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Galmiche S, Charmet T, Rakover A, Chény O, Omar F, David C, Mailles A, Carrat F, Fontanet A. Risk of SARS-CoV-2 infection in professional settings, shops, shared transport, and leisure activities in France, 2020-2022. BMC Public Health 2024; 24:2411. [PMID: 39232732 PMCID: PMC11376041 DOI: 10.1186/s12889-024-19651-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Accepted: 07/30/2024] [Indexed: 09/06/2024] Open
Abstract
PURPOSE The aim of the study was to identify settings associated with SARS-CoV-2 transmission throughout the COVID-19 pandemic in France. METHODS Cases with recent SARS-CoV-2 infection were matched with controls (4:1 ratio) on age, sex, region, population size, and calendar week. Odds ratios for SARS-CoV-2 infection were estimated for nine periods in models adjusting for socio-demographic characteristics, health status, COVID-19 vaccine, and past infection. RESULTS Between October 27, 2020 and October 2, 2022, 175,688 cases were matched with 43,922 controls. An increased risk of infection was documented throughout the study for open-space offices compared to offices without open space (OR range across the nine periods: 1.12 to 1.57) and long-distance trains (1.25 to 1.88), and during most of the study for convenience stores (OR range in the periods with increased risk: 1.15 to 1.44), take-away delivery (1.07 to 1.28), car-pooling with relatives (1.09 to 1.68), taxis (1.08 to 1.89), airplanes (1.20 to 1.78), concerts (1.31 to 2.09) and night-clubs (1.45 to 2.95). No increase in transmission was associated with short-distance shared transport, car-pooling booked over platforms, markets, supermarkets and malls, hairdressers, museums, movie theatres, outdoor sports, and swimming pools. The increased risk of infection in bars and restaurants was no longer present in restaurants after reopening in June 2021. It persisted in bars only among those aged under 40 years. CONCLUSION Closed settings in which people are less likely to wear masks were most affected by SARS-CoV-2 transmission and should be the focus of air quality improvement. CLINICALTRIALS GOV (03/09/2022): NCT04607941.
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Affiliation(s)
- Simon Galmiche
- Emerging Diseases Epidemiology Unit, Institut Pasteur, Université Paris Cité, 25 rue du Docteur Roux, Paris, 75015, France.
- Sorbonne Université, Ecole Doctorale Pierre Louis de Santé Publique, Paris, 75006, France.
| | - Tiffany Charmet
- Emerging Diseases Epidemiology Unit, Institut Pasteur, Université Paris Cité, 25 rue du Docteur Roux, Paris, 75015, France
| | - Arthur Rakover
- Emerging Diseases Epidemiology Unit, Institut Pasteur, Université Paris Cité, 25 rue du Docteur Roux, Paris, 75015, France
| | - Olivia Chény
- Clinical Research Coordination Office, Institut Pasteur, Université Paris Cité, Paris, 75015, France
| | - Faïza Omar
- Department of Public Affairs - Public Statistics, Institut Ipsos, Paris, 75013, France
| | - Christophe David
- Department of Public Affairs - Public Statistics, Institut Ipsos, Paris, 75013, France
| | | | - Fabrice Carrat
- Sorbonne Université, Inserm, IPLESP, Hôpital Saint-Antoine, AP-HP, Paris, 75012, France
| | - Arnaud Fontanet
- Emerging Diseases Epidemiology Unit, Institut Pasteur, Université Paris Cité, 25 rue du Docteur Roux, Paris, 75015, France
- Unité PACRI, Conservatoire National des Arts et Métiers, Paris, 75003, France
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Chan CP, Lee SS, Kwan TH, Wong SYS, Yeoh EK, Wong NS. Population Behavior Changes Underlying Phasic Shifts of SARS-CoV-2 Exposure Settings Across 3 Omicron Epidemic Waves in Hong Kong: Prospective Cohort Study. JMIR Public Health Surveill 2024; 10:e51498. [PMID: 38896447 PMCID: PMC11222765 DOI: 10.2196/51498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 10/26/2023] [Accepted: 05/05/2024] [Indexed: 06/21/2024] Open
Abstract
BACKGROUND Exposure risk was shown to have affected individual susceptibility and the epidemic spread of COVID-19. The dynamics of risk by and across exposure settings alongside the variations following the implementation of social distancing interventions are understudied. OBJECTIVE This study aims to examine the population's trajectory of exposure risk in different settings and its association with SARS-CoV-2 infection across 3 consecutive Omicron epidemic waves in Hong Kong. METHODS From March to June 2022, invitation letters were posted to 41,132 randomly selected residential addresses for the recruitment of households into a prospective population cohort. Through web-based monthly surveys coupled with email reminders, a representative from each enrolled household self-reported incidents of SARS-CoV-2 infections, COVID-19 vaccination uptake, their activity pattern in the workplace, and daily and social settings in the preceding month. As a proxy of their exposure risk, the reported activity trend in each setting was differentiated into trajectories based on latent class growth analyses. The associations of different trajectories of SARS-CoV-2 infection overall and by Omicron wave (wave 1: February-April; wave 2: May-September; wave 3: October-December) in 2022 were evaluated by using Cox proportional hazards models and Kaplan-Meier analysis. RESULTS In total, 33,501 monthly responses in the observation period of February-December 2022 were collected from 5321 individuals, with 41.7% (2221/5321) being male and a median age of 46 (IQR 34-57) years. Against an expanding COVID-19 vaccination coverage from 81.9% to 95.9% for 2 doses and 20% to 77.7% for 3 doses, the cumulative incidence of SARS-CoV-2 infection escalated from <0.2% to 25.3%, 32.4%, and 43.8% by the end of waves 1, 2, and 3, respectively. Throughout February-December 2022, 52.2% (647/1240) of participants had worked regularly on-site, 28.7% (356/1240) worked remotely, and 19.1% (237/1240) showed an assorted pattern. For daily and social settings, 4 and 5 trajectories were identified, respectively, with 11.5% (142/1240) and 14.6% (181/1240) of the participants gauged to have a high exposure risk. Compared to remote working, working regularly on-site (adjusted hazard ratio [aHR] 1.47, 95% CI 1.19-1.80) and living in a larger household (aHR 1.12, 95% CI 1.06-1.18) were associated with a higher risk of SARS-CoV-2 infection in wave 1. Those from the highest daily exposure risk trajectory (aHR 1.46, 95% CI 1.07-2.00) and the second highest social exposure risk trajectory (aHR 1.52, 95% CI 1.18-1.97) were also at an increased risk of infection in waves 2 and 3, respectively, relative to the lowest risk trajectory. CONCLUSIONS In an infection-naive population, SARS-CoV-2 transmission was predominantly initiated at the workplace, accelerated in the household, and perpetuated in the daily and social environments, as stringent restrictions were scaled down. These patterns highlight the phasic shift of exposure settings, which is important for informing the effective calibration of targeted social distancing measures as an alternative to lockdown.
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Affiliation(s)
- Chin Pok Chan
- JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Shui Shan Lee
- Stanley Ho Centre for Emerging Infectious Diseases, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
- S.H. Ho Research Centre for Infectious Diseases, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Tsz Ho Kwan
- JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
- Stanley Ho Centre for Emerging Infectious Diseases, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
- S.H. Ho Research Centre for Infectious Diseases, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Samuel Yeung Shan Wong
- JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Eng-Kiong Yeoh
- JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
- Centre for Health Systems and Policy Research, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Ngai Sze Wong
- JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
- Stanley Ho Centre for Emerging Infectious Diseases, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
- S.H. Ho Research Centre for Infectious Diseases, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
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Hoskins S, Beale S, Nguyen VG, Byrne T, Yavlinsky A, Kovar J, Fong EWL, Geismar C, Navaratnam AMD, van Tongeren M, Johnson AM, Aldridge RW, Hayward A. The changing contributory role to infections of work, public transport, shopping, hospitality and leisure activities throughout the SARS-CoV-2 pandemic in England and Wales. NIHR OPEN RESEARCH 2023; 3:58. [PMID: 39286314 PMCID: PMC11403290 DOI: 10.3310/nihropenres.13443.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 10/26/2023] [Indexed: 09/19/2024]
Abstract
Background Understanding how non-household activities contributed to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections under different levels of national health restrictions is vital. Methods Among adult Virus Watch participants in England and Wales, we used multivariable logistic regressions and adjusted-weighted population attributable fractions (aPAF) assessing the contribution of work, public transport, shopping, and hospitality and leisure activities to infections. Results Under restrictions, among 17,256 participants (502 infections), work [adjusted odds ratio (aOR) 2.01 (1.65-2.44), (aPAF) 30% (22-38%)] and transport [(aOR 1.15 (0.94-1.40), aPAF 5% (-3-12%)], were risk factors for SARS-CoV-2 but shopping, hospitality and leisure were not. Following the lifting of restrictions, among 11,413 participants (493 infections), work [(aOR 1.35 (1.11-1.64), aPAF 17% (6-26%)] and transport [(aOR 1.27 (1.04-1.57), aPAF 12% (2-22%)] contributed most, with indoor hospitality [(aOR 1.21 (0.98-1.48), aPAF 7% (-1-15%)] and leisure [(aOR 1.24 (1.02-1.51), aPAF 10% (1-18%)] increasing. During the Omicron variant, with individuals more socially engaged, among 11,964 participants (2335 infections), work [(aOR 1.28 (1.16-1.41), aPAF (11% (7-15%)] and transport [(aOR 1.16 (1.04-1.28), aPAF 6% (2-9%)] remained important but indoor hospitality [(aOR 1.43 (1.26-1.62), aPAF 20% (13-26%)] and leisure [(aOR 1.35 (1.22-1.48), aPAF 10% (7-14%)] dominated. Conclusions Work and public transport were important to transmissions throughout the pandemic with hospitality and leisure's contribution increasing as restrictions were lifted, highlighting the importance of restricting leisure and hospitality alongside advising working from home, when facing a highly infectious and virulent respiratory infection.
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Affiliation(s)
- Susan Hoskins
- Institute of Health Informatics, University College London, London, England, NW1 2DA, UK
| | - Sarah Beale
- Institute of Health Informatics, University College London, London, England, NW1 2DA, UK
- Institute of Epidemiology and Health Care, University College London, London, WC1E 6BT, UK
| | - Vincent G Nguyen
- Institute of Health Informatics, University College London, London, England, NW1 2DA, UK
- Institute of Epidemiology and Health Care, University College London, London, WC1E 6BT, UK
| | - Thomas Byrne
- Institute of Health Informatics, University College London, London, England, NW1 2DA, UK
| | - Alexei Yavlinsky
- Institute of Health Informatics, University College London, London, England, NW1 2DA, UK
| | - Jana Kovar
- Institute of Epidemiology and Health Care, University College London, London, WC1E 6BT, UK
| | - Erica Wing Lam Fong
- Institute of Health Informatics, University College London, London, England, NW1 2DA, UK
| | - Cyril Geismar
- Institute of Health Informatics, University College London, London, England, NW1 2DA, UK
- Department of Infectious Disease Epidemiology, Imperial College London, London, W2 1NY, UK
| | - Annalan M D Navaratnam
- Institute of Health Informatics, University College London, London, England, NW1 2DA, UK
- Institute of Epidemiology and Health Care, University College London, London, WC1E 6BT, UK
| | - Martie van Tongeren
- Centre for Occupational and Environmental Health, The University of Manchester, Manchester, England, UK
| | - Anne M Johnson
- Institute for Global Health, University College London, London, England, WC1E 6BT, UK
| | - Robert W Aldridge
- Institute of Health Informatics, University College London, London, England, NW1 2DA, UK
| | - Andrew Hayward
- Institute of Epidemiology and Health Care, University College London, London, WC1E 6BT, UK
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Alvarez-Mon MA, Pereira-Sanchez V, Hooker ER, Sanchez F, Alvarez-Mon M, Teo AR. Content and User Engagement of Health-Related Behavior Tweets Posted by Mass Media Outlets From Spain and the United States Early in the COVID-19 Pandemic: Observational Infodemiology Study. JMIR INFODEMIOLOGY 2023; 3:e43685. [PMID: 37347948 PMCID: PMC10445660 DOI: 10.2196/43685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 02/17/2023] [Accepted: 05/30/2023] [Indexed: 06/24/2023]
Abstract
BACKGROUND During the early pandemic, there was substantial variation in public and government responses to COVID-19 in Europe and the United States. Mass media are a vital source of health information and news, frequently disseminating this information through social media, and may influence public and policy responses to the pandemic. OBJECTIVE This study aims to describe the extent to which major media outlets in the United States and Spain tweeted about health-related behaviors (HRBs) relevant to COVID-19, compare the tweeting patterns between media outlets of both countries, and determine user engagement in response to these tweets. METHODS We investigated tweets posted by 30 major media outlets (n=17, 57% from Spain and n=13, 43% from the United States) between December 1, 2019 and May 31, 2020, which included keywords related to HRBs relevant to COVID-19. We classified tweets into 6 categories: mask-wearing, physical distancing, handwashing, quarantine or confinement, disinfecting objects, or multiple HRBs (any combination of the prior HRB categories). Additionally, we assessed the likes and retweets generated by each tweet. Poisson regression analyses compared the average predicted number of likes and retweets between the different HRB categories and between countries. RESULTS Of 50,415 tweets initially collected, 8552 contained content associated with an HRB relevant to COVID-19. Of these, 600 were randomly chosen for training, and 2351 tweets were randomly selected for manual content analysis. Of the 2351 COVID-19-related tweets included in the content analysis, 62.91% (1479/2351) mentioned at least one HRB. The proportion of COVID-19 tweets mentioning at least one HRB differed significantly between countries (P=.006). Quarantine or confinement was mentioned in nearly half of all the HRB tweets in both countries. In contrast, the least frequently mentioned HRBs were disinfecting objects in Spain 6.9% (56/809) and handwashing in the United States 9.1% (61/670). For tweets from the United States mentioning at least one HRB, disinfecting objects had the highest median likes and retweets, whereas mask-wearing- and handwashing-related tweets achieved the highest median number of likes in Spain. Tweets from Spain that mentioned social distancing or disinfecting objects had a significantly lower predicted count of likes compared with tweets mentioning a different HRB (P=.02 and P=.01, respectively). Tweets from the United States that mentioned quarantine or confinement or disinfecting objects had a significantly lower predicted number of likes compared with tweets mentioning a different HRB (P<.001), whereas mask- and handwashing-related tweets had a significantly greater predicted number of likes (P=.04 and P=.02, respectively). CONCLUSIONS The type of HRB content and engagement with media outlet tweets varied between Spain and the United States early in the pandemic. However, content related to quarantine or confinement and engagement with handwashing was relatively high in both countries.
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Affiliation(s)
- Miguel Angel Alvarez-Mon
- Department of Medicine and Medical Specialties, Faculty of Medicine and Health Sciences, University of Alcala, Alcala de Henares, Spain
- Department of Psychiatry and Mental Health, University Hospital Infanta Leonor, Madrid, Spain
- Ramón y Cajal Institute of Sanitary Research (IRYCIS), Madrid, Spain
| | - Victor Pereira-Sanchez
- Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine, New York, NY, United States
| | - Elizabeth R Hooker
- VA Portland Health Care System, Health Services Research & Development Center to Improve Veteran Involvement in Care, Portland, OR, United States
- OHSU-PSU School of Public Health, Oregon Health and Science University, Portland, OR, United States
| | - Facundo Sanchez
- Lincoln Medical and Mental Health Center, New York, NY, United States
- Devers Eye Institute, Portland, OR, United States
| | - Melchor Alvarez-Mon
- Department of Medicine and Medical Specialties, Faculty of Medicine and Health Sciences, University of Alcala, Alcala de Henares, Spain
- Ramón y Cajal Institute of Sanitary Research (IRYCIS), Madrid, Spain
| | - Alan R Teo
- VA Portland Health Care System, Health Services Research & Development Center to Improve Veteran Involvement in Care, Portland, OR, United States
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, United States
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Theodore DA, Branche AR, Zhang L, Graciaa DS, Choudhary M, Hatlen TJ, Osman R, Babu TM, Robinson ST, Gilbert PB, Follmann D, Janes H, Kublin JG, Baden LR, Goepfert P, Gray GE, Grinsztejn B, Kotloff KL, Gay CL, Leav B, Miller J, Hirsch I, Sadoff J, Dunkle LM, Neuzil KM, Corey L, Falsey AR, El Sahly HM, Sobieszczyk ME, Huang Y. Clinical and Demographic Factors Associated With COVID-19, Severe COVID-19, and SARS-CoV-2 Infection in Adults: A Secondary Cross-Protocol Analysis of 4 Randomized Clinical Trials. JAMA Netw Open 2023; 6:e2323349. [PMID: 37440227 PMCID: PMC10346130 DOI: 10.1001/jamanetworkopen.2023.23349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 05/15/2023] [Indexed: 07/14/2023] Open
Abstract
Importance Current data identifying COVID-19 risk factors lack standardized outcomes and insufficiently control for confounders. Objective To identify risk factors associated with COVID-19, severe COVID-19, and SARS-CoV-2 infection. Design, Setting, and Participants This secondary cross-protocol analysis included 4 multicenter, international, randomized, blinded, placebo-controlled, COVID-19 vaccine efficacy trials with harmonized protocols established by the COVID-19 Prevention Network. Individual-level data from participants randomized to receive placebo within each trial were combined and analyzed. Enrollment began July 2020 and the last data cutoff was in July 2021. Participants included adults in stable health, at risk for SARS-CoV-2, and assigned to the placebo group within each vaccine trial. Data were analyzed from April 2022 to February 2023. Exposures Comorbid conditions, demographic factors, and SARS-CoV-2 exposure risk at the time of enrollment. Main Outcomes and Measures Coprimary outcomes were COVID-19 and severe COVID-19. Multivariate Cox proportional regression models estimated adjusted hazard ratios (aHRs) and 95% CIs for baseline covariates, accounting for trial, region, and calendar time. Secondary outcomes included severe COVID-19 among people with COVID-19, subclinical SARS-CoV-2 infection, and SARS-CoV-2 infection. Results A total of 57 692 participants (median [range] age, 51 [18-95] years; 11 720 participants [20.3%] aged ≥65 years; 31 058 participants [53.8%] assigned male at birth) were included. The analysis population included 3270 American Indian or Alaska Native participants (5.7%), 7849 Black or African American participants (13.6%), 17 678 Hispanic or Latino participants (30.6%), and 40 745 White participants (70.6%). Annualized incidence was 13.9% (95% CI, 13.3%-14.4%) for COVID-19 and 2.0% (95% CI, 1.8%-2.2%) for severe COVID-19. Factors associated with increased rates of COVID-19 included workplace exposure (high vs low: aHR, 1.35 [95% CI, 1.16-1.58]; medium vs low: aHR, 1.41 [95% CI, 1.21-1.65]; P < .001) and living condition risk (very high vs low risk: aHR, 1.41 [95% CI, 1.21-1.66]; medium vs low risk: aHR, 1.19 [95% CI, 1.08-1.32]; P < .001). Factors associated with decreased rates of COVID-19 included previous SARS-CoV-2 infection (aHR, 0.13 [95% CI, 0.09-0.19]; P < .001), age 65 years or older (aHR vs age <65 years, 0.57 [95% CI, 0.50-0.64]; P < .001) and Black or African American race (aHR vs White race, 0.78 [95% CI, 0.67-0.91]; P = .002). Factors associated with increased rates of severe COVID-19 included race (American Indian or Alaska Native vs White: aHR, 2.61 [95% CI, 1.85-3.69]; multiracial vs White: aHR, 2.19 [95% CI, 1.50-3.20]; P < .001), diabetes (aHR, 1.54 [95% CI, 1.14-2.08]; P = .005) and at least 2 comorbidities (aHR vs none, 1.39 [95% CI, 1.09-1.76]; P = .008). In analyses restricted to participants who contracted COVID-19, increased severe COVID-19 rates were associated with age 65 years or older (aHR vs <65 years, 1.75 [95% CI, 1.32-2.31]; P < .001), race (American Indian or Alaska Native vs White: aHR, 1.98 [95% CI, 1.38-2.83]; Black or African American vs White: aHR, 1.49 [95% CI, 1.03-2.14]; multiracial: aHR, 1.81 [95% CI, 1.21-2.69]; overall P = .001), body mass index (aHR per 1-unit increase, 1.03 [95% CI, 1.01-1.04]; P = .001), and diabetes (aHR, 1.85 [95% CI, 1.37-2.49]; P < .001). Previous SARS-CoV-2 infection was associated with decreased severe COVID-19 rates (aHR, 0.04 [95% CI, 0.01-0.14]; P < .001). Conclusions and Relevance In this secondary cross-protocol analysis of 4 randomized clinical trials, exposure and demographic factors had the strongest associations with outcomes; results could inform mitigation strategies for SARS-CoV-2 and viruses with comparable epidemiological characteristics.
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Affiliation(s)
- Deborah A. Theodore
- Division of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, New York, New York
| | - Angela R. Branche
- Department of Medicine, Infectious Disease Division, University of Rochester, Rochester, New York
| | - Lily Zhang
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Daniel S. Graciaa
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia
| | - Madhu Choudhary
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | | | - Raadhiya Osman
- Perinatal HIV Research Unit, Chris Hani Baragwanath Academic Hospital, Soweto, South Africa
| | - Tara M. Babu
- Department of Medicine, Division of Allergy & Infectious Diseases, University of Washington, Seattle
| | - Samuel T. Robinson
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Peter B. Gilbert
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington
- Department of Biostatistics, University of Washington, Seattle
| | - Dean Follmann
- Biostatistics Research Branch, National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, Maryland
| | - Holly Janes
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington
- Department of Biostatistics, University of Washington, Seattle
| | - James G. Kublin
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington
| | | | - Paul Goepfert
- Division of Infectious Diseases, Department of Medicine, University of Alabama at Birmingham, Birmingham
| | - Glenda E. Gray
- Perinatal HIV Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- South African Medical Research Council, Cape Town, South Africa
| | - Beatriz Grinsztejn
- Evandro Chagas National Institute of Infectious Diseases-Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
| | - Karen L. Kotloff
- Division of Infectious Disease and Tropical Pediatrics, Department of Pediatrics, University of Maryland School of Medicine, Baltimore
- Department of Medicine, Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore
| | - Cynthia L. Gay
- Department of Medicine, Division of Infectious Diseases, UNC HIV Cure Center, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
| | | | | | - Ian Hirsch
- AstraZeneca BioPharmaceuticals, Cambridge, United Kingdom
| | - Jerald Sadoff
- Janssen Vaccines and Prevention, Leiden, the Netherlands
| | | | - Kathleen M. Neuzil
- Department of Medicine, Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore
| | - Lawrence Corey
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle
| | - Ann R. Falsey
- Department of Medicine, Infectious Disease Division, University of Rochester, Rochester, New York
| | - Hana M. El Sahly
- Infectious Diseases Section, Department of Medicine, Baylor College of Medicine, Houston, Texas
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas
| | - Magdalena E. Sobieszczyk
- Division of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, New York, New York
| | - Yunda Huang
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington
- Department of Global Health, University of Washington, Seattle
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Argyropoulos CD, Leckler J, Salmanton-García J, Constantinou M, Alexandrou A, Themistocleous S, Noula E, Shiamakkides G, Nearchou A, Stewart FA, Albus K, Koniordou M, Kopsidas I, Spivak O, Hellemans M, Hendrickx G, Davis RJ, Azzini AM, Simon PV, Carcas AJ, Askling HH, Vene S, Prellezo JB, Álvarez-Barco E, Macken AJ, Di Marzo R, Luís C, Olesen OF, Frias Iniesta JA, Barta I, Tóth K, Akova M, Bonten MMJ, Cohen-Kandli M, Cox RJ, Součková L, Husa P, Jancoriene L, Launay O, Lundgren J, Mallon P, Mendonça MA, Marques L, Naucler P, Ochando J, Tacconelli E, van Damme P, Zaoutis T, Hofstraat S, Bruijning-Verhagen P, Zeitlinger M, Cornely OA, Pana ZD. Enhancing public health communication of vaccine trials: The pan-European VACCELERATE Toolkit. JMIR Public Health Surveill 2023; 9:e44491. [PMID: 36878478 PMCID: PMC10131613 DOI: 10.2196/44491] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 02/09/2023] [Accepted: 02/28/2023] [Indexed: 03/08/2023] Open
Abstract
BACKGROUND The pan-European VACCELERATE network aims to implement the first transnational harmonised and sustainable vaccine trial Volunteer Registry, serving as single entry-point for volunteers willing to participate in large scale vaccine clinical studies across the European region. The present work exhibits a set of harmonised vaccine trial educational and promotional tools for the general public, designed and disseminated by the pan-European VACCELERATE network. OBJECTIVE The main objectives of the present study are the design and creation of a standard toolkit to increase positive attitudes, and access to trustful information for better access and increased recruitment to vaccine trials for the public community. More specifically, the produced tools are focused on inclusiveness, equity, and they are targeting different population groups, including underserved ones, as potential volunteers for the VACCELERATE Volunteer Registry (elderly, migrants, children and adolescents). The promotion/education material is aligned with the main objectives of the Volunteer Registry, to increase public literacy and awareness regarding vaccine clinical research/trials and trial participation, such as informed consent and legal issues, side effects and frequently asked questions on vaccine trial design. METHODS The tools' development has followed the aims and principles of the VACCELERATE project, focusing on trial inclusiveness and equity and they are adjusted to the local country requirements to improve public health communication. The selection of the produced tools has been based on the cognitive theory, inclusiveness and equity of different aged and under-represented groups, and standardised material from several official trustful sources (e.g. COVAX, ECDC, EUPATI, GAVI and WHO). In addition, team of specialists from different fields (infectious diseases, vaccine research, medicine, education) edited and reviewed the subtitles and scripts for the educational videos, extended brochures, interactive cards and puzzles. Graph designers also selected the colour palette, audio settings and dubbing for the video story-tales and implementation of QR codes. RESULTS This study presents the first set of harmonised promotional and educational materials/tools (i.e. educational cards, educational and promotional videos, extended brochures, flyers, posters, and puzzles) for vaccine clinical research (e.g. COVID-19). The developed tools inform the public about possible benefits and disadvantages of trial participation, but also build the confidence of participants about the safety and efficacy for COVID-19 vaccines and healthcare system. The present material has been translated into several languages and meant to be freely and easily accessible to facilitate dissemination among the participating countries of the VACCELERATE network, as well as among the European and global scientific, industrial, and public community, in general. CONCLUSIONS The produced material could also be useful for filling knowledge gaps of healthcare personnel and providing the appropriate future patient education for vaccine trials, as well as to tackle vaccine hesitancy and parents' concerns for potential participation of children in vaccine trials.
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Affiliation(s)
| | - Janina Leckler
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, DE.,University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD) and Excellence Center for Medical Mycology (ECMM), Cologne, DE
| | - Jon Salmanton-García
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, DE.,University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD) and Excellence Center for Medical Mycology (ECMM), Cologne, DE
| | | | | | | | - Evgenia Noula
- School of Medicine, European University Cyprus, 6 Diogenis Str., Nicosia, CY
| | - George Shiamakkides
- School of Medicine, European University Cyprus, 6 Diogenis Str., Nicosia, CY
| | - Andria Nearchou
- School of Medicine, European University Cyprus, 6 Diogenis Str., Nicosia, CY
| | - Fiona A Stewart
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, DE.,University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD) and Excellence Center for Medical Mycology (ECMM), Cologne, DE
| | - Kerstin Albus
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, DE.,University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD) and Excellence Center for Medical Mycology (ECMM), Cologne, DE
| | - Markela Koniordou
- Collaborative Center for Clinical Epidemiology and Outcomes Research (CLEO), Athens, GR
| | - Ioannis Kopsidas
- Collaborative Center for Clinical Epidemiology and Outcomes Research (CLEO), Athens, GR
| | | | - Margot Hellemans
- Universiteit Antwerpen, Faculty of Medicine and Health Science, VAXINFECTIO, Centre of Evaluation of Vaccination, Antwerp, BE
| | - Greet Hendrickx
- Universiteit Antwerpen, Faculty of Medicine and Health Science, VAXINFECTIO, Centre of Evaluation of Vaccination, Antwerp, BE
| | - Ruth Joanna Davis
- University of Verona, Infectious Diseases, Department of Diagnostic and Public Health, Verona, IT
| | - Anna Maria Azzini
- University of Verona, Infectious Diseases, Department of Diagnostic and Public Health, Verona, IT
| | - Paula Valle Simon
- Hospital La Paz Institute for Health Research (IdiPAZ), Madrid, ES.,Servicio Madrileño de Salud, Madrid, ES
| | - Antonio Javier Carcas
- Hospital La Paz Institute for Health Research (IdiPAZ), Madrid, ES.,Servicio Madrileño de Salud, Madrid, ES
| | - Helena Hervius Askling
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, SE.,Division of Infectious Diseases, Department of Medicine, Solna, Karolinska Institutet, Stockholm, SE
| | - Sirkka Vene
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, SE.,Division of Infectious Diseases, Department of Medicine, Solna, Karolinska Institutet, Stockholm, SE
| | | | - Elena Álvarez-Barco
- Centre for Experimental Pathogen Host Research, University College Dublin School of Medicine, National University of Ireland, Dublin, IE
| | - Alan J Macken
- Centre for Experimental Pathogen Host Research, University College Dublin School of Medicine, National University of Ireland, Dublin, IE
| | | | | | - Ole F Olesen
- European Vaccine Initiative (EVI), Heidelberg, DE
| | - Jesus A Frias Iniesta
- Hospital La Paz Institute for Health Research (IdiPAZ), Madrid, ES.,Servicio Madrileño de Salud, Madrid, ES
| | - Imre Barta
- National Koranyi Institute for Pulmonology, Budapest, HU
| | - Krisztina Tóth
- National Koranyi Institute for Pulmonology, Budapest, HU
| | | | - Marc M J Bonten
- Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, Utrecht, NL.,Department of Medical Microbiology, University Medical Centre Utrecht, Utrecht, NL
| | | | | | - Lenka Součková
- Masaryk University, Brno, Czech Republic, University Hospital Brno, Brno, CZ.,University Hospital Brno, Brno, CZ.,CZECRIN, Brno, CZ
| | - Petr Husa
- Masaryk University, Brno, Czech Republic, University Hospital Brno, Brno, CZ.,University Hospital Brno, Brno, CZ.,CZECRIN, Brno, CZ
| | - Ligita Jancoriene
- Institute of Clinical Medicine, Medical Faculty, Vilnius University, Vilnius, LT.,Vilnius University Hospital Santaros klinikos, Medical Faculty, Vilnius University, Vilnius, LT
| | - Odile Launay
- Institut National de la Santé et de la Recherche Médicale-ANRS Maladies Infectieuses Émergentes, Paris, FR.,Université Paris Cité, Assistance Publique Hopitaux de Paris, Paris, FR
| | - Jens Lundgren
- Centre of Excellence for Health, Immunity and Infections (CHIP), Rigshospitalet, University of Copenhagen, Copenhagen, DK
| | - Patrick Mallon
- Centre for Experimental Pathogen Host Research, University College Dublin School of Medicine, National University of Ireland, Dublin, IE
| | | | | | - Pontus Naucler
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, SE.,Division of Infectious Diseases, Department of Medicine, Solna, Karolinska Institutet, Stockholm, SE
| | - Jordi Ochando
- Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, ES
| | - Evelina Tacconelli
- University of Verona, Infectious Diseases, Department of Diagnostic and Public Health, Verona, IT
| | - Pierre van Damme
- Universiteit Antwerpen, Faculty of Medicine and Health Science, VAXINFECTIO, Centre of Evaluation of Vaccination, Antwerp, BE
| | - Theoklis Zaoutis
- Collaborative Center for Clinical Epidemiology and Outcomes Research (CLEO), Athens, GR
| | - Sanne Hofstraat
- University Medical Centre Utrecht, Utrecht University, Utrecht, NL
| | | | | | - Oliver A Cornely
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, DE.,University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD) and Excellence Center for Medical Mycology (ECMM), Cologne, DE.,University of Cologne, Faculty of Medicine and University Hospital Cologne, Clinical Trials Centre Cologne (ZKS Köln), Cologne, DE.,University of Cologne, Faculty of Medicine and University Hospital Cologne, Center for Molecular Medicine Cologne (CMMC), Cologne, DE.,German Centre for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, DE
| | - Zoi Dorothea Pana
- School of Medicine, European University Cyprus, 6 Diogenis Str., Nicosia, CY
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7
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Silva PGD, Nascimento MSJ, Sousa SIV, Mesquita JR. SARS-CoV-2 in outdoor air following the third wave lockdown release, Portugal, 2021. J Med Microbiol 2023; 72. [PMID: 36763082 DOI: 10.1099/jmm.0.001659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023] Open
Abstract
Aiming to contribute with more data on the presence of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) in outdoor environments, we performed air sampling in outdoor terraces from restaurants in three major cities of Portugal in April 2021, following the third wave lockdown release in the country. Air samples (n=19) were collected in 19 restaurant terraces during lunch time. Each air sample was collected using a Coriolis Compact air sampler, followed by RNA extraction and real-time quantitative PCR for the detection of viral RNA. Viral viability was also assessed through RNAse pre-treatment of samples. Only one of the 19 air samples was positive for SARS-CoV-2 RNA, with 7337 gene copies m-3 for the genomic region N2, with no viable virus in this sample. The low number of positive samples found in this study is not surprising, as sampling took place in outdoor settings where air circulation is optimal, and aerosols are rapidly dispersed by the air currents. These results are consistent with previous reports stating that transmission of SARS-CoV-2 in outdoor spaces is low, although current evidence shows an association of exposures in settings where drinking and eating is possible on-site with an increased risk in acquiring SARS-CoV-2 infection. Moreover, the minimal infectious dose for SARS-CoV-2 still needs to be determined so that the real risk of infection in different environments can be accurately established.
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Affiliation(s)
- Priscilla Gomes da Silva
- ICBAS - School of Medicine and Biomedical Sciences, Porto University, Porto, Portugal.,Epidemiology Research Unit (EPIUnit), Instituto de Saúde Pública da Universidade do Porto, Porto, Portugal.,Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), Porto, Portugal.,LEPABE - Laboratory for Process Engineering, Environment, Biotechnology and Energy, Faculty of Engineering, University of Porto, Porto, Portugal.,ALiCE - Associate Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Porto, Portugal
| | | | - Sofia I V Sousa
- LEPABE - Laboratory for Process Engineering, Environment, Biotechnology and Energy, Faculty of Engineering, University of Porto, Porto, Portugal.,ALiCE - Associate Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Porto, Portugal
| | - João R Mesquita
- ICBAS - School of Medicine and Biomedical Sciences, Porto University, Porto, Portugal.,Epidemiology Research Unit (EPIUnit), Instituto de Saúde Pública da Universidade do Porto, Porto, Portugal.,Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), Porto, Portugal
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8
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Hoskins S, Beale S, Nguyen V, Fragaszy E, Navaratnam AM, Smith C, French C, Kovar J, Byrne T, Fong WLE, Geismar C, Patel P, Yavlinksy A, Johnson AM, Aldridge RW, Hayward A. Settings for non-household transmission of SARS-CoV-2 during the second lockdown in England and Wales - analysis of the Virus Watch household community cohort study. Wellcome Open Res 2022; 7:199. [PMID: 36874571 PMCID: PMC9975411 DOI: 10.12688/wellcomeopenres.17981.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/22/2022] [Indexed: 11/20/2022] Open
Abstract
Background: "Lockdowns" to control serious respiratory virus pandemics were widely used during the coronavirus disease 2019 (COVID-19) pandemic. However, there is limited information to understand the settings in which most transmission occurs during lockdowns, to support refinement of similar policies for future pandemics. Methods: Among Virus Watch household cohort participants we identified those infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outside the household. Using survey activity data, we undertook multivariable logistic regressions assessing the contribution of activities on non-household infection risk. We calculated adjusted population attributable fractions (APAF) to estimate which activity accounted for the greatest proportion of non-household infections during the pandemic's second wave. Results: Among 10,858 adults, 18% of cases were likely due to household transmission. Among 10,475 participants (household-acquired cases excluded), including 874 non-household-acquired infections, infection was associated with: leaving home for work or education (AOR 1.20 (1.02 - 1.42), APAF 6.9%); public transport (more than once per week AOR 1.82 (1.49 - 2.23), public transport APAF 12.42%); and shopping (more than once per week AOR 1.69 (1.29 - 2.21), shopping APAF 34.56%). Other non-household activities were rare and not significantly associated with infection. Conclusions: During lockdown, going to work and using public or shared transport independently increased infection risk, however only a minority did these activities. Most participants visited shops, accounting for one-third of non-household transmission. Transmission in restricted hospitality and leisure settings was minimal suggesting these restrictions were effective. If future respiratory infection pandemics emerge these findings highlight the value of working from home, using forms of transport that minimise exposure to others, minimising exposure to shops and restricting non-essential activities.
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Affiliation(s)
- Susan Hoskins
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
| | - Sarah Beale
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
- Institute of Epidemiology and Healthcare, University College London, London, Greater London, WC1E 7HB, UK
| | - Vincent Nguyen
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
- Institute of Epidemiology and Healthcare, University College London, London, Greater London, WC1E 7HB, UK
| | - Ellen Fragaszy
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, Greater London, WC1E 7HT, UK
| | - Annalan M.D. Navaratnam
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
- Institute of Epidemiology and Healthcare, University College London, London, Greater London, WC1E 7HB, UK
| | - Colette Smith
- Institute of Epidemiology and Healthcare, University College London, London, Greater London, WC1E 7HB, UK
| | - Clare French
- NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Uinversity of Bristol, Bristol, BS8 2BN, UK
| | - Jana Kovar
- Institute of Epidemiology and Healthcare, University College London, London, Greater London, WC1E 7HB, UK
| | - Thomas Byrne
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
| | - Wing Lam Erica Fong
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
| | - Cyril Geismar
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
- Institute of Epidemiology and Healthcare, University College London, London, Greater London, WC1E 7HB, UK
| | - Parth Patel
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
| | - Alexei Yavlinksy
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
| | - Anne M. Johnson
- Institute for Global Health, University College London, London, WC1N 1EH, UK
| | - Robert W. Aldridge
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
| | - Andrew Hayward
- Institute of Epidemiology and Healthcare, University College London, London, Greater London, WC1E 7HB, UK
| | - Virus Watch Collaborative
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, Greater London, WC1E 6BT, UK
- Institute of Epidemiology and Healthcare, University College London, London, Greater London, WC1E 7HB, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, Greater London, WC1E 7HT, UK
- NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Uinversity of Bristol, Bristol, BS8 2BN, UK
- Institute for Global Health, University College London, London, WC1N 1EH, UK
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9
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Suñer C, Coma E, Ouchi D, Hermosilla E, Baro B, Rodríguez-Arias MÀ, Puig J, Clotet B, Medina M, Mitjà O. Association between two mass-gathering outdoor events and incidence of SARS-CoV-2 infections during the fifth wave of COVID-19 in north-east Spain: A population-based control-matched analysis. THE LANCET REGIONAL HEALTH. EUROPE 2022; 15:100337. [PMID: 35237763 PMCID: PMC8883024 DOI: 10.1016/j.lanepe.2022.100337] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Background Many countries have resumed mass-gathering events like music festivals, despite the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spreading. In this study, we aimed to assess the effect of two mass-gathering outdoor events, held during a peak of SARS-CoV-2 transmission, on COVID-19 incidence. Methods This was a retrospective, population-based control-matched analysis. The study population included attendees to two outdoor music festivals held in Catalonia (North-East Spain). The primary objective was to compare the incidence of COVID-19 within the 3-to-10 days following the event between attendees and a population-based control group. Findings The analysis included 18,275 and 27,347 attendees to the first and second festivals, respectively, and their corresponding controls. The post-festival 7-day cumulative COVID-19 incidence among attendees and controls was 4.14% (95% CI 3.86-4.44) vs. 1.69% (1.51-1.88) for the first festival (RR 2.46; 2.16-2.80), and 2.42% (2.35-2.61) and 1.10% (0.99-1.2) for the second festival (RR 2.19; 1.92-2.51). COVID-19 incidence among immunized individuals was also two-fold higher in attendees than in controls. Previous COVID-19 infection, vaccination, and adequate mask-wearing were significantly associated with a lower risk of COVID-19 infection after the events. Interpretation Despite the proven effectiveness of preventive measures such as Ag-RDT screening, mask-wearing and vaccination, caution should be taken when holding these events during a period of high community SARS-CoV-2 transmission. Funding Crowdfunding campaign YoMeCorono (https://www.yomecorono.com/) and the Generalitat de Catalunya.
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