Impact of different control policies for COVID-19 outbreak on the air transportation industry: A comparison between China, the U.S. and Singapore

Exploring data sources and mathematical approaches for estimating human mobility rates and implications for understanding COVID-19 dynamics: a systematic literature review

Human mobility, which refers to the movement of people from one location to another, is believed to be one of the key factors shaping the dynamics of the COVID-19 pandemic. There are multiple reasons that can change human mobility patterns, such as fear of an infection, control measures restricting movement, economic opportunities, political instability, etc. Human mobility rates are complex to estimate as they can occur on various time scales, depending on the context and factors driving the movement. For example, short-term movements are influenced by the daily work schedule, whereas long-term trends can be due to seasonal employment opportunities. The goal of the study is to perform literature review to: (i) identify relevant data sources that can be used to estimate human mobility rates at different time scales, (ii) understand the utilization of variety of data to measure human movement trends under different contexts of mobility changes, and (iii) unraveling the associations between human mobility rates and social determinants of health affecting COVID-19 disease dynamics. The systematic review of literature was carried out to collect relevant articles on human mobility. Our study highlights the use of three major sources of mobility data: public transit, mobile phones, and social surveys. The results also provides analysis of the data to estimate mobility metrics from the diverse data sources. All major factors which directly and indirectly influenced human mobility during the COVID-19 spread are explored. Our study recommends that (a) a significant balance between primitive and new estimated mobility parameters need to be maintained, (b) the accuracy and applicability of mobility data sources should be improved, (c) encouraging broader interdisciplinary collaboration in movement-based research is crucial for advancing the study of COVID-19 dynamics among scholars from various disciplines.

Explaining US travel behavior with perceived threat of pandemic, consumer sentiment, and economic policy uncertainty

Since the COVID-19 outbreak, consumer behavior has been affected by the perceived threat of the pandemic and economic uncertainty. This paper aims to explore the dynamic effects of COVID-19, consumer sentiment, economic policy uncertainty, and fuel prices on travel behavior in the United States. Using updated daily trip data, the results show that consumer sentiment has a positive long-run impact on travel demand for air and auto, suggesting that a positive change in consumer sentiment can boost demand for these modes of transportation in the long term. Additionally, consumer sentiment has a favorable effect (1.34) on demand for long-distance trips, but it has a negative impact (-0.42) on the number of people staying at home. Economic and political shocks have a detrimental impact on demand for air and auto travel, suggesting that consumers reduce the frequency and cost of these transport services if they have pessimistic expectations about the future state of the economy and policy. However, in the short term, US travelers appear to be insensitive to shocks in consumer sentiment and economic policy uncertainty. Regarding the perceived threat of the pandemic, the results indicate that rising COVID-19 cases have a negative long-term effect on demand for air travel (-0.09) and public transit (-0.19), while they are positively associated with demand for auto travel (0.06). Similarly, the increasing number of deaths due to COVID-19 has led to a shift from shared-use mass transportation (air travel and public transit) to private autos and non-motorized travel, such as walking in the short term.

COVID-19 pandemic and air transportation: Summary of Recent Research, Policy Consideration and Future Research Directions

The COVID-19 pandemic can be considered an unparalleled disruption to the aviation industry in the last century. Starting with an at-that-time inconceivable reduction in the number of flights from March 2020 to May 2020, the aviation industry has been trying to navigate through and out of the crisis. This process is accompanied with a significant number of scientific studies, reporting on the direct and indirect impact of the COVID-19 pandemic on aviation and vice versa. This paper reviews the impacts in context of the recent literature. We have collected nearly 200 well-published papers on the subject in the years 2021/2022 and dissected them into a framework of eight categories, built around: airlines, airports, passengers, workforce, markets, contagion, sustainability, and economics. We highlight the essence of findings in the literature and derive a set of future research directions and policy considerations which we deem important on the way towards pandemic-resilient aviation.

How do the smart travel ban policy and intercity travel pattern affect COVID-19 trends? Lessons learned from Iran

COVID-19, as the most significant epidemic of the century, infected 467 million people and took the lives of more than 6 million individuals as of March 19, 2022. Due to the rapid transmission of the disease and the lack of definitive treatment, countries have employed nonpharmaceutical interventions. This study aimed to investigate the effectiveness of the smart travel ban policy, which has been implemented for non-commercial vehicles in the intercity highways of Iran since November 21, 2020. The other goal was to suggest efficient COVID-19 forecasting tools and to examine the association of intercity travel patterns and COVID-19 trends in Iran. To this end, weekly confirmed cases and deaths due to COVID-19 and the intercity traffic flow reported by loop detectors were aggregated at the country's level. The Box-Jenkins methodology was employed to evaluate the policy's effectiveness, using the interrupted time series analysis. The results indicated that the autoregressive integrated moving average with explanatory variable (ARIMAX) model outperformed the univariate ARIMA model in predicting the disease trends based on the MAPE criterion. The weekly intercity traffic and its lagged variables were entered as covariates in both models of the disease cases and deaths. The results indicated that the weekly intercity traffic increases the new weekly COVID-19 cases and deaths with a time lag of two and five weeks, respectively. Besides, the interrupted time series analysis indicated that the smart travel ban policy had decreased intercity travel by around 29%. Nonetheless, it had no significant direct effect on COVID-19 trends. This study suggests that the travel ban policy would not be efficient lonely unless it is coupled with active measures and adherence to health protocols by the people.

A Review of COVID-19-Related Literature on Freight Transport: Impacts, Mitigation Strategies, Recovery Measures, and Future Research Directions

The COVID-19 pandemic has caused significant disruptions in the freight transport sector. The number of studies on the impact of COVID-19 on freight transport and possible mitigation strategies are growing. However, a systematic and comprehensive review highlighting the research themes, main findings, research methods, and future research directions of these studies remains scarce. Therefore, this study presents a mixed review comprising scientometric and systematic reviews to cover these research gaps. Results show that 68 studies have been published on this topic since the beginning of 2020 and that they cover three main themes: the impacts of COVID-19 on freight transport, mitigation strategies, and recovery during and after COVID-19. In addition, we describe the research methods, main findings, and possible research directions in each of them. Thus, the findings of our work present both theoretical and practical analyses of COVID-19-related research on freight transport and provide important future research directions in this domain.

Wealth, health, and beyond: Is COVID-19 less likely to spread in rich neighborhoods?

Since December 2019, the COVID-19 pandemic has quickly spread across the world. The traditional understanding of the relationship between wealth and the spread of contagious diseases is that similar to many precedent epidemics, the pandemic spread easily in poor neighborhoods in many countries. The environmental and socioeconomic implications of the COVID-19 pandemic are still poorly understood, thus this paper examines the relationship between neighborhood characteristics and the spread of the pandemic through a case study of Shenzhen, a Chinese megacity with many low-income rural migrants. The major finding is that wealthier and larger neighborhoods in Shenzhen were more likely to be infected in the first wave of the pandemic in 2020. This spread pattern is likely to result from China’s strict control to prevent the pandemic, human mobility, and demographic characteristics such as income. This finding reveals a new phenomenon that contrasts with the traditional understanding of the influence of wealth on the spread of epidemics. This paper enriches the understanding of the role of neighborhoods in the spread of the pandemic, and it has important public policy implications.

The Impacts of Gradually Terminating Nonpharmaceutical Interventions for SARS-CoV-2: A Mathematical Modelling Analysis

With the expansion of vaccination programs, the policy of terminating nonpharmaceutical interventions for preventing the SARS-CoV-2 pandemic should become more flexible. The current study investigated the clinical and economic outcomes of intervention policies combining nonpharmaceutical interventions and vaccination programs for dealing with the SARS-CoV-2 pandemic. An agent-based transmission model was adopted that describes how a SARS-CoV-2 virus spreads in the populations of China. The model inputs were derived from the literature and expert opinion. The following intervention policies were simulated: no intervention, strict nonpharmaceutical interventions, and nonpharmaceutical interventions for workplace, community, school and home gradually terminated by combining vaccination programs for specified age groups (vaccination age in years: 20–60, 20–70, 20–80, ≥20, ≥10 and whole population). Cumulative infections and deaths in one calendar year, costs and quality-adjusted life years (QALYs) were measured. When the vaccination program was taken up in at least the ≥20 years age group in all populations, nonpharmaceutical interventions for workplace and community settings could be gradually terminated because the cumulative number of infections was < 100 per 100,000 persons. Further ending nonpharmaceutical interventions in school and home settings could not meet the target even when the vaccination program had been taken up in all populations. When cumulative deaths were used as the endpoint, nonpharmaceutical interventions in workplace, community and school settings could be gradually terminated. Vaccine efficacy and coverage have substantial impacts. Terminating nonpharmaceutical interventions in workplace settings could produce the lowest cost when vaccination programs are taken up at least in the ≥10 years age group; this method dominates most intervention strategies due to its lower costs and higher QALYs. According to our findings, nonpharmaceutical interventions might be gradually terminated in Chinese settings.

Wishful thinking? Addressing the long-term implications of COVID-19 for transport in Nigeria

With their inherent economic and infrastructure challenges, developing countries must assess commuters' travel behaviour and establish whether consumers' desire for sustainable transportation is feasible or merely wishful thinking. Using a qualitative research design, these issues were explored based on semi-structured interviews conducted with 72 participants across the six geopolitical zones of Nigeria. Findings suggest that the desires and dreams of the commuters are great, and they want to reduce their journeys, work from home, and do online shopping. However, when they consider the inherent challenges, they can only hope for a better future. COVID-19 has impacted the ownership or use of motorised and non-motorised transport, but this is also influenced by affordability, convenience, and awareness. Likewise, there are long-term effects on home and work location choices, but this is further influenced by the large informal economy of the country, job accessibility and the infrastructural developments across the country.

Impact of air transportation on the spread of Covid-19 between countries based on system dynamics

For the spread COVID-19 between countries through air transportation, the influencing factors are analyzed, a system dynamics model which passes the validity test is established. Then, three key indicators, Basic Reproduction Rate, Initial Infection Individuals and Transfer Rate, are selected as independent variables to analyze the system changes through computer simulation. Based on the analysis, the infectivity of COVID-19 and the number of people transferred by air transportation are important factors affecting the import of epidemics for non-epidemic countries, and the sooner or later control of infectious diseases by epidemic countries has little effect on non-epidemic countries.

Risk of COVID-19 Infection in Public Transportation: The Development of a Model

South Korea's social distancing policies on public transportation only involve mandatory wearing of masks and prohibition of food intake, similar to policies on other indoor spaces. This is not because public transportation is safe from coronavirus disease 2019 (COVID-19), but because no suitable policies based on accurate data have been implemented. To relieve fears regarding contracting COVID-19 infection through public transportation, the government should provide accurate information and take appropriate measures to lower the risk of COVID-19. This study aimed to develop a model for determining the risk of COVID-19 infection on public transportation considering exposure time, mask efficiency, ventilation rate, and distance. The risk of COVID-19 infection on public transportation was estimated, and the effectiveness of measures to reduce the risk was assessed. The correlation between the risk of infection and various factors was identified through sensitivity analysis of major factors. The analysis shows that, in addition to the general indoor space social distancing policy, ventilation system installation, passenger number reduction in a vehicle, and seat distribution strategies were effective. Based on these results, the government should provide accurate guidelines and implement appropriate policies.

Effects of transport-related COVID-19 policy measures: A case study of six developed countries

This study attempts to provide scientifically-sound evidence for designing more effective COVID-19 policies in the transport and public health sectors by comparing 418 policy measures (244 are transport measures) taken in different months of 2020 in Australia, Canada, Japan, New Zealand, the UK, and the US. The effectiveness of each policy is measured using nine indicators of infections and mobilities corresponding to three periods (i.e., one week, two weeks, and one month) before and after policy implementation. All policy measures are categorized based on the PASS approach (P: prepare-protect-provide; A: avoid-adjust; S: shift-share; S: substitute-stop). First, policy effectiveness is compared between policies, between countries, and over time. Second, a dynamic Bayesian multilevel generalized structural equation model is developed to represent dynamic cause-effect relationships between policymaking, its influencing factors and its consequences, within a unified research framework. Third, major policy measures in the six countries are compared. Finally, findings for policymakers are summarized and extensively discussed.