Published on in Vol 23, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24554, first published .
Predicting Norovirus in the United States Using Google Trends: Infodemiology Study

Predicting Norovirus in the United States Using Google Trends: Infodemiology Study

Predicting Norovirus in the United States Using Google Trends: Infodemiology Study

Journals

  1. Zheng B, Lin X, Yin D, Qi X, Tu W. Does Tobler’s first law of geography apply to internet attention? A case study of the Asian elephant northern migration event. PLOS ONE 2023;18(3):e0282474 View
  2. Okunoye B, Ning S, Jemielniak D. Searching for HIV and AIDS Health Information in South Africa, 2004-2019: Analysis of Google and Wikipedia Search Trends. JMIR Formative Research 2022;6(3):e29819 View
  3. Yan W, Du M, Qin C, Liu Q, Wang Y, Liang W, Liu M, Liu J. Association between public attention and monkeypox epidemic: A global lag‐correlation analysis. Journal of Medical Virology 2023;95(1) View
  4. Du M, Qin C, Yan W, Liu Q, Wang Y, Zhu L, Liang W, Liu M, Liu J. Trends in Online Search Activity and the Correlation with Daily New Cases of Monkeypox among 102 Countries or Territories. International Journal of Environmental Research and Public Health 2023;20(4):3395 View
  5. 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 View
  6. Miraji H, Eunice M, Ripanda A, Ngassapa F, Chande O. Naturally occurring emerging contaminants: Where to hide?. HydroResearch 2023;6:203 View
  7. Wang Z, He J, Jin B, Zhang L, Han C, Wang M, Wang H, An S, Zhao M, Zhen Q, Tiejun S, Zhang X. Using Baidu Index Data to Improve Chickenpox Surveillance in Yunnan, China: Infodemiology Study. Journal of Medical Internet Research 2023;25:e44186 View
  8. Ondrikova N, Harris J, Douglas A, Hughes H, Iturriza-Gomara M, Vivancos R, Elliot A, Cunliffe N, Clough H. Predicting Norovirus in England Using Existing and Emerging Syndromic Data: Infodemiology Study. Journal of Medical Internet Research 2023;25:e37540 View
  9. Thakur N, Cui S, Patel K, Azizi N, Knieling V, Han C, Poon A, Shah R. Marburg Virus Outbreak and a New Conspiracy Theory: Findings from a Comprehensive Analysis and Forecasting of Web Behavior. Computation 2023;11(11):234 View
  10. Clark E, Neumann S, Hopkins S, Kostopoulos A, Hagerman L, Dobbins M. Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review. JMIR Public Health and Surveillance 2024;10:e49185 View
  11. Ondrikova N, Clough H, Douglas A, Vivancos R, Itturiza-Gomara M, Cunliffe N, Harris J. Comparison of statistical approaches to predicting norovirus laboratory reports before and during COVID-19: insights to inform public health surveillance. Scientific Reports 2023;13(1) View
  12. Ammerman M, Mullapudi S, Gilbert J, Figueroa K, de Paula Nogueira Cruz F, Bakker K, Eisenberg M, Foxman B, Wigginton K, Santos R. Norovirus GII wastewater monitoring for epidemiological surveillance. PLOS Water 2024;3(1):e0000198 View
  13. Nagra M, Wolffsohn J, Ghorbani-Mojarrad N. Using big data to understand interest in myopia. Optometry and Vision Science 2024;101(1):37 View
  14. Adedire O, Love N, Hughes H, Buchan I, Vivancos R, Elliot A. Early Detection and Monitoring of Gastrointestinal Infections Using Syndromic Surveillance: A Systematic Review. International Journal of Environmental Research and Public Health 2024;21(4):489 View
  15. Guzman H, Zhao L, Swain M, Faust R, Xagoraraki I. Tracking Norovirus in Tri-County Detroit, MI, Using Wastewater Testing, Syndromic Data, and Online Publicly Available Sources. ACS ES&T Water 2024;4(11):4990 View