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

Participatory Epidemiology and Surveillance (106) Crowdsourcing and Mechanical Turks (90) Infectious Diseases (non-STD/STI) (1478) Influenza and Influenza-Like-Illness (ILI) Surveillance (203) Surveillance Systems (427) mHealth for Data Collection and Research (907)

Published on in Vol 3, No 4 (2017): Oct-Dec

Will Participatory Syndromic Surveillance Work in Latin America? Piloting a Mobile Approach to Crowdsource Influenza-Like Illness Data in Guatemala

Will Participatory Syndromic Surveillance Work in Latin America? Piloting a Mobile Approach to Crowdsource Influenza-Like Illness Data in Guatemala

Will Participatory Syndromic Surveillance Work in Latin America? Piloting a Mobile Approach to Crowdsource Influenza-Like Illness Data in Guatemala

Authors of this article:

José Tomás Prieto1, 2 Author Orcid Image ;   Jorge H Jara1 Author Orcid Image ;   Juan Pablo Alvis1 Author Orcid Image ;   Luis R Furlan3 Author Orcid Image ;   Christian Travis Murray1 Author Orcid Image ;   Judith Garcia4 Author Orcid Image ;   Pierre-Jean Benghozi2 Author Orcid Image ;   Susan Cornelia Kaydos-Daniels5 Author Orcid Image
Article Authors Cited by (12) Tweetations (9) Metrics

Journals

  1. Créquit P, Mansouri G, Benchoufi M, Vivot A, Ravaud P. Mapping of Crowdsourcing in Health: Systematic Review. Journal of Medical Internet Research 2018;20(5):e187 View
  2. Stewart R, Rossow J, Eckel S, Bidol S, Ballew G, Signs K, Conover J, Burns E, Bresee J, Fry A, Olsen S, Biggerstaff M. Text-Based Illness Monitoring for Detection of Novel Influenza A Virus Infections During an Influenza A (H3N2)v Virus Outbreak in Michigan, 2016: Surveillance and Survey. JMIR Public Health and Surveillance 2019;5(2):e10842 View
  3. Ibrahim N. Epidemiologic surveillance for controlling Covid-19 pandemic: types, challenges and implications. Journal of Infection and Public Health 2020;13(11):1630 View
  4. Eze E, Gleasure R, Heavin C. Mobile health solutions in developing countries: a stakeholder perspective. Health Systems 2020;9(3):179 View
  5. Wirth F, Johns M, Meurers T, Prasser F. Citizen-Centered Mobile Health Apps Collecting Individual-Level Spatial Data for Infectious Disease Management: Scoping Review. JMIR mHealth and uHealth 2020;8(11):e22594 View
  6. Katayama Y, Kiyohara K, Hirose T, Ishida K, Tachino J, Nakao S, Noda T, Ojima M, Kiguchi T, Matsuyama T, Kitamura T. An Association of Influenza Epidemics in Children With Mobile App Data: Population-Based Observational Study in Osaka, Japan. JMIR Formative Research 2022;6(2):e31131 View
  7. Karageorgos G, Andreadis I, Psychas K, Mourkousis G, Kiourti A, Lazzi G, Nikita K. The Promise of Mobile Technologies for the Health Care System in the Developing World: A Systematic Review. IEEE Reviews in Biomedical Engineering 2019;12:100 View
  8. Atkins N, Harikar M, Duggan K, Zawiejska A, Vardhan V, Vokey L, Dozier M, de los Godos E, Mcswiggan E, Mcquillan R, Theodoratou E, Shi T. What are the characteristics of participatory surveillance systems for influenza-like-illness?. Journal of Global Health 2023;13 View
  9. Leal Neto O, Paolotti D, Dalton C, Carlson S, Susumpow P, Parker M, Phetra P, Lau E, Colizza V, Jan van Hoek A, Kjelsø C, Brownstein J, Smolinski M. Enabling Multicentric Participatory Disease Surveillance for Global Health Enhancement: Viewpoint on Global Flu View. JMIR Public Health and Surveillance 2023;9:e46644 View
  10. Solis Pino A, Ruiz P, Agredo-Delgado V, Mon A, Collazos C. Bibliometric Analysis of the Research Landscape in Human-Computer Interaction in Ibero-America. TecnoLógicas 2024;27(59):e2907 View
  11. Rocha H, Solha E, Furtado V, Justino F, Barreto L, da Silva R, de Oliveira Í, Bates D, de Góes Cavalcanti L, Lima Neto A, de Oliveira E. COVID-19 outbreaks surveillance through text mining applied to electronic health records. BMC Infectious Diseases 2024;24(1) View

Books/Policy Documents

  1. Benghozi P. Les impacts durables de la crise sur le management. View