Working from home 22 months on from the beginning of COVID-19: What have we learned for the future provision of transport services?

COVID-19 has delivered an unintended positive consequence through working from home (WFH). While it may be some time until we are able to indicate, with some confidence, the impact that WFH will have on traffic congestion and crowding on public transport, there is a sense already that it is a game changer, and indeed is one of the most effective policy levers that the transport sector has had for many years in ‘managing’ the performance of the transport network. This paper draws on multiple ways of survey data that have been collected since March 2020 when the pandemic first resulted in severe restrictions in Australia. We present the evidence up to December 2021 on the incidence of WFH and how it has been received by employees and employers from the height of restrictions up to a period when restrictions were relaxed, followed by further lockdowns throughout Australia. We show what this might mean for work productivity, lifestyle, and the changing preferences for passenger modes. With a growing preference, within some occupation classes, to WFH 1 to 2 days a week, and a good spread through the weekdays, we discuss what this means for the way we analyse the impact of transport initiatives on the performance of the transport network with a particular emphasis on the growth in suburbanisation of transport improvements, less costly service and infrastructure improvements, and the changing role of public transport

What does the Quantum of Working from Home do to the Value of Commuting Time used in Transport Appraisal?

The need to recognise and account for the influence of working from home on commuting activity has never been so real as a result of the COVID-19 pandemic. Given a recognition that WFH activity during the pandemic has reduced the amount of commuting activity compared to pre-COVID-19, the inevitable question is raised as to what this might mean for some of the crucial inputs in the appraisal of transport initiatives. One critical value used in benefit-cost analysis is the value of time which converts time into monetary units in the calculation of user benefits. We are interested in whether reduced commuting activity is associated with higher or lower willing to pay to save time. We investigate this possibility with data from the Greater Sydney Metropolitan Area in late 2020 when working from home was at a high level. The findings of a higher average commuter VoT have major implications for the VoT used in transport appraisal given that time savings are the largest user benefit. We suggest a percentage adjustment required to align with the ‘new normal’ as currently known

Relationship between commuting and non-commuting travel activity under the growing incidence of working from home and people’s attitudes towards COVID-19

The COVID-19 pandemic has reshaped the way we live and travel, possibly for many years to come. The ‘New Normal’ seems to be one that is best associated with living with COVID-19 rather that ‘after COVID-19’. After a year or more since the pandemic spread throughout the world, we have amassed a significant amount of evidence on what this is likely to mean for patterns of commuting activity in a setting where working for home (WFH) is becoming a more popular and legitimate alternative to choosing a commuting mode. With WFH continuing to some extent, non-commuting travel is also likely to change as workers and their families have greater flexibility in when and to what extent they conduct their shopping, social-recreation and other non-commuting trip activity. This paper recognises that all trip purpose activity is being impacted by the pandemic and that the drivers of changing number of trips by each and every trip purpose need to be identified as a way of establishing likely future levels of frequency of all trip making. In this paper we develop a series of trip making models for workers and non-workers in New South Wales and Queensland in a metropolitan and a regional setting, using data collected in late 2020. The influence of the number of days WFH is identified as an important influence on the number of one-way weekly trips for various trip purposes, which together with socioeconomic, geographic and attitudinal variables enable us to gain an understanding of what is driving levels of trip-purpose-specific travel during the pandemic. Elasticities and simulated changes are presented as a behaviourally rich way to understand the sensitivity of influences on the frequency of travel

Time Allocation of Reduced Commuting Time during COVID-19 under Working from Home

The COVID-19 pandemic has had a significant impact on the amount of weekly commuting activity, with a commensurate increase in remote working, especially from home. The reduction in the amount of commuting time has resulted in time released for other activities. In this paper we identify the incidence of released time to paid work, unpaid work and leisure, and investigate the key drivers of this allocation. The findings are important in obtaining estimated time benefits from reduced commuting activity with such travel time being traded against work and against leisure, and what this might mean for the future travel, activity location, and lifestyle landscape

The influence of working from home on the number of commuting and non-commuting trips by workers during 2020 and 2021 pre- and post-lockdown in Australia

Since the start of 2020, we have seen major changes in the way communities operate. Mobility behaviour has been drastically impacted by work from home (WFH) and by lockdowns and restrictions in different jurisdictions. This study investigates the influence of WFH and different lockdown patterns on commuting and non-commuting trips in Australia by workers between early 2020 and late 2021. The data includes three waves of data collection to represent different lockdown periods. A multiple discrete-continuous extreme value (MDCEV) model is estimated to represent the number of one-way trips undertaken weekly with different purposes (commuting, work-related, education, shopping, personal business/social recreation), and by different modes (car, public transport, active modes). Explanatory variables include socioeconomic characteristics, location, the time period during the pandemic (i.e., waves), and latent variables. The results suggest that across all waves and jurisdictions, respondents that WFH more often are more likely to undertake relatively more shopping trips and personal business/social recreation trips, perhaps substituting these trips in replacement of their lesser commuting trips. Interestingly, all other influence held constant, individuals who are more concerned about the use of public transport are more likely to undertake commuting trips by all modes, more likely to do shopping trips, and less likely to undertake personal business/social recreation trips – suggesting they are prioritising essential trips rather than social/personal trips

Commuting mode choice and work from home in the later stages of COVID-19: Consolidating a future focussed prediction tool to inform transport and land use planning.

As COVID-19 slowly dissipated after 30 months since March 2020, working from home (WFH) continues to be popular, with support from notable numbers of employees and employers. With growing evidence that we have either reached, or appear to be close to, a level of WFH to some extent that might be described as an equilibrium outcome going forward, we need to update any travel behaviour response models that have been developed during the passage of the pandemic. This paper sets out a commuter model for each day of the week for the Greater Sydney Metropolitan Area as of September 2022 where the alternative responses are to not work, WFH, or commute by one of ten modes available. Given the probability of WFH obtained from a mixed logit model, we construct a mapping equation to establish the sources of statistical variance by origin and destination location that influence the incidence of WFH. The evidence is used as the basis of commenting on what this means for longer-term structural changes on network performance, the likely move to a greater focus on living locally, and the need or otherwise for employers to retain office space. A significant return to the office has recently been promoted by some employers, and we comment on this as to what it might mean for the future of a hybrid working location model

Eliciting preferences for continuing medication among adult patients and parents of children with attention‐deficit hyperactivity disorder

Background: Adherence to medication for attention‐deficit hyperactivity disorder (ADHD) is less than optimal. Previous studies have primarily focused on qualitative assessment of factors that influence medication adherence. Objective: This study aimed to quantify the factors that influence patient and parent preferences for continuing ADHD medication. Method: A discrete‐choice experiment was conducted to investigate preferences. Adults, and parents of children, with ADHD were presented with eight hypothetical choice tasks of three options (Medication A, Medication B, No Medication) described by six attributes related to medication outcomes. Preferences were estimated using a mixed multinomial logit model. Results: Overall, respondents' preferences (n = 216) for continuing medication were negative (mean [β] = −1.426, p < .001); however, a significant heterogeneity in preferences was observed amongst respondents (standard deviation = 0.805, p < .001). Improvements in education, aggressive behaviour, social behaviour and family functioning, and side effects and stigma, influenced respondents' decision to continue taking medication. The respondents were willing to continue medication if they experienced positive effects, but side effects (even moderate) were the strongest concern for not continuing medication. While side effects were the most important factor for both adult patients and parents of children with ADHD, improvement in education was relatively more important for adults and improvement in aggressive behaviour, social behaviour and family functioning was relatively more important for parents of children with ADHD. Parents were more likely to not continue a medication with severe side effects even at the highest level of improvement in education. Conclusions: Side effects are the most important factor that influenced preferences for continuing medication for both adults with ADHD, as well as parents of children with ADHD. While overall the respondents preferred not to take/give medication, discrete‐choice experiment showed that the relative importance of factors that influenced continuation of medications was different for the two groups. Patient and Public Involvement: Adults, and parents of children, with ADHD participated in this study by completing the online questionnaire. The questionnaire was based on findings of research in the literature, as well as earlier focus groups conducted with adults, and parents of children, with ADHD. The face validity of the questionnaire was determined by asking parents of children, and adults, with ADHD (n = 3) to complete the survey and participate in a short discussion on their understanding of the questions and their recommendations on improving the clarity of the survey

The influence of road networks on brown bear spatial distribution and habitat suitability in a human-modified landscape

Roads are human infrastructure that heavily affect wildlife, often with marked impacts on carnivores, including brown bears Ursus arctos. Here, we assessed the potential impact of road networks on the distribution of brown bears in the small, isolated and endangered Cantabrian population of north-western Spain. To ascertain whether local road networks affect brown bear spatial distribution, we first assessed potential influences on the distance of bear locations to roads using candidate models which included topographic variables, landcover types, bear age and reproductive status, traffic volume and road visibility. Then, we built two sets of habitat suitability models, both with and without roads, to discern the possible loss of habitat suitability caused by roads. The mean distance of bear locations to the nearest road was 968 804 m and the closest road was a low traffic road in 72.5% of cases. Candidate models showed little influence of our variables on bear distance to the nearest road, with the exception of elevation. Habitat suitability models revealed that road networks in our study area seem to have almost no effect on brown bear habitat suitability, except for females with yearlings during the denning season. However, this result may also be a consequence of the fact that only a small proportion (16.5%) of the cells classified as suitable bear habitats were crossed by roads, that is, most of the roads are primarily located in unsuitable bear habitats in the Cantabrian Mountains. Compared to previous studies conducted in other populations, mainly North American ones, our findings might suggest a different response of Eurasian brown bears to roads due to a longer bear-human coexistence in Europe versus North America. However, the indirect approach used in our study does not exclude other detrimental effects, for example, road mortality, increased stress and movement pattern disruption, only detectable by more direct approaches such as telemetry

Assessing Multivariate Constraints to Evolution across Ten Long-Term Avian Studies

Background In a rapidly changing world, it is of fundamental importance to understand processes constraining or facilitating adaptation through microevolution. As different traits of an organism covary, genetic correlations are expected to affect evolutionary trajectories. However, only limited empirical data are available. Methodology/Principal Findings We investigate the extent to which multivariate constraints affect the rate of adaptation, focusing on four morphological traits often shown to harbour large amounts of genetic variance and considered to be subject to limited evolutionary constraints. Our data set includes unique long-term data for seven bird species and a total of 10 populations. We estimate population-specific matrices of genetic correlations and multivariate selection coefficients to predict evolutionary responses to selection. Using Bayesian methods that facilitate the propagation of errors in estimates, we compare (1) the rate of adaptation based on predicted response to selection when including genetic correlations with predictions from models where these genetic correlations were set to zero and (2) the multivariate evolvability in the direction of current selection to the average evolvability in random directions of the phenotypic space. We show that genetic correlations on average decrease the predicted rate of adaptation by 28%. Multivariate evolvability in the direction of current selection was systematically lower than average evolvability in random directions of space. These significant reductions in the rate of adaptation and reduced evolvability were due to a general nonalignment of selection and genetic variance, notably orthogonality of directional selection with the size axis along which most (60%) of the genetic variance is found. Conclusions These results suggest that genetic correlations can impose significant constraints on the evolution of avian morphology in wild populations. This could have important impacts on evolutionary dynamics and hence population persistence in the face of rapid environmental change

A Novel Criticality Analysis Method for Assessing Obesity Treatment Efficacy

This is the final version. Available on open access from MDPI via the DOI in this recordData Availability Statement: In accordance with the General Data Protection Regulation (GDPR) guidelines, the database utilised in this study is maintained in a confidential and secure manner within the purview of the Faculty of Health and Life Sciences at Oxford Brookes University. Owing to privacy considerations, access to the dataset is restricted to authorised personnel only.Human gait is a significant indicator of overall health and well-being due to its dependence on metabolic requirements. Abnormalities in gait can indicate the presence of metabolic dysfunction, such as diabetes or obesity. However, detecting these can be challenging using classical methods, which often involve subjective clinical assessments or invasive procedures. In this work, a novel methodology known as Criticality Analysis (CA) was applied to the monitoring of the gait of teenagers with varying amounts of metabolic stress who are taking part in an clinical intervention to increase their activity and reduce overall weight. The CA approach analysed gait using inertial measurement units (IMU) by mapping the dynamic gait pattern into a nonlinear representation space. The resulting dynamic paths were then classified using a Support Vector Machine (SVM) algorithm, which is well-suited for this task due to its ability to handle nonlinear and dynamic data. The combination of the CA approach and the SVM algorithm demonstrated high accuracy and non-invasive detection of metabolic stress. It resulted in an average accuracy within the range of 78.2% to 90%. Additionally, at the group level, it was observed to improve fitness and health during the period of the intervention. Therefore, this methodology showed a great potential to be a valuable tool for healthcare professionals in detecting and monitoring metabolic stress, as well as other associated disorders.Newton Fun