Table. Description of the systems or platforms of digital detection of diseases.
| Title | Country, base year | Strategy type | Data source | Main objectives | Interaction platform |
|---|---|---|---|---|---|
| ProMED | USA, 1996 | A | Secondary | Collecting data in cyberspace related to diseases and conditions. | Website and mobile application |
| GPHIN | Canada, 1997 | A | Secondary | Collecting data in cyberspace related to diseases and conditions. | Website |
| InfluenzaNet | The Netherlands and Belgium, 2003 Portugal, 2005 Italy, 2008 UK, 2009 | B | Primary | Collecting information on influenza-like illness data, made available to the population. | Website and mobile application |
| HealthMap | USA, 2006 | A, B | Primary and secondary | Spatializing epidemiologically relevant information, made available to the population via web. | Website and mobile application* |
| MedISys | Italy, 2007 | A | Secondary | Collecting data in cyberspace related to diseases and conditions. | Website |
| Salud Boricua | USA (for Puerto Rico only), 2008 | B | Primary | Spatializing information on acute febrile syndrome (dengue fever, influenza, leptospirosis) data, made available to the population. | Website |
| Flu Near You | USA, 2011 | B | Primary | Spatializing information on influenza-like illness data, made available to the population. | Website and mobile application |
| Dengue na Web (Dengue in the Web) | Brazil, 2011 | B | Primary | Spatializing information on data related to dengue fever. | Website |
| Observatório da Dengue (Dengue Observatory) | Brazil, 2011 | C | Primary | Spatializing tweets related to dengue fever. | Website |
| Saúde na Copa (Healthy Cup) | Brazil, 2014 | A, B | Primary and secondary | Detecting possible changes in the epidemiological pattern of acute disease occurrence in 12 Brazilian host cities during the 2014 FIFA World Cup. | Website and mobile application |
| Guardiões da Saúde (Guardians of Health) | Brazil, 2016 | B | Primary and secondary | Detecting in advance aggregates of cases of diarrhoeal, respiratory, and exanthematic syndromes in Brazil. | Website and mobile application |
A: Mining of epidemiologically relevant data on the web; B: Participatory surveillance (Active crowdsourcing); C: Data mining on Twitter (Passive crowdsourcing)
* Made by the application Outbreaks Near Me.