Travel restrictions during pandemics: A useful strategy?

A systematic review of COVID-19 transport policies and mitigation strategies around the globe

This paper reports a Scopus-based systematic literature review of a wide variety of transportation policies and mitigation strategies that have been conducted around the world to minimize COVID-19 contagion risk in transportation systems. The review offers a representative coverage of countries across all continents of the planet, as well as among representative climate regions - as weather is an important factor to consider. The readership interested in policies and mitigation strategies is expected to involve a wide range of actors, each involving a particular application context; hence, the literature is also characterized by key attributes such as: transportation mode; actor (users, operators, government, industry); jurisdiction (national, provincial, city, neighborhood); and area of application (planning, regulation, operations, research, incentives). An in-depth analysis of the surveyed literature is then reported, focusing first on condensing the literature into 151 distinct policies and strategies, which are subsequently categorized into 25 broad categories that are discussed at length. The compendium and discussion of strategies and policies reported not only provide comprehensive guidelines to inform various courses of action for decision-makers, planners, and social communicators, but also emphasize on future work and the potential of some of these strategies to be the precursors of meaningful, more sustainable behavioral changes in future mobility patterns.

A straightforward edge centrality concept derived from generalizing degree and strength

Vertex degree—the number of edges that are incident to a vertex—is a fundamental concept in network theory. It is the historically first and conceptually simplest centrality concept to rate the importance of a vertex for a network’s structure and dynamics. Unlike many other centrality concepts, for which joint metrics have been proposed for both vertices and edges, by now there is no concept for an edge centrality analogous to vertex degree. Here, we propose such a concept—termed nearest-neighbor edge centrality—and demonstrate its suitability for a non-redundant identification of central edges in paradigmatic network models as well as in real-world networks from various scientific domains.

Identifying the shifting sources to predict the dynamics of COVID-19 in the U.S

Mobility restriction is a crucial measure to control the transmission of the COVID-19. Research has shown that effective distance measured by the number of travelers instead of physical distance can capture and predict the transmission of the deadly virus. However, these efforts have been limited mainly to a single source of disease. Also, they have not been tested on finer spatial scales. Based on prior work of effective distances on the country level, we propose the multiple-source effective distance, a metric that captures the distance for the virus to propagate through the mobility network on the county level in the U.S. Then, we estimate how the change in the number of sources impacts the global mobility rate. Based on the findings, a new method is proposed to locate sources and estimate the arrival time of the virus. The new metric outperforms the original single-source effective distance in predicting the arrival time. Last, we select two potential sources and quantify the arrival time delay caused by the national emergency declaration. In doing so, we provide quantitative answers on the effectiveness of the national emergency declaration.

Influence of COVID-19 Mobility-Restricting Policies on Individual Travel Behavior in Malaysia

The COVID-19 pandemic has resulted in new postpandemic travel patterns as a result of the stay-at-home policies and restricted movement orders imposed by the Malaysian government. The purpose of this study was to investigate the changes in individual travel behavior after the government imposed a series of lockdowns, also known as movement control orders (MCO). From March to April 2021, a questionnaire survey was distributed throughout Malaysia, and 435 complete responses were collected. Results indicated that the respondents predominantly chose private cars for various traveling purposes during the pandemic. When choosing a travel mode during the pandemic, married respondents and essential workers placed a significantly higher priority on pandemic-related - items such as cleanliness, infection concern, social distance, and wearing face masks, compared to single respondents and nonessential workers. Binary logistic regression models were developed to estimate individuals’ propensity to make trips for different purposes, i.e., work/study, social activities, recreational activities, and religious activities. Results indicated that essential workers were nearly three times more likely than the general population to make a work trip during the pandemic. Regarding social and recreational trips, males were more likely to make such types of trips as compared to females. Furthermore, those who perceived a higher risk of infection were less likely to make social and recreational trips. Regarding religious trips, males were significantly more likely to make such trips during the pandemic as compared to females. In addition, Muslims had significantly higher odds of making a trip for religious purposes during the pandemic. The findings of this study could be useful in transportation planning when considering travel restrictions during pandemics based on peoples’ travel purposes and mode choices.