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Enabling Multicentric Participatory Disease Surveillance for Global Health Enhancement: Viewpoint on Global Flu View.
Leal Neto, Onicio; Paolotti, Daniela; Dalton, Craig; Carlson, Sandra; Susumpow, Patipat; Parker, Matt; Phetra, Polowat; Lau, Eric H Y; Colizza, Vittoria; Jan van Hoek, Albert; Kjelsø, Charlotte; Brownstein, John S; Smolinski, Mark S.
Afiliação
  • Leal Neto O; Ending Pandemics, San Francisco, CA, United States.
  • Paolotti D; Department of Computer Science, ETH Zurich, Zurich, Switzerland.
  • Dalton C; Institute for Scientific Interchange Foundation, Turin, Italy.
  • Carlson S; FluTracking, Newcastle, Australia.
  • Susumpow P; FluTracking, Newcastle, Australia.
  • Parker M; Opendream, Bangkok, Thailand.
  • Phetra P; Opendream, Bangkok, Thailand.
  • Lau EHY; Opendream, Bangkok, Thailand.
  • Colizza V; School of Public Health, University of Hong Kong, Hong Kong, China.
  • Jan van Hoek A; Pierre Louis Institute of Epidemiology and Public Health, INSERM, Sorbonne Université, Paris, France.
  • Kjelsø C; National Institute for Public Health and the Environment, Bilthoven, Netherlands.
  • Brownstein JS; Statens Serum Institute, Copenhagen, Denmark.
  • Smolinski MS; Boston Children Hospital, Harvard University, Boston, MA, United States.
JMIR Public Health Surveill ; 9: e46644, 2023 09 01.
Article em En | MEDLINE | ID: mdl-37490846
ABSTRACT
Participatory surveillance (PS) has been defined as the bidirectional process of transmitting and receiving data for action by directly engaging the target population. Often represented as self-reported symptoms directly from the public, PS can provide evidence of an emerging disease or concentration of symptoms in certain areas, potentially identifying signs of an early outbreak. The construction of sets of symptoms to represent various disease syndromes provides a mechanism for the early detection of multiple health threats. Global Flu View (GFV) is the first-ever system that merges influenza-like illness (ILI) data from more than 8 countries plus 1 region (Hong Kong) on 4 continents for global monitoring of this annual health threat. GFV provides a digital ecosystem for spatial and temporal visualization of syndromic aggregates compatible with ILI from the various systems currently participating in GFV in near real time, updated weekly. In 2018, the first prototype of a digital platform to combine data from several ILI PS programs was created. At that time, the priority was to have a digital environment that brought together different programs through an application program interface, providing a real time map of syndromic trends that could demonstrate where and when ILI was spreading in various regions of the globe. After 2 years running as an experimental model and incorporating feedback from partner programs, GFV was restructured to empower the community of public health practitioners, data scientists, and researchers by providing an open data channel among these contributors for sharing experiences across the network. GFV was redesigned to serve not only as a data hub but also as a dynamic knowledge network around participatory ILI surveillance by providing knowledge exchange among programs. Connectivity between existing PS systems enables a network of cooperation and collaboration with great potential for continuous public health impact. The exchange of knowledge within this network is not limited only to health professionals and researchers but also provides an opportunity for the general public to have an active voice in the collective construction of health settings. The focus on preparing the next generation of epidemiologists will be of great importance to scale innovative approaches like PS. GFV provides a useful example of the value of globally integrated PS data to help reduce the risks and damages of the next pandemic.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Influenza Humana Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Humans Idioma: En Revista: JMIR Public Health Surveill Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Influenza Humana Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Humans Idioma: En Revista: JMIR Public Health Surveill Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos