Domain-Specific Physical Activity and Stroke in Sweden.

Importance: Associations of domain-specific physical activity with stroke incidence and poststroke outcomes have not been extensively studied using long-term, population-based data. Objective: To investigate associations of leisure time, work time, transport, and household physical activity with stroke incidence and death or dependency in activities of daily living (ADL) 3 months after stroke. Design, Setting, and Participants: The prospective, population-based Interplay Between Genetic Susceptibility and External Factors (INTERGENE) cohort study was conducted among a random sample of individuals from an urban-rural area covering western Sweden; 3614 individuals aged 24 to 77 years were examined in 2001 to 2004, and 1394 individuals were reexamined in 2014 to 2016. The median (range) follow-up was 20.0 years (56 days to 21.9 years). Data were analyzed from September through October 2023. Exposure: Physical activity levels were self-reported for leisure time, work time, transportation, and household domains. The mean number of steps taken over a 6-day period was collected in a subgroup of participants using a sealed pedometer. Main Outcomes and Measures: Follow-up for stroke incidence and mortality rates continued until December 31, 2022. The composite outcome of death or ADL dependency was assessed at 3 months after stroke. Results: Among 3614 individuals (mean [SD] age, 51.4 [13.1] years; 1910 female [52.9%]); 269 individuals (7.4%) developed stroke, of whom 120 individuals (44.6%) were dead or ADL dependent at 3 months. Intermediate (adjusted hazard ratio [aHR], 0.54; 95% CI, 0.38-0.77) and high (aHR, 0.47; 95% CI, 0.31-0.73) levels of leisure time physical activity were associated with a reduced incidence of stroke compared with low levels, as was an intermediate level of physical activity in transportation (aHR, 0.69; 95% CI, 0.52-0.93). High levels of leisure time physical activity were also associated with a reduced risk of poststroke death or ADL dependency (adjusted odds ratio, 0.34; 95% CI, 0.16-0.71) compared with low levels. Work time and household physical activity were not associated with stroke incidence or stroke outcomes. In exploratory subgroup analyses, there were interactions between physical activity and smoking (current smoking or smoking in the past year associated with stroke risk only in participants with low or intermediate physical activity: aHR, 2.33; 95% CI, 1.72-3.15) and family history of stroke (first-degree relative with a history of stroke associated with stroke risk only in participants with low or intermediate physical activity: aHR, 1.73; 95% CI, 1.27-2.38). Conclusions and Relevance: In this study, leisure time and transport-related physical activities were associated with a reduced risk of stroke. A high level of leisure time physical activity was also associated with a lower risk of death or ADL dependency 3 months after stroke.

Identification and classification of urban employment centers based on big data: A case study of Beijing.

The layout, scale and spatial form of urban employment centers are important guidelines for the rational layout of public service facilities such as urban transportation, medical care, and education. In this paper, we use Internet cell phone positioning data to identify the workplace and residence of users in the Beijing city area and obtain commuting data of the employed to measure the employment center system in Beijing. Firstly, the employment density distribution is generated using the data of the working places of the employed persons, and the employment centers are identified based on the employment density of Beijing. Then, we use the business registration data of employment centers to measure the industrial diversity within the employment centers by using the ecological Shannon Wiener Diversity Index, and combine the commuting links between employment centers and places of residence to measure the energy level of each employment center, analyze the hinterland and sphere of influence of each center, and finally using the industrial diversity index of employment centers and the average commuting time of employed persons, combined with the K-Means clustering algorithm, to classify the employment centers in Beijing. The employment center identification and classification method based on big data constructed in this study can help solve the limitations of the previous employment center system research in terms of center identification and commuting linkage measurement due to large spatial units and lack of commuting data to a certain extent. The study can provide reference for the regular understanding and technical analysis of employment centers and provide help for the employment multi-center system in Beijing in terms of quantifying the employment spatial structure, guiding the construction of multi-center system, and adjusting the land use rules.

Impacts of active mobility on individual health mediated by physical activities.

Active mobility, encompassing walking and cycling for transportation, is a potential solution to health issues arising from inadequate physical activity in modern society. However, the extent of active mobility's impact on individual physical activity levels, and its association with health as mediated by physical activities, is not fully quantified. This study aims to clarify the direct relationship between active mobility usage and individual health, as well as the indirect relationship mediated by physical activity, with a focus on varying levels of physical activity intensity. Utilizing data from the 2017 U.S. National Household Travel Survey (NHTS), we employed Poisson regression to predict active mobility usage based on socio-demographic and household socio-economic characteristics. A Structural Equation Model (SEM) was then used to investigate the direct and indirect effects of active mobility on individual health, mediated by physical activity. We further segmented individuals according to their intensity of physical activity to examine how such effect differs between different levels of physical activity. The study demonstrates that active mobility usage positively correlates with both the amount and intensity of physical activity. The effect of active mobility on individual health includes a direct positive effect (29% for intensity, 67.7% for amount) and an indirect effect mediated by physical activity (71% for intensity, 32.3% for amount). Notably, the mediation effect of active mobility on health is more substantial in the context of vigorous physical activities compared to light or moderate activities. Our findings reveal a significant positive influence of active mobility on individual health, encompassing both direct and indirect effects mediated by physical activities. These results quantitatively underscore the health benefits of active mobility and suggest the importance of promoting active mobility as a strategy to improve public health.

Safety performance of dedicated and preferential bus lanes using multivariate negative binomial models for Bogotá, Colombia.

Public transport priority systems such as Bus Rapid Transit (BRT) and Buses with High Level of Service (BHLS) are top-rated solutions to mobility in low-income and middle-income cities. There is scientific agreement that the safety performance level of these systems depends on their functional, operational, and infrastructure characteristics. However, there needs to be more evidence on how the different characteristics of bus corridors might influence safety. This paper aims to shed some light on this area by structuring a multivariate negative binomial model comparing crash risk on arterial roads, BRT, and BHLS corridors in Bogotá, Colombia. The analyzed infrastructure includes 712.1 km of arterial roads with standard bus service, 194.1 km of BRT network, and 135.6 km of BHLS network. The study considered crashes from 2015 to 2018 -fatalities, injuries, and property damage only- and 30 operational and infrastructure variables grouped into six classes -exposure, road design, infrastructure, public means of transport, and land use. A multicriteria process was applied for model selection, including the structure and predictive power based on [i] Akaike information criteria, [ii] K-fold cross-validation, and [iii] model parsimony. Relevant findings suggest that in terms of observed and expected accident rates and their relationship with the magnitude of exposure -logarithm of average annual traffic volumes at the peak hour (LOG_AAPHT) and the percentage of motorcycles, cars, buses, and trucks- the greatest risk of fatalities, injuries, and property damage occurs in the BHLS network. BRT network provides lower crash rates in less severe collisions while increasing injuries and fatalities. When comparing the BHLS network and the standard design of arterial roads, BHLS infrastructure, despite increasing mobility benefits, provides the lowest safety performance among the three analyzed networks. Individual factors of the study could also contribute to designing safer roads related to signalized intersection density and curvature. These findings support the unique characteristics and traffic dynamics present in the context of Bogotá that could inform and guide decisions of corresponding authorities in other highly dense urban areas from developing countries.

Life-Space Mobility, Transportation, and the Companionship Network of Members of a Hispanic Senior Center.

OBJECTIVES: Companions (i.e., friends who spend time together) are important for the well-being of older adults. Senior centers in the United States are places for older adults to participate in group activities and form and maintain companionships. However, differences in mobility and transportation may affect the ability of older adults to leverage senior center activities into actual companionships. METHODS: This social network analysis was conducted to characterize the companionship network among members of a senior center in relation to their life-space mobility and transportation resources. An exponential random graph model was estimated to identify mobility- and transportation-related correlates of the likelihood of a companionship tie among senior center members (N = 42). RESULTS: Members had an average of 2 companionships with one another (M = 2.2, SD = 2.7). Companionships were more likely for members with greater life-space mobility (p = .009), who attended the senior center more frequently (p = .004), with automobile ownership in their households (p = .034), and who were not transportation cost-burdened (i.e., spent less than 15% of their income on transportation, p = .005). Demographic characteristics, limitations on instrumental activities of daily living, and being at risk for depression were not significantly associated with the likelihood of companionships. DISCUSSION: These findings extend previous knowledge of the role of life-space mobility and transportation in supporting general social participation for older adults to include the importance of transportation and mobility for having companions within a senior center.

Transport fare and road traffic crashes in Nigeria: insights from a geographical analysis.

Road traffic crashes (RTCs) are significantly high in Nigeria with serious social and health consequences. While existing studies on RTCs have mainly focused on the effect of socio-economic, environmental, human and mechanical factors to address the high rates, the relationship between road transport fares and RTCs has been glossed over in literature. Thus, this study examines the influence of road transport fares and other covariates on RTCs. Data on RTCs and the predictors between 2017 and 2022 were obtained from the records of the National Bureau of Statistics and the Federal Road Safety Corps. Spatial statistical techniques were used for the data analysis. RTCs vary across the country, and Northern Nigeria is the hot spot. Results from the spatial analysis show that road transport fares, population density, and illiteracy rate are significant predictors of RTCs. The study recommends striking a balance between fare affordability, the quality of service provided, and the implementation of effective transportation strategies.

The role of modifiable risk factors in incident cancer in transport, rescue, and security industries.

PURPOSE: Examine the risk for site-specific incident cancer across representative transport, rescue, and security industries. METHODS: This Danish nationwide register-based study included all 302,789 workers from transport, rescue and security industries in 2001-2015 and 2,230,877 individuals aged 18-64 years from a total sample of the economically active population for comparison. We used Cox models to estimate the hazard ratios (HRs) of incident cancers. We categorized site-specific cancers by using population-attributable fraction (PAF) estimates from the previous literature. RESULTS: During an average follow-up of 13.4 years, 22,116 incident cancer cases were recorded in these industries. Compared with the reference population, the age-adjusted cancer incidence with a high PAF was higher among men in seafaring (HR 1.28; 95% CI 1.14-1.43), and land transport (HR 1.32; 95% CI: 1.26-1.37), and among women in seafaring (HR 1.26; 95% CI: 1.01-1.57), land transport (HR 1.21; 95% CI: 1.12-1.32), aviation (HR 1.22; 95% CI: 1.05-1.41), and police force (HR 1.21; 95% CI: 1.04-1.40). Overall, tobacco and physical inactivity were the most significant risk factors of cancer. CONCLUSIONS: Regardless of considerable disparities in incident cancer attributable to modifiable risk factors across industries, the total incident cancer rate was elevated in all industries in both sexes.

A randomized controlled trial investigating the effect of transport duration and age at transport on surplus dairy calves: Part II. Impact on hematological variables.

Surplus dairy calves often arrive at veal and dairy-beef rearing facilities with health and blood metabolite level abnormalities, which can affect their welfare and performance, predisposing them to future health challenges. The objective of this randomized controlled trial was to investigate the effects of transport duration and age at the time of transport on blood parameters in surplus dairy calves following 6, 12, or 16 h of continuous road transportation. All surplus calves from 5 commercial dairy farms in Ontario were enrolled and examined daily before transport (n = 175). On the day of transportation, calves were weighed, blood sampled, and randomly assigned to 6, 12, or 16 h of transportation. Blood samples were then collected immediately after transportation, as well as 24, 48, and 72 h thereafter. Serum was analyzed at a provincial diagnostic laboratory for nonesterified fatty acids (NEFA), ß-hydroxybutyric acid (BHBA), creatine kinase (CK), cholesterol, and haptoglobin. In addition, blood gas and electrolyte values were also assessed at the time of sample collection. Mixed models with repeated measures were used to assess the effects of transport duration, breed, sex, transfer of passive immunity status, weight before transportation, and age at transportation on blood parameters. Immediately following transportation, NEFA and BHBA were greater for calves transported for 12 h (Δ = 0.22 mmol/L NEFA, 95% CI = 0.15 to 0.30; Δ = 0.04 mmol/L BHBA, 95% CI = 0.02 to 0.06) and 16 h (Δ = 0.35 mmol/L NEFA, 95% CI = 0.27 to 0.42; Δ = 0.10 mmol/L BHBA, 95% CI = 0.08 to 0.11) compared with calves transported for 6 h. Glucose was lower immediately following transportation in calves transported for 16 h compared with 6 h (Δ = -15.54 mg/dL, 95% CI = -21.54 to -9.54). In addition, pH and HCO3- were lower in calves transported for 12 (Δ = -0.09 pH, 95% CI = -0.13 to -0.05; Δ = -1.59 mmol/L HCO3-, 95% CI = -2.61 to -0.56) and 16 h (Δ = -0.07 pH, 95% CI = -0.12 to -0.03; Δ = -1.95 mmol/L HCO3-, 95% CI = -2.95 to -0.95) compared with calves transported for 6 h. Calves transported between 15 and 19 d of age had a higher concentration of cholesterol and CK (Δ = 0.27 mmol/L cholesterol; 37.18 U/L CK) compared with 2- to 6-d-old calves, and calves 12 to 14 d old had greater reduction in HCO3- (Δ = -0.92 mmol/L) compared with 2- to 6-d-old calves. These findings show that transporting calves for long distances results in lower glucose concentration and suboptimal energy status, and that this effect varies based on the calf's age.

A Demand-Centric Repositioning Strategy for Bike-Sharing Systems.

Transport-sharing systems are eco-friendly and the most promising services in smart urban environments, where the booming Internet of things (IoT) technologies play an important role in the smart infrastructure. Due to the imbalanced bike distribution, bikes and stalls in the docking stations could be unavailable when needed, leading to bad customer experiences. We develop a dynamic repositioning strategy for the management of bikes in this paper, which supports dispatchers to keep stations in service. Two open datasets are examined, and the exploratory data analysis presents that there is a significant difference of travel patterns between working and non-working days, where the former has an excess demand at rush hours and the latter is usually at a low demand. To evaluate the effect when the demand outstrips a station's capacity, we propose a non-linear scaling technique to transform demand patterns and perform the clustering analysis for each of five categories obtained from the sophisticated analysis of the dataset. Our repositioning strategy is developed according to the transformed demands. Compared with the previous work, numerical simulations reveal that our strategy has a better performance for high-demand stations, and thus can substantially reduce the repositioning cost, which brings benefit to bike-sharing operators for managing the city bike system.

Correlation between mobility in mass transport and mortality due to COVID-19: A comparison of Mexico City, New York, and Madrid from a data science perspective.

In most big cities, public transports are enclosed and crowded spaces. Therefore, they are considered as one of the most important triggers of COVID-19 spread. Most of the existing research related to the mobility of people and COVID-19 spread is focused on investigating highly frequented paths by analyzing data collected from mobile devices, which mainly refer to geo-positioning records. In contrast, this paper tackles the problem by studying mass mobility. The relations between daily mobility on public transport (subway or metro) in three big cities and mortality due to COVID-19 are investigated. Data collected for these purposes come from official sources, such as the web pages of the cities' local governments. To provide a systematic framework, we applied the IBM Foundational Methodology for Data Science to the epidemiological domain of this paper. Our analysis consists of moving averages with a moving window equal to seven days so as to avoid bias due to weekly tendencies. Among the main findings of this work are: a) New York City and Madrid show similar distribution on studied variables, which resemble a Gauss bell, in contrast to Mexico City, and b) Non-pharmaceutical interventions don't bring immediate results, and reductions to the number of deaths due to COVID are observed after a certain number of days. This paper yields partial evidence for assessing the effectiveness of public policies in mitigating the COVID-19 pandemic.

Physical activity and active transportation behaviour among rural, peri-urban and urban children in Kenya, Mozambique and Nigeria: The PAAT Study.

BACKGROUND: Physical activity (PA) is associated with numerous health benefits among children and youth. However, few studies have examined how active transportation (AT) and device-based measures of PA vary within and between countries in sub-Saharan Africa. PURPOSE: This cross-sectional study sought to investigate the prevalence and correlates of AT and device-measured PA among children living in urban, peri-urban and rural areas in three African countries representing Eastern, Western and Southern regions of Africa. METHODS: 3,205 participants (53.3% girls; 46.7% boys) aged 10-12 years were recruited in Kenya, Nigeria and Mozambique. Data were collected using a child questionnaire, a parent/guardian questionnaire and PiezoRx® pedometers. ANCOVA and binary logistic regression analyses were used to examine the correlates of AT and PA while controlling for gender, age, parent education and vehicle ownership. RESULTS: Participants accumulated an average of 45.6±23.5 min/day of moderate-to-vigorous physical activity (MVPA) and 11,215±4,273 steps/day. Kenyan and Mozambican children were significantly more active than their Nigerian counterparts (p<0.001). Only 23% met the MVPA guidelines of 60 min/day. 65.1% of participants engaged in AT to school (and 67.8% for the trip back home) with no gender differences. Living in a rural area, lower parent education, lower vehicle ownership and higher motorcycle ownership were associated with higher odds of AT. Other correlates of AT were country-specific. Girls accumulated less daily MVPA than boys in all countries. MVPA was positively associated with living in less urbanized areas in Nigeria and Mozambique. In Kenya, lower parental education and AT were associated with higher MVPA. Nigerian children's daily MVPA decreased with age and the number of parent-perceived barriers to AT. CONCLUSIONS: Majority of children engaged in AT, but still failed to meet MVPA recommendations. Most correlates of AT and PA were country-specific, suggesting that strategies to encourage both behaviours should be informed by local evidence.

Beyond the dichotomy: How ride-hailing competes with and complements public transport.

Since ride-hailing has become an important travel alternative in many cities worldwide, a fervent debate is underway on whether it competes with or complements public transport services. We use Uber trip data in six cities in the United States and Europe to identify the most attractive public transport alternative for each ride. We then address the following questions: (i) How does ride-hailing travel time and cost compare to the fastest public transport alternative? (ii) What proportion of ride-hailing trips do not have a viable public transport alternative? (iii) How does ride-hailing change overall service accessibility? (iv) What is the relation between demand share and relative competition between the two alternatives? Our findings suggest that the dichotomy-competing with or complementing-is false. Though the vast majority of ride-hailing trips have a viable public transport alternative, between 20% and 40% of them have no viable public transport alternative. The increased service accessibility attributed to the inclusion of ride-hailing is greater in our US cities than in their European counterparts. Demand split is directly related to the relative competitiveness of travel times i.e. when public transport travel times are competitive ride-hailing demand share is low and vice-versa.

Space-time clustering-based method to optimize shareability in real-time ride-sharing.

Real-time ride-sharing has become popular in recent years. However, the underlying optimization problem for this service is highly complex. One of the most critical challenges when solving the problem is solution quality and computation time, especially in large-scale problems where the number of received requests is huge. In this paper, we rely on an exact solving method to ensure the quality of the solution, while using AI-based techniques to limit the number of requests that we feed to the solver. More precisely, we propose a clustering method based on a new shareability function to put the most shareable trips inside separate clusters. Previous studies only consider Spatio-temporal dependencies to do clustering on the mobility service requests, which is not efficient in finding the shareable trips. Here, we define the shareability function to consider all the different sharing states for each pair of trips. Each cluster is then managed with a proposed heuristic framework in order to solve the matching problem inside each cluster. As the method favors sharing, we present the number of sharing constraints to allow the service to choose the number of shared trips. To validate our proposal, we employ the proposed method on the network of Lyon city in France, with half-million requests in the morning peak from 6 to 10 AM. The results demonstrate that the algorithm can provide high-quality solutions in a short time for large-scale problems. The proposed clustering method can also be used for different mobility service problems such as car-sharing, bike-sharing, etc.

Assessing the impact of human mobility to predict regional excess death in Ecuador.

COVID-19 outbreaks have had high mortality in low- and middle-income countries such as Ecuador. Human mobility is an important factor influencing the spread of diseases possibly leading to a high burden of disease at the country level. Drastic control measures, such as complete lockdown, are effective epidemic controls, yet in practice one hopes that a partial shutdown would suffice. It is an open problem to determine how much mobility can be allowed while controlling an outbreak. In this paper, we use statistical models to relate human mobility to the excess death in Ecuador while controlling for demographic factors. The mobility index provided by GRANDATA, based on mobile phone users, represents the change of number of out-of-home events with respect to a benchmark date (March 2nd, 2020). The study confirms the global trend that more men are dying than expected compared to women, and that people under 30 show less deaths than expected, particularly individuals younger than 20 with a death rate reduction between 22 and 27%. The weekly median mobility time series shows a sharp decrease in human mobility immediately after a national lockdown was declared on March 17, 2020 and a progressive increase towards the pre-lockdown level within two months. Relating median mobility to excess deaths shows a lag in its effect: first, a decrease in mobility in the previous two to three weeks decreases excess death and, more novel, we found an increase of mobility variability four weeks prior increases the number of excess deaths.

When more is less: Urban disparities in access to surgical care by transportation means.

BACKGROUND: Structural factors limiting access to surgical care require elucidation. We hypothesize transportation time to hospitals with surgical capacity disproportionately burdens minority populations. METHODS: We identified hospitals with surgical capacity within a 20-mile radius of our city center. Using geocoding, we estimated travel times from each census tract to the nearest facility by car or public bus. RESULTS: For 143 tracts within the county, drive time was 13 ± 4 min and bus time was 33 ± 15 min. Only 41.2% of the population had a facility within 30 min by bus; access was further diminished for those with minority race/ethnicity and/or no insurance. Bus time was associated with percent minority population in a census tract: for each 10% increase in minority population there was a 4.3-min increase in bus time (p < 0.001) when controlling for socioeconomic status and other characteristics. CONCLUSIONS: Geographic information systems analysis has potential to identify communities with disproportionate burden to access surgical services.

Distance Between Home and the Admitting Hospital and Its Effect on Survival of Low Socioeconomic Status Population With Staphylococcus aureus Bacteremia.

OBJECTIVE: Bacteremia is the presence of bacteria in the bloodstream. The objective of this study was to determine the relationship between low socioeconomic status (SES) and the epidemiology, process of care, and outcomes of patients with Staphylococcus aureus bacteremia (SAB). METHODS: We conducted a multicenter, retrospective, cohort study that evaluated adult patients with SAB in 3 Los Angeles County hospitals from July 15, 2012, through May 31, 2018. We determined SES (low SES, intermediate SES, and high SES) for each patient and compared sociodemographic and epidemiologic characteristics, management of care received by patients with SAB (ie, process of care), and outcomes. We used a Cox proportional hazards model to determine predictors of 30-day mortality for each SES group. RESULTS: Of 915 patients included in the sample, 369 (40%) were in the low-SES group, 294 (32%) in the intermediate-SES group, and 252 (28%) in the high-SES group. Most significant predictors of 30-day mortality in the Cox proportional hazards model were admission to an intensive care unit (hazard ratio [HR] = 9.04; 95% CI, 4.26-19.14), Pitt bacteremia score ≥4 indicating critical illness (HR = 4.30; 95% CI, 2.49-7.44), having ≥3 comorbidities (HR = 2.05; 95% CI, 1.09-3.85), and advanced age (HR = 1.03; 95% CI, 1.01-1.05). Distance between home and admitting hospital affected mortality only in the low-SES group (HR = 1.02; 95% CI, 1.00-1.02). CONCLUSIONS: SES did not independently affect the outcome of SAB; however, the farther the patient's residence from the hospital, the greater the negative effect on survival in a low-SES population. Our findings underscore the need to develop multipronged, targeted public health efforts for populations that have transportation barriers to health care.

Effect of the COVID-19 pandemic on bike-sharing demand and hire time: Evidence from Santander Cycles in London.

The COVID-19 pandemic has been influencing travel behaviour in many urban areas around the world since the beginning of 2020. As a consequence, bike-sharing schemes have been affected-partly due to the change in travel demand and behaviour as well as a shift from public transit. This study estimates the varying effect of the COVID-19 pandemic on the London bike-sharing system (Santander Cycles) over the period March-December 2020. We employed a Bayesian second-order random walk time-series model to account for temporal correlation in the data. We compared the observed number of cycle hires and hire time with their respective counterfactuals (what would have been if the pandemic had not happened) to estimate the magnitude of the change caused by the pandemic. The results indicated that following a reduction in cycle hires in March and April 2020, the demand rebounded from May 2020, remaining in the expected range of what would have been if the pandemic had not occurred. This could indicate the resiliency of Santander Cycles. With respect to hire time, an important increase occurred in April, May, and June 2020, indicating that bikes were hired for longer trips, perhaps partly due to a shift from public transit.

COVID-19 and the value of safe transport in the United States.

We investigate the connection between the choice of transportation mode used by commuters and the probability of COVID-19 transmission. This interplay might influence the choice of transportation means for years to come. We present data on commuting, socioeconomic factors, and COVID-19 disease incidence for several US metropolitan areas. The data highlights important connections between population density and mobility, public transportation use, race, and increased likelihood of transmission. We use a transportation model to highlight the effect of uncertainty about transmission on the commuters' choice of transportation means. Using multiple estimation techniques, we found strong evidence that public transit ridership in several US metro areas has been considerably impacted by COVID-19 and by the policy responses to the pandemic. Concerns about disease transmission had a negative effect on ridership, which is over and above the adverse effect from the observed reduction in employment. The COVID-19 effect is likely to reduce the demand for public transport in favor of lower density alternatives. This change relative to the status quo will have implications for fuel use, congestion, accident frequency, and air quality. More vulnerable communities might be disproportionally affected as a result. We point to the need for additional studies to further quantify these effects and to assist policy in planning for the post-COVID-19 transportation future.