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      Exploring the relationship between job characteristics and infection: Application of a COVID-19 job exposure matrix to SARS-CoV-2 infection data in the United Kingdom

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          Abstract

          Objective

          This study aimed to assess whether workplace exposures as estimated via a COVID-19 job exposure matrix (JEM) are associated with SARS-CoV-2 in the UK.

          Methods

          Data on 244 470 participants were available from the Office for National Statistics Coronavirus Infection Survey (CIS) and 16 801 participants from the Virus Watch Cohort, restricted to workers aged 20–64 years. Analysis used logistic regression models with SARS-CoV-2 as the dependent variable for eight individual JEM domains (number of workers, nature of contacts, contact via surfaces, indoor or outdoor location, ability to social distance, use of face covering, job insecurity, and migrant workers) with adjustment for age, sex, ethnicity, index of multiple deprivation (IMD), region, household size, urban versus rural area, and health conditions. Analyses were repeated for three time periods (i) February 2020 (Virus Watch)/April 2020 (CIS) to May 2021), (ii) June 2021 to November 2021, and (iii) December 2021 to January 2022.

          Results

          Overall, higher risk classifications for the first six domains tended to be associated with an increased risk of infection, with little evidence of a relationship for domains relating to proportion of workers with job insecurity or migrant workers. By time there was a clear exposure–response relationship for these domains in the first period only. Results were largely consistent across the two UK cohorts.

          Conclusions

          An exposure–response relationship exists in the early phase of the COVID-19 pandemic for number of contacts, nature of contacts, contacts via surfaces, indoor or outdoor location, ability to social distance and use of face coverings. These associations appear to have diminished over time.

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          Most cited references32

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          Persistence of coronaviruses on inanimate surfaces and their inactivation with biocidal agents

          Summary Currently, the emergence of a novel human coronavirus, SARS-CoV-2, has become a global health concern causing severe respiratory tract infections in humans. Human-to-human transmissions have been described with incubation times between 2-10 days, facilitating its spread via droplets, contaminated hands or surfaces. We therefore reviewed the literature on all available information about the persistence of human and veterinary coronaviruses on inanimate surfaces as well as inactivation strategies with biocidal agents used for chemical disinfection, e.g. in healthcare facilities. The analysis of 22 studies reveals that human coronaviruses such as Severe Acute Respiratory Syndrome (SARS) coronavirus, Middle East Respiratory Syndrome (MERS) coronavirus or endemic human coronaviruses (HCoV) can persist on inanimate surfaces like metal, glass or plastic for up to 9 days, but can be efficiently inactivated by surface disinfection procedures with 62–71% ethanol, 0.5% hydrogen peroxide or 0.1% sodium hypochlorite within 1 minute. Other biocidal agents such as 0.05–0.2% benzalkonium chloride or 0.02% chlorhexidine digluconate are less effective. As no specific therapies are available for SARS-CoV-2, early containment and prevention of further spread will be crucial to stop the ongoing outbreak and to control this novel infectious thread.
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            Ten scientific reasons in support of airborne transmission of SARS-CoV-2

            Heneghan and colleagues' systematic review, funded by WHO, published in March, 2021, as a preprint, states: “The lack of recoverable viral culture samples of SARS-CoV-2 prevents firm conclusions to be drawn about airborne transmission”. 1 This conclusion, and the wide circulation of the review's findings, is concerning because of the public health implications. If an infectious virus spreads predominantly through large respiratory droplets that fall quickly, the key control measures are reducing direct contact, cleaning surfaces, physical barriers, physical distancing, use of masks within droplet distance, respiratory hygiene, and wearing high-grade protection only for so-called aerosol-generating health-care procedures. Such policies need not distinguish between indoors and outdoors, since a gravity-driven mechanism for transmission would be similar for both settings. But if an infectious virus is mainly airborne, an individual could potentially be infected when they inhale aerosols produced when an infected person exhales, speaks, shouts, sings, sneezes, or coughs. Reducing airborne transmission of virus requires measures to avoid inhalation of infectious aerosols, including ventilation, air filtration, reducing crowding and time spent indoors, use of masks whenever indoors, attention to mask quality and fit, and higher-grade protection for health-care staff and front-line workers. 2 Airborne transmission of respiratory viruses is difficult to demonstrate directly. 3 Mixed findings from studies that seek to detect viable pathogen in air are therefore insufficient grounds for concluding that a pathogen is not airborne if the totality of scientific evidence indicates otherwise. Decades of painstaking research, which did not include capturing live pathogens in the air, showed that diseases once considered to be spread by droplets are airborne. 4 Ten streams of evidence collectively support the hypothesis that SARS-CoV-2 is transmitted primarily by the airborne route. 5 First, superspreading events account for substantial SARS-CoV-2 transmission; indeed, such events may be the pandemic's primary drivers. 6 Detailed analyses of human behaviours and interactions, room sizes, ventilation, and other variables in choir concerts, cruise ships, slaughterhouses, care homes, and correctional facilities, among other settings, have shown patterns—eg, long-range transmission and overdispersion of the basic reproduction number (R0), discussed below—consistent with airborne spread of SARS-CoV-2 that cannot be adequately explained by droplets or fomites. 6 The high incidence of such events strongly suggests the dominance of aerosol transmission. Second, long-range transmission of SARS-CoV-2 between people in adjacent rooms but never in each other's presence has been documented in quarantine hotels. 7 Historically, it was possible to prove long-range transmission only in the complete absence of community transmission. 4 Third, asymptomatic or presymptomatic transmission of SARS-CoV-2 from people who are not coughing or sneezing is likely to account for at least a third, and perhaps up to 59%, of all transmission globally and is a key way SARS-CoV-2 has spread around the world, 8 supportive of a predominantly airborne mode of transmission. Direct measurements show that speaking produces thousands of aerosol particles and few large droplets, 9 which supports the airborne route. Fourth, transmission of SARS-CoV-2 is higher indoors than outdoors 10 and is substantially reduced by indoor ventilation. 5 Both observations support a predominantly airborne route of transmission. Fifth, nosocomial infections have been documented in health-care organisations, where there have been strict contact-and-droplet precautions and use of personal protective equipment (PPE) designed to protect against droplet but not aerosol exposure. 11 Sixth, viable SARS-CoV-2 has been detected in the air. In laboratory experiments, SARS-CoV-2 stayed infectious in the air for up to 3 h with a half-life of 1·1 h. 12 Viable SARS-CoV-2 was identified in air samples from rooms occupied by COVID-19 patients in the absence of aerosol-generating health-care procedures 13 and in air samples from an infected person's car. 14 Although other studies have failed to capture viable SARS-CoV-2 in air samples, this is to be expected. Sampling of airborne virus is technically challenging for several reasons, including limited effectiveness of some sampling methods for collecting fine particles, viral dehydration during collection, viral damage due to impact forces (leading to loss of viability), reaerosolisation of virus during collection, and viral retention in the sampling equipment. 3 Measles and tuberculosis, two primarily airborne diseases, have never been cultivated from room air. 15 Seventh, SARS-CoV-2 has been identified in air filters and building ducts in hospitals with COVID-19 patients; such locations could be reached only by aerosols. 16 Eighth, studies involving infected caged animals that were connected to separately caged uninfected animals via an air duct have shown transmission of SARS-CoV-2 that can be adequately explained only by aerosols. 17 Ninth, no study to our knowledge has provided strong or consistent evidence to refute the hypothesis of airborne SARS-CoV-2 transmission. Some people have avoided SARS-CoV-2 infection when they have shared air with infected people, but this situation could be explained by a combination of factors, including variation in the amount of viral shedding between infectious individuals by several orders of magnitude and different environmental (especially ventilation) conditions. 18 Individual and environmental variation means that a minority of primary cases (notably, individuals shedding high levels of virus in indoor, crowded settings with poor ventilation) account for a majority of secondary infections, which is supported by high-quality contact tracing data from several countries.19, 20 Wide variation in respiratory viral load of SARS-CoV-2 counters arguments that SARS-CoV-2 cannot be airborne because the virus has a lower R0 (estimated at around 2·5) 21 than measles (estimated at around 15), 22 especially since R0, which is an average, does not account for the fact that only a minority of infectious individuals shed high amounts of virus. Overdispersion of R0 is well documented in COVID-19. 23 Tenth, there is limited evidence to support other dominant routes of transmission—ie, respiratory droplet or fomite.9, 24 Ease of infection between people in close proximity to each other has been cited as proof of respiratory droplet transmission of SARS-CoV-2. However, close-proximity transmission in most cases along with distant infection for a few when sharing air is more likely to be explained by dilution of exhaled aerosols with distance from an infected person. 9 The flawed assumption that transmission through close proximity implies large respiratory droplets or fomites was historically used for decades to deny the airborne transmission of tuberculosis and measles.15, 25 This became medical dogma, ignoring direct measurements of aerosols and droplets which reveal flaws such as the overwhelming number of aerosols produced in respiratory activities and the arbitrary boundary in particle size of 5 μm between aerosols and droplets, instead of the correct boundary of 100 μm.15, 25 It is sometimes argued that since respiratory droplets are larger than aerosols, they must contain more viruses. However, in diseases where pathogen concentrations have been quantified by particle size, smaller aerosols showed higher pathogen concentrations than droplets when both were measured. 15 In conclusion, we propose that it is a scientific error to use lack of direct evidence of SARS-CoV-2 in some air samples to cast doubt on airborne transmission while overlooking the quality and strength of the overall evidence base. There is consistent, strong evidence that SARS-CoV-2 spreads by airborne transmission. Although other routes can contribute, we believe that the airborne route is likely to be dominant. The public health community should act accordingly and without further delay. © 2021 Ap Garo/Phanie/Science Photo Library 2021
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              Occupation and risk of severe COVID-19: prospective cohort study of 120 075 UK Biobank participants

              To investigate severe COVID-19 risk by occupational group. Baseline UK Biobank data (2006–10) for England were linked to SARS-CoV-2 test results from Public Health England (16 March to 26 July 2020). Included participants were employed or self-employed at baseline, alive and aged <65 years in 2020. Poisson regression models were adjusted sequentially for baseline demographic, socioeconomic, work-related, health, and lifestyle-related risk factors to assess risk ratios (RRs) for testing positive in hospital or death due to COVID-19 by three occupational classification schemes (including Standard Occupation Classification (SOC) 2000). Of 120 075 participants, 271 had severe COVID-19. Relative to non-essential workers, healthcare workers (RR 7.43, 95% CI 5.52 to 10.00), social and education workers (RR 1.84, 95% CI 1.21 to 2.82) and other essential workers (RR 1.60, 95% CI 1.05 to 2.45) had a higher risk of severe COVID-19. Using more detailed groupings, medical support staff (RR 8.70, 95% CI 4.87 to 15.55), social care (RR 2.46, 95% CI 1.47 to 4.14) and transport workers (RR 2.20, 95% CI 1.21 to 4.00) had the highest risk within the broader groups. Compared with white non-essential workers, non-white non-essential workers had a higher risk (RR 3.27, 95% CI 1.90 to 5.62) and non-white essential workers had the highest risk (RR 8.34, 95% CI 5.17 to 13.47). Using SOC 2000 major groups, associate professional and technical occupations, personal service occupations and plant and machine operatives had a higher risk, compared with managers and senior officials. Essential workers have a higher risk of severe COVID-19. These findings underscore the need for national and organisational policies and practices that protect and support workers with an elevated risk of severe COVID-19.
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                Author and article information

                Journal
                Scand J Work Environ Health
                Scand J Work Environ Health
                Scandinavian Journal of Work, Environment & Health
                Nordic Association of Occupational Safety and Health (Finland )
                0355-3140
                1795-990X
                1 April 2023
                20 December 2022
                30 March 2023
                : 49
                : 3
                : 171-181
                Affiliations
                [1 ]Division of Population Health, Health Services Research & Primary Care, University of Manchester, Manchester, UK
                [2 ]Centre for Public Health Data Science, Institute of Health Informatics, University College London, UK
                [3 ]Institute of Epidemiology and Health Care, University College London, London, UK
                [4 ]Department of Medical Statistics, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
                [5 ]Institute of Occupational Medicine, Institute of Occupational Medicine, Edinburgh, UK
                [6 ]Netherlands Organisation for Applied Scientific Research TNO,Unit Healthy Living, Leiden, The Netherlands
                [7 ]Department of Public Health, Erasmus Medical Center Rotterdam, The Netherlands
                [8 ]Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands
                [9 ]Department of Occupational Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Aarhus N, Denmark
                [10 ]Department of Public Health, Research Unit for Environment, Occupation and Health, Danish Ramazzini Centre, Aarhus University, Aarhus, Denmark
                [11 ]Dutch Institution of Applied Science, TNO, Department Risk Analysis (RAPID) – Team Exposure Assessment and Risk Management, CB Utrecht, The Netherlands
                [12 ]Thomas Ashton Institute for Risk and Regulatory Research, University of Manchester, UK
                Author notes
                Correspondence to: Division of Population Health, Health Services Research & Primary Care, University of Manchester, Manchester, UK. [E-mail: sarah.a.rhodes@ 123456manchester.ac.uk ]
                Article
                SJWEH-49-171
                10.5271/sjweh.4076
                10621898
                36537299
                db08b3df-8d80-4596-b60b-0f09215da8d7
                Copyright: © Scandinavian Journal of Work, Environment & Health

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 19 September 2022
                Categories
                Original Article

                cohort,coronavirus,epidemiology,jem,occupation,virus,workplace
                cohort, coronavirus, epidemiology, jem, occupation, virus, workplace

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