Published on in Vol 10, No 10 (2021): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30444, first published .
Detection of Spatiotemporal Clusters of COVID-19–Associated Symptoms and Prevention Using a Participatory Surveillance App: Protocol for the @choum Study

Detection of Spatiotemporal Clusters of COVID-19–Associated Symptoms and Prevention Using a Participatory Surveillance App: Protocol for the @choum Study

Detection of Spatiotemporal Clusters of COVID-19–Associated Symptoms and Prevention Using a Participatory Surveillance App: Protocol for the @choum Study

Journals

  1. Saheb T, Sabour E, Qanbary F, Saheb T. Delineating privacy aspects of COVID tracing applications embedded with proximity measurement technologies & digital technologies. Technology in Society 2022;69:101968 View
  2. Lan Y, Delmelle E. Space-time cluster detection techniques for infectious diseases: A systematic review. Spatial and Spatio-temporal Epidemiology 2023;44:100563 View
  3. Morris R, Wang S. Building a pathway to One Health surveillance and response in Asian countries. Science in One Health 2024;3:100067 View
  4. De Ridder D, Ladoy A, Choi Y, Jacot D, Vuilleumier S, Guessous I, Joost S, Greub G. Environmental and geographical factors influencing the spread of SARS-CoV-2 over 2 years: a fine-scale spatiotemporal analysis. Frontiers in Public Health 2024;12 View