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

Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050) Infodemiology and Infoveillance (1369)

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

Forecasting the West Nile Virus in the United States: An Extensive Novel Data Streams–Based Time Series Analysis and Structural Equation Modeling of Related Digital Searching Behavior

Forecasting the West Nile Virus in the United States: An Extensive Novel Data Streams–Based Time Series Analysis and Structural Equation Modeling of Related Digital Searching Behavior

Forecasting the West Nile Virus in the United States: An Extensive Novel Data Streams–Based Time Series Analysis and Structural Equation Modeling of Related Digital Searching Behavior

Authors of this article:

Abdulla Watad1, 2, 3, 4 Author Orcid Image ;   Samaa Watad5 Author Orcid Image ;   Naim Mahroum1, 2, 3 Author Orcid Image ;   Kassem Sharif1, 2, 3 Author Orcid Image ;   Howard Amital1, 2, 3 Author Orcid Image ;   Nicola Luigi Bragazzi6 Author Orcid Image ;   Mohammad Adawi7, 8, 9 Author Orcid Image
Article Authors Cited by (11) Tweetations (4) Metrics

Journals

  1. Arehart C, David M, Dukic V. Tracking U.S. Pertussis Incidence: Correlation of Public Health Surveillance and Google Search Data Varies by State. Scientific Reports 2019;9(1) View
  2. Mavragani A, Ochoa G. Google Trends in Infodemiology and Infoveillance: Methodology Framework. JMIR Public Health and Surveillance 2019;5(2):e13439 View
  3. Anderson J, Stafford A, Johnson A, Hartwell M, Jellison S, Vassar M. Is World Malaria Day an effective awareness campaign? An evaluation of public interest in malaria during World Malaria Day. Tropical Medicine & International Health 2020;25(11):1416 View
  4. Daughton A, Shelley C, Barnard M, Gerts D, Watson Ross C, Crooker I, Nadiga G, Mukundan N, Vaquera Chavez N, Parikh N, Pitts T, Fairchild G. Mining and Validating Social Media Data for COVID-19–Related Human Behaviors Between January and July 2020: Infodemiology Study. Journal of Medical Internet Research 2021;23(5):e27059 View
  5. Barboza L, Vásquez P, Mery G, Sanchez F, García Y, Calvo J, Rivas T, Pérez M, Salas D. The Role of Mobility and Sanitary Measures on the Delay of Community Transmission of COVID-19 in Costa Rica. Epidemiologia 2021;2(3):294 View
  6. Santangelo O, Gianfredi V, Provenzano S. Wikipedia searches and the epidemiology of infectious diseases: A systematic review. Data & Knowledge Engineering 2022;142:102093 View
  7. Hurley J. How to apply structural equation modelling to infectious diseases concepts. Clinical Microbiology and Infection 2022;28(12):1567 View
  8. Branda F, Abenavoli L, Pierini M, Mazzoli S. Predicting the Spread of SARS-CoV-2 in Italian Regions: The Calabria Case Study, February 2020–March 2022. Diseases 2022;10(3):38 View
  9. 旷 芸. Analysis of Influencing Factors of College Students’ Preventive Behavior in Response to COVID-19 Epidemic. Modern Management 2021;11(08):874 View
  10. Ravalli S, Roggio F, Lauretta G, Di Rosa M, D'Amico A, D'agata V, Maugeri G, Musumeci G. Exploiting real-world data to monitor physical activity in patients with osteoarthritis: the opportunity of digital epidemiology. Heliyon 2022;8(2):e08991 View

Books/Policy Documents

  1. Butt Z. Accelerating Strategic Changes for Digital Transformation in the Healthcare Industry. View