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Murphy C, Lim WW, Mills C, Wong JY, Chen D, Xie Y, Li M, Gould S, Xin H, Cheung JK, Bhatt S, Cowling BJ, Donnelly CA. Effectiveness of social distancing measures and lockdowns for reducing transmission of COVID-19 in non-healthcare, community-based settings. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2023; 381:20230132. [PMID: 37611629 PMCID: PMC10446910 DOI: 10.1098/rsta.2023.0132] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 05/23/2023] [Indexed: 08/25/2023]
Abstract
Social distancing measures (SDMs) are community-level interventions that aim to reduce person-to-person contacts in the community. SDMs were a major part of the responses first to contain, then to mitigate, the spread of SARS-CoV-2 in the community. Common SDMs included limiting the size of gatherings, closing schools and/or workplaces, implementing work-from-home arrangements, or more stringent restrictions such as lockdowns. This systematic review summarized the evidence for the effectiveness of nine SDMs. Almost all of the studies included were observational in nature, which meant that there were intrinsic risks of bias that could have been avoided were conditions randomly assigned to study participants. There were no instances where only one form of SDM had been in place in a particular setting during the study period, making it challenging to estimate the separate effect of each intervention. The more stringent SDMs such as stay-at-home orders, restrictions on mass gatherings and closures were estimated to be most effective at reducing SARS-CoV-2 transmission. Most studies included in this review suggested that combinations of SDMs successfully slowed or even stopped SARS-CoV-2 transmission in the community. However, individual effects and optimal combinations of interventions, as well as the optimal timing for particular measures, require further investigation. This article is part of the theme issue 'The effectiveness of non-pharmaceutical interventions on the COVID-19 pandemic: the evidence'.
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Affiliation(s)
- Caitriona Murphy
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
| | - Wey Wen Lim
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
| | - Cathal Mills
- Department of Statistics, University of Oxford, Oxford, UK
| | - Jessica Y. Wong
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
| | - Dongxuan Chen
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, New Territories, Hong Kong, People's Republic of China
| | - Yanmy Xie
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
| | - Mingwei Li
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, New Territories, Hong Kong, People's Republic of China
| | - Susan Gould
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, UK
- Tropical and Infectious Disease Unit, Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK
| | - Hualei Xin
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
| | - Justin K. Cheung
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
| | - Samir Bhatt
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Kobenhavn, Denmark
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
| | - Benjamin J. Cowling
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, New Territories, Hong Kong, People's Republic of China
| | - Christl A. Donnelly
- Department of Statistics, University of Oxford, Oxford, UK
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
- Pandemic Sciences Institute, University of Oxford, Oxford, UK
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Harris A, Maechling CR, Holl JL, McHugh M. Communities with an anchor institution have higher coronavirus vaccination rates. J Rural Health 2023; 39:61-68. [PMID: 35829624 PMCID: PMC10084273 DOI: 10.1111/jrh.12696] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
PURPOSE Anchor institutions ("anchors") are large employers, rooted in a community by reason of mission, capital, or relationships. Many anchors have encouraged coronavirus vaccination for employees and their families. Our objective was to determine whether the presence of an anchor was associated with a higher county-level vaccination rate. METHODS A cross-sectional study focused on 745 small- and mid-sized US counties. We used data from the Centers for Disease Control and Prevention, Reference USA's US Business Database, Economic Innovation Group's Distressed Communities Index database, 2021 County Health Ratings and Rankings, 2020 US Presidential Election popular vote data, and National Center for Health Statistics urban-rural classification data. We constructed 3 explanatory variables of interest: a binary variable indicating whether the county had an anchor; a continuous variable representing the number of anchors within a county; and the percent of all workers in the county who were employed by an anchor. Multivariable linear regression models were adjusted for race/ethnicity, political party allegiance, rurality, economic distress, and prevalence of smoking and adult obesity. FINDINGS Counties with an anchor had vaccination rates 2.31 (P<.01) percentage points higher than those without an anchor. The number of anchors in a county was also significantly associated with higher vaccination rates. CONCLUSIONS Efforts by anchors to encourage vaccination may have been successful, and that anchors may be well positioned to amplify public health messages. However, the influence and efforts of anchors to increase vaccination did not fully mitigate disparities in vaccination rates by race, ethnicity, and political party allegiance.
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Affiliation(s)
- Alexandra Harris
- Health Sciences Integrated PhD Program, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | | | - Jane L Holl
- Department of Neurology, University of Chicago, Chicago, Illinois, USA
| | - Megan McHugh
- Department of Emergency Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
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Casjens S, Taeger D, Brüning T, Behrens T. Altered Mental Distress Among Employees From Different Occupational Groups and Industries During the COVID-19 Pandemic in Germany. J Occup Environ Med 2022; 64:874-880. [PMID: 35680647 PMCID: PMC9524512 DOI: 10.1097/jom.0000000000002595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVE Mental distress of employees from the financial, public transport, public service, and industrial sector was examined in a cross-sectional study during the second COVID-19 (coronavirus disease 2019) wave in Germany and retrospectively at its beginning. METHODS Mental distress in terms of anxiety and depression symptoms was assessed with the Patient Health Questionnaire-4. High and potential occupational SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection risk (OSIR) was defined based on job information from 1545 non-health care workers. RESULTS The risks for more severe mental distress symptoms increased threefold and twofold, respectively, among employees with high and potential OSIR compared with employees without OSIR. Mental distress severity differed by the extent of work-privacy conflicts, perceived job protection, interactions with colleagues, and overcommitment. CONCLUSIONS Reducing COVID-19 exposure through workplace protective measures, strengthening interactions among colleagues, and supporting employees with work-privacy conflicts could help better protect employees' mental health.
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