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Daniore P, Moser A, Höglinger M, Probst Hensch N, Imboden M, Vermes T, Keidel D, Bochud M, Ortega Herrero N, Baggio S, Chocano-Bedoya P, Rodondi N, Tancredi S, Wagner C, Cullati S, Stringhini S, Gonseth Nusslé S, Veys-Takeuchi C, Zuppinger C, Harju E, Michel G, Frank I, Kahlert CR, Albanese E, Crivelli L, Levati S, Amati R, Kaufmann M, Geigges M, Ballouz T, Frei A, Fehr J, von Wyl V. Interplay of Digital Proximity App Use and SARS-CoV-2 Vaccine Uptake in Switzerland: Analysis of Two Population-Based Cohort Studies. Int J Public Health 2023; 68:1605812. [PMID: 37799349 PMCID: PMC10549773 DOI: 10.3389/ijph.2023.1605812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 08/18/2023] [Indexed: 10/07/2023] Open
Abstract
Objectives: Our study aims to evaluate developments in vaccine uptake and digital proximity tracing app use in a localized context of the SARS-CoV-2 pandemic. Methods: We report findings from two population-based longitudinal cohorts in Switzerland from January to December 2021. Failure time analyses and Cox proportional hazards regression models were conducted to assess vaccine uptake and digital proximity tracing app (SwissCovid) uninstalling outcomes. Results: We observed a dichotomy of individuals who did not use the SwissCovid app and did not get vaccinated, and who used the SwissCovid app and got vaccinated during the study period. Increased vaccine uptake was observed with SwissCovid app use (aHR, 1.51; 95% CI: 1.40-1.62 [CI-DFU]; aHR, 1.79; 95% CI: 1.62-1.99 [CSM]) compared to SwissCovid app non-use. Decreased SwissCovid uninstallation risk was observed for participants who got vaccinated (aHR, 0.55; 95% CI: 0.38-0.81 [CI-DFU]; aHR, 0.45; 95% CI: 0.27-0.78 [CSM]) compared to participants who did not get vaccinated. Conclusion: In evolving epidemic contexts, these findings underscore the need for communication strategies as well as flexible digital proximity tracing app adjustments that accommodate different preventive measures and their anticipated interactions.
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Affiliation(s)
- Paola Daniore
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
| | - André Moser
- Clinical Trials Unit Bern, University of Bern, Bern, Switzerland
| | - Marc Höglinger
- Winterthur Institute of Health Economics, Zurich University of Applied Sciences, Winterthur, Switzerland
| | - Nicole Probst Hensch
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Medea Imboden
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Thomas Vermes
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Dirk Keidel
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Murielle Bochud
- Unisanté, University Center for Primary Care and Public Health, Lausanne, Switzerland
| | - Natalia Ortega Herrero
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
- Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
| | - Stéphanie Baggio
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
- Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
| | - Patricia Chocano-Bedoya
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
- Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
| | - Nicolas Rodondi
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
- Department of General Internal Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Stefano Tancredi
- Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
| | - Cornelia Wagner
- Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
| | - Stéphane Cullati
- Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
- Department of Readaptation and Geriatrics, University of Geneva, Geneva, Switzerland
| | - Silvia Stringhini
- Department of Health and Community Medicine, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Unit of Population Epidemiology, Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Semira Gonseth Nusslé
- Unisanté, University Center for Primary Care and Public Health, Lausanne, Switzerland
| | | | - Claire Zuppinger
- Unisanté, University Center for Primary Care and Public Health, Lausanne, Switzerland
| | - Erika Harju
- Faculty of Health Sciences and Medicine, University of Lucerne, Lucerne, Switzerland
- Clinical Trial Unit, Lucerne Cantonal Hospital, Lucerne, Switzerland
- School of Health Sciences, ZHAW Zurich University of Applied Sciences, Winterthur, Switzerland
| | - Gisela Michel
- Faculty of Health Sciences and Medicine, University of Lucerne, Lucerne, Switzerland
| | - Irène Frank
- Clinical Trial Unit, Lucerne Cantonal Hospital, Lucerne, Switzerland
| | - Christian R. Kahlert
- Department of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
- Infectious Diseases and Hospital Epidemiology, Children’s Hospital of Eastern Switzerland, St. Gallen, Switzerland
| | - Emiliano Albanese
- Institute of Public Health, Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland
| | - Luca Crivelli
- Institute of Public Health, Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland
- Department Business Economics, Health and Social Care, University of Applied Sciences and Arts of Southern Switzerland, Manno, Switzerland
| | - Sara Levati
- Department Business Economics, Health and Social Care, University of Applied Sciences and Arts of Southern Switzerland, Manno, Switzerland
| | - Rebecca Amati
- Institute of Public Health, Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland
| | - Marco Kaufmann
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Marco Geigges
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Tala Ballouz
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Anja Frei
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Jan Fehr
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
- Division of Infectious Disease and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
| | - Viktor von Wyl
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
- Division of Infectious Disease and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
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Salathé M. COVID-19 digital contact tracing worked - heed the lessons for future pandemics. Nature 2023; 619:31-33. [PMID: 37400650 DOI: 10.1038/d41586-023-02130-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/05/2023]
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3
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Daniore P, Nittas V, Ballouz T, Menges D, Moser A, Höglinger M, Villiger P, Schmitz-Grosz K, Von Wyl V. Performance of the Swiss Digital Contact-Tracing App Over Various SARS-CoV-2 Pandemic Waves: Repeated Cross-sectional Analyses. JMIR Public Health Surveill 2022; 8:e41004. [PMID: 36219833 PMCID: PMC9700234 DOI: 10.2196/41004] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 09/28/2022] [Accepted: 10/09/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Digital proximity-tracing apps have been deployed in multiple countries to assist with SARS-CoV-2 pandemic mitigation efforts. However, it is unclear how their performance and effectiveness were affected by changing pandemic contexts and new viral variants of concern. OBJECTIVE The aim of this study is to bridge these knowledge gaps through a countrywide digital proximity-tracing app effectiveness assessment, as guided by the World Health Organization/European Center for Prevention and Disease Control (WHO/ECDC) indicator framework to evaluate the public health effectiveness of digital proximity-tracing solutions. METHODS We performed a descriptive analysis of the digital proximity-tracing app SwissCovid in Switzerland for 3 different periods where different SARS-CoV-2 variants of concern (ie, Alpha, Delta, and Omicron, respectively) were most prevalent. In our study, we refer to the indicator framework for the evaluation of public health effectiveness of digital proximity-tracing apps of the WHO/ECDC. We applied this framework to compare the performance and effectiveness indicators of the SwissCovid app. RESULTS Average daily registered SARS-CoV-2 case rates during our assessment period from January 25, 2021, to March 19, 2022, were 20 (Alpha), 54 (Delta), and 350 (Omicron) per 100,000 inhabitants. The percentages of overall entered authentication codes from positive tests into the SwissCovid app were 9.9% (20,273/204,741), 3.9% (14,372/365,846), and 4.6% (72,324/1,581,506) during the Alpha, Delta, and Omicron variant phases, respectively. Following receipt of an exposure notification from the SwissCovid app, 58% (37/64, Alpha), 44% (7/16, Delta), and 73% (27/37, Omicron) of app users sought testing or performed self-tests. Test positivity among these exposure-notified individuals was 19% (7/37) in the Alpha variant phase, 29% (2/7) in the Delta variant phase, and 41% (11/27) in the Omicron variant phase compared to 6.1% (228,103/3,755,205), 12% (413,685/3,443,364), and 41.7% (1,784,951/4,285,549) in the general population, respectively. In addition, 31% (20/64, Alpha), 19% (3/16, Delta), and 30% (11/37, Omicron) of exposure-notified app users reported receiving mandatory quarantine orders by manual contact tracing or through a recommendation by a health care professional. CONCLUSIONS In constantly evolving pandemic contexts, the effectiveness of digital proximity-tracing apps in contributing to mitigating pandemic spread should be reviewed regularly and adapted based on changing requirements. The WHO/ECDC framework allowed us to assess relevant domains of digital proximity tracing in a holistic and systematic approach. Although the Swisscovid app mostly worked, as reasonably expected, our analysis revealed room for optimizations and further performance improvements. Future implementation of digital proximity-tracing apps should place more emphasis on social, psychological, and organizational aspects to reduce bottlenecks and facilitate their use in pandemic contexts.
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Affiliation(s)
- Paola Daniore
- Institute for Implementation Science in Healthcare, University of Zurich, Zurich, Switzerland
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
| | - Vasileios Nittas
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Tala Ballouz
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Dominik Menges
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - André Moser
- Clinical Trials Unit, University of Bern, Bern, Switzerland
| | - Marc Höglinger
- Winterthur Institute of Health Economics, Zurich University of Applied Sciences, Winterthur, Switzerland
| | | | | | - Viktor Von Wyl
- Institute for Implementation Science in Healthcare, University of Zurich, Zurich, Switzerland
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
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Chambers T, Egan R, Maclennan K, Emery T, Derrett S. Expert insights on digital contact tracing: interviews with contact tracing policy professionals in New Zealand. Health Promot Int 2022; 37:daac059. [PMID: 35788307 PMCID: PMC9255939 DOI: 10.1093/heapro/daac059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Digital contact tracing (DCT) is the application of digital tools to assist with identifying and informing close contacts of a COVID-19 case. DCT is a potential solution to capacity constraints of current manual contact tracing processes. Expert opinion from contact tracing professionals rarely informs public discourse on the benefits and limitations of DCT solutions. Three focus groups were undertaken in New Zealand to understand benefits and limitations of DCT solutions from contact tracing professionals. One was with the National Investigation and Tracing Centre (NITC) and two were with Public Health Units (PHUs). Participants highlighted four key themes including: (i) equity, (ii) privacy, (iii) communication and public perception and (iv) the operational model. Participants were concerned DCT solutions could exacerbate existing health inequities due to lack of access to, or familiarity with, technology. Poor communication and public understanding of DCT were seen as a major threat to both the efficacy of DCT solutions and the wider COVID-19 response. Most importantly, end-users were cautious of the operational model for DCT data that might: (i) attempt to replace manual processes that cannot or should not be automated by technology (case investigations, follow-ups); (ii) place undue burden on citizens and (iii) increase the workload for the current system beyond its capacity, for unproven or limited benefit. To be effective, contact tracing professionals believed DCT technologies must have strong privacy safeguards, a clear and simple communication strategy, interoperability with the existing contact tracing system and a foundation of health equity.
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Affiliation(s)
- Tim Chambers
- Department of Public Health, University of Otago, Wellington, New Zealand
| | - Richard Egan
- Department of Preventive & Social Medicine, University of Otago, Dunedin, New Zealand
| | - Karyn Maclennan
- Ngāi Tahu Māori Health Research Unit, Department of Preventive & Social Medicine, University of Otago, Dunedin, New Zealand
| | - Tepora Emery
- Toi-Ohomai Institute of Technology, Rotorua, New Zealand
| | - Sarah Derrett
- Department of Preventive & Social Medicine, University of Otago, Dunedin, New Zealand
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5
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Ballouz T, Menges D, Aschmann HE, Jung R, Domenghino A, Fehr JS, Puhan MA, von Wyl V. Individual-level Evaluation of the Exposure Notification Cascade in the SwissCovid Digital Proximity Tracing App: An Observational Study. JMIR Public Health Surveill 2022; 8:e35653. [PMID: 35476726 PMCID: PMC9122110 DOI: 10.2196/35653] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 02/03/2022] [Accepted: 04/26/2022] [Indexed: 12/31/2022] Open
Abstract
Background Digital proximity tracing (DPT) aims to complement manual contact tracing (MCT) in identifying exposed contacts and preventing further transmission of SARS-CoV-2 in the population. Although several DPT apps, including SwissCovid, have shown to have promising effects on mitigating the pandemic, several challenges have impeded them from fully achieving the desired results. A key question now relates to how the effectiveness of DPT can be improved, which requires a better understanding of factors influencing its processes. Objective In this study, we aim to provide a detailed examination of the exposure notification (EN) cascade and to evaluate potential contextual influences for successful receipt of an EN and subsequent actions taken by cases and contacts in different exposure settings. Methods We used data from 285 pairs of SARS-CoV-2-infected cases and their contacts within an observational cohort study of cases and contacts identified by MCT and enrolled between August 6, 2020, and January 17, 2021, in the canton of Zurich, Switzerland. We surveyed participants with electronic questionnaires. Data were summarized descriptively and stratified by exposure setting. Results We found that only 79 (58.5%) of 135 contacts using the SwissCovid app whose corresponding cases reported to have triggered the EN also received one. Of these, 18 (22.8%) received the EN before MCT. Compared to those receiving an EN after MCT (61/79, 77.2%), we observed that a higher proportion of contacts receiving an EN before MCT were exposed in nonhousehold settings (11/18, 61.1%, vs 34/61, 55.7%) and their corresponding cases had more frequently reported mild-to-moderate symptoms (14/18, 77.8%, vs 42/61, 68.9%). Of the 18 contacts receiving an EN before MCT, 14 (77.8%) took recommended measures: 12 (66.7%) were tested for SARS-CoV-2, and 7 (38.9%) called the SwissCovid Infoline. In nonhousehold settings, the proportion of contacts taking preventive actions after receiving an EN was higher compared to same-household settings (82%, vs 67%). In addition, 1 (9%) of 11 ENs received in the nonhousehold setting before MCT led to the identification of a SARS-CoV-2-infected case by prompting the contact to get tested. This corresponds to 1 in 85 exposures of a contact to a case in a nonhousehold setting, in which both were app users and the case triggered the EN. Conclusions Our descriptive evaluation of the DPT notification cascade provides further evidence that DPT is an important complementary tool in pandemic mitigation, especially in nonhousehold exposure settings. However, the effect of DPT apps can only be exerted if code generation processes are efficient and exposed contacts are willing to undertake preventive actions. This highlights the need to focus efforts on keeping barriers to efficient code generation as low as possible and promoting not only app adoption but also compliance with the recommended measures upon an EN. Trial Registration International Standard Randomised Controlled Trial Number Registry 14990068; https://doi.org/10.1186/ISRCTN14990068
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Affiliation(s)
- Tala Ballouz
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, Zurich, CH
| | - Dominik Menges
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, Zurich, CH
| | - Hélène E Aschmann
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, Zurich, CH.,Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, US
| | - Ruedi Jung
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, Zurich, CH
| | - Anja Domenghino
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, Zurich, CH.,Department of Visceral and Transplantation Surgery, University Hospital Zurich (USZ), University of Zurich, Zurich, CH
| | - Jan S Fehr
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, Zurich, CH
| | - Milo Alan Puhan
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, Zurich, CH
| | - Viktor von Wyl
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, Zurich, CH.,Institute for Implementation Science in Health Care, University of Zurich, Zurich, CH
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6
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Daniore P, Nittas V, Moser A, Höglinger M, von Wyl V. Using Venn Diagrams to Evaluate Digital Contact Tracing: Panel Survey Analysis. JMIR Public Health Surveill 2021; 7:e30004. [PMID: 34874890 PMCID: PMC8658229 DOI: 10.2196/30004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 07/22/2021] [Accepted: 10/26/2021] [Indexed: 01/11/2023] Open
Abstract
Background Mitigation of the spread of infection relies on targeted approaches aimed at preventing nonhousehold interactions. Contact tracing in the form of digital proximity tracing apps has been widely adopted in multiple countries due to its perceived added benefits of tracing speed and breadth in comparison to traditional manual contact tracing. Assessments of user responses to exposure notifications through a guided approach can provide insights into the effect of digital proximity tracing app use on managing the spread of SARS-CoV-2. Objective The aim of this study was to demonstrate the use of Venn diagrams to investigate the contributions of digital proximity tracing app exposure notifications and subsequent mitigative actions in curbing the spread of SARS-CoV-2 in Switzerland. Methods We assessed data from 4 survey waves (December 2020 to March 2021) from a nationwide panel study (COVID-19 Social Monitor) of Swiss residents who were (1) nonusers of the SwissCovid app, (2) users of the SwissCovid app, or (3) users of the SwissCovid app who received exposure notifications. A Venn diagram approach was applied to describe the overlap or nonoverlap of these subpopulations and to assess digital proximity tracing app use and its associated key performance indicators, including actions taken to prevent SARS-CoV-2 transmission. Results We included 12,525 assessments from 2403 participants, of whom 50.9% (1222/2403) reported not using the SwissCovid digital proximity tracing app, 49.1% (1181/2403) reported using the SwissCovid digital proximity tracing app and 2.5% (29/1181) of the digital proximity tracing app users reported having received an exposure notification. Most digital proximity tracing app users (75.9%, 22/29) revealed taking at least one recommended action after receiving an exposure notification, such as seeking SARS-CoV-2 testing (17/29, 58.6%) or calling a federal information hotline (7/29, 24.1%). An assessment of key indicators of mitigative actions through a Venn diagram approach reveals that 30% of digital proximity tracing app users (95% CI 11.9%-54.3%) also tested positive for SARS-CoV-2 after having received exposure notifications, which is more than 3 times that of digital proximity tracing app users who did not receive exposure notifications (8%, 95% CI 5%-11.9%). Conclusions Responses in the form of mitigative actions taken by 3 out of 4 individuals who received exposure notifications reveal a possible contribution of digital proximity tracing apps in mitigating the spread of SARS-CoV-2. The application of a Venn diagram approach demonstrates its value as a foundation for researchers and health authorities to assess population-level digital proximity tracing app effectiveness by providing an intuitive approach for calculating key performance indicators.
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Affiliation(s)
- Paola Daniore
- Institute for Implementation Science in Healthcare, University of Zurich, Zurich, Switzerland
| | - Vasileios Nittas
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - André Moser
- Clinical Trials Unit Bern, University of Bern, Bern, Switzerland
| | - Marc Höglinger
- Winterthur Institute of Health Economics, Zurich University of Applied Sciences, Winterthur, Switzerland
| | - Viktor von Wyl
- Institute for Implementation Science in Healthcare, University of Zurich, Zurich, Switzerland.,Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
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Lueks W, Benzler J, Bogdanov D, Kirchner G, Lucas R, Oliveira R, Preneel B, Salathé M, Troncoso C, von Wyl V. Toward a Common Performance and Effectiveness Terminology for Digital Proximity Tracing Applications. Front Digit Health 2021; 3:677929. [PMID: 34713149 PMCID: PMC8521913 DOI: 10.3389/fdgth.2021.677929] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 07/08/2021] [Indexed: 11/27/2022] Open
Abstract
Digital proximity tracing (DPT) for Sars-CoV-2 pandemic mitigation is a complex intervention with the primary goal to notify app users about possible risk exposures to infected persons. DPT not only relies on the technical functioning of the proximity tracing application and its backend server, but also on seamless integration of health system processes such as laboratory testing, communication of results (and their validation), generation of notification codes, manual contact tracing, and management of app-notified users. Policymakers and DPT operators need to know whether their system works as expected in terms of speed or yield (performance) and whether DPT is making an effective contribution to pandemic mitigation (also in comparison to and beyond established mitigation measures, particularly manual contact tracing). Thereby, performance and effectiveness are not to be confused. Not only are there conceptual differences but also diverse data requirements. For example, comparative effectiveness measures may require information generated outside the DPT system, e.g., from manual contact tracing. This article describes differences between performance and effectiveness measures and attempts to develop a terminology and classification system for DPT evaluation. We discuss key aspects for critical assessments of whether the integration of additional data measurements into DPT apps may facilitate understanding of performance and effectiveness of planned and deployed DPT apps. Therefore, the terminology and a classification system may offer some guidance to DPT system operators regarding which measurements to prioritize. DPT developers and operators may also make conscious decisions to integrate measures for epidemic monitoring but should be aware that this introduces a secondary purpose to DPT. Ultimately, the integration of further information (e.g., regarding exact exposure time) into DPT involves a trade-off between data granularity and linkage on the one hand, and privacy on the other. More data may lead to better epidemiological information but may also increase the privacy risks associated with the system, and thus decrease public DPT acceptance. Decision-makers should be aware of the trade-off and take it into account when planning and developing DPT systems or intending to assess the added value of DPT relative to the existing contact tracing systems.
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Affiliation(s)
- Wouter Lueks
- Security and Privacy Engineering Laboratory, School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | | | | | | | - Raquel Lucas
- Medical School and Institute of Public Health (EPIUnit), Universidade Do Porto, Porto, Portugal
| | - Rui Oliveira
- Institute for Systems and Computer Engineering, Technology and Science & University of Minho, Porto, Portugal
| | - Bart Preneel
- Department of Electrical Engineering, Katholieke Universiteit Leuven and IMEC, Leuven, Belgium
| | - Marcel Salathé
- Digital Epidemiology Laboratory, School of Life Sciences, School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne, Global Health Institute, Geneva, Switzerland
| | - Carmela Troncoso
- Security and Privacy Engineering Laboratory, School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Viktor von Wyl
- Digital and Mobile Health Group, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.,Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
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8
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Ballouz T, Menges D, Aschmann HE, Domenghino A, Fehr JS, Puhan MA, von Wyl V. Adherence and Association of Digital Proximity Tracing App Notifications With Earlier Time to Quarantine: Results From the Zurich SARS-CoV-2 Cohort Study. Int J Public Health 2021; 66:1603992. [PMID: 34471402 PMCID: PMC8404355 DOI: 10.3389/ijph.2021.1603992] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Accepted: 07/02/2021] [Indexed: 11/13/2022] Open
Abstract
Objectives: We aimed to evaluate the effectiveness of the SwissCovid digital proximity tracing (DPT) app in notifying exposed individuals and prompting them to quarantine earlier compared to individuals notified only by manual contact tracing (MCT). Methods: A population-based sample of cases and close contacts from the Zurich SARS-CoV-2 Cohort was surveyed regarding SwissCovid app use and SARS-CoV-2 exposure. We descriptively analyzed app adherence and effectiveness, and evaluated its effects on the time between exposure and quarantine among contacts using stratified multivariable time-to-event analyses. Results: We included 393 SARS-CoV-2 infected cases and 261 close contacts. 62% of cases reported using SwissCovid and among those, 88% received and uploaded a notification code. 71% of close contacts were app users, of which 38% received a warning. Non-household contacts notified by SwissCovid started quarantine 1 day earlier and were more likely to quarantine earlier than those not warned by the app (HR 1.53, 95% CI 1.15-2.03). Conclusion: These findings provide evidence that DPT may reach exposed contacts faster than MCT, with earlier quarantine and potential interruption of SARS-CoV-2 transmission chains.
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Affiliation(s)
- Tala Ballouz
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zürich, Switzerland.,Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zürich, Zürich, Switzerland
| | - Dominik Menges
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zürich, Switzerland
| | - Hélène E Aschmann
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zürich, Switzerland
| | - Anja Domenghino
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zürich, Switzerland.,Department of Visceral and Transplantation Surgery, University Hospital Zürich, Zürich, Switzerland
| | - Jan S Fehr
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zürich, Switzerland.,Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zürich, Zürich, Switzerland
| | - Milo A Puhan
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zürich, Switzerland
| | - Viktor von Wyl
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zürich, Switzerland.,Institute for Implementation Science in Health Care, University of Zurich, Zürich, Switzerland
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O'Connell J, Abbas M, Beecham S, Buckley J, Chochlov M, Fitzgerald B, Glynn L, Johnson K, Laffey J, McNicholas B, Nuseibeh B, O'Callaghan M, O'Keeffe I, Razzaq A, Rekanar K, Richardson I, Simpkin A, Storni C, Tsvyatkova D, Walsh J, Welsh T, O'Keeffe D. Best Practice Guidance for Digital Contact Tracing Apps: A Cross-disciplinary Review of the Literature. JMIR Mhealth Uhealth 2021; 9:e27753. [PMID: 34003764 PMCID: PMC8189288 DOI: 10.2196/27753] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 03/17/2021] [Accepted: 04/05/2021] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Digital contact tracing apps have the potential to augment contact tracing systems and disrupt COVID-19 transmission by rapidly identifying secondary cases prior to the onset of infectiousness and linking them into a system of quarantine, testing, and health care worker case management. The international experience of digital contact tracing apps during the COVID-19 pandemic demonstrates how challenging their design and deployment are. OBJECTIVE This study aims to derive and summarize best practice guidance for the design of the ideal digital contact tracing app. METHODS A collaborative cross-disciplinary approach was used to derive best practice guidance for designing the ideal digital contact tracing app. A search of the indexed and gray literature was conducted to identify articles describing or evaluating digital contact tracing apps. MEDLINE was searched using a combination of free-text terms and Medical Subject Headings search terms. Gray literature sources searched were the World Health Organization Institutional Repository for Information Sharing, the European Centre for Disease Prevention and Control publications library, and Google, including the websites of many health protection authorities. Articles that were acceptable for inclusion in this evidence synthesis were peer-reviewed publications, cohort studies, randomized trials, modeling studies, technical reports, white papers, and media reports related to digital contact tracing. RESULTS Ethical, user experience, privacy and data protection, technical, clinical and societal, and evaluation considerations were identified from the literature. The ideal digital contact tracing app should be voluntary and should be equitably available and accessible. User engagement could be enhanced by small financial incentives, enabling users to tailor aspects of the app to their particular needs and integrating digital contact tracing apps into the wider public health information campaign. Adherence to the principles of good data protection and privacy by design is important to convince target populations to download and use digital contact tracing apps. Bluetooth Low Energy is recommended for a digital contact tracing app's contact event detection, but combining it with ultrasound technology may improve a digital contact tracing app's accuracy. A decentralized privacy-preserving protocol should be followed to enable digital contact tracing app users to exchange and record temporary contact numbers during contact events. The ideal digital contact tracing app should define and risk-stratify contact events according to proximity, duration of contact, and the infectiousness of the case at the time of contact. Evaluating digital contact tracing apps requires data to quantify app downloads, use among COVID-19 cases, successful contact alert generation, contact alert receivers, contact alert receivers that adhere to quarantine and testing recommendations, and the number of contact alert receivers who subsequently are tested positive for COVID-19. The outcomes of digital contact tracing apps' evaluations should be openly reported to allow for the wider public to review the evaluation of the app. CONCLUSIONS In conclusion, key considerations and best practice guidance for the design of the ideal digital contact tracing app were derived from the literature.
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Affiliation(s)
- James O'Connell
- Lero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland
| | - Manzar Abbas
- Lero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland
| | - Sarah Beecham
- Lero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland
| | - Jim Buckley
- Lero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland
| | - Muslim Chochlov
- Lero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland
| | - Brian Fitzgerald
- Lero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland
| | - Liam Glynn
- School of Medicine, University of Limerick, Limerick, Ireland
| | - Kevin Johnson
- Department of Nursing and Midwifery, University of Limerick, Limerick, Ireland
| | - John Laffey
- School of Medicine, National University of Ireland Galway, Galway, Ireland
- University Hospital Galway, Saolta, Health Services Executive, Galway, Ireland
| | - Bairbre McNicholas
- School of Medicine, National University of Ireland Galway, Galway, Ireland
- University Hospital Galway, Saolta, Health Services Executive, Galway, Ireland
| | - Bashar Nuseibeh
- Lero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland
- School of Computing and Communications, The Open University, Milton Keynes, United Kingdom
| | | | - Ian O'Keeffe
- Lero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland
| | - Abdul Razzaq
- Lero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland
| | - Kaavya Rekanar
- Lero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland
| | - Ita Richardson
- Lero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland
| | - Andrew Simpkin
- School of Mathematics, Statistics and Applied Mathematics, National University of Ireland Galway, Galway, Ireland
| | - Cristiano Storni
- Lero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland
| | - Damyanka Tsvyatkova
- Lero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland
| | - Jane Walsh
- School of Psychology, National University of Ireland Galway, Galway, Ireland
| | - Thomas Welsh
- Lero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland
| | - Derek O'Keeffe
- Lero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland
- School of Medicine, National University of Ireland Galway, Galway, Ireland
- University Hospital Galway, Saolta, Health Services Executive, Galway, Ireland
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Li A, Parent S, Kasmani A, Guan TH, Moore K. COVID-19 outbreak in a personal service setting in Kingston, Ontario, 2020. CANADA COMMUNICABLE DISEASE REPORT = RELEVE DES MALADIES TRANSMISSIBLES AU CANADA 2021; 47:216-223. [PMID: 34035668 PMCID: PMC8127683 DOI: 10.14745/ccdr.v47i04a06] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
BACKGROUND During the coronavirus disease 2019 (COVID-19) pandemic, Ontario created a three-phase reopening framework for the economy. Outbreaks were expected at each phase. One week after Phase Two of reopening in the provincial public health administration region of Kingston, Frontenac, Lennox and Addington (KFL&A), a positive case was reported after three weeks of zero new COVID-19 cases. The objective of this report is to describe this COVID-19 outbreak, linked to a personal service setting (PSS), and the public health response to contain the outbreak. METHODS The outbreak investigation included all COVID-19 cases in KFL&A between June 20, 2020 and July 3, 2020. Public health inspectors and nurses were rapidly deployed to inspect the PSS. A multimodal approach to high-volume testing involved fixed assessment centres, drive-through testing capacity and targeted testing at the outbreak site. Testing was conducted through a real-time polymerase chain reaction assay at the local Public Health Ontario laboratory. RESULTS Thirty-seven cases were associated with the outbreak: 38% through direct PSS exposure; 32% through household contact; and 30% through social and workplace contact. A superspreading event contributed to 38% of total cases. The majority of cases were in the low to mid-quintiles when analyzed for material deprivation. Testing rates increased four-fold compared to the prior baseline weeks in response to media attention and public health messaging, resulting in a low percent positivity. CONCLUSION The interplay of aggressive accessible testing, quick lab turnaround time, contact tracing within 24 hours of positive laboratory results as per provincial standards, frequent public communication, rapid inspections, mandatory self-isolation and face coverings were measures successful in halting the outbreak. Inspections or self-audits should be required at all PSSs prior to reopening and outbreak management must work with PSSs to reduce the possibility of superspreading events.
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Affiliation(s)
- Anthony Li
- Kingston, Frontenac, Lennox & Addington (KFL&A) Public Health, Kingston, ON
- School of Medicine, Queen’s University, Kingston, ON
| | - Stéphanie Parent
- Kingston, Frontenac, Lennox & Addington (KFL&A) Public Health, Kingston, ON
- School of Medicine, Queen’s University, Kingston, ON
| | - Azim Kasmani
- Kingston, Frontenac, Lennox & Addington (KFL&A) Public Health, Kingston, ON
- Public Health and Preventive Medicine Residency Program, Queen’s University, Kingston, ON
| | - T Hugh Guan
- Kingston, Frontenac, Lennox & Addington (KFL&A) Public Health, Kingston, ON
- Public Health and Preventive Medicine Residency Program, Queen’s University, Kingston, ON
| | - Kieran Moore
- Kingston, Frontenac, Lennox & Addington (KFL&A) Public Health, Kingston, ON
- Public Health and Preventive Medicine Residency Program, Queen’s University, Kingston, ON
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11
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El-Haddadeh R, Fadlalla A, Hindi NM. Is There a Place for Responsible Artificial Intelligence in Pandemics? A Tale of Two Countries. INFORMATION SYSTEMS FRONTIERS : A JOURNAL OF RESEARCH AND INNOVATION 2021; 25:1-17. [PMID: 33972823 PMCID: PMC8099995 DOI: 10.1007/s10796-021-10140-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/26/2021] [Indexed: 05/17/2023]
Abstract
This research examines the considerations of responsible Artificial Intelligence in the deployment of AI-based COVID-19 digital proximity tracking and tracing applications in two countries; the State of Qatar and the United Kingdom. Based on the alignment level analysis with the Good AI Society's framework and sentiment analysis of official tweets, the diagnostic analysis resulted in contrastive findings for the two applications. While the application EHTERAZ (Arabic for precaution) in Qatar has fallen short in adhering to the responsible AI requirements, it has contributed significantly to controlling the pandemic. On the other hand, the UK's NHS COVID-19 application has exhibited limited success in fighting the virus despite relatively abiding by these requirements. This underlines the need for obtaining a practical and contextual view for a comprehensive discourse on responsible AI in healthcare. Thereby offering necessary guidance for striking a balance between responsible AI requirements and managing pressures towards fighting the pandemic.
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Affiliation(s)
- Ramzi El-Haddadeh
- College of Business and Economics, Qatar University, P.O. Box 2713, Doha, Qatar
| | - Adam Fadlalla
- College of Business and Economics, Qatar University, P.O. Box 2713, Doha, Qatar
| | - Nitham M. Hindi
- College of Business and Economics, Qatar University, P.O. Box 2713, Doha, Qatar
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12
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Pandl KD, Thiebes S, Schmidt-Kraepelin M, Sunyaev A. How detection ranges and usage stops impact digital contact tracing effectiveness for COVID-19. Sci Rep 2021; 11:9414. [PMID: 33941793 PMCID: PMC8093197 DOI: 10.1038/s41598-021-88768-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 04/14/2021] [Indexed: 01/12/2023] Open
Abstract
To combat the COVID-19 pandemic, many countries around the globe have adopted digital contact tracing apps. Various technologies exist to trace contacts that are potentially prone to different types of tracing errors. Here, we study the impact of different proximity detection ranges on the effectiveness and efficiency of digital contact tracing apps. Furthermore, we study a usage stop effect induced by a false positive quarantine. Our results reveal that policy makers should adjust digital contact tracing apps to the behavioral characteristics of a society. Based on this, the proximity detection range should at least cover the range of a disease spread, and be much wider in certain cases. The widely used Bluetooth Low Energy protocol may not necessarily be the most effective technology for contact tracing.
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Affiliation(s)
- Konstantin D Pandl
- Institute of Applied Informatics and Formal Description Methods, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Scott Thiebes
- Institute of Applied Informatics and Formal Description Methods, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Manuel Schmidt-Kraepelin
- Institute of Applied Informatics and Formal Description Methods, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Ali Sunyaev
- Institute of Applied Informatics and Formal Description Methods, Karlsruhe Institute of Technology, Karlsruhe, Germany.
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13
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Menges D, Aschmann HE, Moser A, Althaus CL, von Wyl V. A Data-Driven Simulation of the Exposure Notification Cascade for Digital Contact Tracing of SARS-CoV-2 in Zurich, Switzerland. JAMA Netw Open 2021; 4:e218184. [PMID: 33929521 PMCID: PMC8087953 DOI: 10.1001/jamanetworkopen.2021.8184] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 03/10/2021] [Indexed: 12/13/2022] Open
Abstract
Importance Digital contact tracing (DCT) apps have been released in several countries to help interrupt SARS-CoV-2 transmission chains. However, the effect of DCT on pandemic mitigation remains to be demonstrated. Objective To estimate key populations and performance indicators along the exposure notification cascade of the SwissCovid DCT app in a clearly defined regional and temporal context. Design, Setting, and Participants This comparative effectiveness study was based on a simulation informed by measured data from issued quarantine recommendations and positive SARS-CoV-2 test results after DCT exposure notifications in the canton of Zurich. A stochastic model was developed to re-create the DCT notification cascade for Zurich. Population sizes at each cascade step were estimated using triangulation based on publicly available administrative and observational research data for the study duration from September 1 to October 31, 2020. The resultant estimates were checked for internal consistency and consistency with upstream or downstream estimates in the cascade. Stochastic sampling from data-informed parameter distributions was performed to explore the robustness of results. Subsequently, key performance indicators were evaluated to assess the potential contribution of DCT compared with manual contact tracing. Main Outcomes and Measures Receiving a voluntary quarantine recommendation and/or a positive SARS-CoV-2 test result after exposure notification. Results In September 2020, 537 app users received a positive SARS-CoV-2 test result in Zurich, 324 of whom received and entered an upload authorization code. This code triggered an app notification for an estimated 1374 (95% simulation interval [SI], 932-2586) proximity contacts and led to 722 information hotline calls, with an estimated 170 callers (95% SI, 154-186) receiving a quarantine recommendation. An estimated 939 (95% SI, 720-1127) notified app users underwent testing for SARS-CoV-2, of whom 30 (95% SI, 23-36) had positive results after an app notification. Key indicator evaluations revealed that the DCT app triggered quarantine recommendations for the equivalent of 5% of all exposed contacts placed in quarantine by manual contact tracing. For every 10.9 (95% SI, 7.6-15.6) upload authorization codes entered in the app, 1 contact had positive test results for SARS-CoV-2 after app notification. Longitudinal indicator analyses demonstrated bottlenecks in the notification cascade, because capacity limits were reached owing to an increased incidence of SARS-CoV-2 infection in October 2020. Conclusions and Relevance In this simulation study of the notification cascade of the SwissCovid DCT app, receipt of exposure notifications was associated with quarantine recommendations and identification of SARS-CoV-2-positive cases. These findings in notified proximity contacts reflect important intermediary steps toward transmission prevention.
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Affiliation(s)
- Dominik Menges
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Hélène E. Aschmann
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - André Moser
- CTU Bern, University of Bern, Bern, Switzerland
| | - Christian L. Althaus
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Viktor von Wyl
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
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14
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Weiß JP, Esdar M, Hübner U. Analyzing the Essential Attributes of Nationally Issued COVID-19 Contact Tracing Apps: Open-Source Intelligence Approach and Content Analysis. JMIR Mhealth Uhealth 2021; 9:e27232. [PMID: 33724920 PMCID: PMC8006898 DOI: 10.2196/27232] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 03/03/2021] [Accepted: 03/12/2021] [Indexed: 12/26/2022] Open
Abstract
Background Contact tracing apps are potentially useful tools for supporting national COVID-19 containment strategies. Various national apps with different technical design features have been commissioned and issued by governments worldwide. Objective Our goal was to develop and propose an item set that was suitable for describing and monitoring nationally issued COVID-19 contact tracing apps. This item set could provide a framework for describing the key technical features of such apps and monitoring their use based on widely available information. Methods We used an open-source intelligence approach (OSINT) to access a multitude of publicly available sources and collect data and information regarding the development and use of contact tracing apps in different countries over several months (from June 2020 to January 2021). The collected documents were then iteratively analyzed via content analysis methods. During this process, an initial set of subject areas were refined into categories for evaluation (ie, coherent topics), which were then examined for individual features. These features were paraphrased as items in the form of questions and applied to information materials from a sample of countries (ie, Brazil, China, Finland, France, Germany, Italy, Singapore, South Korea, Spain, and the United Kingdom [England and Wales]). This sample was purposefully selected; our intention was to include the apps of different countries from around the world and to propose a valid item set that can be relatively easily applied by using an OSINT approach. Results Our OSINT approach and subsequent analysis of the collected documents resulted in the definition of the following five main categories and associated subcategories: (1) background information (open-source code, public information, and collaborators); (2) purpose and workflow (secondary data use and warning process design); (3) technical information (protocol, tracing technology, exposure notification system, and interoperability); (4) privacy protection (the entity of trust and anonymity); and (5) availability and use (release date and the number of downloads). Based on this structure, a set of items that constituted the evaluation framework were specified. The application of these items to the 10 selected countries revealed differences, especially with regard to the centralization of the entity of trust and the overall transparency of the apps’ technical makeup. Conclusions We provide a set of criteria for monitoring and evaluating COVID-19 tracing apps that can be easily applied to publicly issued information. The application of these criteria might help governments to identify design features that promote the successful, widespread adoption of COVID-19 tracing apps among target populations and across national boundaries.
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Affiliation(s)
- Jan-Patrick Weiß
- Health Informatics Research Group, Faculty of Business Management and Social Sciences, University of Applied Sciences Osnabrueck, Osnabrück, Germany
| | - Moritz Esdar
- Health Informatics Research Group, Faculty of Business Management and Social Sciences, University of Applied Sciences Osnabrueck, Osnabrück, Germany
| | - Ursula Hübner
- Health Informatics Research Group, Faculty of Business Management and Social Sciences, University of Applied Sciences Osnabrueck, Osnabrück, Germany
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15
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von Wyl V. Challenges for Nontechnical Implementation of Digital Proximity Tracing During the COVID-19 Pandemic: Media Analysis of the SwissCovid App. JMIR Mhealth Uhealth 2021; 9:e25345. [PMID: 33606658 PMCID: PMC7919847 DOI: 10.2196/25345] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 11/27/2020] [Accepted: 02/18/2021] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Several countries have released digital proximity tracing (DPT) apps to complement manual contact tracing for combatting the SARS-CoV-2 pandemic. DPT aims to notify app users about proximity exposures to persons infected with SARS-CoV-2 so that they can self-quarantine. The success of DPT apps depends on user acceptance and the embedding of DPT into the pandemic mitigation strategy. OBJECTIVE By searching for media articles published during the first 3 months after DPT launch, the implementation of DPT in Switzerland was evaluated to inform similar undertakings in other countries. The second aim of the study was to create a link between reported DPT implementation challenges and normalization process theory for planning and optimizing complex digital health interventions, which can provide useful guidance for decision-making in DPT design and implementation. METHODS A Swiss media database was searched for articles on the Swiss DPT app (SwissCovid) published in German or French between July 4 and October 3, 2020. In a structured process, topics were extracted and clustered manually from articles that were deemed pertinent. Extracted topics were mapped to four NPT constructs, which reflected the flow of intervention development from planning, stakeholder onboarding, and execution to critical appraisal. Coherence constructs describe sense-making by stakeholders, cognitive participation constructs reflect participants' efforts to create engagement with the intervention, collective actions refer to intervention execution and joint stakeholder efforts to make the intervention work, and reflexive monitoring refers to collective risk-benefit appraisals to create improvements. RESULTS Out of 94 articles deemed pertinent and selected for closer inspection, 38 provided unique information on implementation challenges. Five challenge areas were identified: communication challenges, challenges for DPT to interface with other processes, fear of resource competition with established pandemic mitigation measures, unclear DPT effectiveness, and obstacles to greater user coverage and compliance. Specifically, several articles mentioned unclear DPT benefits to affect commitment and to raise fears among different health system actors regarding resource competition. Moreover, media reports indicated process interface challenges such as delays or unclear responsibilities in the notification cascade, as well as misunderstandings and unmet communication needs from health system actors. Finally, reports suggested misaligned incentives, not only for app usage by the public but also for process engagement by other actors in the app notification cascade. NPT provided a well-fitting framework to contextualize the different DPT implementation challenges and to highlight improvement strategies, namely a better alignment of stakeholder incentives, or stakeholder-specific communication to address their concerns about DPT. CONCLUSIONS Early experiences from one of the first adopters of DPT indicate that nontechnical implementation challenges may affect the effectiveness of DPT. The NPT analysis provides a novel perspective on DPT implementation and stresses the need for stakeholder inclusion in development and operationalization.
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Affiliation(s)
- Viktor von Wyl
- Epidemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
- Institute for Implementation Science in Health Care, University of Zurich, Zürich, Switzerland
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16
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Amann J, Sleigh J, Vayena E. Digital contact-tracing during the Covid-19 pandemic: An analysis of newspaper coverage in Germany, Austria, and Switzerland. PLoS One 2021; 16:e0246524. [PMID: 33534839 PMCID: PMC7857553 DOI: 10.1371/journal.pone.0246524] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 01/20/2021] [Indexed: 12/20/2022] Open
Abstract
Governments around the globe have started to develop and deploy digital contact tracing apps to gain control over the spread of the novel coronavirus (Covid-19). The appropriateness and usefulness of these technologies as a containment measure have since sparked political and academic discussions globally. The present paper contributes to this debate through an exploration of how the national daily newspapers in Germany, Austria, and Switzerland reported on the development and adoption of digital contact-tracing apps during early and after stages of the lockdown. These countries were among the first in Europe to develop apps and were critical voices in the debate of decentralized vs. centralized data processing. We conducted thematic analysis on news coverage published between January and May 2020 in high-circulation national daily newspapers from Germany, Austria, and Switzerland. A total of 148 articles from nine newspaper companies were included in the final analysis. From our analysis emerged six core themes of the development and adoption of digital contact tracing apps: 1) data governance; 2) role of IT giants; 3) scientific rigor; 4) voluntariness; 5) functional efficacy; 6) role of the app. These results shed light on the different facets of discussion regarding digital contact tracing as portrayed in German-speaking media. This study complements emerging survey data on public perceptions of digital contact tracing apps by providing a better understanding of the ideas circulating in the media ecosystem.
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Affiliation(s)
- Julia Amann
- Health Ethics and Policy Lab, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland
| | - Joanna Sleigh
- Health Ethics and Policy Lab, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland
| | - Effy Vayena
- Health Ethics and Policy Lab, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland
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17
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Munzert S, Selb P, Gohdes A, Stoetzer LF, Lowe W. Tracking and promoting the usage of a COVID-19 contact tracing app. Nat Hum Behav 2021; 5:247-255. [PMID: 33479505 DOI: 10.1038/s41562-020-01044-x] [Citation(s) in RCA: 76] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Accepted: 12/22/2020] [Indexed: 11/09/2022]
Abstract
Digital contact tracing apps have been introduced globally as an instrument to contain the COVID-19 pandemic. Yet, privacy by design impedes both the evaluation of these tools and the deployment of evidence-based interventions to stimulate uptake. We combine an online panel survey with mobile tracking data to measure the actual usage of Germany's official contact tracing app and reveal higher uptake rates among respondents with an increased risk of severe illness, but lower rates among those with a heightened risk of exposure to COVID-19. Using a randomized intervention, we show that informative and motivational video messages have very limited effect on uptake. However, findings from a second intervention suggest that even small monetary incentives can strongly increase uptake and help make digital contact tracing a more effective tool.
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Affiliation(s)
| | - Peter Selb
- Department of Politics and Public Administration, University of Konstanz, Konstanz, Germany
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18
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von Wyl V, Höglinger M, Sieber C, Kaufmann M, Moser A, Serra-Burriel M, Ballouz T, Menges D, Frei A, Puhan MA. Drivers of Acceptance of COVID-19 Proximity Tracing Apps in Switzerland: Panel Survey Analysis. JMIR Public Health Surveill 2021; 7:e25701. [PMID: 33326411 PMCID: PMC7790736 DOI: 10.2196/25701] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 12/03/2020] [Accepted: 12/03/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Digital proximity tracing apps have been released to mitigate the transmission of SARS-CoV-2, the virus known to cause COVID-19. However, it remains unclear how the acceptance and uptake of these apps can be improved. OBJECTIVE This study aimed to investigate the coverage of the SwissCovid app and the reasons for its nonuse in Switzerland during a period of increasing incidence of COVID-19 cases. METHODS We collected data between September 28 and October 8, 2020, via a nationwide online panel survey (COVID-19 Social Monitor, N=1511). We examined sociodemographic and behavioral factors associated with app use by using multivariable logistic regression, whereas reasons for app nonuse were analyzed descriptively. RESULTS Overall, 46.5% (703/1511) of the survey participants reported they used the SwissCovid app, which was an increase from 43.9% (662/1508) reported in the previous study wave conducted in July 2020. A higher monthly household income (ie, income >CHF 10,000 or >US $11,000 vs income ≤CHF 6000 or CONCLUSIONS Eliminating technical hurdles and communicating the benefits of digital proximity tracing apps are crucial to promote further uptake and adherence of such apps and, ultimately, enhance their effectiveness to aid pandemic mitigation strategies.
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Affiliation(s)
- Viktor von Wyl
- Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
- Institute for Implementation Science in Health Care, University of Zurich, Zürich, Switzerland
| | - Marc Höglinger
- Winterthur Institute of Health Economics, Zurich University of Applied Sciences, Winterthur, Switzerland
| | - Chloé Sieber
- Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
| | - Marco Kaufmann
- Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
| | - André Moser
- Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
| | - Miquel Serra-Burriel
- Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
| | - Tala Ballouz
- Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
| | - Dominik Menges
- Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
| | - Anja Frei
- Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
| | - Milo Alan Puhan
- Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
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Buitrago-Garcia D, Egli-Gany D, Counotte MJ, Hossmann S, Imeri H, Ipekci AM, Salanti G, Low N. Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: A living systematic review and meta-analysis. PLoS Med 2020; 17:e1003346. [PMID: 32960881 DOI: 10.1101/2020.04.25.20079103] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 08/18/2020] [Indexed: 05/28/2023] Open
Abstract
BACKGROUND There is disagreement about the level of asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We conducted a living systematic review and meta-analysis to address three questions: (1) Amongst people who become infected with SARS-CoV-2, what proportion does not experience symptoms at all during their infection? (2) Amongst people with SARS-CoV-2 infection who are asymptomatic when diagnosed, what proportion will develop symptoms later? (3) What proportion of SARS-CoV-2 transmission is accounted for by people who are either asymptomatic throughout infection or presymptomatic? METHODS AND FINDINGS We searched PubMed, Embase, bioRxiv, and medRxiv using a database of SARS-CoV-2 literature that is updated daily, on 25 March 2020, 20 April 2020, and 10 June 2020. Studies of people with SARS-CoV-2 diagnosed by reverse transcriptase PCR (RT-PCR) that documented follow-up and symptom status at the beginning and end of follow-up or modelling studies were included. One reviewer extracted data and a second verified the extraction, with disagreement resolved by discussion or a third reviewer. Risk of bias in empirical studies was assessed with an adapted checklist for case series, and the relevance and credibility of modelling studies were assessed using a published checklist. We included a total of 94 studies. The overall estimate of the proportion of people who become infected with SARS-CoV-2 and remain asymptomatic throughout infection was 20% (95% confidence interval [CI] 17-25) with a prediction interval of 3%-67% in 79 studies that addressed this review question. There was some evidence that biases in the selection of participants influence the estimate. In seven studies of defined populations screened for SARS-CoV-2 and then followed, 31% (95% CI 26%-37%, prediction interval 24%-38%) remained asymptomatic. The proportion of people that is presymptomatic could not be summarised, owing to heterogeneity. The secondary attack rate was lower in contacts of people with asymptomatic infection than those with symptomatic infection (relative risk 0.35, 95% CI 0.10-1.27). Modelling studies fit to data found a higher proportion of all SARS-CoV-2 infections resulting from transmission from presymptomatic individuals than from asymptomatic individuals. Limitations of the review include that most included studies were not designed to estimate the proportion of asymptomatic SARS-CoV-2 infections and were at risk of selection biases; we did not consider the possible impact of false negative RT-PCR results, which would underestimate the proportion of asymptomatic infections; and the database does not include all sources. CONCLUSIONS The findings of this living systematic review suggest that most people who become infected with SARS-CoV-2 will not remain asymptomatic throughout the course of the infection. The contribution of presymptomatic and asymptomatic infections to overall SARS-CoV-2 transmission means that combination prevention measures, with enhanced hand hygiene, masks, testing tracing, and isolation strategies and social distancing, will continue to be needed.
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Affiliation(s)
- Diana Buitrago-Garcia
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Graduate School of Health Sciences, University of Bern, Bern, Switzerland
| | - Dianne Egli-Gany
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Michel J Counotte
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Stefanie Hossmann
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Hira Imeri
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Aziz Mert Ipekci
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Georgia Salanti
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Nicola Low
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
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Buitrago-Garcia D, Egli-Gany D, Counotte MJ, Hossmann S, Imeri H, Ipekci AM, Salanti G, Low N. Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: A living systematic review and meta-analysis. PLoS Med 2020; 17:e1003346. [PMID: 32960881 PMCID: PMC7508369 DOI: 10.1371/journal.pmed.1003346] [Citation(s) in RCA: 614] [Impact Index Per Article: 153.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 08/18/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND There is disagreement about the level of asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We conducted a living systematic review and meta-analysis to address three questions: (1) Amongst people who become infected with SARS-CoV-2, what proportion does not experience symptoms at all during their infection? (2) Amongst people with SARS-CoV-2 infection who are asymptomatic when diagnosed, what proportion will develop symptoms later? (3) What proportion of SARS-CoV-2 transmission is accounted for by people who are either asymptomatic throughout infection or presymptomatic? METHODS AND FINDINGS We searched PubMed, Embase, bioRxiv, and medRxiv using a database of SARS-CoV-2 literature that is updated daily, on 25 March 2020, 20 April 2020, and 10 June 2020. Studies of people with SARS-CoV-2 diagnosed by reverse transcriptase PCR (RT-PCR) that documented follow-up and symptom status at the beginning and end of follow-up or modelling studies were included. One reviewer extracted data and a second verified the extraction, with disagreement resolved by discussion or a third reviewer. Risk of bias in empirical studies was assessed with an adapted checklist for case series, and the relevance and credibility of modelling studies were assessed using a published checklist. We included a total of 94 studies. The overall estimate of the proportion of people who become infected with SARS-CoV-2 and remain asymptomatic throughout infection was 20% (95% confidence interval [CI] 17-25) with a prediction interval of 3%-67% in 79 studies that addressed this review question. There was some evidence that biases in the selection of participants influence the estimate. In seven studies of defined populations screened for SARS-CoV-2 and then followed, 31% (95% CI 26%-37%, prediction interval 24%-38%) remained asymptomatic. The proportion of people that is presymptomatic could not be summarised, owing to heterogeneity. The secondary attack rate was lower in contacts of people with asymptomatic infection than those with symptomatic infection (relative risk 0.35, 95% CI 0.10-1.27). Modelling studies fit to data found a higher proportion of all SARS-CoV-2 infections resulting from transmission from presymptomatic individuals than from asymptomatic individuals. Limitations of the review include that most included studies were not designed to estimate the proportion of asymptomatic SARS-CoV-2 infections and were at risk of selection biases; we did not consider the possible impact of false negative RT-PCR results, which would underestimate the proportion of asymptomatic infections; and the database does not include all sources. CONCLUSIONS The findings of this living systematic review suggest that most people who become infected with SARS-CoV-2 will not remain asymptomatic throughout the course of the infection. The contribution of presymptomatic and asymptomatic infections to overall SARS-CoV-2 transmission means that combination prevention measures, with enhanced hand hygiene, masks, testing tracing, and isolation strategies and social distancing, will continue to be needed.
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Affiliation(s)
- Diana Buitrago-Garcia
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Graduate School of Health Sciences, University of Bern, Bern, Switzerland
| | - Dianne Egli-Gany
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Michel J. Counotte
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Stefanie Hossmann
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Hira Imeri
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Aziz Mert Ipekci
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Georgia Salanti
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Nicola Low
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
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