Occupational characteristics associated with SARS-CoV-2 infection in the UK Biobank during August-November 2020: A cohort study

BACKGROUND: Occupational exposures may play a key role in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection risk. We used a job-exposure matrix linked to the UK Biobank to measure occupational characteristics and estimate associations with a positive SARS-CoV-2 test. METHODS: People reporting job titles at their baseline interview in England who were \u3c 65 years of age in 2020 were included. Healthcare workers were excluded because of differential access to testing. Jobs were linked to the US Occupational Information Network (O*NET) job exposure matrix. O*NET-based scores were examined for occupational physical proximity, exposure to diseases/infection, working outdoors exposed to weather, and working outdoors under cover (score range = 1-5). Jobs were classified as remote work using two algorithms. SARS-CoV-2 test results were evaluated between August 5th-November 10th, 2020, when the UK was released from lockdown. Cox regression was used to calculate adjusted hazard ratios (aHRs), accounting for age, sex, race, education, neighborhood deprivation, assessment center, household size, and income. RESULTS: We included 115,451 people with job titles, of whom 1746 tested positive for SARS-CoV-2. A one-point increase in physical proximity score was associated with 1.14 times higher risk of SARS-CoV-2 (95%CI = 1.05-1.24). A one-point increase in the exposure to diseases/infections score was associated with 1.09 times higher risk of SARS-CoV-2 (95%CI = 1.02-1.16). People reporting jobs that could not be done remotely had higher risk of SARS-CoV-2 regardless of the classification algorithm used (aHRs = 1.17 and 1.20). Outdoors work showed an association with SARS-CoV-2 (exposed to weather aHR = 1.06, 95%CI = 1.01-1.11; under cover aHR = 1.08, 95%CI = 1.00-1.17), but these associations were not significant after accounting for whether work could be done remotely. CONCLUSION: People in occupations that were not amenable to remote work, required closer physical proximity, and required more general exposure to diseases/infection had higher risk of a positive SARS-CoV-2 test. These findings provide additional evidence that coronavirus disease 2019 (COVID-19) is an occupational disease, even outside of the healthcare setting, and indicate that strategies for mitigating transmission in in-person work settings will remain important

Using Innovation-Corps (I-Corps™) methods to adapt a mobile health (mHealth) obesity treatment for community mental health settings

BACKGROUND: We employed Innovation Corps (I-Corps™) methods to adaptation of a mobile health (mHealth) short-message-system (SMS) -based interactive obesity treatment approach (iOTA) for adults with severe mentall illness receiving care in community settings. METHODS: We hypothesized jobs to be done in three broad stakeholder groups: decision makers (DM = state and community clinic administrators), clinician consumers (CC = case managers, peer supports, nurses, prescribers) and service consumers (SC = patients, peers and family members). Semistructured interviews ( RESULTS: Four themes emerged across groups: education, inertia, resources and ownership. Sub-themes in education and ownership differed between DM and CC groups on implementation ownership, intersecting with professional development, suggesting the importance of training and supervision in scalability. Sub-themes in resources and intertia differed between CC and SC groups, suggesting illness severity and access to healthy food as major barriers to engagement, whereas the SC group identified the need for enhanced emotional support, in addition to pragmatic skills like menu planning and cooking, to promote health behavior change. Although SMS was percieved as a viable education and support tool, CC and DM groups had limited familiarity with use in clinical care delivery. CONCLUSIONS: Based on customer discovery, the characteristics of a minimum viable iOTA for implementation, scalability and sustainability include population- and context-specific adaptations to treatment content, interventionist training and delivery mechanism. Successful implementation of an SMS-based intervention will likely require micro-adaptations to fit specific clinical settings