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Abstract Background Previous research has highlighted links between occupation and risk of COVID-19 transmission and suggests that occupational risk is influenced by covariates including socio-economic status, and deprivation. This study examined the perspectives of local authority teams of how changes in policy and advice, as set out in the UK government report ‘Living with COVID,’ affected COVID-19 transmission risk, response and resilience in workplace settings in Greater Manchester, an area that was disproportionately affected by the pandemic. Methods The project, which took place between August and November 2022, undertook a mixed methods approach to incorporate wide-ranging reflections of changes following the publication of ‘Living with COVID’. Quantitative data was collected from local employers (n = 149) and employees (n = 397) using online surveys, and qualitative interview data was collected from Greater Manchester local authority teams (n = 19). Results The research highlighted the inequitable impact of the pandemic on those already experiencing health inequalities, including people on more precarious employment contracts or those who were unable to work from home during the pandemic. The study found that the facilitators that helped local authorities to support employers to manage transmission included clear, detailed and timely national and local guidance, good communication, partnership working, funding, and timely access to data. Barriers to supporting employers included contradictory or confusing national guidance, structural inequalities, lack of funding, and delayed access to data. Interview participants reported that they were now utilising lessons learnt during the pandemic, along with the that partnerships developed, in order to tackle wider health issues and to prepare for future pandemics or health crises. Conclusion The findings of the study, which concur with previously published research conducted as part of the PROTECT project, highlight the importance of active reflection on the lessons learned during the course of the pandemic. The study draws on PH and EH teams’ perspectives of managing COVID-19 transmission, in an area that was disproportionately affected by the pandemic, in order to add to our understanding of the best ways to ensure preparedness for future pandemics or health crises at a national level.

Occupational use of cleaning products can cause asthma in healthcare workers but the cleaning agents responsible are not yet known. This study aimed to identify respiratory and other hazards in cleaning products on the National Health Service (NHS) supply chain online catalogue and used in the NHS. Information on cleaning products, their composition, and H-statements that identified hazard characteristics of chemical substances in them was obtained from chemical safety data sheets (SDSs). Furthermore, a quantitative structure-activity relationship model and a published asthmagen list were used to identify potential additional respiratory hazards. 473 cleaning products and 229 substances were identified. SDSs reported only 4 respiratory sensitizers but an additional 51 were suggested by the other 2 methods. In contrast, 25 respiratory irritants were identified using SDSs and only one from the asthmagen list. This comprehensive overview of cleaning agents' hazards has potential use in future risk assessment and epidemiological studies.

The IMPRoving Exposure aSSessment Methodologies for Epidemiological Studies on Pesticides (IMPRESS) project (http://www.impress-project.org/) aimed to further the understanding of the performance of pesticide exposure assessment methods (EAMs). To achieve this the IMPRESS project used two approaches to assess EAM performance, using existing and newly collected data from five studies from three different countries and use of published secondary data to undertake three meta-analyses for selected chronic health outcomes. Based on the findings of the IMPRESS project we provide in this paper insights on the overarching research question “How can exposure assessments for pesticides in epidemiological studies be improved”? Exposure assessment is a critical component of pesticide epidemiological studies. EAMs used and epidemiological practices employed need to reflect the changing nature and complexities of pesticide exposure in various occupational settings. To properly assess the association between exposure and selected health outcomes, the choice of EAM should provide a clear exposure contrast within the study population. Acquiring a practical understanding of the pesticide use practices is crucial to determine whether factors such as frequency or intensity of exposure have to be considered in planned analyses. Biomonitoring may be more beneficially applied intensively in a focussed exposure assessment analysis of a particular cohort, which can be used to determine the most relevant exposure factors within that cohort-specific context. Overall, improving pesticide exposure assessment in epidemiological studies requires a multi-disciplinary approach. A next step for the wider scientific community may be to consider the development of a decision tree to aid the selection of suitable EAMs. Such a decision tree would need to consider and be based on multiple parameters including, but not limited to, study type, health endpoint, socio-demographic context, farming system, pesticide used, and application methods.

Introduction Workplace features such as ventilation, temperature and the extent of contact are all likely to relate to personal risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Occupations relating to healthcare, social care, education, transport and food production and retail are thought to have increased risks, but the extent to which these risks are elevated and how they have varied over time is unclear. Methods We searched for population cohort studies conducted in Europe that compared coronavirus disease 2019 (COVID-19) outcomes between two or more different occupational groups. Data were extracted on relative differences between occupational groups, split into four time-periods corresponding to pandemic waves. Results We included data from 17 studies. 11 studies used SARS-CoV-2 as their outcome measure and six used COVID-19 hospitalisation and mortality. During waves one and two, the majority of studies saw elevated risks in the five groups that we looked at. Only seven studies used data from wave three onwards. Elevated risks were observed in waves three and four for social care and education workers in some studies. Conclusions Evidence relating to occupational differences in COVID-19 outcomes in Europe largely focuses on the early part of the pandemic. There is consistent evidence that the direction and magnitude of differences varied with time. Workers in the healthcare, transport and food production sectors saw highly elevated risks in the early part of the pandemic in the majority of studies but this did not appear to continue. There was evidence that elevated risks of infection in the education and social care sectors may have persisted.

Safety Data Sheets (SDSs) are used to inform downstream users of any hazardous substances in chemical products and advise on how to manage the risks from using these products. It is therefore important that information on the SDS is accurate and consistent. This study investigates the accuracy and consistency of hazard information included in the SDSs of cleaning products used in the healthcare sector in England and Wales.Data on cleaning products used in the National Health Service (NHS) in England and Wales and their chemical composition and any hazard information (as H-statements) were collected from the products’ SDSs obtained from the NHS supply online catalogue. By each hazard, mainly respiratory hazards, the number of hazardous substances specified as hazardous in all SDSs was identified. Moreover, we investigated hazard characteristics of substances identified by only SDS (at least one SDS) or only through Harmonised Classifications and Labeling (CLH) or by SDS and through CLH simultaneously.In total, 229 unique chemical substances were found in 473 cleaning products’ SDSs. All 4 respiratory sensitisiers were identified in all SDSs and through CLH. However, only 14 of the 25 respiratory irritants (56.0 %) were consistently labelled across all SDSs. Although respiratory irritation characteristics of 3 substances were classified through CLH, it was not identified by any of the relevant SDSs.Substantially incorrect and inconsistent health hazard information for the same substances was identified across SDSs. Therefore, healthcare workers and their managers may not receive accurate information on the presence of and potential for exposure to hazardous substances in the cleaning products they are using.

Abstract Background The COVID-19 pandemic had a significant impact on the operations and functionality of the public transport sector in the UK. This paper reflects on the experience of this sector through the pandemic period, and considers recommendations for any future mitigations required for either new COVID-19 waves or a different public health emergency. Methods Semi-structured interviews were carried out with public transport experts, organisational leaders, workers and passengers in two phases: Phase 1 from January to May 2021, and Phase 2 from December 2021 to February 2022. Interviews were analysed thematically. Results Using the ‘What? So What? Now What?’ reflective model, ideas are drawn out to describe (a) what changes occurred, (b) what effects these changes had on service provision as well as perceptions of risk and mitigation and (c) what lessons have been learned and how these findings can feed into pandemic preparedness for the future. Respondent reflections focussed on the importance of communication, leadership, and maintaining compliance. Conclusions The wealth of experience gained through the COVID-19 pandemic in the public transport sector is extremely valuable. Through reflection on this experience, specific recommendations are made relating to these factors, covering: maintaining links across industry, access to information and data, understanding of mitigation effectiveness, improving messaging, challenges of behavioural mitigations, and clear lines of accountability. The recommendations made on the basis of this reflective process will help to improve public health strategy within the public transport sector.

OBJECTIVES: This study investigates the associations between the Danish version of a job exposure matrix for COVID-19 (COVID-19-JEM) and Danish register-based SARS-CoV-2 infection information across three waves of the pandemic. The COVID-19-JEM consists of four dimensions on transmission: two on mitigation measures, and two on precarious work characteristics. METHODS: The study comprised 2 021 309 persons from the Danish working population between 26 February 2020 and 15 December 2021. Logistic regression models were applied to assess the associations between the JEM dimensions and overall score and SARS-CoV-2 infection across three infection waves, with peaks in March–April 2020, December–January 2021, and February–March 2022. Sex, age, household income, country of birth, wave, residential region and during wave 3 vaccination status were accounted for. RESULTS: Higher risk scores within the transmission and mitigation dimensions and the overall JEM score resulted in higher odds ratios (OR) of a SARS-CoV-2 infection. OR attenuated across the three waves with ranges of 1.08–5.09 in wave 1, 1.06–1.60 in wave 2, and 1.05–1.45 in those not (fully) vaccinated in wave 3. In wave 3, no associations were found for those fully vaccinated. In all waves, the two precarious work dimensions showed weaker or inversed associations. CONCLUSIONS: The COVID-19-JEM is a promising tool for assessing occupational exposure to SARS-CoV-2 and other airborne infectious agents that mainly spread between people who are in close contact with each other. However, its usefulness depends on applied restrictions and the vaccination status in the population of interest.

OBJECTIVES: COVID-19 mitigations have had a profound impact on workplaces, however, multisectoral comparisons of how work-related mitigations were applied are limited. This study aimed to investigate (i) occupational differences in the usage of key work-related mitigations over time and (ii) workers’ perceptions of these mitigations.METHODS: Employed/self-employed Virus Watch study participants (N=6279) responded to a mitigation-related online survey covering the periods of December 2020–February 2022. Logistic regression was used to investigate occupation- and time-related differences in the usage of work-related mitigation methods. Participants’ perceptions of mitigation methods were investigated descriptively using proportions.RESULTS: Usage of work-related mitigation methods differed between occupations and over time, likely reflecting variation in job roles, workplace environments, legislation and guidance. Healthcare workers had the highest predicted probabilities for several mitigations, including reporting frequent hand hygiene [predicted probability across all survey periods 0.61 (95% CI 0.56–0.66)] and always wearing face coverings [predicted probability range 0.71 (95% CI 0.66–0.75) – 0.80 (95% CI 0.76–0.84) across survey periods]. There were significant cross-occupational trends towards reduced mitigations during periods of less stringent national restrictions. The majority of participants across occupations (55–88%) agreed that most mitigations were reasonable and worthwhile even after the relaxation of national restrictions; agreement was lower for physical distancing (39–44%).CONCLUSIONS: While usage of work-related mitigations appeared to vary alongside stringency of national restrictions, agreement that most mitigations were reasonable and worthwhile remained substantial. Further investigation into the factors underlying between-occupational differences could assist pandemic planning and prevention of workplace COVID-19 transmission.

Global public transport strategies changed significantly through the pandemic to help restrict the spread of SARS-CoV-2, keep travellers and workers safe and ensure service sustainability. UK Government guidance during phases of lock-down led to greatly reduced usage. By February 2022, most restrictions lifted but the sector was struggling with wider issues including the cost of living crisis, effects of war in Ukraine, industrial action, BREXIT and staff shortages. With public transport stakeholders, we developed policy recommendations to assist the sector with recovery from the pandemic. Priorities included increasing footfall while keeping workers and passengers safe following removal of most COVID-19 restrictions, and contributing to wider agendas of societal interconnectivity, levelling up and climate goals.This paper focusses specifically on the UK, drawing on longitudinal qualitative interviews with experts, organisational representatives (including unions), transport workers and passengers conducted between January 2021 and September 2022.This longitudinal approach allowed examination of changes in opinions across the sector over time. There was a shift in perceptions and priorities regarding both COVID-19 safety and business stability. Initially the focus was on delivering/receiving an essential service while maintaining the safety of workers and travellers. However, over time, although safety in relation to potential viral spread remained (especially for experts) this became secondary to business stability (organisational leaders) and service reliability (passengers) and the wider context (COVID-19 risk, energy costs, worker shortages, travel patterns etc.) had changed significantly.Policy recommendations are made for short term recovery, preparedness for future health emergencies and longer-term sustainability of the sector.

An individual's likelihood of developing non-communicable diseases is often influenced by the types, intensities and duration of exposures at work. Job exposure matrices provide exposure estimates associated with different occupations. However, due to their time-consuming expert curation process, job exposure matrices currently cover only a subset of possible workplace exposures and may not be regularly updated. Scientific literature articles describing exposure studies provide important supporting evidence for developing and updating job exposure matrices, since they report on exposures in a variety of occupational scenarios. However, the constant growth of scientific literature is increasing the challenges of efficiently identifying relevant articles and important content within them. Natural language processing methods emulate the human process of reading and understanding texts, but in a fraction of the time. Such methods can increase the efficiency of both finding relevant documents and pinpointing specific information within them, which could streamline the process of developing and updating job exposure matrices. Named entity recognition is a fundamental natural language processing method for language understanding, which automatically identifies mentions of domain-specific concepts (named entities) in documents, e.g., exposures, occupations and job tasks. State-of-the-art machine learning models typically use evidence from an annotated corpus, i.e., a set of documents in which named entities are manually marked up (annotated) by experts, to learn how to detect named entities automatically in new documents. We have developed a novel annotated corpus of scientific articles to support machine learning based named entity recognition relevant to occupational substance exposures. Through incremental refinements to the annotation process, we demonstrate that expert annotators can attain high levels of agreement, and that the corpus can be used to train high-performance named entity recognition models. The corpus thus constitutes an important foundation for the wider development of natural language processing tools to support the study of occupational exposures.

Abstract Background UK local authorities that experienced sustained high levels of COVID-19 between 1st March 2020 and 28th February 2021 were described by the UK Scientific Advisory Group for Emergencies as areas of enduring prevalence. This research was carried out in order to examine the views of local authority Directors of Public Health, who played a crucial role in the local response to COVID-19, on reasons for sustained high levels of prevalence in some areas, alongside an investigation of the mitigation strategies that they implemented during the course of the pandemic. Methods Interviews were conducted with Directors of Public Health in 19 local authority areas across England, between July and November 2021. This included nine areas identified as areas of enduring prevalence and ten ‘comparison’ areas. Results The outcomes of this study suggests that the geographical differences in prevalence rates are strongly influenced by health inequalities. Structural factors including deprivation, employment, and housing, due to their disproportionate impact on specific groups, converged with demographic factors, including ethnicity and age, and vaccination rates, and were identified as the main drivers of enduring prevalence. There are key differences in these drivers both within and, to a lesser extent, between local authorities. Other than these structural barriers, no major differences in facilitators or barriers to COVID-19 mitigation were identified between areas of varying prevalence. The main features of successful mitigation strategies were a locally tailored approach and partnership working involving local authority departments working with local health, community, voluntary and business organisations. Conclusions This study is the first to add the voices of Directors of Public Health, who played a crucial role in the local COVID-19 response. Areas of enduring prevalence existed during the pandemic which were caused by a complex mix of structural factors related to inequalities. Participants advised that more research is needed on the effectiveness of mitigation strategies and other measures to reduce the impact of structural inequalities, to better understand the factors that drive prevalence. This would include an assessment of how these factors combine to predict transmission and how this varies between different areas.

OBJECTIVE: This study aimed to investigate the effects of occupational exposures on the risk of a positive COVID-19 test, and whether this differed across pandemic waves.METHODS: Data from 207 034 workers from The Netherlands with test data on COVID-19 from June 2020 until August 2021 were available. Occupational exposure was estimated by using the eight dimensions of a COVID-19 job exposure matrix (JEM). Personal characteristics, household composition and residence area were derived from Statistics Netherlands. A test-negative design was applied in which the risk of a positive test was analyzed in a conditional logit model.RESULTS: All eight dimensions of occupational exposure included in the JEM increased the odds of a positive test for the entire study period and three pandemic waves [OR ranging from 1.09, (95% confidence interval (CI) 1.02–1.17) to 1.77 (95% CI 1.61–1.96)]. Adjusting for a previous positive test and other covariates strongly reduced the odds to be infected, but most dimensions remained at elevated risk. Fully adjusted models showed that contaminated work spaces and face covering were mostly relevant in the first two pandemic waves, whereas income insecurity showed higher odds in the third wave. Several occupations have a higher predicted value for a positive COVID-19 test, with variation over time.Discussion Occupational exposures are associated with a higher risk of a positive test, but variations over time exist in occupations with the highest risks. These findings provide insights for interventions among workers for future pandemic waves of COVID-19 or other respiratory epidemics.

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.

Abstract Background Workers across different occupations vary in their risk of SARS-CoV-2 infection, but the direct contribution of occupation to this relationship is unclear. This study aimed to investigate how infection risk differed across occupational groups in England and Wales up to April 2022, after adjustment for potential confounding and stratification by pandemic phase. Methods Data from 15,190 employed/self-employed participants in the Virus Watch prospective cohort study were used to generate risk ratios for virologically- or serologically-confirmed SARS-CoV-2 infection using robust Poisson regression, adjusting for socio-demographic and health-related factors and non-work public activities. We calculated attributable fractions (AF) amongst the exposed for belonging to each occupational group based on adjusted risk ratios (aRR). Results Increased risk was seen in nurses (aRR = 1.44, 1.25–1.65; AF = 30%, 20–39%), doctors (aRR = 1.33, 1.08–1.65; AF = 25%, 7–39%), carers (1.45, 1.19–1.76; AF = 31%, 16–43%), primary school teachers (aRR = 1.67, 1.42- 1.96; AF = 40%, 30–49%), secondary school teachers (aRR = 1.48, 1.26–1.72; AF = 32%, 21–42%), and teaching support occupations (aRR = 1.42, 1.23–1.64; AF = 29%, 18–39%) compared to office-based professional occupations. Differential risk was apparent in the earlier phases (Feb 2020—May 2021) and attenuated later (June—October 2021) for most groups, although teachers and teaching support workers demonstrated persistently elevated risk across waves. Conclusions Occupational differences in SARS-CoV-2 infection risk vary over time and are robust to adjustment for socio-demographic, health-related, and non-workplace activity-related potential confounders. Direct investigation into workplace factors underlying elevated risk and how these change over time is needed to inform occupational health interventions.

Objective: We aim to showcase the impact of applying eight different self-reported and urinary biomarker-based exposure measures for glyphosate and mancozeb on the association with sleep problems in a study among 253 smallholder farmers in Uganda. Methods: The questionnaire-based exposure measures included: (1) the number of application days of any pesticide in the last 7 days (never, 1–2; >2 days) and six glyphosate and mancozeb-specific measures: (2) application status over the last 12 months (yes/no), (3) recent application status (never, last 7 days and last 12 months), (4) the number of application days last 12 months, (5) average exposure-intensity scores (EIS) and (6) EIS-weighted number of application days in last 12 months. Based on 384 repeated urinary biomarker concentrations of ethylene thiourea (ETU) and glyphosate from 84 farmers, we also estimated (7) average biomarker concentrations for all 253 farmers. Also in the 84 farmers the measured pre-work and post-work biomarker concentrations were used (8). Multivariable logistic regression models were used to assess the association between the exposure measures and selected Medical Outcomes Study Sleep Scale (MOS-SS) indices (6-item, sleep inadequacy and snoring). Results: We observed positive associations between (1) any pesticide application in the last 7 days with all three MOS-SS indices. Glyphosate application in the last 7 days (3) and mancozeb application in the last 12 months (3) were associated with the 6-item sleep problem index. The estimated average urinary glyphosate concentrations showed an exposure–response association with the 6-item sleep problem index and sleep inadequacy in the same direction as based on self-reported glyphosate application in the last 7 days. In the analysis with the subset of 84 farmers, both measured and modelled post-work urinary glyphosate concentration showed an association with snoring. Conclusions: Self-reported, estimated average biomarker concentrations and measured urinary biomarker exposure measures of glyphosate and mancozeb showed similar exposure–response associations with sleep outcomes.

Background Understanding how non-household activities contributed to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections under different levels of national health restrictions is vital. Methods Among adult Virus Watch participants in England and Wales, we used multivariable logistic regressions and adjusted-weighted population attributable fractions (aPAF) assessing the contribution of work, public transport, shopping, and hospitality and leisure activities to infections. Results Under restrictions, among 17,256 participants (502 infections), work [adjusted odds ratio (aOR) 2.01 (1.65–2.44), (aPAF) 30% (22–38%)] and transport [(aOR 1.15 (0.94–1.40), aPAF 5% (-3–12%)], were risk factors for SARS-CoV-2 but shopping, hospitality and leisure were not. Following the lifting of restrictions, among 11,413 participants (493 infections), work [(aOR 1.35 (1.11–1.64), aPAF 17% (6–26%)] and transport [(aOR 1.27 (1.04–1.57), aPAF 12% (2–22%)] contributed most, with indoor hospitality [(aOR 1.21 (0.98–1.48), aPAF 7% (-1–15%)] and leisure [(aOR 1.24 (1.02–1.51), aPAF 10% (1–18%)] increasing. During the Omicron variant, with individuals more socially engaged, among 11,964 participants (2335 infections), work [(aOR 1.28 (1.16–1.41), aPAF (11% (7–15%)] and transport [(aOR 1.16 (1.04–1.28), aPAF 6% (2–9%)] remained important but indoor hospitality [(aOR 1.43 (1.26–1.62), aPAF 20% (13–26%)] and leisure [(aOR 1.35 (1.22–1.48), aPAF 10% (7–14%)] dominated. Conclusions Work and public transport were important to transmissions throughout the pandemic with hospitality and leisure’s contribution increasing as restrictions were lifted, highlighting the importance of restricting leisure and hospitality alongside advising working from home, when facing a highly infectious and virulent respiratory infection.

OBJECTIVE: This study aimed to understand whether the proportionate mortality of COVID-19 for various occupational groups has varied over the pandemic. METHODS: We used the Office for National Statistics (ONS) mortality data for England and Wales. The deaths (20–64 years) were classified as either COVID-19-related using ICD-10 codes (U07.1, U07.2), or from other causes. Occupational data recorded at the time of death was coded using the SOC10 coding system into 13 groups. Three time periods (TP) were used: (i) January 2020 to September 2020; (ii) October 2020–May 2021; and (iii) June 2021–October 2021. We analyzed the data with logistic regression and compared odds of death by COVID-19 to other causes, adjusting for age, sex, deprivation, region, urban/rural and population density. RESULTS: Healthcare professionals and associates had a higher proportionate odds of COVID-19 death in TP1 compared to non-essential workers but were not observed to have increased odds thereafter. Medical support staff had increased odds of death from COVID-19 during both TP1 and TP2, but this had reduced by TP3. This latter pattern was also seen for social care, food retail and distribution, and bus and coach drivers. Taxi and cab drivers were the only group that had higher odds of death from COVID-19 compared to other causes throughout the whole period under study [TP1: odds ratio (OR) 2.42, 95% confidence interval (CI) 1.99–2.93; TP2: OR 3.15, 95% CI 2.63–3.78; TP3: OR 1.7, 95% CI 1.26–2.29]. CONCLUSION: Differences in the odds of death from COVID-19 between occupational groups has declined over the course of the pandemic, although some occupations have remained relatively high throughout.

Low-cost personal exposure monitors (PEMs) to measure personal exposure to air pollution are potentially promising tools for health research. However, their adoption requires robust validation. This study evaluated the performance of twenty-one Plume Lab Flow2s (PLFs) by comparing its air pollutant measurements, particulate matter with a diameter of 2.5 μm or less (PM2.5), 10 μm or less (PM10), and nitrogen dioxide (NO2), against several high-quality air pollution monitors under field conditions (at indoor, outdoor, and roadside locations). Correlation and regression analysis were used to evaluate measurements obtained by different PLFs against reference instrumentation. For all measured pollutants, the overall correlation coefficient between the PLFs and the reference instruments was often weak (r < 0.4). Moderate correlation was observed for one PLF unit at the indoor location and two units at the roadside location when measuring PM2.5, but not for PM10 and NO2 concentration. During periods of particularly higher pollution, 11 PLF tools showed stronger regression results (R2 values > 0.5) with one-hour and 9 PLF units with one-minute time interval. Results show that the PLF cannot be used robustly to determine high and low exposure to poor air. Therefore, the use of PLFs in research studies should be approached with caution if data quality is important to the research outputs.

OBJECTIVE: This study aimed to construct a job exposure matrix (JEM) for risk of becoming infected with the SARS-CoV-2 virus in an occupational setting. METHODS: Experts in occupational epidemiology from three European countries (Denmark, The Netherlands and the United Kingdom) defined the relevant exposure and workplace characteristics with regard to possible exposure to the SARS-CoV-2 virus. In an iterative process, experts rated the different dimensions of the COVID-19-JEM for each job title within the International Standard Classification of Occupations system 2008 (ISCO-08). Agreement scores, weighted kappas, and variances were estimated. RESULTS: The COVID-19-JEM contains four determinants of transmission risk [number of people, nature of contacts, contaminated workspaces and location (indoors or outdoors)], two mitigation measures (social distancing and face covering), and two factors for precarious work (income insecurity and proportion of migrants). Agreement scores ranged from 0.27 [95% confidence interval (CI) 0.25–0.29] for ‘migrants’ to 0.76 (95% CI 0.74–0.78) for ‘nature of contacts’. Weighted kappas indicated moderate-to-good agreement for all dimensions [ranging from 0.60 (95% CI 0.60–0.60) for ‘face covering’ to 0.80 (95% CI 0.80–0.80) for ‘contaminated workspaces’], except for ‘migrants’ (0.14 (95% CI -0.07–0.36). As country differences remained after several consensus exercises, the COVID-19-JEM also has a country-axis. CONCLUSIONS: The COVID-19-JEM assesses the risk at population level using eight dimensions related to SARS-COV-2 infections at work and will improve our ability to investigate work-related risk factors in epidemiological studies. The dimensions of the COVID-19-JEM could also be valuable for other future communicable diseases in the workplace.

ObjectiveWe aimed to use mathematical models of SARS-COV-2 to assess the potential efficacy of non-pharmaceutical interventions on transmission in the parcel delivery and logistics sector.MethodsWe devloped a network-based model of workplace contacts based on data and consultations from companies in the parcel delivery and logistics sectors. We used these in stochastic simulations of disease transmission to predict the probability of workplace outbreaks in this settings. Individuals in the model have different viral load trajectories based on SARS-CoV-2 in-host dynamics, which couple to their infectiousness and test positive probability over time, in order to determine the impact of testing and isolation measures.ResultsThe baseline model (without any interventions) showed different workplace infection rates for staff in different job roles. Based on our assumptions of contact patterns in the parcel delivery work setting we found that when a delivery driver was the index case, on average they infect only 0.14 other employees, while for warehouse and office workers this went up to 0.65 and 2.24 respectively. In the LIDD setting this was predicted to be 1.40, 0.98, and 1.34 respectively. Nonetheless, the vast majority of simulations resulted in 0 secondary cases among customers (even without contact-free delivery). Our results showed that a combination of social distancing, office staff working from home, and fixed driver pairings (all interventions carried out by the companies we consulted) reduce the risk of workplace outbreaks by 3-4 times.ConclusionThis work suggests that, without interventions, significant transmission could have occured in these workplaces, but that these posed minimal risk to customers. We found that identifying and isolating regular close-contacts of infectious individuals (i.e. house-share, carpools, or delivery pairs) is an efficient measure for stopping workplace outbreaks. Regular testing can make these isolation measures even more effective but also increases the number of staff isolating at one time. It is therefore more efficient to use these isolation measures in addition to social distancing and contact reduction interventions, rather than instead of, as these reduce both transmission and the number of people needing to isolate at one time.

There are important differences in the risk of SARS-CoV-2 infection and death depending on occupation. Infections in healthcare workers have received the most attention, and there are clearly increased risks for intensive care unit workers who are caring for COVID-19 patients. However, a number of other occupations may also be at an increased risk, particularly those which involve social care or contact with the public. A large number of data sets are available with the potential to assess occupational risks of COVID-19 incidence, severity, or mortality. We are reviewing these data sets as part of the Partnership for Research in Occupational, Transport, Environmental COVID Transmission (PROTECT) initiative, which is part of the National COVID-19 Core Studies. In this report, we review the data sets available (including the key variables on occupation and potential confounders) for examining occupational differences in SARS-CoV-2 infection and COVID-19 incidence, severity and mortality. We also discuss the possible types of analyses of these data sets and the definitions of (occupational) exposure and outcomes. We conclude that none of these data sets are ideal, and all have various strengths and weaknesses. For example, mortality data suffer from problems of coding of COVID-19 deaths, and the deaths (in England and Wales) that have been referred to the coroner are unavailable. On the other hand, testing data is heavily biased in some periods (particularly the first wave) because some occupations (e.g. healthcare workers) were tested more often than the general population. Random population surveys are, in principle, ideal for estimating population prevalence and incidence, but are also affected by non-response. Thus, any analysis of the risks in a particular occupation or sector (e.g. transport), will require a careful analysis and triangulation of findings across the various available data sets.

Abstract Background Workplace transmission is a significant contributor to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreaks. Previous studies have found that infectious illness presenteeism could contribute to outbreaks in occupational settings and identified multiple occupational and organisational risk factors. Amid the COVID-19 pandemic, it is imperative to investigate presenteeism particularly in relation to respiratory infectious disease (RID). Hence, this rapid review aims to determine the prevalence of RID-related presenteeism, including COVID-19, and examines the reported reasons and associated risk factors. Methods The review followed a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) search approach and focused on studies published in English and Chinese. Database searches included MEDLINE, EMBASE, Web of Science, China Knowledge Resource Integrated Database (CNKI) and preprint databases MedRxiv and BioRxiv. Results The search yielded 54 studies, of which four investigated COVID-19-related presenteeism. Prevalence of work presenteeism ranged from 14.1 to 55% for confirmed RID, and 6.6 to 100% for those working with suspected or subclinical RID. The included studies demonstrated that RID-related presenteeism is associated with occupation, sick pay policy, age, gender, health behaviour and perception, vaccination, peer pressure and organisational factors such as presenteeism culture. Conclusions This review demonstrates that presenteeism or non-adherence to isolation guidance is a real concern and can contribute to workplace transmissions and outbreaks. Policies which would support workers financially and improve productivity, should include a range of effective non-pharmaceutical inventions such as workplace testing, promoting occupational health services, reviewing pay and bonus schemes and clear messaging to encourage workers to stay at home when ill. Future research should focus on the more vulnerable and precarious occupational groups, and their inter-relationships, to develop comprehensive intervention programs to reduce RID-related presenteeism.

BackgroundThe incidence of thrombotic complications is high in COVID-19 patients with severe disease. As key regulators of thrombus formation, platelets likely play a crucial role as mediators of severe acute respiratory syndrome coronavirus 2 associated pathogenesis. Studies have reported that parameters reflecting platelet size, known as platelet volume indices (PVI), are raised in patients with thrombosis and can predict poor outcomes. This systematic review evaluates the potential for PVI to be used as a predictor of COVID-19 morbidity and mortality.MethodsEnglish and Chinese databases were searched electronically to identify studies reporting data on mean platelet volume, platelet distribution width or platelet-large cell ratio in COVID-19 patients. Included articles underwent a quality rating and descriptive narrative analysis.ResultsThirty-two studies were included in the systematic review. The results show a general trend for PVI to be raised in severe COVID-19 patients and non-survivors, with 14 studies reporting significant differences of baseline PVI between severe and mild disease. Nonetheless, longitudinal studies showed varying PVI trends over the course of the disease and evidence for PVI to be associated with disease progression was limited. The quality rating of 12 studies was poor, 16 were rated fair and four were good. Most studies were retrospective in design, used small study populations and did not consider confounding factors that influence platelet volume. Studies also contained technical flaws in PVI measurement, limiting the reliability of the results.ConclusionThe evidence on the clinical usefulness of PVI is greatly limited by the lack of prospective evaluation, together with technical problems in measuring PVI. Carefully designed prospective studies are warranted.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=304305, identifier CRD42022304305.

Background: Evaluating and managing exposures to chemical, physical and biological stressors, which frequently interplay with psychological stressors as well as social and behavioural aspects, is crucial for protecting human and environmental health and transitioning towards a sustainable future. Advances in our understanding of exposure rely on input from well-trained exposure scientists. However, no education programmes in Europe are currently explicitly dedicated to cover the broader range of exposure science approaches, applications, stressors and receptors. Objective: To address this challenge, a curriculum is needed that yields credible, well-defined career pathways in exposure science. Methods: Needs and conditions for advancing exposure science education in Europe were identified. As a starting point for a way forward, harmonised learning outcomes for exposure science were defined at each level of the European Qualifications Framework. The course programme coordinators were recruited for three varying courses, with respect to the course level and the proportion of the curriculum dedicated to exposure science. These courses were assessed via our systematic course review procedure. Finally, strategic objectives and actions are proposed to build exposure science education programmes. Results: The ISES Europe ‘Education, Training and Communication’ expert working group developed a framework for creating a viable exposure science curriculum. Harmonised learning outcomes were structured under eight learning levels, categorised by knowledge, skills and competence. Illustrative case studies demonstrated how education providers integrated these learning outcomes for their educational context and aligned the overall exposure science curriculum. Conclusions: The international recognition and adoption of exposure science education will enable advances in addressing global exposure science challenges for various stressors, from behavioural aspects from individual to population scale, and effective communication between exposure scientists and relevant stakeholders and policy makers, as part of the European Exposure Science Strategy 2020–2030.

We read with great interest the paper by Reuter et al (1) on the differences in risk of SARS-CoV2 infection by occupation during the first pandemic wave in Germany. Occupation has been linked with differential risks of infection (2, 3) as well as severe disease and death (4, 5). Hence, this is a potentially very important paper, advancing the evidence in relation to occupational risk factors for infection. This study makes use of an existing cohort (the German National Cohort – NAKO), with data from over 100 000 workers who were employed or self-employed and completed a COVID-19 questionnaire. SARS-CoV2 infection was assessed through a self-reported positive PCR test carried out in a doctor’s practice, test centre or in a hospital. The main analyses used a Poisson regression model to obtain incidence rates of infection by occupation, both crude and analyses adjusted for potential confounding factors (sociodemographic and employment related factors) were carried out. Based on the results of the analyses, the authors conclude that (i) there were relatively high infection rates in healthcare and personal services but also in business management and business services, (ii) there were relatively low infection rates in manufacturing and production related occupations, and (iii) there was an inverse social gradient between occupational position and risk of infection, with higher risk in occupations with advanced tertiary degrees/managers. Like other studies, these analyses found relatively high infection rates in essential occupations. However, important differences with other studies included the inverse social gradient and the relatively high infection rates in occupations with management responsibility and requiring higher degrees. The authors postulated a possible explanation for this finding, stating that managers in Germany may be at higher risk due to recreational ski trips. Although this may well be a partial explanation, we argue that there is a more likely explanation for the high rates in higher educated people and those working in the healthcare sector. These groups are more likely to have been tested, particularly during the early stage of the pandemic, compared to other occupations such as those working in manufacturing and production-related occupations. This could be due to differential access to testing due to employer requirements or financial restraints (especially at times when tests were not free for all in Germany, https://www.reuters.com/business/healthcare-pharmaceuticals/germany-offer-free-covid-19-tests-saturday-2021-11-12/) or different motivations for testing (due to lack of sick pay or self-employment). The authors estimate the infection rates using these positive tests as the numerator and the total cohort population (many of whom have never been tested) as the denominator. Therefore, if there is a differential likelihood of testing between different occupations, this would lead to bias in the results. It is relatively simple to address this problem by using a test-negative design (6, 7), which is a type of case–control approach where those with a positive test are compared to those who have tested negative (ie, excluding those who have never been tested). This has been widely used as the gold standard method for studying vaccine effectiveness (8) and is increasingly being used to study risk factors for COVID-19 infection. We would encourage the authors to carry out such analyses and present the results in their response to this letter. If, as we expect, the high relative risks in those with higher education and/or managers are reduced in these analyses, this would strongly indicate that the reported findings are primarily due to selection bias. References 1. Reuter M, Rigó M, Formazin M, Liebers F, Latza U, Castell S et al. Occupation and SARS-CoV-2 infection risk in 108 960 workers during the first pandemic wave in Germany. Scand J Work Environ Health – online first. https://doi.org/10.5271/sjweh.4037 2. Rhodes S, Wilkinson J, Pearce N, Mueller W, Cherrie M, Stocking K, et al. Occupational differences in SARS-CoV-2 infection: Analysis of the UK ONS Coronavirus (COVID-19) Infection Survey. medRxiv. 2022 https://doi.org/10.1101/2022.04.28.22273177 3. Beale S, Patel P, Rodger A, Braithwaite I, Byrne T, Fong WLE, et al. Occupation, work-related contact and SARS-CoV-2 anti-nucleocapsid serological status: findings from the Virus Watch prospective cohort study. Occup Environ Med. 2022. https://doi.org/10.1136/oemed-2021-107920 4. Nafilyan V, Pawelek P, Ayoubkhani D, Rhodes S, Pembrey L, Matz M, et al. Occupation and COVID-19 mortality in England: a national linked data study of 14.3 million adults. Occup Environ Med. 2022;79(7):433-41. https://doi.org/10.1136/oemed-2021-107818 5. Mutambudzi M, Niedzwiedz C, Macdonald EB, Leyland A, Mair F, Anderson J, et al. Occupation and risk of severe COVID-19: prospective cohort study of 120 075 UK Biobank participants. Occup Environ Med. 2021;78(5):307-14. https://doi.org/10.1136/oemed-2020-106731 6. Vandenbroucke JP, Brickley EB, Pearce N, Vandenbroucke-Grauls CMJE. The Evolving Usefulness of the Test-negative Design in Studying Risk Factors for COVID-19. Epidemiology. 2022;33(2):e7-e8. https://doi.org/10.1097/EDE.0000000000001438 7. Vandenbroucke JP, Brickley EB, Vandenbroucke-Grauls CMJE, Pearce N. A Test-Negative Design with Additional Population Controls Can Be Used to Rapidly Study Causes of the SARS-CoV-2 Epidemic. Epidemiology. 2020;31(6):836-43. https://doi.org/10.1097/EDE.0000000000001251 8. Cerqueira-Silva T, Katikireddi SV, de Araujo Oliveira V, Flores-Ortiz R, Júnior JB, Paixão ES, et al. Vaccine effectiveness of heterologous CoronaVac plus BNT162b2 in Brazil. Nature Med. 2022;28(4):838-43. https://doi.org/10.1038/s41591-022-01701-w

BackgroundThe emergence of SARS-CoV-2 triggered a chain of public health responses that radically changed our way of living and working. Non-healthcare sectors, such as the logistics sector, play a key role in such responses. This research aims to qualitatively evaluate the non-pharmaceutical interventions (NPIs) implemented in the UK logistics sector during the COVID-19 pandemic.MethodsWe conducted nine semi-structured interviews in July-August 2020 and May-June 2021. In total 11 interviewees represented six companies occupying a range of positions in the UK's logistics sector, including takeaway food delivery, large and small goods delivery and home appliance installation, and logistics technology providers. Thematic analysis was completed using NVivo12. Codes relevant to NPIs were grouped into themes and mapped deductively onto an adapted Hierarchy of Control (HoC) framework, focusing on delivery workers. Codes relevant to the implementation process of NPIs were grouped into themes/subthemes to identify key characteristics of rapid responses, and barriers and facilitators.ResultsHoC analysis suggests the sector has implemented a wide range of risk mitigation measures, with each company developing their own portfolio of measures. Contact-free delivery was the most commonly implemented measure and perceived effective. The other implemented measures included social distancing, internal contact tracing, communication and collaboration with other key stakeholders of the sector. Process evaluation identified facilitators of rapid responses including capacity to develop interventions internally, localized government support, strong external mandates, effective communication, leadership support and financial support for self-isolation, while barriers included unclear government guidance, shortage of testing capacity and supply, high costs and diversified language and cultural backgrounds. Main sustainability issues included compliance fatigue, and the possible mental health impacts of a prolonged rapid response.ConclusionsThis research identified drivers and obstacles of rapid implementation of NPIs in response to a respiratory infection pandemic. Existing implementation process models do not consider speed to respond and the absence or lack of guidance in emergency situations such as the COVID-19. We recommend the development of a rapid response model to inform the design of effective and sustainable infection prevention and control policies and to focus future research priorities.

Objective To explore the patterns of sickness absence in National Health Service (NHS) staff attributable to mental ill health during the first wave of the COVID-19 epidemic in March–July 2020.Design Case-referent analysis of a secondary dataset.Setting NHS Trusts in England.Participants Pseudonymised data on 959 356 employees who were continuously employed by NHS trusts during 1 January 2019 to 31 July 2020.Main outcome measures Trends in the burden of sickness absence due to mental ill health from 2019 to 2020 according to demographic, regional and occupational characteristics.Results Over the study period, 164 202 new sickness absence episodes for mental ill health were recorded in 12.5% (119 525) of the study sample. There was a spike of sickness absence for mental ill health in March–April 2020 (899 730 days lost) compared with 519 807 days in March–April 2019; the surge was driven by an increase in new episodes of long-term absence and had diminished by May/June 2020. The increase was greatest in those aged >60 years (227%) and among employees of Asian and Black ethnic origin (109%–136%). Among doctors and dentists, the number of days absent declined by 12.7%. The biggest increase was in London (122%) and the smallest in the East Midlands (43.7%); the variation between regions reflected the rates of COVID-19 sickness absence during the same period.Conclusion Although the COVID-19 epidemic led to an increase in sickness absence attributed to mental ill health in NHS staff, this had substantially declined by May/June 2020, corresponding with the decrease in pressures at work as the first wave of the epidemic subsided.

There are important differences in the risk of SARS-CoV-2 infection and death depending on occupation. Infections in healthcare workers have received the most attention, and there are clearly increased risks for intensive care unit workers who are caring for COVID-19 patients. However, a number of other occupations may also be at an increased risk, particularly those which involve social care or contact with the public. A large number of data sets are available with the potential to assess occupational risks of COVID-19 incidence, severity, or mortality. We are reviewing these data sets as part of the Partnership for Research in Occupational, Transport, Environmental COVID Transmission (PROTECT) initiative, which is part of the National COVID-19 Core Studies. In this report, we review the data sets available (including the key variables on occupation and potential confounders) for examining occupational differences in SARS-CoV-2 infection and COVID-19 incidence, severity and mortality. We also discuss the possible types of analyses of these data sets and the definitions of (occupational) exposure and outcomes. We conclude that none of these data sets are ideal, and all have various strengths and weaknesses. For example, mortality data suffer from problems of coding of COVID-19 deaths, and the deaths (in England and Wales) that have been referred to the coroner are unavailable. On the other hand, testing data is heavily biased in some periods (particularly the first wave) because some occupations (e.g. healthcare workers) were tested more often than the general population. Random population surveys are, in principle, ideal for estimating population prevalence and incidence, but are also affected by non-response. Thus, any analysis of the risks in a particular occupation or sector (e.g. transport), will require a careful analysis and triangulation of findings across the various available data sets.

Background: Reducing occupational ill-health from chemical and biological agents is realized primarily through the mitigation and elimination of hazardous exposures. Despite evidence of declining exposure in European and North-American workplaces, comprehensive studies of the effectiveness of workplace interventions for reducing hazardous exposure and associated work-related ill-health seem rare. We reviewed occupational intervention studies targeting exposure to chemical and biological agents, and determined trends in frequency and quality of such studies.Methods: We searched Embase, Medline, and Web of Science for peer-reviewed original articles on occupational intervention studies published 1960–2019, aimed at reducing workers' exposure to dusts, gases, fumes, or liquids of chemical, biological, or mineral nature, or workers' risks for associated health outcomes. The frequency of articles, intervention types, intervention endpoints, and study quality of published intervention studies between 1960 and 2019 and according to 10-year intervals were analyzed.Results: Of 3,663 retrieved articles, 146 intervention studies were identified and reviewed, of which 63 concerned control measures, 43 behavioral change, 28 use of personal protective equipment, and 12 workplace policies. Intervention endpoints were occupational exposures (73%), health outcomes (22%), and a combination of both (5%). Of reviewed studies, 38% involved a control group, 16% randomized the intervention, 86% were planned interventions, and 86% compared exposure or health outcomes pre and post intervention. Over time the number of intervention studies identified in this search increased from none during 1960–1969 to ~60 during 2000–2009 and 2010–2019, respectively. The study quality improved over time, with no studies during 1960–1989 that complied with the highest quality criteria. During 2000–2009 and 2010–2019 16 and 12% of studies, respectively, were judged to be of highest quality.Conclusion: Despite an improvement over the last six decades in the frequency and quality of intervention studies targeting exposure to chemicals and biological agents, the absolute number of intervention studies remains low, particularly when considering only high quality studies. Occupational exposure to chemical and biological agents is still causing excessive disease in workforces worldwide. To reduce occupational ill-health caused by these exposures, it is important to expand the evidence on (cost-)effectiveness and transferability of interventions to reduce exposure and health effects.

Abstract Background Brain tumor etiology is poorly understood. Based on their ability to pass through the blood–brain barrier, it has been hypothesized that exposure to metals may increase the risk of brain cancer. Results from the few epidemiological studies on this issue are limited and inconsistent. Methods We investigated the relationship between glioma risk and occupational exposure to five metals - lead, cadmium, nickel, chromium and iron- as well as to welding fumes, using data from the seven-country INTEROCC study. A total of 1800 incident glioma cases and 5160 controls aged 30–69 years were included in the analysis. Lifetime occupational exposure to the agents was assessed using the INTEROCC JEM, a modified version of the Finnish job exposure matrix FINJEM. Results In general, cases had a slightly higher prevalence of exposure to the various metals and welding fumes than did controls, with the prevalence among ever exposed ranging between 1.7 and 2.2% for cadmium to 10.2 and 13.6% for iron among controls and cases, respectively. However, in multivariable logistic regression analyses, there was no association between ever exposure to any of the agents and risk of glioma with odds ratios (95% confidence intervals) ranging from 0.8 (0.7–1.0) for lead to 1.1 (0.7–1.6) for cadmium. Results were consistent across models considering cumulative exposure or duration, as well as in all sensitivity analyses conducted. Conclusions Findings from this large-scale international study provide no evidence for an association between occupational exposure to any of the metals under scrutiny or welding fumes, and risk of glioma.

Nanotechnology as a key enabling technology offers great potential for economy and society, but may also bring new threats to workers´ health due to new aspects of hazard, ways of transport, nanoparticles transformation and accumulation. Even if principal paradigms of classical toxicology are probably applicable to nanostructured materials, important gaps still exist. One of the most important topics to be developed is the occupational exposure assessment with special attention paid to the exposure measurement and exposure scenarios building. This article brings insight into the state-of-the-art of the nanotechnology safety and analyses key needs in this new safety domain.

Occupational lung diseases are an important public health issue and are avoidable through preventive interventions in the workplace. Up-to-date knowledge about changes in exposure to occupational hazards as a result of technological and industrial developments is essential to the design and implementation of efficient and effective workplace preventive measures. New occupational agents with unknown respiratory health effects are constantly introduced to the market and require periodic health surveillance among exposed workers to detect early signs of adverse respiratory effects. In addition, the ageing workforce, many of whom have pre-existing respiratory conditions, poses new challenges in terms of the diagnosis and management of occupational lung diseases. Primary preventive interventions aimed to reduce exposure levels in the workplace remain pivotal for elimination of the occupational lung disease burden. To achieve this goal there is still a clear need for setting standard occupational exposure limits based on transparent evidence-based methodology, in particular for carcinogens and sensitising agents that expose large working populations to risk. The present overview, focused on the occupational lung disease burden in Europe, proposes directions for all parties involved in the prevention of occupational lung disease, from researchers and occupational and respiratory health professionals to workers and employers.

A major challenge in biomonitoring studies with members of the general public is ensuring their continued involvement throughout the necessary length of the research. The paper presents evidence on the use of community researchers, recruited from local study areas, as a mechanism for ensuring effective recruitment and retention of farmer and resident participants for a pesticides biomonitoring study. The evidence presented suggests that community researchers' abilities to build and sustain trusting relationships with participants enhanced the rigour of the study as a result of their on-the-ground responsiveness and flexibility resulting in data collection beyond targets expected.

Penconazole is a widely used fungicide in the UK; however, to date, there have been no peer-reviewed publications reporting human metabolism, excretion or biological monitoring data. The objectives of this study were to i) develop a robust analytical method, ii) determine biomarker levels in volunteers exposed to penconazole, and, finally, to iii) measure the metabolites in samples collected as part of a large investigation of rural residents’ exposure. An LC-MS/MS method was developed for penconazole and two oxidative metabolites. Three volunteers received a single oral dose of 0.03 mg/kg body weight and timed urine samples were collected and analysed. The volunteer study demonstrated that both penconazole-OH and penconazole-COOH are excreted in humans following an oral dose and are viable biomarkers. Excretion is rapid with a half-life of less than four hours. Mean recovery of the administered dose was 47% (range 33%–54%) in urine treated with glucuronidase to hydrolyse any conjugates. The results from the residents’ study showed that levels of penconazole-COOH in this population were low with >80% below the limit of detection. Future sampling strategies that include both end of exposure and next day urine samples, as well as contextual data about the route and time of exposure, are recommended.