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Atkins N, Harikar M, Duggan K, Zawiejska A, Vardhan V, Vokey L, Dozier M, de los Godos EF, Mcswiggan E, Mcquillan R, Theodoratou E, Shi T. What are the characteristics of participatory surveillance systems for influenza-like-illness? J Glob Health 2023; 13:04130. [PMID: 37856769 PMCID: PMC10587643 DOI: 10.7189/jogh.13.04130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2023] Open
Abstract
Background Seasonal influenza causes significant morbidity and mortality, with an estimated 9.4 million hospitalisations and 290 000-650 000 respiratory related-deaths globally each year. Influenza can also cause mild illness, which is why not all symptomatic persons might necessarily be tested for influenza. To monitor influenza activity, healthcare facility-based syndromic surveillance for influenza-like illness is often implemented. Participatory surveillance systems for influenza-like illness (ILI) play an important role in influenza surveillance and can complement traditional facility-based surveillance systems to provide real-time estimates of influenza-like illness activity. However, such systems differ in designs between countries and contexts, making it necessary to identify their characteristics to better understand how they fit traditional surveillance systems. Consequently, we aimed to investigate the performance of participatory surveillance systems for ILI worldwide. Methods We systematically searched four databases for relevant articles on influenza participatory surveillance systems for ILI. We extracted data from the included, eligible studies and assessed their quality using the Joanna Briggs Critical Appraisal Tools. We then synthesised the findings using narrative synthesis. Results We included 39 out of 3797 retrieved articles for analysis. We identified 26 participatory surveillance systems, most of which sought to capture the burden and trends of influenza-like illness and acute respiratory infections among cohorts with risk factors for influenza-like illness. Of all the surveillance system attributes assessed, 52% reported on correlation with other surveillance systems, 27% on representativeness, and 21% on acceptability. Among studies that reported these attributes, all systems were rated highly in terms of simplicity, flexibility, sensitivity, utility, and timeliness. Most systems (87.5%) were also well accepted by users, though participation rates varied widely. However, despite their potential for greater reach and accessibility, most systems (90%) fared poorly in terms of representativeness of the population. Stability was a concern for some systems (60%), as was completeness (50%). Conclusions The analysis of participatory surveillance system attributes showed their potential in providing timely and reliable influenza data, especially in combination with traditional hospital- and laboratory led-surveillance systems. Further research is needed to design future systems with greater uptake and utility.
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Affiliation(s)
- Nadege Atkins
- Center for Population Health Sciences, Usher Institute, University of Edinburgh, Scotland, UK
- UNCOVER (Usher Network for COVID-19 Evidence Reviews) Usher Institute, University of Edinburgh, Edinburgh, UK
- Joint first authorship
| | - Mandara Harikar
- Center for Population Health Sciences, Usher Institute, University of Edinburgh, Scotland, UK
- UNCOVER (Usher Network for COVID-19 Evidence Reviews) Usher Institute, University of Edinburgh, Edinburgh, UK
- Joint first authorship
| | - Kirsten Duggan
- Center for Population Health Sciences, Usher Institute, University of Edinburgh, Scotland, UK
- UNCOVER (Usher Network for COVID-19 Evidence Reviews) Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Agnieszka Zawiejska
- Center for Population Health Sciences, Usher Institute, University of Edinburgh, Scotland, UK
- UNCOVER (Usher Network for COVID-19 Evidence Reviews) Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Vaishali Vardhan
- Center for Population Health Sciences, Usher Institute, University of Edinburgh, Scotland, UK
- UNCOVER (Usher Network for COVID-19 Evidence Reviews) Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Laura Vokey
- Center for Population Health Sciences, Usher Institute, University of Edinburgh, Scotland, UK
- UNCOVER (Usher Network for COVID-19 Evidence Reviews) Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Marshall Dozier
- Center for Population Health Sciences, Usher Institute, University of Edinburgh, Scotland, UK
- UNCOVER (Usher Network for COVID-19 Evidence Reviews) Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Emma F de los Godos
- Center for Population Health Sciences, Usher Institute, University of Edinburgh, Scotland, UK
- UNCOVER (Usher Network for COVID-19 Evidence Reviews) Usher Institute, University of Edinburgh, Edinburgh, UK
- Equal contribution
| | - Emilie Mcswiggan
- Center for Population Health Sciences, Usher Institute, University of Edinburgh, Scotland, UK
- UNCOVER (Usher Network for COVID-19 Evidence Reviews) Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Ruth Mcquillan
- Center for Population Health Sciences, Usher Institute, University of Edinburgh, Scotland, UK
- UNCOVER (Usher Network for COVID-19 Evidence Reviews) Usher Institute, University of Edinburgh, Edinburgh, UK
- Equal contribution
| | - Evropi Theodoratou
- Center for Population Health Sciences, Usher Institute, University of Edinburgh, Scotland, UK
- UNCOVER (Usher Network for COVID-19 Evidence Reviews) Usher Institute, University of Edinburgh, Edinburgh, UK
- Equal contribution
| | - Ting Shi
- Center for Population Health Sciences, Usher Institute, University of Edinburgh, Scotland, UK
- Equal contribution
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Zeeb H, Pigeot I, Schüz B. [Digital public health-an overview]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2020; 63:137-144. [PMID: 31919531 DOI: 10.1007/s00103-019-03078-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
The rapid development and proliferation of digital health technologies have not only changed the medical professions, but offer great potential for public health, particularly in health promotion and disease prevention.At the same time, this emerging field is also characterized by conceptual and terminological fuzziness, a marked lack of high-quality evidence, and an absence of an honest discussion of unintended consequences and side effects. Further challenges for digital public health lie in the fact that the development of new health technologies is mainly driven by technological progress and less by evidence-based needs and research in public health.In this overview paper, we aim at conceptually denoting the field of digital public health, using principal public health functions as guiding principles. We discuss some current applications of digital health technologies in fulfilling public health functions and propose a needs-based development of digital health technologies.We will further address specific challenges to digital public health, in particular socio-economic differences in the usage of and profiting from digital health technologies, data protection and privacy issues, as well as ethical issues.
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Affiliation(s)
- Hajo Zeeb
- Leibniz WissenschaftsCampus Digital Public Health Bremen, Bremen, Deutschland. .,Leibniz-Institut für Präventionsforschung und Epidemiologie - BIPS, Achterstr. 30, 28359, Bremen, Deutschland. .,Fachbereich Human- und Gesundheitswissenschaften, Universität Bremen, Bremen, Deutschland.
| | - Iris Pigeot
- Leibniz WissenschaftsCampus Digital Public Health Bremen, Bremen, Deutschland.,Leibniz-Institut für Präventionsforschung und Epidemiologie - BIPS, Achterstr. 30, 28359, Bremen, Deutschland.,Fachbereich Mathematik und Informatik, Universität Bremen, Bremen, Deutschland
| | - Benjamin Schüz
- Leibniz WissenschaftsCampus Digital Public Health Bremen, Bremen, Deutschland.,Fachbereich Human- und Gesundheitswissenschaften, Institut für Public Health und Pflegeforschung, Universität Bremen, Bremen, Deutschland
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Geneviève LD, Martani A, Wangmo T, Paolotti D, Koppeschaar C, Kjelsø C, Guerrisi C, Hirsch M, Woolley-Meza O, Lukowicz P, Flahault A, Elger BS. Participatory Disease Surveillance Systems: Ethical Framework. J Med Internet Res 2019; 21:e12273. [PMID: 31124466 PMCID: PMC6660191 DOI: 10.2196/12273] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Revised: 03/08/2019] [Accepted: 03/29/2019] [Indexed: 12/23/2022] Open
Abstract
Advances in information technology are changing public health at an unprecedented rate. Participatory surveillance systems are contributing to public health by actively engaging digital (eg, Web-based) communities of volunteer citizens to report symptoms and other pertinent information on public health threats and also by empowering individuals to promptly respond to them. However, this digital model raises ethical issues on top of those inherent in traditional forms of public health surveillance. Research ethics are undergoing significant changes in the digital era where not only participants' physical and psychological well-being but also the protection of their sensitive data have to be considered. In this paper, the digital platform of Influenzanet is used as a case study to illustrate those ethical challenges posed to participatory surveillance systems using digital platforms and mobile apps. These ethical challenges include the implementation of electronic consent, the protection of participants' privacy, the promotion of justice, and the need for interdisciplinary capacity building of research ethics committees. On the basis of our analysis, we propose a framework to regulate and strengthen ethical approaches in the field of digital public health surveillance.
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Affiliation(s)
| | - Andrea Martani
- Institute for Biomedical Ethics, University of Basel, Basel, Switzerland
| | - Tenzin Wangmo
- Institute for Biomedical Ethics, University of Basel, Basel, Switzerland
| | | | - Carl Koppeschaar
- De Grote Griepmeting, Science in Action BV, Amsterdam, Netherlands
| | | | - Caroline Guerrisi
- Sorbonne Université, Institut National de la Santé et de la Recherche Médicale, Institut Pierre Louis d'Épidémiologie et de Santé Publique, Paris, France
| | - Marco Hirsch
- German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany
| | - Olivia Woolley-Meza
- ETH Zurich, Swiss Federal Institute of Technology, Zurich, Switzerland
- Novartis Pharma AG, Basel, Switzerland
| | - Paul Lukowicz
- German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany
| | - Antoine Flahault
- Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Bernice Simone Elger
- Institute for Biomedical Ethics, University of Basel, Basel, Switzerland
- University Center of Legal Medicine, University of Geneva, Geneva, Switzerland
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