Cargando…

Enabling Multicentric Participatory Disease Surveillance for Global Health Enhancement: Viewpoint on Global Flu View

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 concentratio...

Descripción completa

Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10504624/
https://www.ncbi.nlm.nih.gov/pubmed/37490846
http://dx.doi.org/10.2196/46644
_version_ 1785106765511131136
author 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
author_facet 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
author_sort Leal Neto, Onicio
collection PubMed
description 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.
format Online
Article
Text
id pubmed-10504624
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher JMIR Publications
record_format MEDLINE/PubMed
spelling pubmed-105046242023-09-17 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 JMIR Public Health Surveill Viewpoint 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. JMIR Publications 2023-09-01 /pmc/articles/PMC10504624/ /pubmed/37490846 http://dx.doi.org/10.2196/46644 Text en ©Onicio Leal Neto, Daniela Paolotti, Craig Dalton, Sandra Carlson, Patipat Susumpow, Matt Parker, Polowat Phetra, Eric H Y Lau, Vittoria Colizza, Albert Jan van Hoek, Charlotte Kjelsø, John S Brownstein, Mark S Smolinski. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 01.09.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on https://publichealth.jmir.org, as well as this copyright and license information must be included.
spellingShingle Viewpoint
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
Enabling Multicentric Participatory Disease Surveillance for Global Health Enhancement: Viewpoint on Global Flu View
title Enabling Multicentric Participatory Disease Surveillance for Global Health Enhancement: Viewpoint on Global Flu View
title_full Enabling Multicentric Participatory Disease Surveillance for Global Health Enhancement: Viewpoint on Global Flu View
title_fullStr Enabling Multicentric Participatory Disease Surveillance for Global Health Enhancement: Viewpoint on Global Flu View
title_full_unstemmed Enabling Multicentric Participatory Disease Surveillance for Global Health Enhancement: Viewpoint on Global Flu View
title_short Enabling Multicentric Participatory Disease Surveillance for Global Health Enhancement: Viewpoint on Global Flu View
title_sort enabling multicentric participatory disease surveillance for global health enhancement: viewpoint on global flu view
topic Viewpoint
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10504624/
https://www.ncbi.nlm.nih.gov/pubmed/37490846
http://dx.doi.org/10.2196/46644
work_keys_str_mv AT lealnetoonicio enablingmulticentricparticipatorydiseasesurveillanceforglobalhealthenhancementviewpointonglobalfluview
AT paolottidaniela enablingmulticentricparticipatorydiseasesurveillanceforglobalhealthenhancementviewpointonglobalfluview
AT daltoncraig enablingmulticentricparticipatorydiseasesurveillanceforglobalhealthenhancementviewpointonglobalfluview
AT carlsonsandra enablingmulticentricparticipatorydiseasesurveillanceforglobalhealthenhancementviewpointonglobalfluview
AT susumpowpatipat enablingmulticentricparticipatorydiseasesurveillanceforglobalhealthenhancementviewpointonglobalfluview
AT parkermatt enablingmulticentricparticipatorydiseasesurveillanceforglobalhealthenhancementviewpointonglobalfluview
AT phetrapolowat enablingmulticentricparticipatorydiseasesurveillanceforglobalhealthenhancementviewpointonglobalfluview
AT lauerichy enablingmulticentricparticipatorydiseasesurveillanceforglobalhealthenhancementviewpointonglobalfluview
AT colizzavittoria enablingmulticentricparticipatorydiseasesurveillanceforglobalhealthenhancementviewpointonglobalfluview
AT janvanhoekalbert enablingmulticentricparticipatorydiseasesurveillanceforglobalhealthenhancementviewpointonglobalfluview
AT kjelsøcharlotte enablingmulticentricparticipatorydiseasesurveillanceforglobalhealthenhancementviewpointonglobalfluview
AT brownsteinjohns enablingmulticentricparticipatorydiseasesurveillanceforglobalhealthenhancementviewpointonglobalfluview
AT smolinskimarks enablingmulticentricparticipatorydiseasesurveillanceforglobalhealthenhancementviewpointonglobalfluview