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Restrictions on travel and in-person commercial activities in many countries (e.g., the United States, China, European countries, etc.) due to the global outbreak and rapid spread of the coronavirus disease 2019 (COVID-19) have severely impacted the global supply chain and subsequently affected freight transportation and logistics. This chapter summarizes the findings from the analysis of truck axle and weight data from existing highway detector infrastructure to investigate the impacts of COVID-19 on freight trucking activity. Three aspects of COVID-19 truck impacts were explored: drayage, long and short-haul movements, and payload characteristics. This analysis revealed disparate impacts of this pandemic on freight trucking activity because of local and foreign policies, supply chain bottlenecks, and the dynamic changes in consumer behavior. Due to the ongoing effects of COVID-19, it is not yet possible to distinguish between transient and long-term impacts on freight trucking activity. Nonetheless, a future expansion of the study area and the incorporation of other complementary data sources may provide further insights into the pandemic’s impacts on freight movement. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Introduction: Maintaining physical activity is a modifiable risk factor for cognitive impairment. However, despite numerous public health interventions, older adults do not routinely meet activity guidelines. Online interventions offer an alternative means of engaging with this group. The role of an online intervention holds particular value in the context of a global pandemic where people have become accustomed to digital living. Furthermore, such an intervention negates barriers frequently faced by older adults in attending face to face interventions, whilst providing an economically viable option. This study explored the factors which maximise engagement in an online programme to promote physical activity. Methods: A qualitative study was conducted with adults aged 50 and over. Individual were recruited through the online UK PROTECT study cohort. Four focus groups (n=21) examined key contributors to engagement with a digital programme to promote physical activity. Iterative Categorization was utilised to identify categories and themes of the focus group data. Semi-structured interviews were subsequently conducted (n=5) whereby participants were asked to comment on a concept-stage online intervention. Results: Four major themes emerged from the focus group data: interaction at the fore, incentives as foundations, fitting around me and identity is critical. The semi-structured interviews identified further key areas of programme acceptability and specific needs for enhancing engagement. Conclusions: Older adults are open to using digital physical activity programmes, with the recent COVID-19 pandemic driving an appetite for online delivery. Any interventionmust be tailored to individual usability preferences and take account of the fitness, health and lifestyle needs specific to older adults. Furthermore, the conceptual-stage intervention used in this study was found to be acceptable, with key changes needed to maximise engagement.
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BACKGROUND: Continuous positive airway pressure (CPAP) therapy is commonly used for respiratory failure due to severe COVID-19 pneumonitis, including in patients deemed not likely to benefit from invasive mechanical ventilation (nIMV). Little evidence exists demonstrating superiority over conventional oxygen therapy, whilst ward-level delivery of CPAP presents practical challenges. We sought to compare clinical outcomes of oxygen therapy versus CPAP therapy in patients with COVID-19 who were nIMV. METHODS: This retrospective multi-centre cohort evaluation included patients diagnosed with COVID-19 who were nIMV, had a treatment escalation plan of ward-level care and clinical frailty scale ≤ 6. Recruitment occurred during the first two waves of the UK COVID-19 pandemic in 2020; from 1st March to May 31st, and from 1st September to 31st December. Patients given CPAP were compared to patients receiving oxygen therapy that required FiO2 ≥0.4 for more than 12 hours at hospitals not providing ward-level CPAP. Logistic regression modelling was performed to compare 30-day mortality between treatment groups, accounting for important confounders and within-hospital clustering. FINDINGS: Seven hospitals provided data for 479 patients during the UK COVID-19 pandemic in 2020. Overall 30-day mortality was 75.6% in the oxygen group (186/246 patients) and 77.7% in the CPAP group (181/233 patients). A lack of evidence for a treatment effect persisted in the adjusted model (adjusted odds ratio 0.84 95% CI 0.57-1.23, p=0.37). 49.8% of patients receiving CPAP-therapy (118/237) chose to discontinue it. INTERPRETATION: No survival difference was found between using oxygen alone or CPAP to treat patients with severe COVID-19 who were nIMV. A high patient-initiated discontinuation rate for CPAP suggests a significant treatment burden. Further reflection is warranted on the current treatment guidance and widespread application of CPAP in this setting. FUNDING: L Pearmain is supported by the MRC (MR/R00191X/1). TW Felton is supported by the NIHR Manchester Biomedical Research Centre.
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Introduction The risk of severe morbidity after COVID-19 infection is high inolder adults (Lithander et al, 2020). Subsequent responsive UKGovernment guidance for older adults included self-isolationduring the pandemic. It is therefore hypothesised that during thepandemic older adults are inadvertently deconditioned due toiatrogenic factors such as inactivity, social isolation, hospital-avoidance and malnutrition, and present with reduced resilienceto illness and lower levels of function. The OPU continued to admitCOVID-negative, or recently termed “COVID-protected”, patientsthroughout the pandemic. Data captured prior to, and during theCOVID-19 pandemic has been compared to explore theimplications on older adults, and elicit whether they are protectedfrom the consequences of the pandemic? Method Demographic and physical function data (average 6 m gait-speed,Elderly Mobility Scale) were captured pre-and through-pandemicfor all patients admitted to a COVID-negative OPU ward over a onemonth period. Ethical review was provided through local Trustgovernance process. Results Pre-pandemic 2019 (n = 67, mean(±SD) age 82.7(±8.2) years, 61%,hospital length-of-stay (LOS) 7.9(±7.3) days, hospital mortality-rate 7.2%) and through-pandemic 2020 (n = 73, 83.1(±8.3) years,59%♀, LOS 9.0(±9.1) days, hospital mortality-rate 7.5%) datawere captured during July 2019 and May 2020 respectively. Therewere no between-group differences in age [t(-.313) = 138, p = 0.755], gender [X , 1 df, p = 0.782], LOS [t(0.78) = 134, p = 0.44], orhospital mortality-rate [X 1 df, p = 0.96]. Through-pandemicpatients had a significantly slower 6 m gait-speed (0.11(±0.05)m.s-1) than pre-pandemic (0.16(±0.24) m.s-1);[t(2.74) = 93, p = 0.007] and lower median (IQR) Elderly Mobility Scale (4(6 IQR) vs9 (12 IQR) [u = 866, p = 0.015]). Conclusion Our data indicates this relatively short period of self-isolationmight have significant implications on the physical function of older adults. The likely mechanism is iatrogenic deconditioning.Critical Public Health and policy responses are required to mitigatethese unforeseen risks by deploying prehabilitative counter-measures and accurately targeted hospital and communityrehabilitation. 2 2.
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AIM: To describe the effect of the stringent lockdown measures, introduced in the UK on 23 March 2020 to curtail the transmission of COVID-19, on glycaemic control in people with type 1 diabetes using flash glucose monitoring. METHODS: We undertook an observational study of 572 individuals with type 1 diabetes for whom paired flash glucose monitoring data were available between early March and May 2020. The primary outcome was change in flash glucose monitoring variables. We also assessed clinical variables associated with change in glycaemic control. RESULTS: Percentage of time in range increased between March and May 2020 [median (interquartile range) 53 (41-64)% vs 56 (45-68)%; P < 0.001], with associated improvements in standard deviation of glucose (P <0.001) and estimated HbA1c (P <0.001). There was a small reduction in the number of individuals meeting the hypoglycaemia target of <5% per day (64% vs 58%; P = 0.004). Comparing changes in flash glucose monitoring data from March to May in 2019 with the same period in 2020 confirmed that these differences were confined to 2020. Socio-economic deprivation was an independent predictor of a ≥5% reduction in time in range during lockdown (odds ratio 0.45 for people in the two most affluent Scottish Index of Multiple Deprivation quintiles; P <0.001). CONCLUSIONS: Lockdown was not associated with a significant deterioration in glycaemic control in people with type 1 diabetes using flash glucose monitoring. However, socio-economic deprivation appeared to increase the risk of decline in glycaemic control, which has implications for how support is focused in challenging times.