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

Theme Issue 2017: Participatory Disease Surveillance (Skoll Global Threats/Hunter Medical Res Institute) (9) Infectious Diseases (non-STD/STI) (1490) Influenza and Influenza-Like-Illness (ILI) Surveillance (203) LGBTQ Issues (416) Participatory Epidemiology and Surveillance (107)

Published on in Vol 3, No 3 (2017): Jul-Sept

Influenzanet: Citizens Among 10 Countries Collaborating to Monitor Influenza in Europe

Influenzanet: Citizens Among 10 Countries Collaborating to Monitor Influenza in Europe

Influenzanet: Citizens Among 10 Countries Collaborating to Monitor Influenza in Europe

Authors of this article:

Carl E Koppeschaar1 Author Orcid Image ;   Vittoria Colizza2 Author Orcid Image ;   Caroline Guerrisi2 Author Orcid Image ;   Clément Turbelin2 Author Orcid Image ;   Jim Duggan3 Author Orcid Image ;   W John Edmunds4 Author Orcid Image ;   Charlotte Kjelsø5 Author Orcid Image ;   Ricardo Mexia6 Author Orcid Image ;   Yamir Moreno7 Author Orcid Image ;   Sandro Meloni7 Author Orcid Image ;   Daniela Paolotti8 Author Orcid Image ;   Daniela Perrotta8 Author Orcid Image ;   Edward van Straten9 Author Orcid Image ;   Ana O Franco4, 10 Author Orcid Image
Article Authors Cited by (46) Tweetations (32) Metrics

Journals

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  2. Smolinski M, Crawley A, Olsen J, Jayaraman T, Libel M. Participatory Disease Surveillance: Engaging Communities Directly in Reporting, Monitoring, and Responding to Health Threats. JMIR Public Health and Surveillance 2017;3(4):e62 View
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  4. Geneviève L, Martani A, Wangmo T, Paolotti D, Koppeschaar C, Kjelsø C, Guerrisi C, Hirsch M, Woolley-Meza O, Lukowicz P, Flahault A, Elger B. Participatory Disease Surveillance Systems: Ethical Framework. Journal of Medical Internet Research 2019;21(5):e12273 View
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  9. Leal Neto O, Cruz O, Albuquerque J, Nacarato de Sousa M, Smolinski M, Pessoa Cesse E, Libel M, Vieira de Souza W. Participatory Surveillance Based on Crowdsourcing During the Rio 2016 Olympic Games Using the Guardians of Health Platform: Descriptive Study. JMIR Public Health and Surveillance 2020;6(2):e16119 View
  10. Kalimeri K, Delfino M, Cattuto C, Perrotta D, Colizza V, Guerrisi C, Turbelin C, Duggan J, Edmunds J, Obi C, Pebody R, Franco A, Moreno Y, Meloni S, Koppeschaar C, Kjelsø C, Mexia R, Paolotti D, Scarpino S. Unsupervised extraction of epidemic syndromes from participatory influenza surveillance self-reported symptoms. PLOS Computational Biology 2019;15(4):e1006173 View
  11. Richard A, Müller L, Wisniak A, Thiabaud A, Merle T, Dietrich D, Paolotti D, Jeannot E, Flahault A. Grippenet: A New Tool for the Monitoring, Risk-Factor and Vaccination Coverage Analysis of Influenza-Like Illness in Switzerland. Vaccines 2020;8(3):343 View
  12. Geneviève L, Wangmo T, Dietrich D, Woolley-Meza O, Flahault A, Elger B. Research Ethics in the European Influenzanet Consortium: Scoping Review. JMIR Public Health and Surveillance 2018;4(4):e67 View
  13. von Wyl V. Challenges for Nontechnical Implementation of Digital Proximity Tracing During the COVID-19 Pandemic: Media Analysis of the SwissCovid App. JMIR mHealth and uHealth 2021;9(2):e25345 View
  14. de Gier B, de Oliveira Bressane Lima P, van Gaalen R, de Boer P, Alblas J, Ruijten M, van Gageldonk-Lafeber A, Waegemaekers T, Schreijer A, van den Hof S, Hahné S. Occupation- and age-associated risk of SARS-CoV-2 test positivity, the Netherlands, June to October 2020. Eurosurveillance 2020;25(50) View
  15. Roy S, Cherevko A, Chakraborty S, Ghosh N, Ghosh P. Leveraging Network Science for Social Distancing to Curb Pandemic Spread. IEEE Access 2021;9:26196 View
  16. Ali S, Cowling B. Influenza Virus: Tracking, Predicting, and Forecasting. Annual Review of Public Health 2021;42(1):43 View
  17. Mahmud A, Chowdhury S, Sojib K, Chowdhury A, Quader M, Paul S, Saidy M, Uddin R, Engø-Monsen K, Buckee C. Participatory syndromic surveillance as a tool for tracking COVID-19 in Bangladesh. Epidemics 2021;35:100462 View
  18. McDonald S, van den Wijngaard C, Wielders C, Friesema I, Soetens L, Paolotti D, van den Hof S, van Hoek A. Risk factors associated with the incidence of self-reported COVID-19-like illness: data from a web-based syndromic surveillance system in the Netherlands. Epidemiology and Infection 2021;149 View
  19. De Ridder D, Loizeau A, Sandoval J, Ehrler F, Perrier M, Ritch A, Violot G, Santolini M, Greshake Tzovaras B, Stringhini S, Kaiser L, Pradeau J, Joost S, Guessous I. Detection of Spatiotemporal Clusters of COVID-19–Associated Symptoms and Prevention Using a Participatory Surveillance App: Protocol for the @choum Study. JMIR Research Protocols 2021;10(10):e30444 View
  20. Kostkova P, Saigí-Rubió F, Eguia H, Borbolla D, Verschuuren M, Hamilton C, Azzopardi-Muscat N, Novillo-Ortiz D. Data and Digital Solutions to Support Surveillance Strategies in the Context of the COVID-19 Pandemic. Frontiers in Digital Health 2021;3 View
  21. Cawley C, Bergey F, Mehl A, Finckh A, Gilsdorf A. Novel Methods in the Surveillance of Influenza-Like Illness in Germany Using Data From a Symptom Assessment App (Ada): Observational Case Study. JMIR Public Health and Surveillance 2021;7(11):e26523 View
  22. Plans Rubió P, Jambrina A, Rius P, Carmona G, Rabanal M, Gironès M. High Influenza Vaccine Effectiveness and Absence of Increased Influenza-like-Illness Epidemic Activity in the 2021–2022 Influenza Season in Catalonia (Spain) Based on Surveillance Data Collected by Sentinel Pharmacies. Vaccines 2022;10(12):2140 View
  23. Roy S, Ghosh P. Scalable and distributed strategies for socially distanced human mobility. Applied Network Science 2021;6(1) View
  24. Wang Z, Ntambara J, Lu Y, Dai W, Meng R, Qian D. Construction of Influenza Early Warning Model Based on Combinatorial Judgment Classifier: A Case Study of Seasonal Influenza in Hong Kong. Current Medical Science 2022;42(1):226 View
  25. Marmara V, Marmara D, McMenemy P, Kleczkowski A. Cross-sectional telephone surveys as a tool to study epidemiological factors and monitor seasonal influenza activity in Malta. BMC Public Health 2021;21(1) View
  26. Rosenfeld R, Tibshirani R. Epidemic tracking and forecasting: Lessons learned from a tumultuous year. Proceedings of the National Academy of Sciences 2021;118(51) View
  27. Gendy M, Yuce M. Emerging Technologies Used in Health Management and Efficiency Improvement During Different Contact Tracing Phases Against COVID-19 Pandemic. IEEE Reviews in Biomedical Engineering 2023;16:38 View
  28. Melms L, Falk E, Schieffer B, Jerrentrup A, Wagner U, Matrood S, Schaefer J, Müller T, Hirsch M, Cheong S. Towards a COVID-19 symptom triad: The importance of symptom constellations in the SARS-CoV-2 pandemic. PLOS ONE 2021;16(11):e0258649 View
  29. Leal-Neto O, Egger T, Schlegel M, Flury D, Sumer J, Albrich W, Babouee Flury B, Kuster S, Vernazza P, Kahlert C, Kohler P. Digital SARS-CoV-2 Detection Among Hospital Employees: Participatory Surveillance Study. JMIR Public Health and Surveillance 2021;7(11):e33576 View
  30. Storey V, Lukyanenko R, Grange C. Fighting Pandemics with Physical Distancing Management Technologies. Journal of Database Management 2022;33(1):1 View
  31. Roy S, Biswas P, Ghosh P. Spatiotemporal tracing of pandemic spread from infection data. Scientific Reports 2021;11(1) View
  32. Teirlinck A, de Gier B, Meijer A, Donker G, de Lange M, Koppeschaar C, van der Hoek W, Kretzschmar M, McDonald S. The incidence of symptomatic infection with influenza virus in the Netherlands 2011/2012 through 2016/2017, estimated using Bayesian evidence synthesis. Epidemiology and Infection 2019;147 View
  33. Tsang T, Huang X, Guo Y, Lau E, Cowling B, Ip D. Monitoring School Absenteeism for Influenza-Like Illness Surveillance: Systematic Review and Meta-analysis. JMIR Public Health and Surveillance 2023;9:e41329 View
  34. Shausan A, Nazarathy Y, Dyda A. Emerging data inputs for infectious diseases surveillance and decision making. Frontiers in Digital Health 2023;5 View
  35. Zhang X, Jin Y, Lu Y, Huang L, Wu C, Lv S, Chen Z, Xiang H, Zhou X. Infectious disease control: from health security strengthening to health systems improvement at global level. Global Health Research and Policy 2023;8(1) View
  36. Greffe S, Guerrisi C, Souty C, Vilcu A, Hayem G, Costantino F, Padovano I, Bourgault I, Trad S, Ponsoye M, Vilaine E, Debin M, Turbelin C, Blanchon T, Hanslik T. Influenza‐like illness in individuals treated with immunosuppressants, biologics, and/or systemic corticosteroids for autoimmune or chronic inflammatory disease: A crowdsourced cohort study, France, 2017–2018. Influenza and Other Respiratory Viruses 2023;17(6) View
  37. Bokányi E, Vizi Z, Koltai J, Röst G, Karsai M. Real-time estimation of the effective reproduction number of COVID-19 from behavioral data. Scientific Reports 2023;13(1) View
  38. Dall’Amico L, Kleynhans J, Gauvin L, Tizzoni M, Ozella L, Makhasi M, Wolter N, Language B, Wagner R, Cohen C, Tempia S, Cattuto C, Aleta A. Estimating household contact matrices structure from easily collectable metadata. PLOS ONE 2024;19(3):e0296810 View
  39. Chan C, Lee S, Kwan T, Wong S, Yeoh E, Wong N. Population Behavior Changes Underlying Phasic Shifts of SARS-CoV-2 Exposure Settings Across 3 Omicron Epidemic Waves in Hong Kong: Prospective Cohort Study. JMIR Public Health and Surveillance 2024;10:e51498 View
  40. Valerio M, Laher B, Phuka J, Lichand G, Paolotti D, Leal Neto O. Participatory Disease Surveillance for the Early Detection of Cholera-Like Diarrheal Disease Outbreaks in Rural Villages in Malawi: Prospective Cohort Study. JMIR Public Health and Surveillance 2024;10:e49539 View

Books/Policy Documents

  1. Lipsitch M, Santillana M. Global Catastrophic Biological Risks. View
  2. Primo P, Antunes M, Ramos M, Siqueira C, Oliveira A, Mendes J. Digital Services in Crisis, Disaster, and Emergency Situations. View
  3. Mejova Y. Handbook of Computational Social Science for Policy. View
  4. Richiardi L, Pizzi C, Paolotti D, Blumenberg C. Handbook of Epidemiology. View