauenfeld L, Nann D, Sulyok Z, Feng Y, Sulyok M. Forecasting tuberculosis using diabetes-related google trends data. Pathogens and Global Health 2020;114(5):236 View
  8. Ardabili S, Mosavi A, Ghamisi P, Ferdinand F, Varkonyi-Koczy A, Reuter U, Rabczuk T, Atkinson P. COVID-19 Outbreak Prediction with Machine Learning. Algorithms 2020;13(10):249 View
  9. Gabarron E, Rivera-Romero O, Miron-Shatz T, Grainger R, Denecke K. Role of Participatory Health Informatics in Detecting and Managing Pandemics: Literature Review. Yearbook of Medical Informatics 2021;30(01):200 View
  10. Aragón-Ayala C, Copa-Uscamayta J, Herrera L, Zela-Coila F, Quispe-Juli C. Interest in COVID-19 in Latin America and the Caribbean: an infodemiological study using Google Trends. Cadernos de Saúde Pública 2021;37(10) View
  11. Rosario-Acevedo R, Biryukov S, Bozue J, Cote C. Plague Prevention and Therapy: Perspectives on Current and Future Strategies. Biomedicines 2021;9(10):1421 View
  12. Gupta R, Mohanty V, Balappanavar A, Chahar P, Rijhwani K, Bhatia S. Infodemiology for oral health and disease: A scoping review. Health Information & Libraries Journal 2022;39(3):207 View
  13. Olukanmi S, Nelwamondo F, Nwulu N. Utilizing Google Search Data With Deep Learning, Machine Learning and Time Series Modeling to Forecast Influenza-Like Illnesses in South Africa. IEEE Access 2021;9:126822 View
  14. Elsalti A, Darkhabani M, Alrifaai M, Mahroum N. Celebrities and Medical Awareness—The Case of Celine Dion and Stiff-Person Syndrome. International Journal of Environmental Research and Public Health 2023;20(3):1936 View
  15. KONAK F, ÖZKAHVECİ E. BLOCKCHAIN ÜZERİNE YENİ BİR HALKA: NON-FUNGIBLE TOKEN (NFT)'NİN BİLİNİRLİĞİ ÜZERİNE BİR ARAŞTIRMA. Düzce Üniversitesi Sosyal Bilimler Dergisi 2023;13(1):97 View
  16. Yang Y, Wan X, Zhang N, Wu Z, Qiu R, Yuan J, Xie Y. Analysis and modelling of global online public interest in multiple other infectious diseases due to the COVID‐19 pandemic. Journal of Evaluation in Clinical Practice 2024 View

Books/Policy Documents

  1. Babu D, Guruprasanna K, Rao Y, Jayakrishna K, Dayanandam G, Reddy P, Chandirika T. Information Systems for Intelligent Systems. View
  2. Butt Z. Accelerating Strategic Changes for Digital Transformation in the Healthcare Industry. View
  3. Makinde O. Health and Medical Geography in Africa. View