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

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