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Psihogios A, Brianne Bota A, Mithani SS, Greyson D, Zhu DT, Fung SG, Wilson SE, Fell DB, Top KA, Bettinger JA, Wilson K. A scoping review of active, participant-centred, digital adverse events following immunization (AEFI) surveillance: A Canadian immunization research network study. Vaccine 2022; 40:4065-4080. [PMID: 35680501 DOI: 10.1016/j.vaccine.2022.04.103] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 04/06/2022] [Accepted: 04/29/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Post-licensure adverse events following immunization (AEFI) surveillance is conducted to monitor vaccine safety, such as identifying batch/brand issues and rare reactions, which consequently improves community confidence. The integration of technology has been proposed to improve AEFI surveillance, however, there is an absence of description regarding which digital solutions are successfully being used and their unique characteristics. OBJECTIVES The objectives of this scoping review were to 1) map the research landscape on digital systems used for active, participant-centred, AEFI surveillance and 2) describe their core components. METHODS We conducted a scoping review informed by the PRISMA Extension for Scoping Reviews (PRSIMA-ScR) guideline. OVID-Medline, Embase Classic + Embase, and Medrxiv were searched by a medical librarian from January 1, 2000 to January 28th, 2021. Two independent reviewers determined which studies met inclusion based on pre-specified eligibility criteria. Data extraction was conducted using pre-made tables with specific variables by one investigator and verified by a second. RESULTS Twenty-seven publications met inclusion, the majority of which came from Australia (n = 15) and Canada (n = 6). The most studied active, participant-centred, digital AEFI surveillance systems were SmartVax (n = 8) (Australia), Vaxtracker (n = 7) (Australia), and Canadian National Vaccine Safety (CANVAS) Network (Canada) (n = 6). The two most common methods of communicating with vaccinees reported were short-message-service (SMS) (n = 15) and e-mail (n = 14), with online questionnaires being the primary method of data collection (n = 20). CONCLUSION Active, participant-centred, digital AEFI surveillance is an area actively being researched as depicted by the literature landscape mapped by this scoping reviewWe hypothesize that the AEFI surveillance approach herein described could become a primary method of collecting self-reported subjective symptoms and reactogenicity from vaccinees, complementing existing systems. Future evaluation of identified digital solutions is necessary to bring about improvements to current vaccine surveillance systems to meet contemporary and future public health needs.
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Affiliation(s)
- Athanasios Psihogios
- Ottawa Hospital Research Institute, Clinical Epidemiology Program, Ottawa, Canada
| | - A Brianne Bota
- Ottawa Hospital Research Institute, Clinical Epidemiology Program, Ottawa, Canada
| | - Salima S Mithani
- Ottawa Hospital Research Institute, Clinical Epidemiology Program, Ottawa, Canada
| | - Devon Greyson
- School of Population and Public Health, University of British Columbia, Vancouver, Canada
| | - David T Zhu
- Ottawa Hospital Research Institute, Clinical Epidemiology Program, Ottawa, Canada
| | - Stephen G Fung
- Children's Hospital of Eastern Ontario (CHEO) Research Institute, Ottawa, Canada
| | - Sarah E Wilson
- Public Health Ontario, Toronto, ON, Canada; Dalla Lana School of Public Health, University of Toronto, Canada; ICES, Toronto, ON, Canada
| | - Deshayne B Fell
- Children's Hospital of Eastern Ontario (CHEO) Research Institute, Ottawa, Canada; School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Karina A Top
- Departments of Pediatrics and Community Health & Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Julie A Bettinger
- Vaccine Evaluation Center, Department of Pediatrics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, Canada
| | - Kumanan Wilson
- Ottawa Hospital Research Institute, Clinical Epidemiology Program, Ottawa, Canada; School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada; Department of Medicine, University of Ottawa, Ottawa, Canada; Bruyère Research Institute, Ottawa, Canada.
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Koppeschaar CE, Colizza V, Guerrisi C, Turbelin C, Duggan J, Edmunds WJ, Kjelsø C, Mexia R, Moreno Y, Meloni S, Paolotti D, Perrotta D, van Straten E, Franco AO. Influenzanet: Citizens Among 10 Countries Collaborating to Monitor Influenza in Europe. JMIR Public Health Surveill 2017; 3:e66. [PMID: 28928112 PMCID: PMC5627046 DOI: 10.2196/publichealth.7429] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Revised: 06/23/2017] [Accepted: 06/26/2017] [Indexed: 11/13/2022] Open
Abstract
Background The wide availability of the Internet and the growth of digital communication technologies have become an important tool for epidemiological studies and health surveillance. Influenzanet is a participatory surveillance system monitoring the incidence of influenza-like illness (ILI) in Europe since 2003. It is based on data provided by volunteers who self-report their symptoms via the Internet throughout the influenza season and currently involves 10 countries. Objective In this paper, we describe the Influenzanet system and provide an overview of results from several analyses that have been performed with the collected data, which include participant representativeness analyses, data validation (comparing ILI incidence rates between Influenzanet and sentinel medical practice networks), identification of ILI risk factors, and influenza vaccine effectiveness (VE) studies previously published. Additionally, we present new VE analyses for the Netherlands, stratified by age and chronic illness and offer suggestions for further work and considerations on the continuity and sustainability of the participatory system. Methods Influenzanet comprises country-specific websites where residents can register to become volunteers to support influenza surveillance and have access to influenza-related information. Participants are recruited through different communication channels. Following registration, volunteers submit an intake questionnaire with their postal code and sociodemographic and medical characteristics, after which they are invited to report their symptoms via a weekly electronic newsletter reminder. Several thousands of participants have been engaged yearly in Influenzanet, with over 36,000 volunteers in the 2015-16 season alone. Results In summary, for some traits and in some countries (eg, influenza vaccination rates in the Netherlands), Influenzanet participants were representative of the general population. However, for other traits, they were not (eg, participants underrepresent the youngest and oldest age groups in 7 countries). The incidence of ILI in Influenzanet was found to be closely correlated although quantitatively higher than that obtained by the sentinel medical practice networks. Various risk factors for acquiring an ILI infection were identified. The VE studies performed with Influenzanet data suggest that this surveillance system could develop into a complementary tool to measure the effectiveness of the influenza vaccine, eventually in real time. Conclusions Results from these analyses illustrate that Influenzanet has developed into a fast and flexible monitoring system that can complement the traditional influenza surveillance performed by sentinel medical practices. The uniformity of Influenzanet allows for direct comparison of ILI rates between countries. It also has the important advantage of yielding individual data, which can be used to identify risk factors. The way in which the Influenzanet system is constructed allows the collection of data that could be extended beyond those of ILI cases to monitor pandemic influenza and other common or emerging diseases.
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Affiliation(s)
| | - Vittoria Colizza
- UPMC Univ Paris 06, Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136), Sorbonne Universités, Paris, France
| | - Caroline Guerrisi
- UPMC Univ Paris 06, Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136), Sorbonne Universités, Paris, France
| | - Clément Turbelin
- UPMC Univ Paris 06, Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136), Sorbonne Universités, Paris, France
| | - Jim Duggan
- School of Engineering and Informatics, National University of Ireland, Galway, Ireland
| | - W John Edmunds
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | | | - Ricardo Mexia
- Instituto Nacional de Saúde Doutor Ricardo Jorge, Lisbon, Portugal
| | - Yamir Moreno
- Institute for Biocomputation and Physics of Complex Systems, Department of Theoretical Physics, University of Zaragoza, Zaragoza, Spain
| | - Sandro Meloni
- Institute for Biocomputation and Physics of Complex Systems, Department of Theoretical Physics, University of Zaragoza, Zaragoza, Spain
| | | | | | | | - Ana O Franco
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.,Instituto Gulbenkian de Ciência, Oeiras, Portugal
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