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

Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Infodemiology and Infoveillance (1349) Food Safety and Foodborne Diseases (9) Participatory Epidemiology and Surveillance (119) Reviews on Public Health Technology and Innovation (69)

Published on in Vol 4, No 2 (2018): Apr-Jun

Identifying Methods for Monitoring Foodborne Illness: Review of Existing Public Health Surveillance Techniques

Identifying Methods for Monitoring Foodborne Illness: Review of Existing Public Health Surveillance Techniques

Identifying Methods for Monitoring Foodborne Illness: Review of Existing Public Health Surveillance Techniques

Authors of this article:

Rachel A Oldroyd1, 2 Author Orcid Image ;   Michelle A Morris1, 3 Author Orcid Image ;   Mark Birkin1, 2 Author Orcid Image
Article Authors Cited by (16) Tweetations (37) Metrics

Journals

  1. Mooney S, Garber M. Sampling and Sampling Frames in Big Data Epidemiology. Current Epidemiology Reports 2019;6(1):14 View
  2. Oldroyd R, Morris M, Birkin M. Food safety vulnerability: Neighbourhood determinants of non-compliant establishments in England and Wales. Health & Place 2020;63:102325 View
  3. Moumni Abdou H, Dahbi I, Akrim M, Meski F, Khader Y, Lakranbi M, Ezzine H, Khattabi A. Outbreak Investigation of a Multipathogen Foodborne Disease in a Training Institute in Rabat, Morocco: Case-Control Study. JMIR Public Health and Surveillance 2019;5(3):e14227 View
  4. Lynch M, Knezevic I, Ryan K, Cahill N. Opportunities for Qualitative Analysis of Social Media Platforms in Dietetic Research and Practice. Canadian Journal of Dietetic Practice and Research 2021;82(2):79 View
  5. Deng X, Cao S, Horn A. Emerging Applications of Machine Learning in Food Safety. Annual Review of Food Science and Technology 2021;12(1):513 View
  6. Wang H, Cui W, Guo Y, Du Y, Zhou Y. Machine Learning Prediction of Foodborne Disease Pathogens: Algorithm Development and Validation Study. JMIR Medical Informatics 2021;9(1):e24924 View
  7. Nychas G, Sims E, Tsakanikas P, Mohareb F. Data Science in the Food Industry. Annual Review of Biomedical Data Science 2021;4(1):341 View
  8. Rebinsky R, Anderson L, Morgenstern J. Identifying non-traditional electronic datasets for population-level surveillance and prevention of cardiometabolic diseases: a scoping review protocol. BMJ Open 2021;11(8):e053485 View
  9. Oldroyd R, Morris M, Birkin M. Predicting Food Safety Compliance for Informed Food Outlet Inspections: A Machine Learning Approach. International Journal of Environmental Research and Public Health 2021;18(23):12635 View
  10. Qian C, Liu Y, Barnett-Neefs C, Salgia S, Serbetci O, Adalja A, Acharya J, Zhao Q, Ivanek R, Wiedmann M. A perspective on data sharing in digital food safety systems. Critical Reviews in Food Science and Nutrition 2023;63(33):12513 View

Books/Policy Documents

  1. Chen X, Wang H. Data Science. View
  2. Buckeridge D. Intelligent Systems in Medicine and Health. View
  3. Pujahari R, Khan R. Artificial Intelligence Applications in Agriculture and Food Quality Improvement. View