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Fong WLE, Nguyen VG, Burns R, Boukari Y, Beale S, Braithwaite I, Byrne TE, Geismar C, Fragaszy E, Hoskins S, Kovar J, Navaratnam AMD, Oskrochi Y, Patel P, Tweed S, Yavlinsky A, Hayward AC, Aldridge RW. The incidence of COVID-19-related hospitalisation in migrants in the UK: Findings from the Virus Watch prospective community cohort study. J Migr Health 2024; 9:100218. [PMID: 38559897 PMCID: PMC10978526 DOI: 10.1016/j.jmh.2024.100218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 08/11/2023] [Accepted: 02/26/2024] [Indexed: 04/04/2024] Open
Abstract
Background Migrants in the United Kingdom (UK) may be at higher risk of SARS-CoV-2 exposure; however, little is known about their risk of COVID-19-related hospitalisation during waves 1-3 of the pandemic. Methods We analysed secondary care data linked to Virus Watch study data for adults and estimated COVID-19-related hospitalisation incidence rates by migration status. To estimate the total effect of migration status on COVID-19 hospitalisation rates, we ran mixed-effect Poisson regression for wave 1 (01/03/2020-31/08/2020; wildtype), and mixed-effect negative binomial regressions for waves 2 (01/09/2020-31/05/2021; Alpha) and 3 (01/06/2020-31/11/2021; Delta). Results of all models were then meta-analysed. Results Of 30,276 adults in the analyses, 26,492 (87.5 %) were UK-born and 3,784 (12.5 %) were migrants. COVID-19-related hospitalisation incidence rates for UK-born and migrant individuals across waves 1-3 were 2.7 [95 % CI 2.2-3.2], and 4.6 [3.1-6.7] per 1,000 person-years, respectively. Pooled incidence rate ratios across waves suggested increased rate of COVID-19-related hospitalisation in migrants compared to UK-born individuals in unadjusted 1.68 [1.08-2.60] and adjusted analyses 1.35 [0.71-2.60]. Conclusion Our findings suggest migration populations in the UK have excess risk of COVID-19-related hospitalisations and underscore the need for more equitable interventions particularly aimed at COVID-19 vaccination uptake among migrants.
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Affiliation(s)
- Wing Lam Erica Fong
- Institute of Health Informatics, University College London, London NW1 2DA, UK
| | - Vincent G Nguyen
- Institute of Health Informatics, University College London, London NW1 2DA, UK
- Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK
- Department of Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK
| | - Rachel Burns
- Institute of Health Informatics, University College London, London NW1 2DA, UK
| | - Yamina Boukari
- Institute of Health Informatics, University College London, London NW1 2DA, UK
| | - Sarah Beale
- Institute of Health Informatics, University College London, London NW1 2DA, UK
- Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK
| | - Isobel Braithwaite
- Institute of Health Informatics, University College London, London NW1 2DA, UK
| | - Thomas E Byrne
- Institute of Health Informatics, University College London, London NW1 2DA, UK
| | - Cyril Geismar
- Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK
- Department of Infectious Disease Epidemiology, MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London W2 1PG, UK
| | - Ellen Fragaszy
- Institute of Health Informatics, University College London, London NW1 2DA, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK
| | - Susan Hoskins
- Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK
| | - Jana Kovar
- Institute of Health Informatics, University College London, London NW1 2DA, UK
| | - Annalan MD Navaratnam
- Institute of Health Informatics, University College London, London NW1 2DA, UK
- Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK
| | - Youssof Oskrochi
- Institute of Health Informatics, University College London, London NW1 2DA, UK
| | - Parth Patel
- Institute of Health Informatics, University College London, London NW1 2DA, UK
| | - Sam Tweed
- Institute of Health Informatics, University College London, London NW1 2DA, UK
| | - Alexei Yavlinsky
- Institute of Health Informatics, University College London, London NW1 2DA, UK
| | - Andrew C Hayward
- Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK
| | - Robert W Aldridge
- Institute of Health Informatics, University College London, London NW1 2DA, UK
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Navaratnam AMD, O'Callaghan C, Beale S, Nguyen V, Aryee A, Braithwaite I, Byrne TE, Fong WLE, Fragaszy E, Geismar C, Hoskins S, Kovar J, Patel P, Shrotri M, Weber S, Yavlinsky A, Aldridge RW, Hayward AC. Eyeglasses and risk of COVID-19 transmission-analysis of the Virus Watch Community Cohort study. Int J Infect Dis 2024; 139:28-33. [PMID: 38008351 DOI: 10.1016/j.ijid.2023.10.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 10/20/2023] [Accepted: 10/27/2023] [Indexed: 11/28/2023] Open
Abstract
OBJECTIVES The importance of SARS-CoV-2 transmission via the eyes is unknown, with previous studies mainly focusing on protective eyewear in healthcare settings. This study aimed to test the hypothesis that wearing eyeglasses is associated with a lower risk of COVID-19. METHODS Participants from the Virus Watch prospective community cohort study responded to a questionnaire on the use of eyeglasses and contact lenses. Infection was confirmed through data linkage, self-reported positive results, and, for a subgroup, monthly capillary antibody testing. Multivariable logistic regression models, controlling for age, sex, income, and occupation, were used to identify the odds of infection depending on frequency and purpose of eyeglasses or contact lenses use. RESULTS A total of 19,166 participants responded to the questionnaire, with 13,681 (71.3%, CI 70.7-72.0) reporting they wore eyeglasses. Multivariable logistic regression model showed a 15% lower odds of infection for those who reported using eyeglasses always for general use (odds ratio [OR] 0.85, 95% 0.77-0.95, P = 0.002) compared to those who never wore eyeglasses. The protective effect was reduced for those who said wearing eyeglasses interfered with mask-wearing and was absent for contact lens wearers. CONCLUSIONS People who wear eyeglasses have a moderate reduction in risk of COVID-19 infection, highlighting that eye protection may make a valuable contribution to the reduction of transmission in community and healthcare settings.
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Affiliation(s)
| | - Christopher O'Callaghan
- Infection, Immunity & Inflammation Department, Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Sarah Beale
- Institute of Health Informatics, University College London, London, UK; Institute of Epidemiology and Health Care, University College London, London, UK
| | - Vincent Nguyen
- Institute of Health Informatics, University College London, London, UK
| | - Anna Aryee
- Institute of Health Informatics, University College London, London, UK
| | | | - Thomas E Byrne
- Institute of Health Informatics, University College London, London, UK
| | | | - Ellen Fragaszy
- Institute of Health Informatics, University College London, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Cyril Geismar
- Institute of Health Informatics, University College London, London, UK
| | - Susan Hoskins
- Institute of Health Informatics, University College London, London, UK
| | - Jana Kovar
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Parth Patel
- Institute of Health Informatics, University College London, London, UK
| | - Madhumita Shrotri
- Institute of Health Informatics, University College London, London, UK
| | - Sophie Weber
- Institute of Health Informatics, University College London, London, UK
| | - Alexei Yavlinsky
- Institute of Health Informatics, University College London, London, UK
| | - Robert W Aldridge
- Institute of Health Informatics, University College London, London, UK
| | - Andrew C Hayward
- Institute of Epidemiology and Health Care, University College London, London, UK
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3
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Patel P, Beale S, Nguyen V, Braithwaite I, Byrne TE, Erica Fong WL, Fragaszy E, Geismar C, Hoskins S, Navaratnam AMD, Shrotri M, Kovar J, Aryee A, Hayward AC, Aldridge RW. Inequalities in access to paid sick leave among workers in England and Wales. Int J Health Plann Manage 2023; 38:1864-1876. [PMID: 37549127 PMCID: PMC10946983 DOI: 10.1002/hpm.3697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 07/20/2023] [Indexed: 08/09/2023] Open
Abstract
BACKGROUND It is poorly understood which workers lack access to sick pay in England and Wales. This evidence gap has been of particular interest in the context of the Covid-19 pandemic given the relationship between presenteeism and infectious disease transmission. METHOD This cross-sectional analysis (n = 8874) was nested within a large community cohort study based across England and Wales (Virus Watch). An online survey in February 2021 asked participants in work if they had access to paid sick leave. We used logistic regression to examine sociodemographic factors associated with lacking access to sick pay. RESULTS Only 66% (n = 5864) of participants reported access to sick pay. South Asian workers (adjusted odds ratio [OR] 1.40, 95% confidence interval [CI] 1.06-1.83) and those from Other minority ethnic backgrounds (OR 2.93, 95% CI 1.54-5.59) were more likely to lack access to sick pay compared to White British workers. Older workers (OR range 1.72 [1.53-1.93]-5.26 [4.42-6.26]), workers in low-income households (OR 2.53, 95% CI 2.15-2.98) and those in transport, trade, and service occupations (OR range 2.03 [1.58-2.61]-5.29 [3.67-7.72]) were also more likely to lack access to sick pay compared respectively to workers aged 25-44, those in high income households and managerial occupations. DISCUSSION Unwarranted age and ethnic inequalities in sick pay access are suggestive of labour market discrimination. Occupational differences are also cause for concern. Policymakers should consider expanding access to sick pay to mitigate transmission of Covid-19 and other endemic respiratory infections in the community, and in the context of pandemic preparation.
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Affiliation(s)
- Parth Patel
- Institute of Health InformaticsUniversity College LondonLondonUK
| | - Sarah Beale
- Institute of Health InformaticsUniversity College LondonLondonUK
- Institute of Epidemiology and Health CareUniversity College LondonLondonUK
| | - Vincent Nguyen
- Institute of Health InformaticsUniversity College LondonLondonUK
| | | | - Thomas E. Byrne
- Institute of Health InformaticsUniversity College LondonLondonUK
| | | | - Ellen Fragaszy
- Institute of Health InformaticsUniversity College LondonLondonUK
- Department of Infectious Disease EpidemiologyLondon School of Hygiene and Tropical MedicineLondonUK
| | - Cyril Geismar
- Institute of Health InformaticsUniversity College LondonLondonUK
| | - Susan Hoskins
- Institute of Epidemiology and Health CareUniversity College LondonLondonUK
| | | | | | - Jana Kovar
- Institute of Epidemiology and Health CareUniversity College LondonLondonUK
| | - Anna Aryee
- Institute of Health InformaticsUniversity College LondonLondonUK
| | - Andrew C. Hayward
- Institute of Epidemiology and Health CareUniversity College LondonLondonUK
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Byrne T, Kovar J, Beale S, Braithwaite I, Fragaszy E, Fong WLE, Geismar C, Hoskins S, Navaratnam AMD, Nguyen V, Patel P, Shrotri M, Yavlinsky A, Hardelid P, Wijlaars L, Nastouli E, Spyer M, Aryee A, Cox I, Lampos V, Mckendry RA, Cheng T, Johnson AM, Michie S, Gibbs J, Gilson R, Rodger A, Abubakar I, Hayward A, Aldridge RW. Cohort Profile: Virus Watch-understanding community incidence, symptom profiles and transmission of COVID-19 in relation to population movement and behaviour. Int J Epidemiol 2023; 52:e263-e272. [PMID: 37349899 PMCID: PMC10555858 DOI: 10.1093/ije/dyad087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 05/31/2023] [Indexed: 06/24/2023] Open
Affiliation(s)
- Thomas Byrne
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Jana Kovar
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Sarah Beale
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Isobel Braithwaite
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Ellen Fragaszy
- Institute of Epidemiology and Health Care, University College London, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Wing Lam Erica Fong
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Cyril Geismar
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Susan Hoskins
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Annalan M D Navaratnam
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Vincent Nguyen
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Parth Patel
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Madhumita Shrotri
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Alexei Yavlinsky
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Pia Hardelid
- Department of Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Linda Wijlaars
- Department of Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Eleni Nastouli
- Department of Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
- Francis Crick Institute, London, UK
- University College London Hospital, London, UK
| | | | - Anna Aryee
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Ingemar Cox
- Department of Computer Science, University College London, London, UK
| | - Vasileios Lampos
- Department of Computer Science, University College London, London, UK
| | - Rachel A Mckendry
- London Centre for Nanotechnology and Division of Medicine, University College London, London, UK
| | - Tao Cheng
- SpaceTimeLab, Department of Civil, Environmental and Geomatic Engineering, University College London, London, UK
| | - Anne M Johnson
- Centre for Population Research in Sexual Health and HIV, Institute for Global Health, London, UK
| | - Susan Michie
- Centre for Behaviour Change, University College London, London, UK
| | - Jo Gibbs
- Institute for Global Health, University College London, London, UK
| | - Richard Gilson
- Institute for Global Health, University College London, London, UK
| | - Alison Rodger
- Institute for Global Health, University College London, London, UK
- Royal Free London NHS Foundation Trust, London, UK
| | - Ibrahim Abubakar
- Institute for Global Health, University College London, London, UK
| | - Andrew Hayward
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Robert W Aldridge
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
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5
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Braithwaite I, Adamson J, Petrou G. Housing and climate: UK homes need urgent adaptation to protect our health. BMJ 2023; 383:2235. [PMID: 37793702 DOI: 10.1136/bmj.p2235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/06/2023]
Affiliation(s)
| | | | - Giorgos Petrou
- Institute for Environmental Design and Engineering, University College London
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6
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Boukari Y, Beale S, Nguyen V, Fong WLE, Burns R, Yavlinsky A, Hoskins S, Lewis K, Geismar C, Navaratnam AM, Braithwaite I, Byrne TE, Oskrochi Y, Tweed S, Kovar J, Patel P, Hayward A, Aldridge R. SARS-CoV-2 infections in migrants and the role of household overcrowding: a causal mediation analysis of Virus Watch data. J Epidemiol Community Health 2023; 77:649-655. [PMID: 37463770 PMCID: PMC10511992 DOI: 10.1136/jech-2022-220251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 07/07/2023] [Indexed: 07/20/2023]
Abstract
BACKGROUND Migrants are over-represented in SARS-CoV-2 infections globally; however, evidence is limited for migrants in England and Wales. Household overcrowding is a risk factor for SARS-CoV-2 infection, with migrants more likely to live in overcrowded households than UK-born individuals. We aimed to estimate the total effect of migration status on SARS-CoV-2 infection and to what extent household overcrowding mediated this effect. METHODS We included a subcohort of individuals from the Virus Watch prospective cohort study during the second SARS-CoV-2 wave (1 September 2020-30 April 2021) who were aged ≥18 years, self-reported the number of rooms in their household and had no evidence of SARS-CoV-2 infection pre-September 2020. We estimated total, indirect and direct effects using Buis' logistic decomposition regression controlling for age, sex, ethnicity, clinical vulnerability, occupation, income and whether they lived with children. RESULTS In total, 23 478 individuals were included. 9.07% (187/2062) of migrants had evidence of infection during the study period vs 6.27% (1342/21 416) of UK-born individuals. Migrants had 22% higher odds of infection during the second wave (total effect; OR 1.22, 95% CI 1.01 to 1.47). Household overcrowding accounted for approximately 36% (95% CI -4% to 77%) of these increased odds (indirect effect, OR 1.07, 95% CI 1.03 to 1.12; proportion accounted for: indirect effect on log odds scale/total effect on log odds scale=0.36). CONCLUSION Migrants had higher odds of SARS-CoV-2 infection during the second wave compared with UK-born individuals and household overcrowding explained 36% of these increased odds. Policy interventions to reduce household overcrowding for migrants are needed as part of efforts to tackle health inequalities during the pandemic and beyond.
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Affiliation(s)
- Yamina Boukari
- Institute of Health Informatics, University College London, London, UK
| | - Sarah Beale
- Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Vincent Nguyen
- Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | | | - Rachel Burns
- Institute of Health Informatics, University College London, London, UK
| | - Alexei Yavlinsky
- Institute of Health Informatics, University College London, London, UK
| | - Susan Hoskins
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Kate Lewis
- Population, Policy and Practice Department, University College London Great Ormond Street Institute of Child Health, London, UK
| | - Cyril Geismar
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Annalan Md Navaratnam
- Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
| | | | - Thomas E Byrne
- Institute of Health Informatics, University College London, London, UK
| | - Youssof Oskrochi
- Institute of Health Informatics, University College London, London, UK
| | - Sam Tweed
- Institute of Health Informatics, University College London, London, UK
| | - Jana Kovar
- Institute of Health Informatics, University College London, London, UK
| | - Parth Patel
- Institute of Health Informatics, University College London, London, UK
| | - Andrew Hayward
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Robert Aldridge
- Institute of Health Informatics, University College London, London, UK
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7
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Geismar C, Nguyen V, Fragaszy E, Shrotri M, Navaratnam AMD, Beale S, Byrne TE, Fong WLE, Yavlinsky A, Kovar J, Hoskins S, Braithwaite I, Aldridge RW, Hayward AC, White PJ, Jombart T, Cori A. Bayesian reconstruction of SARS-CoV-2 transmissions highlights substantial proportion of negative serial intervals. Epidemics 2023; 44:100713. [PMID: 37579586 DOI: 10.1016/j.epidem.2023.100713] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 07/25/2023] [Accepted: 07/31/2023] [Indexed: 08/16/2023] Open
Abstract
BACKGROUND The serial interval is a key epidemiological measure that quantifies the time between the onset of symptoms in an infector-infectee pair. It indicates how quickly new generations of cases appear, thus informing on the speed of an epidemic. Estimating the serial interval requires to identify pairs of infectors and infectees. Yet, most studies fail to assess the direction of transmission between cases and assume that the order of infections - and thus transmissions - strictly follows the order of symptom onsets, thereby imposing serial intervals to be positive. Because of the long and highly variable incubation period of SARS-CoV-2, this may not always be true (i.e an infectee may show symptoms before their infector) and negative serial intervals may occur. This study aims to estimate the serial interval of different SARS-CoV-2 variants whilst accounting for negative serial intervals. METHODS This analysis included 5 842 symptomatic individuals with confirmed SARS-CoV-2 infection amongst 2 579 households from September 2020 to August 2022 across England & Wales. We used a Bayesian framework to infer who infected whom by exploring all transmission trees compatible with the observed dates of symptoms, based on a wide range of incubation period and generation time distributions compatible with estimates reported in the literature. Serial intervals were derived from the reconstructed transmission pairs, stratified by variants. RESULTS We estimated that 22% (95% credible interval (CrI) 8-32%) of serial interval values are negative across all VOC. The mean serial interval was shortest for Omicron BA5 (2.02 days, 1.26-2.84) and longest for Alpha (3.37 days, 2.52-4.04). CONCLUSIONS This study highlights the large proportion of negative serial intervals across SARS-CoV-2 variants. Because the serial interval is widely used to estimate transmissibility and forecast cases, these results may have critical implications for epidemic control.
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Affiliation(s)
- Cyril Geismar
- MRC Centre for Global Infectious Disease Analysis and NIHR Health Protection Research Unit in Modelling and Health Economics, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK; Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK.
| | - Vincent Nguyen
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Ellen Fragaszy
- Institute of Epidemiology and Health Care, University College London, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Madhumita Shrotri
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Annalan M D Navaratnam
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Sarah Beale
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK; Institute of Epidemiology and Health Care, University College London, London, UK
| | - Thomas E Byrne
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Wing Lam Erica Fong
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Alexei Yavlinsky
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Jana Kovar
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Susan Hoskins
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Isobel Braithwaite
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Robert W Aldridge
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Andrew C Hayward
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Peter J White
- MRC Centre for Global Infectious Disease Analysis and NIHR Health Protection Research Unit in Modelling and Health Economics, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Thibaut Jombart
- MRC Centre for Global Infectious Disease Analysis and NIHR Health Protection Research Unit in Modelling and Health Economics, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Anne Cori
- MRC Centre for Global Infectious Disease Analysis and NIHR Health Protection Research Unit in Modelling and Health Economics, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
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8
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Geismar C, Nguyen V, Fragaszy E, Shrotri M, Navaratnam AMD, Beale S, Byrne TE, Fong WLE, Yavlinsky A, Kovar J, Hoskins S, Braithwaite I, Aldridge RW, Hayward AC. Symptom profiles of community cases infected by influenza, RSV, rhinovirus, seasonal coronavirus, and SARS-CoV-2 variants of concern. Sci Rep 2023; 13:12511. [PMID: 37532756 PMCID: PMC10397315 DOI: 10.1038/s41598-023-38869-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 07/16/2023] [Indexed: 08/04/2023] Open
Abstract
Respiratory viruses that were suppressed through previous lockdowns during the COVID-19 pandemic have recently started to co-circulate with SARS-CoV-2. Understanding the clinical characteristics and symptomatology of different respiratory viral infections can help address the challenges related to the identification of cases and the understanding of SARS-CoV-2 variants' evolutionary patterns. Flu Watch (2006-2011) and Virus Watch (2020-2022) are household community cohort studies monitoring the epidemiology of influenza, respiratory syncytial virus, rhinovirus, seasonal coronavirus, and SARS-CoV-2, in England and Wales. This study describes and compares the proportion of symptoms reported during illnesses infected by common respiratory viruses. The SARS-CoV-2 symptom profile increasingly resembles that of other respiratory viruses as new strains emerge. Increased cough, sore throat, runny nose, and sneezing are associated with the emergence of the Omicron strains. As SARS-CoV-2 becomes endemic, monitoring the evolution of its symptomatology associated with new variants will be critical for clinical surveillance.
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Affiliation(s)
- Cyril Geismar
- MRC Centre for Global Infectious Disease Analysis and NIHR Health Protection Research Unit in Modelling and Health Economics, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK.
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK.
| | - Vincent Nguyen
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Ellen Fragaszy
- Institute of Epidemiology and Health Care, University College London, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Madhumita Shrotri
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Annalan M D Navaratnam
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Sarah Beale
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Thomas E Byrne
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Wing Lam Erica Fong
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Alexei Yavlinsky
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Jana Kovar
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Susan Hoskins
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Isobel Braithwaite
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Robert W Aldridge
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Andrew C Hayward
- Institute of Epidemiology and Health Care, University College London, London, UK
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9
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Nguyen VG, Yavlinsky A, Beale S, Hoskins S, Byrne TE, Lampos V, Braithwaite I, Fong WLE, Fragaszy E, Geismar C, Kovar J, Navaratnam AMD, Patel P, Shrotri M, Weber S, Hayward AC, Aldridge RW. Comparative effectiveness of different primary vaccination courses on mRNA-based booster vaccines against SARs-COV-2 infections: a time-varying cohort analysis using trial emulation in the Virus Watch community cohort. Int J Epidemiol 2023; 52:342-354. [PMID: 36655537 PMCID: PMC10114109 DOI: 10.1093/ije/dyad002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 01/13/2023] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND The Omicron B.1.1.529 variant increased severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in doubly vaccinated individuals, particularly in the Oxford-AstraZeneca COVID-19 vaccine (ChAdOx1) recipients. To tackle infections, the UK's booster vaccination programmes used messenger ribonucleic acid (mRNA) vaccines irrespective of an individual's primary course vaccine type, and prioritized the clinically vulnerable. These mRNA vaccines included the Pfizer-BioNTech COVID-19 vaccine (BNT162b2) the Moderna COVID-19 vaccine (mRNA-1273). There is limited understanding of the effectiveness of different primary vaccination courses on mRNA booster vaccines against SARs-COV-2 infections and how time-varying confounders affect these evaluations. METHODS Trial emulation was applied to a prospective community observational cohort in England and Wales to reduce time-varying confounding-by-indication driven by prioritizing vaccination based upon age, vulnerability and exposure. Trial emulation was conducted by meta-analysing eight adult cohort results whose booster vaccinations were staggered between 16 September 2021 and 05 January 2022 and followed until 23 January 2022. Time from booster vaccination until SARS-CoV-2 infection, loss of follow-up or end of study was modelled using Cox proportional hazard models and adjusted for age, sex, minority ethnic status, clinically vulnerability and deprivation. RESULTS A total of 19 159 participants were analysed, with 11 709 ChAdOx1 primary courses and 7450 BNT162b2 primary courses. Median age, clinical vulnerability status and infection rates fluctuate through time. In mRNA-boosted adults, 7.4% (n = 863) of boosted adults with a ChAdOx1 primary course experienced a SARS-CoV-2 infection compared with 7.7% (n = 571) of those who had BNT162b2 as a primary course. The pooled adjusted hazard ratio (aHR) was 1.01 with a 95% confidence interval (CI) of: 0.90 to 1.13. CONCLUSION After an mRNA booster dose, we found no difference in protection comparing those with a primary course of BNT162b2 with those with a ChAdOx1 primary course. This contrasts with pre-booster findings where previous research shows greater effectiveness of BNT162b2 than ChAdOx1 in preventing infection.
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Affiliation(s)
- Vincent Grigori Nguyen
- Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Alexei Yavlinsky
- Institute of Health Informatics, University College London, London, UK
| | - Sarah Beale
- Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Susan Hoskins
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Thomas E Byrne
- Institute of Health Informatics, University College London, London, UK
| | - Vasileios Lampos
- Department of Computer Science, University College London, London, UK
| | | | | | - Ellen Fragaszy
- Institute of Health Informatics, University College London, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Cyril Geismar
- Institute of Health Informatics, University College London, London, UK
| | - Jana Kovar
- Institute of Epidemiology and Health Care, University College London, London, UK
| | | | - Parth Patel
- Institute of Health Informatics, University College London, London, UK
| | - Madhumita Shrotri
- Institute of Health Informatics, University College London, London, UK
| | - Sophie Weber
- Institute of Health Informatics, University College London, London, UK
| | - Andrew C Hayward
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Robert W Aldridge
- Institute of Health Informatics, University College London, London, UK
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10
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Roberts M, Colley K, Currie M, Eastwood A, Li KH, Avery LM, Beevers LC, Braithwaite I, Dallimer M, Davies ZG, Fisher HL, Gidlow CJ, Memon A, Mudway IS, Naylor LA, Reis S, Smith P, Stansfeld SA, Wilkie S, Irvine KN. The Contribution of Environmental Science to Mental Health Research: A Scoping Review. Int J Environ Res Public Health 2023; 20:5278. [PMID: 37047894 PMCID: PMC10094550 DOI: 10.3390/ijerph20075278] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Revised: 02/22/2023] [Accepted: 02/28/2023] [Indexed: 06/19/2023]
Abstract
Mental health is influenced by multiple complex and interacting genetic, psychological, social, and environmental factors. As such, developing state-of-the-art mental health knowledge requires collaboration across academic disciplines, including environmental science. To assess the current contribution of environmental science to this field, a scoping review of the literature on environmental influences on mental health (including conditions of cognitive development and decline) was conducted. The review protocol was developed in consultation with experts working across mental health and environmental science. The scoping review included 202 English-language papers, published between 2010 and 2020 (prior to the COVID-19 pandemic), on environmental themes that had not already been the subject of recent systematic reviews; 26 reviews on climate change, flooding, air pollution, and urban green space were additionally considered. Studies largely focused on populations in the USA, China, or Europe and involved limited environmental science input. Environmental science research methods are primarily focused on quantitative approaches utilising secondary datasets or field data. Mental health measurement was dominated by the use of self-report psychometric scales. Measures of environmental states or exposures were often lacking in specificity (e.g., limited to the presence or absence of an environmental state). Based on the scoping review findings and our synthesis of the recent reviews, a research agenda for environmental science's future contribution to mental health scholarship is set out. This includes recommendations to expand the geographical scope and broaden the representation of different environmental science areas, improve measurement of environmental exposure, prioritise experimental and longitudinal research designs, and giving greater consideration to variation between and within communities and the mediating pathways by which environment influences mental health. There is also considerable opportunity to increase interdisciplinarity within the field via the integration of conceptual models, the inclusion of mixed methods and qualitative approaches, as well as further consideration of the socio-political context and the environmental states that can help support good mental health. The findings were used to propose a conceptual model to parse contributions and connections between environmental science and mental health to inform future studies.
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Affiliation(s)
- Michaela Roberts
- Social, Economic and Geographical Sciences Department, The James Hutton Institute, Craigiebuckler, Aberdeen, Scotland AB15 8QH, UK
| | - Kathryn Colley
- Social, Economic and Geographical Sciences Department, The James Hutton Institute, Craigiebuckler, Aberdeen, Scotland AB15 8QH, UK
| | - Margaret Currie
- Social, Economic and Geographical Sciences Department, The James Hutton Institute, Craigiebuckler, Aberdeen, Scotland AB15 8QH, UK
| | - Antonia Eastwood
- Social, Economic and Geographical Sciences Department, The James Hutton Institute, Craigiebuckler, Aberdeen, Scotland AB15 8QH, UK
| | - Kuang-Heng Li
- Social, Economic and Geographical Sciences Department, The James Hutton Institute, Craigiebuckler, Aberdeen, Scotland AB15 8QH, UK
| | - Lisa M. Avery
- Environmental and Biochemical Sciences Department, The James Hutton Institute, Craigiebuckler, Aberdeen, Scotland AB15 8QH, UK
| | - Lindsay C. Beevers
- Institute of Infrastructure and Environment, School of Energy, Geoscience, Infrastructure and Society, Heriot-Watt University, Edinburgh EH14 4AS, UK
| | - Isobel Braithwaite
- UCL Institute of Health Informatics, 222 Euston Road, London NW1 2DA, UK
| | - Martin Dallimer
- Sustainability Research Institute, School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK
| | - Zoe G. Davies
- Durrell Institute of Conservation and Ecology (DICE), School of Anthropology and Conservation, University of Kent, Canterbury, Kent CT2 7NR, UK
| | - Helen L. Fisher
- King’s College London, Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, 16 De Crespigny Park, London SE5 8AF, UK
- Economic & Social Research Council (ESRC) Centre for Society and Mental Health, King’s College London, 44-46 Aldwych, London WC2B 4LL, UK
| | - Christopher J. Gidlow
- Centre for Health and Development (CHAD), Staffordshire University, Leek Road, Stoke-on-Trent ST4 2DF, UK
| | - Anjum Memon
- Department of Primary Care and Public Health, Brighton and Sussex Medical School, Brighton BN1 9PH, UK
| | - Ian S. Mudway
- MRC Centre for Environment and Health, Imperial College London, White City Campus, London W12 0BZ, UK
- NIHR Health Protection Research Units in Environmental Exposures and Health, and Chemical and Radiation Threats and Hazards, Imperial College London, White City Campus, London W12 0BZ, UK
| | - Larissa A. Naylor
- School of Geographical & Earth Sciences, East Quadrangle, University of Glasgow, Glasgow G12 8QQ, UK
| | - Stefan Reis
- UK Centre for Ecology & Hydrology, Bush Estate, Penicuik EH26 0QB, UK
- European Centre for Environment and Human Health, University of Exeter Medical School, Knowledge Spa, Truro, Cornwall TR1 3HD, UK
| | - Pete Smith
- Institute of Biological and Environmental Sciences, University of Aberdeen, 23 St Machar Drive, Aberdeen AB24 3UU, UK
| | - Stephen A. Stansfeld
- Centre for Psychiatry, Barts and the London School of Medicine, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
| | - Stephanie Wilkie
- School of Psychology, Murray Library, City Campus, University of Sunderland, Sunderland SR1 3SD, UK
| | - Katherine N. Irvine
- Social, Economic and Geographical Sciences Department, The James Hutton Institute, Craigiebuckler, Aberdeen, Scotland AB15 8QH, UK
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11
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Nguyen V, Liu Y, Mumford R, Flanagan B, Patel P, Braithwaite I, Shrotri M, Byrne T, Beale S, Aryee A, Fong WLE, Fragaszy E, Geismar C, Navaratnam AMD, Hardelid P, Kovar J, Pope A, Cheng T, Hayward A, Aldridge R. Tracking Changes in Mobility Before and After the First SARS-CoV-2 Vaccination Using Global Positioning System Data in England and Wales (Virus Watch): Prospective Observational Community Cohort Study. JMIR Public Health Surveill 2023; 9:e38072. [PMID: 36884272 PMCID: PMC9997704 DOI: 10.2196/38072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 08/05/2022] [Accepted: 09/29/2022] [Indexed: 03/09/2023] Open
Abstract
BACKGROUND Evidence suggests that individuals may change adherence to public health policies aimed at reducing the contact, transmission, and spread of the SARS-CoV-2 virus after they receive their first SARS-CoV-2 vaccination when they are not fully vaccinated. OBJECTIVE We aimed to estimate changes in median daily travel distance of our cohort from their registered addresses before and after receiving a SARS-CoV-2 vaccine. METHODS Participants were recruited into Virus Watch starting in June 2020. Weekly surveys were sent out to participants, and vaccination status was collected from January 2021 onward. Between September 2020 and February 2021, we invited 13,120 adult Virus Watch participants to contribute toward our tracker subcohort, which uses the GPS via a smartphone app to collect data on movement. We used segmented linear regression to estimate the median daily travel distance before and after the first self-reported SARS-CoV-2 vaccine dose. RESULTS We analyzed the daily travel distance of 249 vaccinated adults. From 157 days prior to vaccination until the day before vaccination, the median daily travel distance was 9.05 (IQR 8.06-10.09) km. From the day of vaccination to 105 days after vaccination, the median daily travel distance was 10.08 (IQR 8.60-12.42) km. From 157 days prior to vaccination until the vaccination date, there was a daily median decrease in mobility of 40.09 m (95% CI -50.08 to -31.10; P<.001). After vaccination, there was a median daily increase in movement of 60.60 m (95% CI 20.90-100; P<.001). Restricting the analysis to the third national lockdown (January 4, 2021, to April 5, 2021), we found a median daily movement increase of 18.30 m (95% CI -19.20 to 55.80; P=.57) in the 30 days prior to vaccination and a median daily movement increase of 9.36 m (95% CI 38.6-149.00; P=.69) in the 30 days after vaccination. CONCLUSIONS Our study demonstrates the feasibility of collecting high-volume geolocation data as part of research projects and the utility of these data for understanding public health issues. Our various analyses produced results that ranged from no change in movement after vaccination (during the third national lock down) to an increase in movement after vaccination (considering all periods, up to 105 days after vaccination), suggesting that, among Virus Watch participants, any changes in movement distances after vaccination are small. Our findings may be attributable to public health measures in place at the time such as movement restrictions and home working that applied to the Virus Watch cohort participants during the study period.
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Affiliation(s)
- Vincent Nguyen
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, United Kingdom
- Institute of Epidemiology and Health Care, University College London, London, United Kingdom
| | - Yunzhe Liu
- SpaceTimeLab, Department of Civil, Environmental and Geomatic Engineering, University College London, London, United Kingdom
| | - Richard Mumford
- Technical Research Department, Esri, Edinburgh, United Kingdom
| | | | - Parth Patel
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, United Kingdom
| | - Isobel Braithwaite
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, United Kingdom
| | - Madhumita Shrotri
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, United Kingdom
| | - Thomas Byrne
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, United Kingdom
| | - Sarah Beale
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, United Kingdom
- Institute of Epidemiology and Health Care, University College London, London, United Kingdom
| | - Anna Aryee
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, United Kingdom
| | - Wing Lam Erica Fong
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, United Kingdom
| | - Ellen Fragaszy
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, United Kingdom
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Cyril Geismar
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, United Kingdom
- Institute of Epidemiology and Health Care, University College London, London, United Kingdom
| | - Annalan M D Navaratnam
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, United Kingdom
- Institute of Epidemiology and Health Care, University College London, London, United Kingdom
| | - Pia Hardelid
- Department of Population, Policy and Practice, University College London Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Jana Kovar
- Institute of Epidemiology and Health Care, University College London, London, United Kingdom
| | - Addy Pope
- Technical Research Department, Esri, Edinburgh, United Kingdom
| | - Tao Cheng
- SpaceTimeLab, Department of Civil, Environmental and Geomatic Engineering, University College London, London, United Kingdom
| | - Andrew Hayward
- Institute of Epidemiology and Health Care, University College London, London, United Kingdom
| | - Robert Aldridge
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, United Kingdom
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Mulrenan C, Braithwaite I, Brook A, Crossley R, Loud E, Mavrodaris A. Comment: A sustainable and equitable response to the cost-of-living crisis is urgently needed. Public Health Pract (Oxf) 2023; 5:100367. [PMID: 36852167 PMCID: PMC9958386 DOI: 10.1016/j.puhip.2023.100367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 01/19/2023] [Accepted: 01/31/2023] [Indexed: 02/12/2023] Open
Affiliation(s)
- Claire Mulrenan
- London School of Hygiene & Tropical Medicine, London, WC1H 9SH, UK,Corresponding author. Commercial Determinants Research Group, Faculty of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, WC1H 9SH, UK.
| | | | - Anna Brook
- University of Sheffield, Sheffield, S10 2TN, UK
| | | | - Emily Loud
- Bedfordshire Luton and Milton Keynes Integrated Care System, UK
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13
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Beale S, Burns R, Braithwaite I, Byrne T, Lam Erica Fong W, Fragaszy E, Geismar C, Hoskins S, Kovar J, Navaratnam AMD, Nguyen V, Patel P, Yavlinsky A, Van Tongeren M, Aldridge RW, Hayward A. Occupation, Worker Vulnerability, and COVID-19 Vaccination Uptake: Analysis of the Virus Watch prospective cohort study. Vaccine 2022; 40:7646-7652. [PMID: 36372668 PMCID: PMC9637514 DOI: 10.1016/j.vaccine.2022.10.080] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 10/28/2022] [Accepted: 10/29/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND Occupational disparities in COVID-19 vaccine uptake can impact the effectiveness of vaccination programmes and introduce particular risk for vulnerable workers and those with high workplace exposure. This study aimed to investigate COVID-19 vaccine uptake by occupation, including for vulnerable groups and by occupational exposure status. METHODS We used data from employed or self-employed adults who provided occupational information as part of the Virus Watch prospective cohort study (n = 19,595) and linked this to study-obtained information about vulnerability-relevant characteristics (age, medical conditions, obesity status) and work-related COVID-19 exposure based on the Job Exposure Matrix. Participant vaccination status for the first, second, and third dose of any COVID-19 vaccine was obtained based on linkage to national records and study records. We calculated proportions and Sison-Glaz multinomial 95% confidence intervals for vaccine uptake by occupation overall, by vulnerability-relevant characteristics, and by job exposure. FINDINGS Vaccination uptake across occupations ranged from 89-96% for the first dose, 87-94% for the second dose, and 75-86% for the third dose, with transport, trade, service and sales workers persistently demonstrating the lowest uptake. Vulnerable workers tended to demonstrate fewer between-occupational differences in uptake than non-vulnerable workers, although clinically vulnerable transport workers (76%-89% across doses) had lower uptake than several other occupational groups (maximum across doses 86%-96%). Workers with low SARS-CoV-2 exposure risk had higher vaccine uptake (86%-96% across doses) than those with elevated or high risk (81-94% across doses). INTERPRETATION Differential vaccination uptake by occupation, particularly amongst vulnerable and highly-exposed workers, is likely to worsen occupational and related socioeconomic inequalities in infection outcomes. Further investigation into occupational and non-occupational factors influencing differential uptake is required to inform relevant interventions for future COVID-19 booster rollouts and similar vaccination programmes.
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Affiliation(s)
- Sarah Beale
- Centre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK; Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK.
| | - Rachel Burns
- Centre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK
| | - Isobel Braithwaite
- Centre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK
| | - Thomas Byrne
- Centre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK
| | - Wing Lam Erica Fong
- Centre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK
| | - Ellen Fragaszy
- Centre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK
| | - Cyril Geismar
- Centre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK; Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK
| | - Susan Hoskins
- Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK
| | - Jana Kovar
- Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK
| | - Annalan M D Navaratnam
- Centre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK; Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK
| | - Vincent Nguyen
- Centre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK; Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK
| | - Parth Patel
- Centre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK
| | - Alexei Yavlinsky
- Centre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK
| | - Martie Van Tongeren
- Centre for Occupational and Environmental Health, University of Manchester, Manchester M13 9PL, UK
| | - Robert W Aldridge
- Centre for Public Health Data Science, Institute of Health Informatics, University College London NW1 2DA, UK
| | - Andrew Hayward
- Institute of Epidemiology and Health Care, University College London, London WC1E 7HB, UK
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14
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Geismar C, Nguyen V, Fragaszy E, Shrotri M, Navaratnam AMD, Beale S, Byrne TE, Fong WLE, Yavlinsky A, Kovar J, Braithwaite I, Aldridge RW, Hayward AC, White P, Jombart T, Cori A. Bayesian reconstruction of household transmissions to infer the serial interval of COVID-19 by variants of concern: analysis from a prospective community cohort study (Virus Watch). Lancet 2022; 400 Suppl 1:S40. [PMID: 36929985 PMCID: PMC9691060 DOI: 10.1016/s0140-6736(22)02250-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
BACKGROUND The serial interval is a key epidemiological measure that quantifies the time between an infector's and an infectee's onset of symptoms. This measure helps investigate epidemiological links between cases, and is an important parameter in transmission models used to estimate transmissibility and inform control strategies. The emergence of multiple variants of concern (VOC) during the SARS-CoV-2 pandemic has led to uncertainties about potential changes in the serial interval of COVID-19. We estimated the household serial interval of multiple VOC using data collected by the Virus Watch study. This online, prospective, community cohort study followed-up entire households in England and Wales since mid-June 2020. METHODS This analysis included 5842 symptomatic individuals with confirmed SARS-CoV-2 infection among 2579 households from Sept 1, 2020, to Aug 10, 2022. SARS-CoV-2 variant designation was based upon national surveillance data of variant prevalence by date and geographical region. We used a Bayesian framework to infer who infected whom by exploring all transmission trees compatible with the observed dates of symptoms, given assumptions on the incubation period and generation time distributions using the R package outbreaker2. FINDINGS We characterised the serial interval of COVID-19 by VOC. The mean serial interval was shortest for omicron BA5 (2·02 days; 95% credible interval [CrI] 1·26-2·84) and longest for alpha (3·37 days; 2·52-4·04). The mean serial interval before alpha (wild-type) was 2·29 days (95% CrI 1·39-2·94), 3·11 days (2·28-3·90) for delta, 2·72 days (2·01-3·47) for omicron BA1, and 2·67 days (1·90-3·46) for omicron BA2. We estimated that 17% (95% CrI 5-26) of serial interval values are negative across all variants. INTERPRETATION Most methods estimating the reproduction number from incidence time series do not allow for a negative serial interval by construction. Further research is needed to extend these methods and assess biases introduced by not accounting for negative serial intervals. To our knowledge, this study is the first to use a Bayesian framework to estimate the serial interval of all major SARS-CoV-2 VOC from thousands of confirmed household cases. FUNDING UK Medical Research Council and Wellcome Trust.
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Affiliation(s)
- Cyril Geismar
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK.
| | - Vincent Nguyen
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Ellen Fragaszy
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Madhumita Shrotri
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Annalan M D Navaratnam
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Sarah Beale
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK; Institute of Epidemiology and Health Care, University College London, London, UK
| | - Thomas E Byrne
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Wing Lam Erica Fong
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Alexei Yavlinsky
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Jana Kovar
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Isobel Braithwaite
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Robert W Aldridge
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Andrew C Hayward
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Peter White
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Thibaut Jombart
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Anne Cori
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
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Shrotri M, Fragaszy E, Nguyen V, Navaratnam AMD, Geismar C, Beale S, Kovar J, Byrne TE, Fong WLE, Patel P, Aryee A, Braithwaite I, Johnson AM, Rodger A, Hayward AC, Aldridge RW. Spike-antibody responses to COVID-19 vaccination by demographic and clinical factors in a prospective community cohort study. Nat Commun 2022; 13:5780. [PMID: 36184633 PMCID: PMC9526787 DOI: 10.1038/s41467-022-33550-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 09/22/2022] [Indexed: 12/04/2022] Open
Abstract
Vaccination constitutes the best long-term solution against Coronavirus Disease-2019; however, vaccine-derived immunity may not protect all groups equally, and the durability of protective antibodies may be short. We evaluate Spike-antibody responses following BNT162b2 or ChAdOx1-S vaccination amongst SARS-CoV2-naive adults across England and Wales enrolled in a prospective cohort study (Virus Watch). Here we show BNT162b2 recipients achieved higher peak antibody levels after two doses; however, both groups experience substantial antibody waning over time. In 8356 individuals submitting a sample ≥28 days after Dose 2, we observe significantly reduced Spike-antibody levels following two doses amongst individuals reporting conditions and therapies that cause immunosuppression. After adjusting for these, several common chronic conditions also appear to attenuate the antibody response. These findings suggest the need to continue prioritising vulnerable groups, who have been vaccinated earliest and have the most attenuated antibody responses, for future boosters.
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Affiliation(s)
- Madhumita Shrotri
- Institute of Health Informatics, University College London, London, UK
| | - Ellen Fragaszy
- Institute of Health Informatics, University College London, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK
| | - Vincent Nguyen
- Institute of Health Informatics, University College London, London, UK
| | | | - Cyril Geismar
- Institute of Health Informatics, University College London, London, UK
| | - Sarah Beale
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Jana Kovar
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Thomas E Byrne
- Institute of Health Informatics, University College London, London, UK
| | | | - Parth Patel
- Institute of Health Informatics, University College London, London, UK
| | - Anna Aryee
- Institute of Health Informatics, University College London, London, UK
| | | | - Anne M Johnson
- Institute for Global Health, University College London, London, UK
| | - Alison Rodger
- Institute for Global Health, University College London, London, UK
| | - Andrew C Hayward
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Robert W Aldridge
- Institute of Health Informatics, University College London, London, UK.
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16
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Navaratnam AMD, Shrotri M, Nguyen V, Braithwaite I, Beale S, Byrne TE, Fong WLE, Fragaszy E, Geismar C, Hoskins S, Kovar J, Patel P, Yavlinsky A, Aryee A, Rodger A, Hayward AC, Aldridge RW. Nucleocapsid and spike antibody responses following virologically confirmed SARS-CoV-2 infection: an observational analysis in the Virus Watch community cohort. Int J Infect Dis 2022; 123:104-111. [PMID: 35987470 PMCID: PMC9385348 DOI: 10.1016/j.ijid.2022.07.053] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 07/20/2022] [Accepted: 07/21/2022] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVES Seroprevalence studies can provide a measure of SARS-CoV-2 cumulative incidence, but a better understanding of spike and nucleocapsid (anti-N) antibody dynamics following infection is needed to assess the longevity of detectability. METHODS Adults aged ≥18 years, from households enrolled in the Virus Watch prospective community cohort study in England and Wales, provided monthly capillary blood samples, which were tested for spike antibody and anti-N. Participants self-reported vaccination dates and past medical history. Previous polymerase chain reaction (PCR) swabs were obtained through Second Generation Surveillance System linkage data. The primary outcome variables were seropositivity and total anti-N and spike antibody levels after PCR-confirmed infection. RESULTS A total of 13,802 eligible individuals provided 58,770 capillary blood samples. A total of 537 of these had a previous positive PCR-confirmed SARS-CoV-2 infection within 0-269 days of antibody sample date, among them 432 (80.45%) having a positive anti-N result. Median anti-N levels peaked between days 90 and 119 after PCR results and then began to decline. There is evidence of anti-N waning from 120 days onwards, with earlier waning for females and younger age categories. CONCLUSION Our findings suggest that anti-N has around 80% sensitivity for identifying previous COVID-19 infection, and the duration of detectability is affected by sex and age.
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Affiliation(s)
| | - Madhumita Shrotri
- Institute of Health Informatics, University College London, United Kingdom
| | - Vincent Nguyen
- Institute of Health Informatics, University College London, United Kingdom
| | - Isobel Braithwaite
- Institute of Health Informatics, University College London, United Kingdom
| | - Sarah Beale
- Institute of Epidemiology and Health Care, University College London, London, United Kingdom
| | - Thomas E Byrne
- Institute of Health Informatics, University College London, United Kingdom
| | | | - Ellen Fragaszy
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, United Kingdom
| | - Cyril Geismar
- Institute of Health Informatics, University College London, United Kingdom
| | - Susan Hoskins
- Institute of Health Informatics, University College London, United Kingdom
| | - Jana Kovar
- Institute of Epidemiology and Health Care, University College London, London, United Kingdom
| | - Parth Patel
- Institute of Health Informatics, University College London, United Kingdom
| | - Alexei Yavlinsky
- Institute of Health Informatics, University College London, United Kingdom
| | - Anna Aryee
- Institute of Health Informatics, University College London, United Kingdom
| | - Alison Rodger
- Institute for Global Health, University College London, London, United Kingdom
| | - Andrew C Hayward
- Institute of Epidemiology and Health Care, University College London, London, United Kingdom
| | - Robert W Aldridge
- Institute of Health Informatics, University College London, United Kingdom.
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17
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Aldridge RW, Yavlinsky A, Nguyen V, Eyre MT, Shrotri M, Navaratnam AMD, Beale S, Braithwaite I, Byrne T, Kovar J, Fragaszy E, Fong WLE, Geismar C, Patel P, Rodger A, Johnson AM, Hayward A. SARS-CoV-2 antibodies and breakthrough infections in the Virus Watch cohort. Nat Commun 2022; 13:4869. [PMID: 35982056 PMCID: PMC9387883 DOI: 10.1038/s41467-022-32265-5] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 07/22/2022] [Indexed: 12/27/2022] Open
Abstract
A range of studies globally demonstrate that the effectiveness of SARS-CoV-2 vaccines wane over time, but the total effect of anti-S antibody levels on risk of SARS-CoV-2 infection and whether this varies by vaccine type is not well understood. Here we show that anti-S levels peak three to four weeks following the second dose of vaccine and the geometric mean of the samples is nine fold higher for BNT162b2 than ChAdOx1. Increasing anti-S levels are associated with a reduced risk of SARS-CoV-2 infection (Hazard Ratio 0.85; 95%CIs: 0.79-0.92). We do not find evidence that this antibody relationship with risk of infection varies by second dose vaccine type (BNT162b2 vs. ChAdOx1). In keeping with our anti-S antibody data, we find that people vaccinated with ChAdOx1 had 1.64 times the odds (95% confidence interval 1.45-1.85) of a breakthrough infection compared to BNT162b2. We anticipate our findings to be useful in the estimation of the protective effect of anti-S levels on risk of infection due to Delta. Our findings provide evidence about the relationship between antibody levels and protection for different vaccines and will support decisions on optimising the timing of booster vaccinations and identifying individuals who should be prioritised for booster vaccination, including those who are older, clinically extremely vulnerable, or received ChAdOx1 as their primary course. Our finding that risk of infection by anti-S level does not interact with vaccine type, but that individuals vaccinated with ChAdOx1 were at higher risk of infection, provides additional support for the use of using anti-S levels for estimating vaccine efficacy.
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Affiliation(s)
- Robert W Aldridge
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK.
| | - Alexei Yavlinsky
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Vincent Nguyen
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Max T Eyre
- Centre of Health Informatics, Computing and Statistics, Lancaster Medical School, Lancaster University, Lancaster, UK
- Liverpool School of Tropical Medicine, Liverpool, UK
| | - Madhumita Shrotri
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Annalan M D Navaratnam
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Sarah Beale
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Isobel Braithwaite
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Thomas Byrne
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Jana Kovar
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Ellen Fragaszy
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Wing Lam Erica Fong
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Cyril Geismar
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Parth Patel
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Alison Rodger
- Institute for Global Health, University College London, London, UK
| | - Anne M Johnson
- Institute for Global Health, University College London, London, UK
| | - Andrew Hayward
- Centre of Health Informatics, Computing and Statistics, Lancaster Medical School, Lancaster University, Lancaster, UK
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18
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Yavlinsky A, Beale S, Nguyen V, Shrotri M, Byrne T, Geismar C, Fragaszy E, Hoskins S, Fong WLE, Navaratnam AMD, Braithwaite I, Patel P, Kovar J, Hayward A, Aldridge RW. Anti-spike antibody trajectories in individuals previously immunised with BNT162b2 or ChAdOx1 following a BNT162b2 booster dose. Wellcome Open Res 2022. [DOI: 10.12688/wellcomeopenres.17914.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Background: The two most common SARS-CoV-2 vaccines in the UK, BNT162b2 (Pfizer-BioNTech) and ChAdOx1 nCoV-19 (Oxford-AstraZeneca), employ different immunogenic mechanisms. Compared to BNT162b2, two-dose immunisation with ChAdOx1 induces substantially lower peak anti-spike antibody (anti-S) levels and is associated with a higher risk of breakthrough infections. To provide preliminary indication of how a third booster BNT162b2 dose impacts anti-S levels, we performed a cross-sectional analysis using capillary blood samples from vaccinated adults participating in Virus Watch, a prospective community cohort study in England and Wales. Methods: Blood samples were analysed using Roche Elecsys Anti-SARS-CoV-2 S immunoassay. We analysed anti-S levels by week since the third dose for vaccines administered on or after 1 September 2021 and stratified the results by second-dose vaccine type (ChAdOx1 or BNT162b2), age, sex and clinical vulnerability. Results: Anti-S levels peaked at two weeks post-booster for BNT162b2 (22,185 U/mL; 95%CI: 21,406-22,990) and ChAdOx1 second-dose recipients (19,203 U/mL; 95%CI: 18,094-20,377). These were higher than the corresponding peak antibody levels post-second dose for BNT162b2 (12,386 U/mL; 95%CI: 9,801-15,653, week 2) and ChAdOx1 (1,192 U/mL; 95%CI: 818-1735, week 3). No differences emerged by second dose vaccine type, age, sex or clinical vulnerability. Anti-S levels declined post-booster for BNT162b2 (half-life=44 days) and ChAdOx1 second dose recipients (half-life=40 days). These rates of decline were steeper than those post-second dose for BNT162b2 (half-life=54 days) and ChAdOx1 (half-life=80 days). Conclusions: Our findings suggest that peak anti-S levels are higher post-booster than post-second dose, but levels are projected to be similar after six months for BNT162b2 recipients. Higher peak anti-S levels post-booster may partially explain the increased effectiveness of booster vaccination compared to two-dose vaccination against symptomatic infection with the Omicron variant. Faster waning trajectories post-third dose may have implications for the timing of future booster campaigns or four-dose vaccination regimens for the clinically vulnerable.
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19
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Beale S, Patel P, Rodger A, Braithwaite I, Byrne T, Fong WLE, Fragaszy E, Geismar C, Kovar J, Navaratnam A, Nguyen V, Shrotri M, Aryee A, Aldridge R, Hayward A. Occupation, work-related contact and SARS-CoV-2 anti-nucleocapsid serological status: findings from the Virus Watch prospective cohort study. Occup Environ Med 2022; 79:oemed-2021-107920. [PMID: 35450951 PMCID: PMC9072780 DOI: 10.1136/oemed-2021-107920] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 03/28/2022] [Indexed: 11/25/2022]
Abstract
OBJECTIVES Risk of SARS-CoV-2 infection varies across occupations; however, investigation into factors underlying differential risk is limited. We aimed to estimate the total effect of occupation on SARS-CoV-2 serological status, whether this is mediated by workplace close contact, and how exposure to poorly ventilated workplaces varied across occupations. METHODS We used data from a subcohort (n=3775) of adults in the UK-based Virus Watch cohort study who were tested for SARS-CoV-2 anti-nucleocapsid antibodies (indicating natural infection). We used logistic decomposition to investigate the relationship between occupation, contact and seropositivity, and logistic regression to investigate exposure to poorly ventilated workplaces. RESULTS Seropositivity was 17.1% among workers with daily close contact vs 10.0% for those with no work-related close contact. Compared with other professional occupations, healthcare, indoor trade/process/plant, leisure/personal service, and transport/mobile machine workers had elevated adjusted total odds of seropositivity (1.80 (1.03 to 3.14) - 2.46 (1.82 to 3.33)). Work-related contact accounted for a variable part of increased odds across occupations (1.04 (1.01 to 1.08) - 1.23 (1.09 to 1.40)). Occupations with raised odds of infection after accounting for work-related contact also had greater exposure to poorly ventilated workplaces. CONCLUSIONS Work-related close contact appears to contribute to occupational variation in seropositivity. Reducing contact in workplaces is an important COVID-19 control measure.
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Affiliation(s)
- Sarah Beale
- UCL Institute of Epidemiology and Health Care, University College London, London, UK
| | - Parth Patel
- UCL Institute of Health Informatics, University College London, London, UK
| | - Alison Rodger
- UCL Institute of Health Informatics, University College London, London, UK
| | - Isobel Braithwaite
- Extreme Events and Health Protection Team, Centre for Radiation, Chemicals and Environmental Hazards, Public Health England, London, UK
| | - Thomas Byrne
- UCL Institute of Health Informatics, University College London, London, UK
| | | | - Ellen Fragaszy
- UCL Institute of Health Informatics, University College London, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Cyril Geismar
- UCL Institute of Health Informatics, University College London, London, UK
| | - Jana Kovar
- UCL Institute of Epidemiology and Health Care, University College London, London, UK
- UCL Institute of Health Informatics, University College London, London, UK
| | - Annalan Navaratnam
- UCL Institute of Health Informatics, University College London, London, UK
| | - Vincent Nguyen
- UCL Institute of Health Informatics, University College London, London, UK
| | - Madhumita Shrotri
- UCL Institute of Health Informatics, University College London, London, UK
| | - Anna Aryee
- UCL Institute of Health Informatics, University College London, London, UK
| | - Robert Aldridge
- UCL Institute of Health Informatics, University College London, London, UK
| | - Andrew Hayward
- UCL Institute of Epidemiology and Health Care, University College London, London, UK
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20
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Fragaszy E, Shrotri M, Geismar C, Aryee A, Beale S, Braithwaite I, Byrne T, Eyre MT, Fong WLE, Gibbs J, Hardelid P, Kovar J, Lampos V, Nastouli E, Navaratnam AM, Nguyen V, Patel P, Aldridge RW, Hayward A. Symptom profiles and accuracy of clinical case definitions for COVID-19 in a community cohort: results from the Virus Watch study. Wellcome Open Res 2022; 7:84. [PMID: 37745779 PMCID: PMC10514573 DOI: 10.12688/wellcomeopenres.17479.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/31/2022] [Indexed: 09/23/2023] Open
Abstract
Background: Understanding symptomatology and accuracy of clinical case definitions for community COVID-19 cases is important for Test, Trace and Isolate (TTI) and future targeting of early antiviral treatment. Methods: Community cohort participants prospectively recorded daily symptoms and swab results (mainly undertaken through the UK TTI system). We compared symptom frequency, severity, timing, and duration in test positive and negative illnesses. We compared the test performance of the current UK TTI case definition (cough, high temperature, or loss of or altered sense of smell or taste) with a wider definition adding muscle aches, chills, headache, or loss of appetite. Results: Among 9706 swabbed illnesses, including 973 SARS-CoV-2 positives, symptoms were more common, severe and longer lasting in swab positive than negative illnesses. Cough, headache, fatigue, and muscle aches were the most common symptoms in positive illnesses but also common in negative illnesses. Conversely, high temperature, loss or altered sense of smell or taste and loss of appetite were less frequent in positive illnesses, but comparatively even less frequent in negative illnesses. The current UK definition had 81% sensitivity and 47% specificity versus 93% and 27% respectively for the broader definition. 1.7-fold more illnesses met the broader case definition than the current definition. Conclusions: Symptoms alone cannot reliably distinguish COVID-19 from other respiratory illnesses. Adding additional symptoms to case definitions could identify more infections, but with a large increase in the number needing testing and the number of unwell individuals and contacts self-isolating whilst awaiting results.
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Affiliation(s)
- Ellen Fragaszy
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Madhumita Shrotri
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Cyril Geismar
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Anna Aryee
- Centre of Health Informatics, Computing and Statistics, Lancaster University, Lancaster, UK
| | - Sarah Beale
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Isobel Braithwaite
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Thomas Byrne
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Max T. Eyre
- Centre of Health Informatics, Computing and Statistics, Lancaster University, Lancaster, UK
- Liverpool School of Tropical Medicine, Liverpool, UK
| | - Wing Lam Erica Fong
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Jo Gibbs
- Institute for Global Health, University College London, London, UK
| | - Pia Hardelid
- Population, Policy and Practice Research and Teaching Department, University College London, London, UK
| | - Jana Kovar
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Vasileios Lampos
- Department of Computer Science, University College London, London, UK
| | - Eleni Nastouli
- Francis Crick Institute, London, UK
- Department of Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Annalan M.D. Navaratnam
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Vincent Nguyen
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Parth Patel
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Robert W. Aldridge
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Andrew Hayward
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Virus Watch Collaborative
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
- Institute of Epidemiology and Health Care, University College London, London, UK
- Centre of Health Informatics, Computing and Statistics, Lancaster University, Lancaster, UK
- Liverpool School of Tropical Medicine, Liverpool, UK
- Institute for Global Health, University College London, London, UK
- Population, Policy and Practice Research and Teaching Department, University College London, London, UK
- Department of Computer Science, University College London, London, UK
- Francis Crick Institute, London, UK
- Department of Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
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21
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Aldridge RW, Pineo H, Fragaszy E, Eyre MT, Kovar J, Nguyen V, Beale S, Byrne T, Aryee A, Smith C, Devakumar D, Taylor J, Katikireddi SV, Fong WLE, Geismar C, Patel P, Shrotri M, Braithwaite I, Patni N, Navaratnam AMD, Johnson A, Hayward A. Household overcrowding and risk of SARS-CoV-2: analysis of the Virus Watch prospective community cohort study in England and Wales. Wellcome Open Res 2021. [DOI: 10.12688/wellcomeopenres.17308.1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Background: Household overcrowding is associated with increased risk of infectious diseases across contexts and countries. Limited data exist linking household overcrowding and risk of COVID-19. We used data collected from the Virus Watch cohort to examine the association between overcrowded households and SARS-CoV-2. Methods: The Virus Watch study is a household community cohort of acute respiratory infections in England and Wales. We calculated overcrowding using the measure of persons per room for each household. We considered two primary outcomes: PCR-confirmed positive SARS-CoV-2 antigen tests and laboratory-confirmed SARS-CoV-2 antibodies. We used mixed-effects logistic regression models that accounted for household structure to estimate the association between household overcrowding and SARS-CoV-2 infection. Results: 26,367 participants were included in our analyses. The proportion of participants with a positive SARS-CoV-2 PCR result was highest in the overcrowded group (9.0%; 99/1,100) and lowest in the under-occupied group (4.2%; 980/23,196). In a mixed-effects logistic regression model, we found strong evidence of an increased odds of a positive PCR SARS-CoV-2 antigen result (odds ratio 2.45; 95% CI:1.43–4.19; p-value=0.001) and increased odds of a positive SARS-CoV-2 antibody result in individuals living in overcrowded houses (3.32; 95% CI:1.54–7.15; p-value<0.001) compared with people living in under-occupied houses. Conclusion: Public health interventions to prevent and stop the spread of SARS-CoV-2 should consider the risk of infection for people living in overcrowded households and pay greater attention to reducing household transmission.
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22
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Byrne T, Patel P, Shrotri M, Beale S, Michie S, Butt J, Hawkins N, Hardelid P, Rodger A, Aryee A, Braithwaite I, Fong WLE, Fragaszy E, Geismar C, Kovar J, Navaratnam AMD, Nguyen V, Hayward A, Aldridge RW. Trends, patterns and psychological influences on COVID-19 vaccination intention: Findings from a large prospective community cohort study in England and Wales (Virus Watch). Vaccine 2021; 39:7108-7116. [PMID: 34728095 PMCID: PMC8498741 DOI: 10.1016/j.vaccine.2021.09.066] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 09/27/2021] [Accepted: 09/28/2021] [Indexed: 12/27/2022]
Abstract
BACKGROUND Vaccination intention is key to the success of any vaccination programme, alongside vaccine availability and access. Public intention to take a COVID-19 vaccine is high in England and Wales compared to other countries, but vaccination rate disparities between ethnic, social and age groups has led to concern. METHODS Online survey of prospective household community cohort study participants across England and Wales (Virus Watch). Vaccination intention was measured by individual participant responses to 'Would you accept a COVID-19 vaccine if offered?', collected in December 2020 and February 2021. Responses to a 13-item questionnaire collected in January 2021 were analysed using factor analysis to investigate psychological influences on vaccination intention. RESULTS Survey response rate was 56% (20,785/36,998) in December 2020 and 53% (20,590/38,727) in February 2021, with 14,880 adults reporting across both time points. In December 2020, 1,469 (10%) participants responded 'No' or 'Unsure'. Of these people, 1,266 (86%) changed their mind and responded 'Yes' or 'Already had a COVID-19 vaccine' by February 2021. Vaccination intention increased across all ethnic groups and levels of social deprivation. Age was most strongly associated with vaccination intention, with 16-24-year-olds more likely to respond "Unsure" or "No" versus "Yes" than 65-74-year-olds in December 2020 (OR: 4.63, 95 %CI: 3.42, 6.27 & OR 7.17 95 %CI: 4.26, 12.07 respectively) and February 2021 (OR: 27.92 95 %CI: 13.79, 56.51 & OR 17.16 95 %CI: 4.12, 71.55). The association between ethnicity and vaccination intention weakened, but did not disappear, over time. Both vaccine- and illness-related psychological factors were shown to influence vaccination intention. CONCLUSIONS Four in five adults (86%) who were reluctant or intending to refuse a COVID-19 vaccine in December 2020 had changed their mind in February 2021 and planned to accept, or had already accepted, a vaccine.
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Affiliation(s)
- Thomas Byrne
- Centre for Public Health Data Science, Institute of Health Informatics, University College, 222 Euston Rd, London NW1 2DA, UK.
| | - Parth Patel
- Centre for Public Health Data Science, Institute of Health Informatics, University College, 222 Euston Rd, London NW1 2DA, UK.
| | - Madhumita Shrotri
- Centre for Public Health Data Science, Institute of Health Informatics, University College, 222 Euston Rd, London NW1 2DA, UK
| | - Sarah Beale
- Centre for Public Health Data Science, Institute of Health Informatics, University College, 222 Euston Rd, London NW1 2DA, UK; Institute of Epidemiology and Health Care, University College London, 1-19 Torrington Place, London WC1E 7HB, UK
| | - Susan Michie
- Centre for Behaviour Change, University College London, 1-19 Torrington Place, London WC1E 7HB, UK
| | - Jabeer Butt
- Race Equality Foundation, 27 Greenwood Pl, London NW5 1LB, UK
| | | | - Pia Hardelid
- Department of Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, 30 Guilford St, London WC1N 1EH, UK
| | - Alison Rodger
- Institute for Global Health, University College London, 30 Guilford St, London WC1N 1EH, UK; Royal Free London NHS Foundation Trust, Pond Street, London, NW3 2QG, UK
| | - Anna Aryee
- Centre for Public Health Data Science, Institute of Health Informatics, University College, 222 Euston Rd, London NW1 2DA, UK
| | - Isobel Braithwaite
- Centre for Public Health Data Science, Institute of Health Informatics, University College, 222 Euston Rd, London NW1 2DA, UK
| | - Wing Lam Erica Fong
- Centre for Public Health Data Science, Institute of Health Informatics, University College, 222 Euston Rd, London NW1 2DA, UK
| | - Ellen Fragaszy
- Centre for Public Health Data Science, Institute of Health Informatics, University College, 222 Euston Rd, London NW1 2DA, UK; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel St, London WC1E 7HT, UK
| | - Cyril Geismar
- Centre for Public Health Data Science, Institute of Health Informatics, University College, 222 Euston Rd, London NW1 2DA, UK; Institute of Epidemiology and Health Care, University College London, 1-19 Torrington Place, London WC1E 7HB, UK
| | - Jana Kovar
- Institute of Epidemiology and Health Care, University College London, 1-19 Torrington Place, London WC1E 7HB, UK
| | - Annalan M D Navaratnam
- Centre for Public Health Data Science, Institute of Health Informatics, University College, 222 Euston Rd, London NW1 2DA, UK; Institute of Epidemiology and Health Care, University College London, 1-19 Torrington Place, London WC1E 7HB, UK
| | - Vincent Nguyen
- Centre for Public Health Data Science, Institute of Health Informatics, University College, 222 Euston Rd, London NW1 2DA, UK; Institute of Epidemiology and Health Care, University College London, 1-19 Torrington Place, London WC1E 7HB, UK
| | - Andrew Hayward
- Institute of Epidemiology and Health Care, University College London, 1-19 Torrington Place, London WC1E 7HB, UK
| | - Robert W Aldridge
- Centre for Public Health Data Science, Institute of Health Informatics, University College, 222 Euston Rd, London NW1 2DA, UK.
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Beale S, Braithwaite I, Navaratnam AM, Hardelid P, Rodger A, Aryee A, Byrne TE, Fong EWL, Fragaszy E, Geismar C, Kovar J, Nguyen V, Patel P, Shrotri M, Aldridge R, Hayward A. Deprivation and exposure to public activities during the COVID-19 pandemic in England and Wales. J Epidemiol Community Health 2021; 76:319-326. [PMID: 34642240 PMCID: PMC8520599 DOI: 10.1136/jech-2021-217076] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 09/19/2021] [Indexed: 11/24/2022]
Abstract
Background Differential exposure to public activities may contribute to stark deprivation-related inequalities in SARS-CoV-2 infection and outcomes but has not been directly investigated. We set out to investigate whether participants in Virus Watch—a large community cohort study based in England and Wales—reported differential exposure to public activities and non-household contacts during the autumn–winter phase of the COVID-19 pandemic according to postcode-level socioeconomic deprivation. Methods Participants (n=20 120–25 228 across surveys) reported their daily activities during 3 weekly periods in late November 2020, late December 2020 and mid-February 2021. Deprivation was quantified based on participants’ residential postcode using English or Welsh Index of Multiple Deprivation quintiles. We used Poisson mixed-effect models with robust standard errors to estimate the relationship between deprivation and risk of exposure to public activities during each survey period. Results Relative to participants in the least deprived areas, participants in the most deprived areas exhibited elevated risk of exposure to vehicle sharing (adjusted risk ratio (aRR) range across time points: 1.73–8.52), public transport (aRR: 3.13–5.73), work or education outside of the household (aRR: 1.09–1.21), essential shops (aRR: 1.09–1.13) and non-household contacts (aRR: 1.15–1.19) across multiple survey periods. Conclusion Differential exposure to essential public activities—such as attending workplaces and visiting essential shops—is likely to contribute to inequalities in infection risk and outcomes. Public health interventions to reduce exposure during essential activities and financial and practical support to enable low-paid workers to stay at home during periods of intense transmission may reduce COVID-related inequalities.
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Affiliation(s)
- Sarah Beale
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK.,Department of Epidemiology and Public Health, University College London, London, UK
| | - Isobel Braithwaite
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Annalan Md Navaratnam
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Pia Hardelid
- Centre for Paediatric Epidemiology and Biostatistics, UCL Institute of Child Health, London, UK
| | - Alison Rodger
- Research Department of Infection and Population Health, Royal Free Campus, University College London, London, UK
| | - Anna Aryee
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Thomas E Byrne
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Erica Wing Lam Fong
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Ellen Fragaszy
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK.,Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medecine, London, UK
| | - Cyril Geismar
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Jana Kovar
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Vincent Nguyen
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Parth Patel
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Madhumita Shrotri
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Robert Aldridge
- Centre for Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Andrew Hayward
- Department of Epidemiology and Public Health, University College London, London, UK
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24
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Beale S, Byrne T, Fragaszy E, Kovar J, Nguyen V, Aryee A, Fong WLE, Geismar C, Patel P, Shrotri M, Patni N, Braithwaite I, Navaratnam A, Johnson AM, Aldridge RW, Hayward AC. Reported exposure to SARS-CoV-2 and relative perceived importance of different settings for SARS-CoV-2 acquisition in England and Wales: Analysis of the Virus Watch Community Cohort. Wellcome Open Res 2021. [DOI: 10.12688/wellcomeopenres.17067.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
We aimed to assess the relative importance of different settings for SARS-CoV-2 transmission in a large community cohort based on perceived location of infection for self-reported confirmed SARS-COV-2 cases. We demonstrate the importance of home, work and education as perceived venues for transmission. In children, education was most important and in older adults essential shopping was of high importance. Our findings support public health messaging about infection control at home, advice on working from home and restrictions in different venues.
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Abstract
Climate change is already having unequal effects on the mental health of individuals and communities and will increasingly compound pre-existing mental health inequalities globally. Psychiatrists have a vital part to play in improving both awareness and scientific understanding of structural mechanisms that perpetuate these inequalities, and in responding to global calls for action to promote climate justice and resilience, which are central foundations for good mental and physical health.
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Affiliation(s)
- Shuo Zhang
- South London and the Maudsley NHS Trust, UK
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26
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Affiliation(s)
- Isobel Braithwaite
- University College London (UCL) Public Health Data Science Research Group, Institute of Health Informatics, UCL, London, UK.
| | - Chantal Edge
- UCL Collaborative Centre for Inclusion Health, UCL, London, UK
| | - Dan Lewer
- UCL Collaborative Centre for Inclusion Health, UCL, London, UK
| | - Jake Hard
- Royal College of General Practitioners Secure Environments Group, London, UK
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27
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Lewer D, Braithwaite I, Bullock M, Eyre MT, White PJ, Aldridge RW, Story A, Hayward AC. COVID-19 among people experiencing homelessness in England: a modelling study. Lancet Respir Med 2020; 8:1181-1191. [PMID: 32979308 PMCID: PMC7511167 DOI: 10.1016/s2213-2600(20)30396-9] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 08/19/2020] [Accepted: 08/26/2020] [Indexed: 12/23/2022]
Abstract
BACKGROUND People experiencing homelessness are vulnerable to COVID-19 due to the risk of transmission in shared accommodation and the high prevalence of comorbidities. In England, as in some other countries, preventive policies have been implemented to protect this population. We aimed to estimate the avoided deaths and health-care use among people experiencing homelessness during the so-called first wave of COVID-19 in England-ie, the peak of infections occurring between February and May, 2020-and the potential impact of COVID-19 on this population in the future. METHODS We used a discrete-time Markov chain model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection that included compartments for susceptible, exposed, infectious, and removed individuals, to explore the impact of the pandemic on 46 565 individuals experiencing homelessness: 35 817 living in 1065 hostels for homeless people, 3616 sleeping in 143 night shelters, and 7132 sleeping outside. We ran the model under scenarios varying the incidence of infection in the general population and the availability of prevention measures: specialist hotel accommodation, infection control in homeless settings, and mixing with the general population. We divided our scenarios into first wave scenarios (covering Feb 1-May 31, 2020) and future scenarios (covering June 1, 2020-Jan 31, 2021). For each scenario, we ran the model 200 times and reported the median and 95% prediction interval (2·5% and 97·5% quantiles) of the total number of cases, the number of deaths, the number hospital admissions, and the number of intensive care unit (ICU) admissions. FINDINGS Up to May 31, 2020, we calibrated the model to 4% of the homeless population acquiring SARS-CoV-2, and estimated that 24 deaths (95% prediction interval 16-34) occurred. In this first wave of SARS-CoV-2 infections in England, we estimated that the preventive measures imposed might have avoided 21 092 infections (19 777-22 147), 266 deaths (226-301), 1164 hospital admissions (1079-1254), and 338 ICU admissions (305-374) among the homeless population. If preventive measures are continued, we projected a small number of additional cases between June 1, 2020, and Jan 31, 2021, with 1754 infections (1543-1960), 31 deaths (21-45), 122 hospital admissions (100-148), and 35 ICU admissions (23-47) with a second wave in the general population. However, if preventive measures are lifted, outbreaks in homeless settings might lead to larger numbers of infections and deaths, even with low incidence in the general population. In a scenario with no second wave and relaxed measures in homeless settings in England, we projected 12 151 infections (10 718-13 349), 184 deaths (151-217), 733 hospital admissions (635-822), and 213 ICU admissions (178-251) between June 1, 2020, and Jan 31, 2021. INTERPRETATION Outbreaks of SARS-CoV-2 in homeless settings can lead to a high attack rate among people experiencing homelessness, even if incidence remains low in the general population. Avoidance of deaths depends on prevention of transmission within settings such as hostels and night shelters. FUNDING National Institute for Health Research, Wellcome, and Medical Research Council.
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Affiliation(s)
- Dan Lewer
- UCL Collaborative Centre for Inclusion Health, University College London, London, UK.
| | - Isobel Braithwaite
- UCL Public Health Data Science Research Group, Institute of Health Informatics, University College London, London, UK
| | - Miriam Bullock
- UCL Collaborative Centre for Inclusion Health, University College London, London, UK
| | - Max T Eyre
- Centre for Health Informatics, Computing, and Statistics, Lancaster University Medical School, Lancaster, UK
| | - Peter J White
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK; Modelling and Economics Unit, National Infection Service, Public Health England, London, UK
| | - Robert W Aldridge
- UCL Public Health Data Science Research Group, Institute of Health Informatics, University College London, London, UK
| | - Alistair Story
- UCL Collaborative Centre for Inclusion Health, University College London, London, UK; Find and Treat, University College London Hospitals NHS Foundation Trust, London, UK
| | - Andrew C Hayward
- UCL Collaborative Centre for Inclusion Health, University College London, London, UK
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Abstract
Evidence for the use of automated or partly automated contact-tracing tools to contain severe acute respiratory syndrome coronavirus 2 is scarce. We did a systematic review of automated or partly automated contact tracing. We searched PubMed, EMBASE, OVID Global Health, EBSCO Medical COVID Information Portal, Cochrane Library, medRxiv, bioRxiv, arXiv, and Google Advanced for articles relevant to COVID-19, severe acute respiratory syndrome, Middle East respiratory syndrome, influenza, or Ebola virus, published from Jan 1, 2000, to April 14, 2020. We also included studies identified through professional networks up to April 30, 2020. We reviewed all full-text manuscripts. Primary outcomes were the number or proportion of contacts (or subsequent cases) identified. Secondary outcomes were indicators of outbreak control, uptake, resource use, cost-effectiveness, and lessons learnt. This study is registered with PROSPERO (CRD42020179822). Of the 4036 studies identified, 110 full-text studies were reviewed and 15 studies were included in the final analysis and quality assessment. No empirical evidence of the effectiveness of automated contact tracing (regarding contacts identified or transmission reduction) was identified. Four of seven included modelling studies that suggested that controlling COVID-19 requires a high population uptake of automated contact-tracing apps (estimates from 56% to 95%), typically alongside other control measures. Studies of partly automated contact tracing generally reported more complete contact identification and follow-up compared with manual systems. Automated contact tracing could potentially reduce transmission with sufficient population uptake. However, concerns regarding privacy and equity should be considered. Well designed prospective studies are needed given gaps in evidence of effectiveness, and to investigate the integration and relative effects of manual and automated systems. Large-scale manual contact tracing is therefore still key in most contexts.
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Affiliation(s)
- Isobel Braithwaite
- UCL Public Health Data Science Research Group, Institute of Health Informatics, University College London, London, UK
| | - Thomas Callender
- Department of Applied Health Research, University College London, London, UK
| | - Miriam Bullock
- UCL Collaborative Centre for Inclusion Health, University College London, London, UK
| | - Robert W Aldridge
- UCL Public Health Data Science Research Group, Institute of Health Informatics, University College London, London, UK
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Foster JM, Beasley R, Braithwaite I, Harrison T, Holliday M, Pavord I, Reddel HK. Patient experiences of as-needed budesonide-formoterol by Turbuhaler® for treatment of mild asthma; a qualitative study. Respir Med 2020; 175:106154. [PMID: 33190085 DOI: 10.1016/j.rmed.2020.106154] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 07/29/2020] [Accepted: 09/09/2020] [Indexed: 12/24/2022]
Abstract
BACKGROUND Combination low-dose budesonide-formoterol, taken as-needed for symptom relief reduces exacerbation risk and is recommended for treatment of mild asthma. The NovelQ qualitative study explored patients' attitudes toward using this novel therapy. METHODS Adults with mild asthma using reliever-only treatment were randomised to as-needed budesonide-formoterol Turbuhaler® in a multinational, 52-week open-label randomised controlled trial (NovelSTART-ACTRN12615000999538). A subgroup were interviewed to explore their attitudes to use of as-needed budesonide-formoterol after receiving it for ≥10 months. Semi-structured interviews were conducted until saturation, audio-recorded, and thematically analysed. RESULTS Analysis of 35 participants (66% female; mean age 43.5 [range 18-74]; mean Asthma Control Questionnaire score 1.09 ± SD0.55) interviews identified 5 themes, each including both barriers and facilitators to therapy use. Themes were: 'Treatment effectiveness' i.e. how well symptoms were relieved and/or prevented; 'Lifestyle fit of the regimen' e.g. the extent to which the treatment regimen integrated into the patient's daily life; 'Attitudes toward medication use and safety' e.g. openness for new reliever treatments, beliefs about treatment necessity or side effects; 'Device attributes' e.g. perceived ease of use; and 'Doctor-patient relationship' e.g. impact of health professional support on new treatment acceptance. CONCLUSIONS A wide range of factors seem to drive the opinions of mild asthma patients on as-needed budesonide-formoterol therapy. Many patients perceived both positive and negative treatment attributes, and their individual evaluation of these attributes determined their likelihood of using it after the study. Supportive patient-physician interactions appear key to addressing patient barriers. Recommendations for patient-centred discussions, developed from this research, are provided.
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Affiliation(s)
- J M Foster
- Clinical Management Group, Woolcock Institute of Medical Research, University of Sydney, Sydney, Australia.
| | - R Beasley
- Medical Research Institute of New Zealand, Wellington, New Zealand.
| | - I Braithwaite
- Medical Research Institute of New Zealand, Wellington, New Zealand.
| | - T Harrison
- Nottingham Respiratory Medicine Unit and NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK.
| | - M Holliday
- Medical Research Institute of New Zealand, Wellington, New Zealand.
| | - I Pavord
- Respiratory Medicine Unit, Oxford Respiratory NIHR Biomedical Research Centre, University of Oxford, Oxford, UK.
| | - H K Reddel
- Clinical Management Group, Woolcock Institute of Medical Research, University of Sydney, Sydney, Australia.
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Allen M, Braithwaite I, Collinson S, Oskrochi Y, Basu A. A view from UK public health registrars on the challenges of COVID-19. Lancet 2020; 395:1830. [PMID: 32473098 PMCID: PMC7255284 DOI: 10.1016/s0140-6736(20)31058-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Accepted: 04/23/2020] [Indexed: 11/18/2022]
Affiliation(s)
| | - Isobel Braithwaite
- Institute of Health Informatics, University College London, London NW1 2DA, UK.
| | - Shelui Collinson
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | | | - Anamika Basu
- Faculty of Public Health and Policy, London School of Hygiene & Tropical Medicine, London, UK
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31
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Braithwaite I, Zhang S, Kirkbride JB, Osborn DPJ, Hayes JF. Air Pollution (Particulate Matter) Exposure and Associations with Depression, Anxiety, Bipolar, Psychosis and Suicide Risk: A Systematic Review and Meta-Analysis. Environ Health Perspect 2019; 127:126002. [PMID: 31850801 PMCID: PMC6957283 DOI: 10.1289/ehp4595] [Citation(s) in RCA: 265] [Impact Index Per Article: 53.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Revised: 11/05/2019] [Accepted: 11/08/2019] [Indexed: 05/19/2023]
Abstract
BACKGROUND Particulate air pollution's physical health effects are well known, but associations between particulate matter (PM) exposure and mental illness have not yet been established. However, there is increasing interest in emerging evidence supporting a possible etiological link. OBJECTIVES This systematic review aims to provide a comprehensive overview and synthesis of the epidemiological literature to date by investigating quantitative associations between PM and multiple adverse mental health outcomes (depression, anxiety, bipolar disorder, psychosis, or suicide). METHODS We undertook a systematic review and meta-analysis. We searched Medline, PsycINFO, and EMBASE from January 1974 to September 2017 for English-language human observational studies reporting quantitative associations between exposure to PM < 1.0 μ m in aerodynamic diameter (ultrafine particles) and PM < 2.5 and < 10 μ m in aerodynamic diameter (PM 2.5 and PM 10 , respectively) and the above psychiatric outcomes. We extracted data, appraised study quality using a published quality assessment tool, summarized methodological approaches, and conducted meta-analyses where appropriate. RESULTS Of 1,826 citations identified, 22 met our overall inclusion criteria, and we included 9 in our primary meta-analyses. In our meta-analysis of associations between long-term (> 6 months ) PM 2.5 exposure and depression (n = 5 studies), the pooled odds ratio was 1.102 per 10 - μ g / m 3 PM 2.5 increase (95% CI: 1.023, 1.189; I 2 = 0.00 % ). Two of the included studies investigating associations between long-term PM 2.5 exposure and anxiety also reported statistically significant positive associations, and we found a statistically significant association between short-term PM 10 exposure and suicide in meta-analysis at a 0-2 d cumulative exposure lag. DISCUSSION Our findings support the hypothesis of an association between long-term PM 2.5 exposure and depression, as well as supporting hypotheses of possible associations between long-term PM 2.5 exposure and anxiety and between short-term PM 10 exposure and suicide. The limited literature and methodological challenges in this field, including heterogeneous outcome definitions, exposure assessment, and residual confounding, suggest further high-quality studies are warranted to investigate potentially causal associations between air pollution and poor mental health. https://doi.org/10.1289/EHP4595.
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Affiliation(s)
- Isobel Braithwaite
- Institute for Health Informatics, University College London, London, UK
- Division of Psychiatry, University College London, London, UK
| | - Shuo Zhang
- Health Services and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience, Kings’ College London, London, UK
| | | | - David P. J. Osborn
- Division of Psychiatry, University College London, London, UK
- Camden and Islington National Health Service Foundation Trust, London, UK
| | - Joseph F. Hayes
- Division of Psychiatry, University College London, London, UK
- Camden and Islington National Health Service Foundation Trust, London, UK
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Murphy R, Stewart AW, Hancox RJ, Wall CR, Braithwaite I, Beasley R, Mitchell EA. Obesity, underweight and BMI distribution characteristics of children by gross national income and income inequality: results from an international survey. Obes Sci Pract 2018; 4:216-228. [PMID: 29951212 PMCID: PMC6009988 DOI: 10.1002/osp4.169] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2017] [Revised: 03/20/2018] [Accepted: 03/22/2018] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Economic wealth and income inequality may impact on childhood BMI distribution by affecting overconsumption of food and sedentary forms of transportation and entertainment across the whole or some of the population. OBJECTIVES To determine whether BMI distribution of children differs by gross national income (GNI) per capita and Gini index derived from World Bank data. METHODS Secondary analysis of largely self-reported height and weight data from a multi-country, cross-sectional study (ISAAC), of 77,963 children aged 6-7 (from 19 countries) and 205,388 adolescents aged 13-14 (from 36 countries), were used to examine underweight vs obesity prevalence and BMI distribution skewness, median and dispersion. RESULTS Children and adolescents from 'lower' GNI countries had higher prevalence of underweight than those from 'higher' GNI countries (6% vs 3%, p = 0.03; 2% vs 1%, p = 0.05 respectively), but the prevalence of obesity was not different (2% vs 5%, p = 0.29; 2% vs 2%, p = 0.66). BMI distribution of participants from 'higher' GNI countries had higher median, without significant difference in skewness or dispersion compared to 'lower' GNI countries (higher medians +1.1 kg/m2 for 6-7 year olds, and + 0.7 kg/m2, +1.2 kg/m2 for 13-14 year old girls and boys respectively). Gini index was not associated with underweight or obesity prevalence in either children or adolescents, nor with any BMI distribution characteristics with one exception. Adolescent girls from higher income inequality countries had a greater median BMI (+0.7 kg/m2) and a less skewed BMI distribution. CONCLUSIONS It appears that the obesogenic impact of economic prosperity affects all children similarly. Income inequality may have a gender specific effect affecting BMI distribution in adolescent girls.
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Affiliation(s)
- R. Murphy
- Department of Medicine, Faculty of Medical and Health SciencesThe University of AucklandNew Zealand
| | - A. W. Stewart
- School of Population Health, Faculty of Medical and Health SciencesThe University of AucklandNew Zealand
| | - R. J. Hancox
- Department of Preventive & Social Medicine, Dunedin School of MedicineUniversity of OtagoDunedinNew Zealand
| | - C. R. Wall
- Discipline of Nutrition and Dietetics, Faculty of Medical and Health SciencesThe University of AucklandNew Zealand
| | - I. Braithwaite
- Medical Research Institute of New ZealandWellingtonNew Zealand
| | - R. Beasley
- Medical Research Institute of New ZealandWellingtonNew Zealand
| | - E. A. Mitchell
- Department of Paediatrics: Child and Youth Health, Faculty of Medical and Health SciencesThe University of AucklandNew Zealand
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Mitchell EA, Stewart AW, Braithwaite I, Hancox RJ, Murphy R, Wall C, Beasley R. Birth weight and subsequent body mass index in children: an international cross-sectional study. Pediatr Obes 2017; 12:280-285. [PMID: 27170099 DOI: 10.1111/ijpo.12138] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2015] [Revised: 03/01/2016] [Accepted: 03/09/2016] [Indexed: 11/26/2022]
Abstract
BACKGROUND The reported association between birth weight and subsequent body mass index (BMI) is conflicting. OBJECTIVES To examine the relationship between birth weight and BMI in children aged 6-7 years. METHODS Secondary analysis of data from a multi-centre, multi-country, cross-sectional study (International Study of Asthma and Allergies in Childhood (ISAAC) Phase Three). Parents/guardians of children aged 6-7 years completed questionnaires about their children's birth weight, current height and weight and whether their mother smoked in the first year of the child's life. A general linear mixed model was used to determine the association between BMI and birth weight. RESULTS A total of 72 111 children (17 countries) were included in the analysis. There was a positive association of birth weight with BMI (for each kg increase in birth weight the BMI at 6-7 increased by 0.47 (SE 0.02) kg/m2 ; p < 0.0001) with a clear gradient by birth weight category. There was no statistically significant interaction between birth weight and Gross National Income (GNI). CONCLUSIONS There is a positive linear relationship between birth weight and BMI in 6-7 year old children, which is present in both high and low income countries.
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Affiliation(s)
- E A Mitchell
- Department of Paediatrics, Child and Youth Health, Faculty of Medicine and Health Sciences, The University of Auckland, Auckland, New Zealand
| | - A W Stewart
- School of Population Health, The University of Auckland, Auckland, New Zealand
| | - I Braithwaite
- Medical Research Institute of New Zealand, Wellington, New Zealand
| | - R J Hancox
- Department of Preventive and Social Medicine, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand
| | - R Murphy
- Department of Medicine, Faculty of Medicine and Health Sciences, The University of Auckland, New Zealand
| | - C Wall
- Department of Nutrition, The University of Auckland, New Zealand
| | - R Beasley
- Medical Research Institute of New Zealand, Wellington, New Zealand
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Caswell-Smith R, Hosking A, Cripps T, Holweg C, Matthews J, Holliday M, Maillot C, Fingleton J, Weatherall M, Braithwaite I, Beasley R. Reference ranges for serum periostin in a population without asthma or chronic obstructive pulmonary disease. Clin Exp Allergy 2016; 46:1303-14. [PMID: 27237923 DOI: 10.1111/cea.12763] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2016] [Revised: 05/09/2016] [Accepted: 05/24/2016] [Indexed: 02/05/2023]
Abstract
BACKGROUND The clinical utility of serum periostin as a type 2 biomarker in asthma is limited by lack of reference range values derived from a population without respiratory disease. OBJECTIVE To derive age- and sex-related reference intervals for serum periostin from an adult population without asthma or COPD. METHODS Serum periostin levels were measured in 480 individuals, comprising 60 female and 60 male adults in each of the 18- to 30-year, 31- to 45-year, 46- to 60-year and 61- to 75-year age groups. Key exclusion criteria included a doctor's diagnosis of asthma, chronic bronchitis or COPD, and a history of wheezing or use of respiratory inhalers in the last 12 months. The distribution of periostin and logarithm-transformed periostin levels was derived, and 90% confidence intervals for an individual prediction were calculated. RESULTS The distribution of serum periostin was right skewed with a mean (SD) periostin of 51.2 (11.9) ng/mL, median (IQR) 50.1 (43.1 to 56.9) ng/mL and range 28.1 to 136.4 ng/mL. There was no association between logarithm periostin and age or sex, although levels were low in current smokers. The 90% confidence limits for periostin were 35.0 and 71.1 ng/mL. CONCLUSIONS AND CLINICAL RELEVANCE Serum periostin levels in adults without asthma or COPD are similar to those in adults with asthma. Serum periostin measurements do not need to be adjusted to take account of a patient's age or sex, although levels are lower in current smokers. Reference values for serum periostin levels in adults without asthma or COPD are provided.
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Affiliation(s)
- R Caswell-Smith
- Medical Research Institute of New Zealand, Wellington, New Zealand.,Victoria University of Wellington, Wellington, New Zealand
| | - A Hosking
- Medical Research Institute of New Zealand, Wellington, New Zealand.,University of Auckland, Auckland, New Zealand
| | - T Cripps
- Medical Research Institute of New Zealand, Wellington, New Zealand
| | - C Holweg
- Genentech Inc, San Francisco, CA, USA
| | | | - M Holliday
- Medical Research Institute of New Zealand, Wellington, New Zealand
| | - C Maillot
- Medical Research Institute of New Zealand, Wellington, New Zealand
| | - J Fingleton
- Medical Research Institute of New Zealand, Wellington, New Zealand
| | - M Weatherall
- Medical Research Institute of New Zealand, Wellington, New Zealand.,University of Otago, Wellington, New Zealand
| | - I Braithwaite
- Medical Research Institute of New Zealand, Wellington, New Zealand.,Victoria University of Wellington, Wellington, New Zealand.,Capital & Coast District Health Board, Wellington, New Zealand
| | - R Beasley
- Medical Research Institute of New Zealand, Wellington, New Zealand. .,Victoria University of Wellington, Wellington, New Zealand. .,Capital & Coast District Health Board, Wellington, New Zealand.
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Braithwaite I, Dunbar L, Eathorne A, Weatherall M, Beasley R. Venous thromboembolism rates in patients with lower limb immobilization after Achilles tendon injury are unchanged after the introduction of prophylactic aspirin: audit. J Thromb Haemost 2016; 14:331-5. [PMID: 26663418 DOI: 10.1111/jth.13224] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2015] [Accepted: 12/03/2015] [Indexed: 11/28/2022]
Abstract
UNLABELLED ESSENTIALS: We audited venous thromboembolism (VTE) in Achilles injuries after the use of prophylactic aspirin. We audited 218 patients with Achilles injury requiring lower limb immobilization for ≥ 1 week. Fourteen patients (6.4%, 95% CI 3.6% to 10.5%) developed symptomatic and confirmed VTE. The incidence was similar to the 6.3% identified in the same patient group prior to the use of aspirin. BACKGROUND/OBJECTIVE We report a follow-up audit of the incidence of venous thromboembolism (VTE) in patients requiring lower limb immobilization because of Achilles tendon injury, since the introduction of a policy to routinely prescribe 100 mg of aspirin daily. PATIENTS/METHODS We studied 218 patients aged 18-65 years who attended the Orthopaedic Assessment Unit at Wellington Hospital between January 2013 and December 2014 with Achilles tendon injury requiring lower limb immobilization for ≥ 1 week. Information on assessment of VTE risk, prescription of aspirin and symptomatic VTE occurring within 70 days of immobilization was obtained and compared with the same information collected with the same method in the same patient group between January 2006 and December 2007, before the policy to routinely prescribe aspirin was introduced. RESULTS A total of 189 of 218 (93%) patients were prescribed aspirin, as compared with 0.5% previously. Fourteen patients (6.4%, 95% confidence interval 3.6-10.5%) developed symptomatic radiologically confirmed VTE (10 distal deep vein thromboses [DVTs], two proximal DVTs, one pulmonary embolism [PE], and one PE with distal DVT). Aspirin was prescribed to all patients who subsequently developed a VTE; in one of 14, a recognized risk factor was documented. The VTE incidence was similar to the 6.3% identified in the previous audit. CONCLUSION Lower limb immobilization following Achilles tendon injury confers a high risk of VTE even with aspirin prophylaxis. Consideration should be given to prophylaxis with low molecular weight heparin during lower limb immobilization following Achilles tendon injury, as this has proven efficacy in this clinical situation.
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Affiliation(s)
- I Braithwaite
- Medical Research Institute of New Zealand, Wellington, New Zealand
- Victoria University of Wellington, Wellington, New Zealand
- Capital & Coast District Health Board, Wellington, New Zealand
| | - L Dunbar
- Capital & Coast District Health Board, Wellington, New Zealand
| | - A Eathorne
- Medical Research Institute of New Zealand, Wellington, New Zealand
- University of Otago, Wellington, New Zealand
| | - M Weatherall
- Capital & Coast District Health Board, Wellington, New Zealand
- University of Otago, Wellington, New Zealand
| | - R Beasley
- Medical Research Institute of New Zealand, Wellington, New Zealand
- Victoria University of Wellington, Wellington, New Zealand
- Capital & Coast District Health Board, Wellington, New Zealand
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Walpole SC, Mortimer F, Inman A, Braithwaite I, Thompson T. Exploring emerging learning needs: a UK-wide consultation on environmental sustainability learning objectives for medical education. Int J Med Educ 2015; 6:191-200. [PMID: 26702552 PMCID: PMC4691188 DOI: 10.5116/ijme.5643.62cd] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2015] [Accepted: 11/11/2015] [Indexed: 05/04/2023]
Abstract
OBJECTIVE This study aimed to engage wide-ranging stakeholders and develop consensus learning objectives for undergraduate and postgraduate medical education. METHODS A UK-wide consultation garnered opinions of healthcare students, healthcare educators and other key stakeholders about environmental sustainability in medical education. The policy Delphi approach informed this study. Draft learning objectives were revised iteratively during three rounds of consultation: online questionnaire or telephone interview, face-to-face seminar and email consultation. RESULTS Twelve draft learning objectives were developed based on review of relevant literature. In round one, 64 participants' median ratings of the learning objectives were 3.5 for relevance and 3.0 for feasibility on a Likert scale of one to four. Revisions were proposed, e.g. to highlight relevance to public health and professionalism. Thirty three participants attended round two. Conflicting opinions were explored. Added content areas included health benefits of sustainable behaviours. To enhance usability, restructuring provided three overarching learning objectives, each with subsidiary points. All participants from rounds one and two were contacted in round three, and no further edits were required. CONCLUSIONS This is the first attempt to define consensus learning objectives for medical students about environmental sustainability. Allowing a wide range of stakeholders to comment on multiple iterations of the document stimulated their engagement with the issues raised and ownership of the resulting learning objectives.
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Affiliation(s)
| | | | - Alice Inman
- Centre for Sustainable Healthcare, Oxford, UK
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Riley J, Braithwaite I, Shirtcliffe P, Caswell-Smith R, Hunt A, Bowden V, Power S, Stanley T, Crane J, Ingham T, Weatherall M, Mitchell EA, Beasley R. Randomized controlled trial of asthma risk with paracetamol use in infancy--a feasibility study. Clin Exp Allergy 2015; 45:448-56. [PMID: 25303337 DOI: 10.1111/cea.12433] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2014] [Revised: 09/03/2014] [Accepted: 09/26/2014] [Indexed: 11/29/2022]
Abstract
BACKGROUND There is non-experimental evidence that paracetamol (acetaminophen) use may increase the risk of developing asthma. However, numerous methodological issues need to be resolved before undertaking a randomized controlled trial to investigate this hypothesis. OBJECTIVE To establish the feasibility of a randomized controlled trial of liberal paracetamol as usually given by parents/guardians vs. a comparator (restricted paracetamol in accordance with WHO guidelines, ibuprofen or placebo), and childhood asthma risk. METHODS Questionnaires were completed by parents/guardians of infants admitted to Wellington Hospital with bronchiolitis to assess views about comparator treatments. Subsequently, infants of parents/guardians who provided informed consent were randomized to restricted or liberal paracetamol use for 3 months with paracetamol use recorded. RESULTS Of 120 eligible participants, 72 (60%) parents/guardians completed the questionnaire. Ibuprofen, restricted paracetamol and placebo were acceptable to 42 (58%), 29 (40%) and 9 (12%) parents/guardians, respectively. 36 (30%) infants were randomized to restricted or liberal paracetamol. Paracetamol use was greater for the liberal vs. restricted group for reported [Hodges-Lehmann estimator of difference 0.94 mg/kg/day (95% CI 0.2-3.52), P = 0.02] and measured use [Hodges-Lehmann estimator of difference 2.11 mg/kg/day (95% CI 0.9-4.18), P = 0.004]. The median reported and measured use of paracetamol was 2.0-fold and 3.5-fold greater in the liberal vs. restricted group. CONCLUSIONS AND CLINICAL RELEVANCE Although separation in paracetamol dosing is likely to be achieved with a liberal vs. restricted paracetamol regime, ibuprofen is the preferred comparator treatment in the proposed RCT of paracetamol use and risk of asthma in childhood.
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Affiliation(s)
- J Riley
- Medical Research Institute of New Zealand, Wellington, New Zealand
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Weatherall M, Ioannides S, Braithwaite I, Beasley R. The association between paracetamol use and asthma: causation or coincidence? Clin Exp Allergy 2015; 45:108-13. [PMID: 25220564 DOI: 10.1111/cea.12410] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
A better understanding of the causation of asthma and allergic disorders could potentially lead to intervention strategies that reduce their prevalence and severity. One potential causative factor is the use of paracetamol. Most of the evidence for the link with asthma is from non-experimental studies of paracetamol exposure in utero, infancy, childhood and adult life; however, it has been difficult to rule out confounding and bias in the associations observed. The two randomized clinical trials of the effect of paracetamol in patients with asthma have been difficult to interpret, due to methodological issues. There have been no randomized controlled trials of paracetamol use and the development of asthma. Both asthma and paracetamol use are common, and so even if there is a relatively small effect of paracetamol exposure on the development of asthma or its severity, then such an effect would be of major public health significance. It is proposed that randomized controlled trials of the effect of paracetamol on the development of asthma and its severity are a high research priority.
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Affiliation(s)
- M Weatherall
- University of Otago Wellington, Wellington, New Zealand
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39
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Hancox RJ, Stewart AW, Braithwaite I, Beasley R, Murphy R, Mitchell EA. Association between breastfeeding and body mass index at age 6-7 years in an international survey. Pediatr Obes 2015; 10:283-7. [PMID: 25291239 DOI: 10.1111/ijpo.266] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2013] [Revised: 08/04/2014] [Accepted: 09/02/2014] [Indexed: 01/29/2023]
Abstract
BACKGROUND Breastfeeding is believed to reduce children's risk for obesity but data are conflicting. It is also uncertain if breastfeeding has different effects on obesity in high- and low-income countries. OBJECTIVES This study aimed to investigate the association between having been breastfed and body mass index (BMI) in 6- to 7-year-old children in a large international survey. METHODS Parents/guardians reported whether their child had been breastfed and their current height and weight. Some centres measured height and weight directly. Analyses adjusted for whether height and weight were reported or measured, child's age, sex, country gross national income and centre. RESULTS Data were available for 76,635 participants from 31 centres in 18 countries. Reported breastfeeding rates varied from 27 to 98%. After adjusting for potential confounders, the estimated BMI difference was 0.04 kg m(-2) lower among those who had been breastfed (P = 0.07). The risk for being overweight or obese was slightly lower among breastfed children (odds ratio = 0.95, P = 0.012). There was no evidence that the association between breastfeeding and BMI was different in lower income countries compared with higher income countries. CONCLUSIONS The findings suggest that breastfeeding has little impact on children's BMI. Increasing breastfeeding is unlikely to reduce the global epidemic of childhood obesity.
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Affiliation(s)
- R J Hancox
- Department of Preventive and Social Medicine, Dunedin School of Medicine, University of Otago, New Zealand
| | - A W Stewart
- School of Population Health, Faculty of Medical and Health Sciences, The University of Auckland, New Zealand
| | - I Braithwaite
- Medical Research Institute of New Zealand, Wellington, New Zealand.,Capital and Coast District Health Board, Wellington, New Zealand
| | - R Beasley
- Medical Research Institute of New Zealand, Wellington, New Zealand.,Capital and Coast District Health Board, Wellington, New Zealand
| | - R Murphy
- Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, New Zealand
| | - E A Mitchell
- Department of Paediatrics: Child and Youth Health, Faculty of Medical and Health Sciences, The University of Auckland, New Zealand
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Abstract
We report the case of a 40-year-old right-handed man who developed a right subclavian vein thrombosis due to work as a TV cameraman. He presented with a sudden onset of marked swelling and blue discolouration of his right arm 3 weeks after the most strenuous and prolonged episode of TV camera work that he had ever undertaken. This involved carrying a 9kg camera on his shoulder, with his right arm flexed and abducted, for a 60min period with provocation of severe pain and marked discomfort persisting during the subsequent 3 weeks before presentation. A clinical diagnosis of upper extremity deep vein thrombosis (UEDVT) was made, with the diagnosis confirmed by ultrasound. He was treated with catheter-induced thrombolysis and a 3 month course of anticoagulation. He was advised that his UEDVT was caused by his occupation and that he should no longer work as a cameraman. This case shows the importance of identifying any occupational cause of UEDVT.
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Affiliation(s)
- R Beasley
- Medical Research Institute of New Zealand, Wellington 6021, New Zealand, Capital and Coast District Health Board, Respiratory Medicine, Wellington 6021, New Zealand,
| | - I Braithwaite
- Medical Research Institute of New Zealand, Wellington 6021, New Zealand
| | - R Evans
- Capital and Coast District Health Board, Vascular Surgery, Wellington 6021, New Zealand
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Affiliation(s)
- Trevor Thompson
- School of Social and Community Medicine, University of Bristol, Bristol BS8 2PS, UK.
| | | | | | | | - Stefi Barna
- Norwich Medical School, University of East Anglia, Norwich, Norfolk, UK
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Braithwaite I. Bring me solutions. Assoc Med J 2014. [DOI: 10.1136/sbmj.g2886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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Pawluk A, Braithwaite I. Corporate influence on climate negotiations. Assoc Med J 2014. [DOI: 10.1136/sbmj.g2616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Murphy R, Stewart AW, Braithwaite I, Beasley R, Hancox RJ, Mitchell EA. Antibiotic treatment during infancy and increased body mass index in boys: an international cross-sectional study. Int J Obes (Lond) 2013; 38:1115-9. [PMID: 24257411 DOI: 10.1038/ijo.2013.218] [Citation(s) in RCA: 127] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2013] [Revised: 10/28/2013] [Accepted: 11/03/2013] [Indexed: 12/27/2022]
Abstract
OBJECTIVE To investigate whether antibiotic exposure during the first year of life is associated with increased childhood body mass index (BMI). DESIGN Secondary analysis from a multi-centre, multi-country, cross-sectional study (The International Study of Asthma and Allergies in Childhood Phase Three). SUBJECTS A total of 74 946 children from 31 centres in 18 countries contributed data on antibiotic use in the first 12 months of life and current BMI. METHODS Parents/guardians of children aged 5-8 years completed questionnaires that included questions about their children's current height and weight, and whether in the child's first 12 months of life, they had received any antibiotics, paracetamol, were breastfed or the mother/female guardian smoked cigarettes, and whether the child had wheezed in the past 12 months. A general linear mixed model was used to determine the association of antibiotic exposure with BMI, adjusting for age, sex, centre, BMI measurement type (self-reported or measured), maternal smoking, breastfeeding, paracetamol use, gross national income and current wheeze. RESULTS There was a significant interaction between sex and early-life antibiotic exposure. Early-life antibiotic exposure was associated with increased childhood BMI in boys (+0.107 kg m(-2), P<0.0001), but not in girls (-0.008 kg m(-2), P=0.75) after controlling for age, centre and BMI measurement type. The association remained in boys (+0.104 kg m(-2), P<0.0007), after adjustment for maternal smoking, breastfeeding, paracetamol use and current wheeze. There was no interaction between age, maternal smoking, breastfeeding, paracetamol use, gross national income and current wheeze in the association between early antibiotic exposure and BMI. CONCLUSIONS Exposure to antibiotics during the first 12 months of life is associated with a small increase in BMI in boys aged 5-8 years in this large international cross-sectional survey. By inference this provides additional support for the importance of gut microbiota in modulating the risk of obesity, with a sex-specific effect.
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Affiliation(s)
- R Murphy
- Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
| | - A W Stewart
- School of Population Health, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
| | - I Braithwaite
- Medical Research Institute of New Zealand, Newtown, New Zealand
| | - R Beasley
- Medical Research Institute of New Zealand, Newtown, New Zealand
| | - R J Hancox
- Department of Preventive and Social Medicine, Dunedin School of Medicine, University of Otago, Otago, New Zealand
| | - E A Mitchell
- Department of Paediatrics: Child and Youth Health, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
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Braithwaite I. Climate change, health, and the NHS. Assoc Med J 2013. [DOI: 10.1136/sbmj.f1755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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46
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Naqvi SG, Iqbal S, Reynolds T, Braithwaite I, Banim R. Is a lateral view essential in management of hip fracture? Eur J Radiol 2012; 81:3394-6. [DOI: 10.1016/j.ejrad.2012.03.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2011] [Accepted: 03/18/2012] [Indexed: 10/28/2022]
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Abstract
Individuals with severe injuries were investigated 5 years after the traumatic events, and predictors of anxiety and depression disorders were identified. Trauma victims were selected who had an Injury Severity Score of > or = 16 and were brought to all hospitals in the Mersey region and North Wales over 1 year. The 212 patients aged > or = 15 years who left the hospital alive and lived within an accessible distance of the study hospital in Warrington were contacted 5 years later and 158 (74.5%) received follow-up assessment. Thirty-eight subjects (36.9%) reported "definite" anxiety and/or depression disorders and, of these, only 21.1% reported taking psychotropic medications. Factors associated with anxiety and/or depression disorders at follow-up were: sequelae of head injury (i.e., cognitive problems, posttraumatic seizures, facial pain): writing impairment: disability due to thorax problems; and a new trauma during follow-up. Initial severity or types of injuries and overall residual disability rated by the investigator were not strong predictors of anxiety and/or depression disorders at follow-up.
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Affiliation(s)
- M Piccinelli
- Servizio di Psicologia Medica, Universitá di Verona, Italy
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Abstract
This study aimed to identify the morphological abnormalities of the intervertebral disc, as demonstrated by lumbar discography, that are associated with pain radiation to the hip, groin, buttock or lower limb. We carried out a retrospective review of 99 consecutive lumbar discogram reports. The association of disc degeneration, annular tears (partial or full thickness) and the level of disc injected was determined with respect to the presence and pattern of radiating pain. A total of 260 discs were injected, of which 179 were considered abnormal. Posterior annular tears were demonstrated in 84 discs, anterior annular tears in 15 discs and 45 discs had both anterior and posterior tears. A significant association was identified between isolated posterior tears and the production of concordant radiating pain (P = 0.0041). No difference was identified between partial thickness posterior tears and full thickness posterior tears associated with leak of contrast medium, with regard to radiating pain. Similarly, there was no significant association between disc level injected and the pattern of pain radiation. The results indicate that pain experienced in the buttock, hip, groin or lower limb can arise from the posterior annulus of the intervertebral disc without direct involvement of the nerve root.
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Affiliation(s)
- A Saifuddin
- Department of Radiology, The Royal National Orthopaedic Hospital Trust, Middlesex, UK
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Braithwaite I, White J, Saifuddin A, Renton P, Taylor BA. Vertebral end-plate (Modic) changes on lumbar spine MRI: correlation with pain reproduction at lumbar discography. Eur Spine J 1998; 7:363-8. [PMID: 9840468 PMCID: PMC3611292 DOI: 10.1007/s005860050091] [Citation(s) in RCA: 250] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
The vertebral end-plate has been identified as a possible source of discogenic low back pain. MRI demonstrates end-plate (Modic) changes in 20-50% of patients with low back pain. The aim of this study was to investigate the association between Modic changes on MRI and discogenic back pain on lumbar discography. The MRI studies and discograms of 58 patients with a clinical diagnosis of discogenic back pain were reviewed and the presence of a Modic change was correlated with pain reproduction at 152 disc levels. Twenty-three discs with adjacent Modic changes were injected, 21 of which were associated with pain reproduction. However, pain was also reproduced at 69 levels where no Modic change was seen. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for a Modic change as a marker of a painful disc were 23.3%, 96.8%, 91.3% and 46.5% respectively. Modic changes, therefore, appear to be a relatively specific but insensitive sign of a painful lumbar disc in patients with discogenic low back pain.
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Affiliation(s)
- I Braithwaite
- Department of Spinal Surgery, The Royal National Orthopaedic Hospital Trust, Stanmore, Middlesex, UK
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50
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Abstract
STUDY DESIGN Retrospective review of magnetic resonance imaging and discography in patients investigated for low back pain before spinal fusion. OBJECTIVE To determine the sensitivity of magnetic resonance imaging in the detection of painful anular tears manifested by the high-intensity zone. SUMMARY OF BACKGROUND DATA Two studies have produced results showing that magnetic resonance imaging has a high specificity for the detection of painful anular tears manifested by a high-intensity zone. However, in a recent study, results showed no significant correlation between the high-intensity zone and pain reproduction. The sensitivity of magnetic resonance imaging in identifying anular tears in a symptomatic population has not been determined. METHODS Anular tears were identified in magnetic resonance images by the presence of a high-intensity zone in the posterior anulus. The results were compared with the demonstration of painful anular tears on discogram, which has been considered the gold standard. RESULTS The study group comprised 58 patients (31 men, 27 women; mean age 42, range 21-63 years). One hundred and fifty-two discs were injected and examined by discography, and 108 were considered degenerate. Of these, 86 had anular tears (54 posterior, 6 anterior, 26 both). Seventy anular tears were associated with concordant pain provocation. Twenty-seven high-intensity zones were identified in magnetic resonance imaging, of which 24 were associated with pain reproduction by discography. The sensitivity, specificity, positive predictive value, and negative predictive value of magnetic resonance imaging in the diagnosis of concordantly painful posterior anular tears are therefore 26.7%, 95.2%, 88.9%, and 47%, respectively. CONCLUSION These results confirm that the high-intensity zone is a marker of a painful posterior anular tear. However, the usefulness of this sign is limited by low sensitivity.
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Affiliation(s)
- A Saifuddin
- Department of Radiology, Royal National Orthopaedic Hospital Trust, Stanmore, Middlesex, United Kingdom
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