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The global COVID-19 outbreak has demanded drastic actions and policies from the governments and local authorities to stem the spread of the virus. Most of the measures involve behavioural changes from citizens to reduce their social contact to a minimum. Thus, these actions influence individual activity patterns and transport systems in different ways. This paper studies the short-term impacts on the transport system caused by the different policies adopted by the Colombian government and local authorities to contain the COVID-19 spread. Using official and secondary data concerning the seven most populated cities in Colombia, we analyse the impacts on three components of the transport system: air transport, freight transport, and urban transport. Results show that national policies and local decisions have decreased the demand for motorised trips across the cities, diminishing congestion levels, reducing transit ridership, and creating a reduction in transport externalities. The country banned air transport for passengers and only allowed air cargo for medical and necessary supplies, which will have negative consequences for the economics of the airline industry. During the first three months of the COVID-19, freight was the most resilient transport component. However, freight trips diminished around 38%, affecting mainly the supply chain of nonessential products. During the pandemic, governments need to provide subsidies to maintain the system supply to avoid crowdedness and promote active transport by allocating less-used street space to cyclists and pedestrians. In the short term, transportation service providers will face a financial crisis, deepened by the pandemic, which will require government assistance for their recovery. [ABSTRACT FROM AUTHOR]

There is a considerable gap between the existing knowledge used to estimate the value of time in passenger transport when compared with the framework of analysis developed for freight transport. In this paper, we applied a model that is gaining recognition in the context of passenger values of time estimation known as random valuation (RV) to a context in which there is little evidence of its application: freight value of time estimation (FVOT). Secondly, we compared this model to the commonly used methodology, random utility (RU). We analysed several levels of model specification to estimate the FVOT using data from a stated choice experiment applied in five of the main cargo transport road corridors of Colombia. The analysis accounts for the value of time differentiated by vehicle type. Results suggest that the RV models performed better for the same dataset than its counterpart RU in all cases. Another aspect to highlight is that the FVOT value obtained with the RU approach was pretty similar to those obtained with the RV in most cases. Also, the estimates FVOT for empty trips are closer, and in some cases higher, than those of loaded trips. [ABSTRACT FROM AUTHOR]

Transportation networks and systems are vulnerable to natural disasters. During disaster response operations, the degraded functionality of the system can negatively impact the affected population because disrupting relief activitiesincreases human suffering resulting from the lack of access to essential goods or services. Mathematical formulations for assessing transportation network vulnerability do not generally consider this lack of access or deprivation costs, and can lead to inappropriate strategies for humanitarian assistance. This paper proposes a transportation network vulnerability assessment model that allows identifying critical links for the development of high impact disaster response operations. The model is based on an economic analysis that considers the logistical costs of the distribution operations and the external effects derived from the delays in the provision of basic supplies (deprivation costs). The approach is particularly useful for planning resilient disaster response plans in the preparednessstage, prioritizing investment for mitigation and adaptation, and prioritizing the rehabilitation (access restoration) of the disrupted links in the response and recovery stages. In addition to numerical experiments using case study networks, the authors implemented the model to the coffee-producing region of Colombia, which was hit by an earthquake in 1999. [ABSTRACT FROM AUTHOR]

There is worldwide concern about the presence of factors that affect the performance of students in the computer science/engineering (CS) education process. Gender, socioeconomic and institutional factors may create gaps that affect not only the quality of education but also the entire society. This paper examines the influence of these factors on the performance of two tests used in Colombia for assessing the quality of education: The SABER-11, applied to senior high-school students, and SABER-PRO, applied to senior CS students (N = 2,964). We used effect size to compare mean difference by gender, and correlation and multiple regression analysis to examine the influence of socioeconomic and institutional factors, and the results of the SABER-11 on SABER-PRO. The results suggest the existence of moderate gender differences, favouring men. at the high-school level; however, when compared to the undergraduate level, we found evidence of significant gaps in all evaluated topics and of men performing better than women do. Results also suggest the existence of gaps associated with income, parental education, and the nature and quality of the university and the academic program where the student studies. [ABSTRACT FROM AUTHOR]

Several cities have restricted the use of private vehicles based on the last digit of a vehicle's license plate to reduce traffic congestion and pollution. However, the effectiveness of this measure has been questioned. In 2017, a hybrid scheme, License Plate Restriction Charging (LPRC), was implemented in Cali, Colombia. With this scheme, drivers can pay a charge (monthly, quarterly, or yearly) to circumvent the restriction, while the revenue is used to subsidise the BRT System. Cali was the first city in Latin America to implement such a scheme, while Colombia's capital, Bogota, adopted a similar policy in 2020. This article analyses the evolution of the measure using official information. In addition, we conducted a stated preferences survey and estimated a choice model to evaluate the behaviour of car owners to policy variables. Results show that LPRC price is the most relevant attribute in decision-making. Increasing the number of days with traffic restrictions and extending the hours of vehicle use restriction increases drivers' probability of paying for the LPRC. As currently implemented in Cali, the LPRC is a fixed cost that does not vary according to the car use level, encouraging users who pay for the exemption to use their car as much as possible to make the most out of the payment. Furthermore, the revenue from the charge contributes only marginally to financing the BRT. Finally, we propose several changes in the policy to improve its efficiency. Among them, consider a daily payment and hardening the current driving restriction. [ABSTRACT FROM AUTHOR]