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After the widespread impact of the COVID-19 pandemic, all public transport, including urban rail transit, inevitably adopted a vigorous physical-distancing policy to prevent the disease from spreading among passengers. Adoption of this measure resulted in a substantial reduction in train service capability and required control of the risk contact exposure duration. Thus, this paper proposes the Skip-Stop Strategy Patterns (3S–P) decision-support model to incorporate social distancing constraints in train operations. The 3S–P model is a two-stage, multi-objective optimization model for scheduling train skip-stop patterns to satisfy the study's two main objectives of minimizing the average passenger travel time and unserved passengers. In the proposed model, the first optimization identifies the optimal train skip-stop patterns, while the second assigns these patterns to establish an hourly train schedule. The paper's case study uses data from the Bangkok Mass Transit System (BTS) SkyTrain Silom Line in Bangkok, Thailand and considers the 0.5, 1, 1.5, and 2 m social distancing schemes. The results reveal that the optimal train skip-stop patterns are superior to the all-stop alternative with, on average, a 13.4% faster travel time at the same level of unserved passengers. Furthermore, the non-dominated schedules from the second optimization decrease the numbers of unserved passengers given equal average passenger travel times. • Decision-support model proposed for urban train operation policy in COVID-19 pandemic. • Two-stage multi-objective optimization to schedule train skip-stop patterns. • Trade-off among social distancing policy, passenger travel time, and unserved passengers. • Skip-stop schemes have 13.4% faster passenger travel times than all-stop. [ABSTRACT FROM AUTHOR]

This paper examines the impacts of emergency cash-transfers on individuals' social distancing behaviour and beliefs about COVID-19. We focus on the impacts of "Auxilio Emergencial" (AE): a large-scale cash-transfer in Brazil targeting low-income individuals who were unemployed or informally employed during the pandemic. To identify causal effects we exploit exogenous variation, arising from the AE design, in individuals' access to the cash-transfer programme. Using data from an online survey, our results suggest that eligibility to the emergency cash transfer led to a reduced likelihood of individuals contracting COVID-19, likely to have been driven by a reduction in working hours. Moreover, the cash transfer seems to have increased perceptions about the seriousness of coronavirus, while also exacerbating misconceptions about the pandemic. These findings indicate effects of emergency cash-transfers in determining individuals' narratives about a pandemic, in enabling social distancing and potentially in reducing the spread of the disease. [ABSTRACT FROM AUTHOR]

Longevity expectations (LE) are subjective assessments of future health status that can influence a number of individual health protective decisions. This is especially true during a pandemic such as COVID-19, as the risk of ill health depends more than ever on such protective decisions. This paper examines the causal effect of LE on some protective health behaviors and a number of decisions regarding forgoing health care. We use data from the Survey of Health Ageing and Retirement in Europe, and we draw on an instrumental variable strategy exploiting individual level information on parental age at death. Consistent with the too healthy to be sick hypothesis, we find that individuals, exhibiting higher expected longevity, are more likely to engage in protective behaviours, and are less likely to forgo medical treatment. We estimate that a one standard deviation increase in LE increases the probability to comply always with social distancing by 0.6%, to meet people less often by 0.4% and decreases the probability to forgo any medical treatment by 0.6%. Our estimates vary depending on supply side restrictions influencing the availability of health care, as well as individual characteristics such as gender and the presence of pre-existing health conditions. [ABSTRACT FROM AUTHOR]

Covid-19 has had a major impact on public transport systems across the world. Public financial support has been needed to maintain services in the face of drastically reduced ridership and adjustment to the need for social distancing. This paper explores the challenge this poses to current methods of delivery of public transport services and argues that a simple return to the status quo is unlikely as public transport adjusts to a new normal of more home working and fear of crowded spaces. In turn this impacts most on the transport disadvantaged. The paper argues that this may spell the end of the prevailing model of a deregulated competitive public transport that has prevailed in the United Kingdom and require a major rethinking of the way to provide an efficient and effective transport system. Such a rethink will depend on understanding the interplay of private and social norms and building public trust. • Transport impacts of Covid-19. • Public transport. • Government funding. • Transport planning. • United Kingdom. [ABSTRACT FROM AUTHOR]

The COVID-19 disease continues to cause unparalleled disruption to life and the economy world over. This paper is the second in what will be an ongoing series of analyses of a longitudinal travel and activity survey. In this paper we examine data collected over a period of late May to early June in Australia, following four-to-six weeks of relatively flat new cases in COVID-19 after the initial nationwide outbreak, as many state jurisdictions have begun to slowly ease restrictions designed to limit the spread of the SARS-CoV-2 virus. We find that during this period, travel activity has started to slowly return, in particular by private car, and in particular for the purposes of shopping and social or recreational activities. Respondents indicate comfort with the idea of meeting friends or returning to shops, so authorities need to be aware of potential erosion of social distancing and appropriate COVID-safe behaviour in this regard. There is still a concern about using public transport, though it has diminished noticeably since the first wave of data collection. We see that working from home continues to be an important strategy in reducing travel and pressure on constrained transport networks, and a policy measure that if carried over to a post-pandemic world, will be an important step towards a more sustainable transport future. We find that work from home has been a generally positive experience with a significant number of respondents liking to work from home moving forward, with varying degrees of employer support, at a level above those seen before COVID-19. Thus, any investment to capitalise on current levels of work from home should be viewed as an investment in transport. • Aggregate travel has increased by 50% but is still less than two-thirds of that which occurred prior to COVID-19. • Motor vehicle travel rebounding more than other modes, those planning a return to train and bus intended to do so strongly. • Large increases in activity planned for shopping and social and recreation purposes. • People feel most comfortable with meeting with friends, going to the shops and visiting restaurants. • Working from home continues, and has been largely positive for those who have been able to do so.. • Concern about the risk of COVID-19 has decreased significantly since the initial outbreak. [ABSTRACT FROM AUTHOR]

• Developing a time-fractional compartmental model that incorporates the effect of contact tracing for Covid-19. • Describe the effective reproduction number in terms of observable quantities. • Discuss effects of tracking, reporting and monitoring in contact tracing. • Monitoring proportion of reported cases which must be tracked to ensure that the reproduction number is below one. • Numerical simulations are done to discuss the impact of contact tracing on the pandemic. Contact Tracing (CT) is one of the measures taken by government and health officials to reduce the spread of the novel coronavirus. In this paper, we investigate its efficacy by developing a compartmental model for assessing its impact on mitigating the spread of the virus. We describe the impact on the reproduction number R 0 of COVID-19. In particular, we discuss the importance and relevance of parameters of the model such as the number of reported cases, effectiveness of tracking and monitoring policy, and the transmission rates to contact tracing. We describe the terms "perfect tracking", "perfect monitoring" and "perfect reporting" to indicate that traced contacts will be tracked while incubating, tracked contacts are efficiently monitored so that they do not cause secondary infections, and all infected persons are reported, respectively. We consider three special scenarios: (1) perfect monitoring and perfect tracking of contacts of a reported case, (2) perfect reporting of cases and perfect monitoring of tracked reported cases and (3) perfect reporting and perfect tracking of contacts of reported cases. Furthermore, we gave a lower bound on the proportion of contacts to be traced to ensure that the effective reproduction, R c , is below one and describe R c in terms of observable quantities such as the proportion of reported and traced cases. Model simulations using the COVID-19 data obtained from John Hopkins University for some selected states in the US suggest that even late intervention of CT may reasonably reduce the transmission of COVID-19 and reduce peak hospitalizations and deaths. In particular, our findings suggest that effective monitoring policy of tracked cases and tracking of traced contacts while incubating are more crucial than tracing more contacts. The use of CT coupled with other measures such as social distancing, use of face mask, self-isolation or quarantine and lockdowns will greatly reduce the spread of the epidemic as well as peak hospitalizations and total deaths. [ABSTRACT FROM AUTHOR]

In this paper, we conduct a mobility reduction rate comparison between the first and second COVID-19 waves in several localities from America and Europe using Google community mobility reports (CMR) data. Through multi-dimensional visualization, we are able to compare the reduction in mobility from the different lockdown periods for each locality selected, simultaneously considering multiple place categories provided in CMR. In addition, our analysis comprises a 56-day lockdown period for each locality and COVID-19 wave, which we analyze both as 56-day periods and as 14-day consecutive windows. We use locality-wise calibrated CMR data, which we process through seasonal-trend decomposition by LOESS (STL) to isolate trend from seasonal and noise effects. We scale trend data to draw Pareto-compliant conclusions using radar charts. For each temporal granularity considered, data for a given place category is aggregated using the area under the curve (AUC) approach. In general, reduction rates observed during the first wave were much higher than during the second. Alarmingly, December holiday season mobility in some of the localities reached pre-pandemic levels for some of the place categories reported. Manaus was the only locality where second wave mobility was nearly as reduced as during the first wave, likely due to the P1 variant outbreak and oxygen supply crisis. [Display omitted] • We compare social distancing adherence in different localities during two COVID-19 waves. • Reduction rates reveal contrasting social distancing dynamics over time. • In general, mobility reduction was much higher during the first wave. • Holiday season mobility reached pre-pandemic levels for some locations. [ABSTRACT FROM AUTHOR]

• There is significant variation in people's compliance with lockdown measures introduced by governments to curb the spread of the COVID-19. • Much of the variation can be explained by different cultural traits. • Individualism, which emphasises personal freedom, makes government intervention harder, whereas collectivism, which emphasises the wellbeing of the group, makes collective action easier. • We conclude that cultural factors play a critical role in successful policy implementation. In the first wave of the pandemic, places where geographic mobility declined more rapidly saw fewer cases of COVID-19. And yet, there is significant variation in people's compliance with the lockdown measures introduced by governments in order to curb the spread of the virus. In this paper, we show that much of this variation can be explained by different cultural traits. Specifically, we advance the hypothesis that individualism, which puts greater value on personal freedom, makes government intervention harder, whereas collectivism, which emphasises the wellbeing of the group, makes collective action easier. We find support for these ideas across 111 countries, but also when exploiting within country variation in the two largest economies in the world: China and the United States. Across a host of specifications, people were less abiding by the lockdown rules in places with greater prevalence of individualistic cultural traits. We conclude that cultural factors play a critical role in successful policy implementation. [ABSTRACT FROM AUTHOR]

The paper describes research activities of monitoring, modeling, and planning of people mobility in Rome during the Covid-19 epidemic period from March to June 2020. The results of data collection for different transport modes (walking, bicycle, car, and transit) are presented and analyzed. A specific focus is provided for the subway mass transit, where 1 m interpersonal distancing is required to prevent the risks for Covid-19 contagion together with the use of masks and gloves. A transport system model has been calibrated on the data collected during the lockdown period –when people's behavior significantly changed because of smart-working adoption and contagion fear– and was applied to predict future mobility scenarios under different assumptions on economic activities restarting. Based on the estimations of passenger loading, a timing policy that differentiates the opening hours of the shops depending on their commercial category was implemented, and an additional bus transit service was introduced to avoid incompatible loads of the subway lines with the required interpersonal distancing. [ABSTRACT FROM AUTHOR]

The ongoing COVID-19 pandemic has drastically altered daily life in cities across the world. To slow the spread of COVID-19, many countries have introduced mobility restrictions, ordered the temporary closure of businesses, and encouraged social distancing. These policies have directly and indirectly influenced travel behaviour, particularly modal preferences. The purpose of this paper to explore modality profiles for non-mandatory trips and analyze how they have changed in response to the pandemic and pandemic-related public health policies. The data used for this study were collected from web-based surveys conducted in the Greater Toronto Area. Modality profiles were identified through the application of latent class cluster analysis, with six modality profiles being identified for both the pre-pandemic and pandemic periods. The results indicate that the importance of public transit has declined during the pandemic, while the roles of private vehicles and active modes have become more prominent. However, individuals' changes in modal preferences vary based on their pre-pandemic modality profile. In particular, it appears that pre-pandemic transit users with access to a private vehicle have substituted public transit for travel by private vehicle, while those without private vehicle access are continuing to use public transit for non-mandatory trips. Consequently, pandemic-related transportation policies should consider those who do not have access to a private vehicle and aim to help those making non-mandatory trips using transit or active modes comply with local public health guidelines while travelling. The results highlight how the changes in modal preferences that occurred due to the pandemic differ among different segments of the population. • COVID-19 pandemic restrictions have changed modality profiles for non-mandatory trips. • The impacts of the pandemic on mobility vary among different segments of the population. • Private vehicles and active modes are now playing a more prominent role in mobility. • Public transit use is less prevalent now than it was before the pandemic. • Some transit trips have been replaced by walking, ride-sourcing, and taxi trips. [ABSTRACT FROM AUTHOR]

The outbreak of COVI-19 and the restrictive measures on the mobility of people in Brazil have raised serious concerns about the survival and recovery of passenger transport companies, especially those that generate public agglomerations. There are some policy proposals that aim to recover this set of sectors in the face of the adverse effects of the COVID-19 outbreak. This study contributes to this debate in course and analyzes the economic effects of two scenarios of recovery for this type of transport services in the Brazilian economy up to the end of 2022: (i) one with a 50% recovery until the end of 2021 and (ii) another with a 50% sectorial recovery until June 2022. This distinction allows us to assess the impact of the speed of recovery. In both scenarios, we also consider likely changes in the labor market, family preferences, and government spending. To accomplish this task, we developed a dynamic computable general equilibrium model that recognizes a Social Accounting Matrix (SAM) and has details of the transport sectors. The main findings suggest that the drop in these transport services is the main contributing factor to the decline in the Brazilian GDP growth (−2.2%) in the period of social distance measures. However, faster recovery of these sectors can generate a marginal effect of 0.5 percentage points on GDP at the end of 2021. In the recovery period, due to the redistributive effects of income, the family demand for public transport is expected to grow post- COVID-19 outbreak, while the demand for private transport is reduced, especially in the basket of goods of the poorest households. Vehicle, bus, and aircraft manufacture seems sensitive to the recovery time of the demand for transport services with public agglomerations. • The paper develops a SAM-based dynamic CGE models detailing the transport sectors. • With a faster recovery in the transport service, the endogenous response of the Brazilian economy is more intense. • The income effect of the emergency resource policy alters the modal distribution in the household budget. • Manufacture of vehicles, buses and aircraft are sensitive to the recovery time scenarios. [ABSTRACT FROM AUTHOR]

Social distancing has been adopted as a strategy to contain the advance of the pandemic until specific solutions to combat the virus are available. Many economic sectors and social activities need to continue despite the viruses, and most social distancing policies disregard individual choices, resulting in greater or lesser adherence to isolation. In this paper, we characterize the differentiation of access to essential activities within Brazilian cities during social distancing and the intention to maintain behavior changes concerning these activities in the post-pandemic period. The results showed that the behavior regarding essential activities during the pandemic is not independent of variables associated with pre-pandemic travel patterns, isolation conditions, and socioeconomic factors. Post-pandemic intention proved to be statistically dependent on factors associated with the activities' characteristics and experiences during the pandemic. Accessibility-oriented planning can guide urban and transportation policies more equitably through the identification of the most affected groups by activity disruption. At the same time, the incorporation of new routines less dependent on displacement offers opportunities to review public space. [Display omitted] • Less schooling, self-employed or less frequent commuters changed less work routine. • Young, less schooling or low-income people maintained educational and purchase trips. • Higher schooling people have more chances to keep essential tasks without traveling. • Public transport users had fewer opportunities to switch from routine to purchasing. • Post-pandemic intention is statistically dependent on activities' characteristics. [ABSTRACT FROM AUTHOR]

While many efforts are currently devoted to vaccines development and administration, social distancing measures, including severe restrictions such as lockdowns, remain fundamental tools to contain the spread of COVID-19. A crucial point for any government is to understand, on the basis of the epidemic curve, the right temporal instant to set up a lockdown and then to remove it. Different strategies are being adopted with distinct shades of intensity. USA and Europe tend to introduce restrictions of considerable temporal length. They vary in time: a severe lockdown may be reached and then gradually relaxed. An interesting alternative is the Australian model where short and sharp responses have repeatedly tackled the virus and allowed people a return to near normalcy. After a few positive cases are detected, a lockdown is immediately set. In this paper we show that the Australian model can be generalized and given a rigorous mathematical analysis, casting strategies of the type short-term pain for collective gain in the context of sliding-mode control , an important branch of nonlinear control theory. This allows us to gain important insights regarding how to implement short-term lockdowns, obtaining a better understanding of their merits and possible limitations. Effects of vaccines administration in improving the control law's effectiveness are also illustrated. Our model predicts the duration of the severe lockdown to be set to maintain e.g. the number of people in intensive care under a certain threshold. After tuning our strategy exploiting data collected in Italy, it turns out that COVID-19 epidemic could be e.g. controlled by alternating one or two weeks of complete lockdown with one or two months of freedom, respectively. Control strategies of this kind, where the lockdown's duration is well circumscribed, could be important also to alleviate coronavirus impact on economy. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has suddenly modified the lifestyle of a large portion of the population around the world. This pandemic is also the first one in decades that has severely impacted many countries of the Global North. Governments have had to adopt wide-scope and desperate measures to face the abnormal situation and to reduce the stress of their health care systems. These measures have been based on reducing the physical-social interaction and mobility (closing schools and some economic activities, or fostering telework, among others), increasing the physical distance between people, and recommending washing hands frequently and wearing masks. Thus, the COVID-19 may change many habits of people and the ways we interact with others after the current pandemic. It would also imply changes in mobility habits. Many questions arise about the willingness and acceptability of changes, and who would have to impulse them and how. This paper aims to study and understand individuals' acceptability towards a set of generic measures related to urban mobility in Spain, one of the countries most affected by the COVID-19 pandemic. To that end, we conducted an online survey during the lockdown in Spring (2020). More than 75% of respondents would accept restrictions on car use after the return to normal, and more than 90% agree on increasing the space for pedestrians and cyclists on streets. Furthermore, 75% of respondents would change the primary transport mode towards a more sustainable transport mode if it would decrease the incidence or severity of the COVID-19. These results show that the respondents are overall in favor of a new urban hierarchy that gives more importance to the most sustainable modes, reducing the public space devoted to the car, which means the possibility of turning the COVID-19 crisis into an opportunity to make Spanish cities more sustainable. • Impacts of COVID-19 on mobility patterns and behavior in Spain. • Acceptance of policies to restrict car use and increase soft mode space in a post-COVID-19 scenario. • Policy measures are recommended based on the survey and the Binary Logit models rresults. [ABSTRACT FROM AUTHOR]

Since late 2019, COVID-19 has devastated the global economy, with indirect implications for the environment. As governments' prioritized health and implemented measures such as the closure of non-essential businesses and social distancing, many workers have lost their jobs, been furloughed, or started working from home. Consequently, the world of work has drastically transformed and this period is likely to have major implications for mobility, transportation and the environment. This paper estimates the potential for people to engage in remote work and social distancing using O*NET data and Irish Census data and calculates the potential emission savings, by commuter type from a switch to remote working and occupational social distancing. The results show that while those who commute by car have a relatively high potential for remote work, they are less likely to be able to engage in social distancing in their workplace. While this may be negative for employment prospects in the short run, our analysis indicates that this pattern has the potential for positive environmental implications in the short and long run. [ABSTRACT FROM AUTHOR]

This paper presents a review of social distancing measures deployed by transit agencies in the United States and Canada during the COVID-19 pandemic and discusses how specific operators across the two countries have implemented changes. Challenges and impacts on their operations are also provided. Social distancing is one of the community mitigation measures traditionally implemented during influenza pandemics and the novel coronavirus pandemic. Research has shown that social distancing is effective in containing the spread of disease. This is applicable to the current situation with the novel coronavirus, given the lack of effective vaccines and treatments in the United States and Canada in the first eight months of the pandemic. Moreover, social distancing is particularly useful in settings where community transmission is substantial. Directives for social distancing were issued in several states and public transit operators were charged with how to provide for physical distance of six feet between passengers on their property including physical infrastructure such as station buildings and rolling infrastructure (rolling stock) including trains, subway cars and buses. Operational changes were also required due to physical distancing, e.g. adding train cars to provide for opportunities to physically distance on the train. Examples of some measures discussed in this research includes taping off every other seat on buses, increasing the total length of trains by adding cars, separating bus drivers from passengers with plastic sheeting, rear door boarding, etc. This research also analyzes long-term impacts for transit operators and challenges to encourage passengers to return to public transit after lockdown requirements ordered by government officials are lifted. A section on the policies that are being explored by government to continue to sustain public transportation is also included. • We review the interventions deployed by public transit operators to comply with social distancing measures. • We explore operational changes recommended to facilitate physical distancing. • We analyze the impacts for transit operators and challenges for passengers to return to public transit post pandemic. • We discuss the challenges for transit to return to pre-pandemic conditions and some solutions explored. [ABSTRACT FROM AUTHOR]

This paper analyses how promoting social distancing changes infection rates and welfare. In the pool of people seeking personal contacts, a greater preference for distance increases the prevalence of infection and worsens everyone's welfare. In contrast, prevention and treatment reduce prevalence and improve payoffs. The results are driven by adverse selection—people who prefer more matches are likelier disease carriers. A given decrease in the number of matches is a smaller proportional reduction for people with many contacts, thus increases the fraction of infected in the pool. The greater disease risk further decreases contact-seeking and payoffs. Abstinence education has the same effect on sexually transmitted diseases as promoting social distancing on Covid-19 and for the same reason. [ABSTRACT FROM AUTHOR]

• The paper predicts the COVID-19 epidemic in the US with different vaccine effectiveness and coverage. • The required vaccine effectiveness and coverage to suppress the epidemic are calculated. • The degree to relax social distancing and face mask use depends on the vaccine effectiveness and coverage. Multiple candidates of COVID-19 vaccines have entered Phase III clinical trials in the United States (US). There is growing optimism that social distancing restrictions and face mask requirements could be eased with widespread vaccine adoption soon. We developed a dynamic compartmental model of COVID-19 transmission for the four most severely affected states (New York, Texas, Florida, and California). We evaluated the vaccine effectiveness and coverage required to suppress the COVID-19 epidemic in scenarios when social contact was to return to pre-pandemic levels and face mask use was reduced. Daily and cumulative COVID-19 infection and death cases from 26th January to 15th September 2020 were obtained from the Johns Hopkins University Coronavirus resource center and used for model calibration. Without a vaccine (scenario 1), the spread of COVID-19 could be suppressed in these states by maintaining strict social distancing measures and face mask use levels. But relaxing social distancing restrictions to the pre-pandemic level without changing the current face mask use would lead to a new COVID-19 outbreak, resulting in 0.8–4 million infections and 15,000–240,000 deaths across these four states over the next 12 months. Under this circumstance, introducing a vaccine (scenario 2) would partially offset this negative impact even if the vaccine effectiveness and coverage are relatively low. However, if face mask use is reduced by 50% (scenario 3), a vaccine that is only 50% effective (weak vaccine) would require coverage of 55–94% to suppress the epidemic in these states. A vaccine that is 80% effective (moderate vaccine) would only require 32–57% coverage to suppress the epidemic. In contrast, if face mask usage stops completely (scenario 4), a weak vaccine would not suppress the epidemic, and further major outbreaks would occur. A moderate vaccine with coverage of 48–78% or a strong vaccine (100% effective) with coverage of 33–58% would be required to suppress the epidemic. Delaying vaccination rollout for 1–2 months would not substantially alter the epidemic trend if the current non-pharmaceutical interventions are maintained. The degree to which the US population can relax social distancing restrictions and face mask use will depend greatly on the effectiveness and coverage of a potential COVID-19 vaccine if future epidemics are to be prevented. Only a highly effective vaccine will enable the US population to return to life as it was before the pandemic. [ABSTRACT FROM AUTHOR]

In this paper, we present a mathematical model of an infectious disease according to the characteristics of the COVID-19 pandemic. The proposed enhanced model, which will be referred to as the SEIR (Susceptible–Exposed–Infectious–Recovered) model with population migration, is inspired by the role that asymptomatic infected individuals, as well as population movements can play a crucial role in spreading the virus. In the model, the infected and the basic reproduction numbers are compared under the influence of intervention policies. The experimental simulation results show the impact of social distancing and migration-in rates on reducing the total number of infections and the basic reproductions. And then, the importance of controlling the number of migration-in people and the policy of restricting residents' movements in preventing the spread of COVID-19 pandemic are verified. • Establish a mathematical model of an infectious disease based on the characteristics of COVID-19. • Calculate the curve of the number of infections based on the Euler numerical method. • Analyze and compare the effects of different anti-epidemic policies on reducing the number of infections. [ABSTRACT FROM AUTHOR]

• This paper summarised the major types of SARS-COV-2 cluster infections worldwide. • Sixty-five studies were included, involving 108 cluster infections. • The major types of clusters were families, community transmission, etc. To summarise the major types of SARS-CoV-2 cluster infections worldwide through a comprehensive systematic review. All studies published between 01 January–15 June 2020 on COVID-19 cluster infections in English electronic databases were searched, including PubMed, Embase, Web of Knowledge, and Scopus. All included studies were independently screened and evaluated by two authors, and information from each study was extracted using a standard form. Sixty-five studies were included, which involved 108 cluster infections from 13 countries, areas or territories. Seventy-two (66.7%) of the cluster infections were reported in China. The major types of cluster infections were families, community transmission, nosocomial infection, gatherings, transportation, shopping malls, conferences, tourists, religious organisations, workers, prisons, offices, and nursing homes. The SARS-CoV-2 can be transmitted in various circumstances, and cluster infections play an important role in the rapid evolution of COVID-19 transmission. Prevention and control measures such as social distancing must be strictly implemented to contain these cluster infections. [ABSTRACT FROM AUTHOR]

When 2020 began, we had no idea what was to unfold globally as we learnt about the Novel-Coronavirus in Wuhan, in the Hubei province of China. As this virus spread rapidly, it became a matter of time before many countries began to implement measures to try and contain the spread of the disease. COVID-19 as it is referred to, resulted in two main approaches to fighting the viral pandemic, either through a progressive set of measures to slow down the number of identified cases designed to 'flatten the curve' over time (anticipated to be at least six months), or to attack it by the severest of measures including a total lock-down and/or herding exposure to fast track 'immunisation' while we await a vaccine. The paper reports the findings from the first phase of an ongoing survey designed to identify the changing patterns in travel activity of Australian residents as a result of the stage 2 restrictions imposed by the Australian government. The main restrictions, in addition to social distancing of at least 1.5 m, are closure of entry to Australia (except residents returning), and closure of non-essential venues such as night clubs, restaurants, mass attendee sporting events, churches, weddings, and all social gatherings in any circumstance. With some employers encouraging working from home and others requiring it, in addition to job losses, and many children attending school online from home, the implications on travel activity is extreme. We identify the initial impacts associated with the first month of stricter social distancing measures introduced in Australia. • General support for the actions of government and business. • Widespread suppression of travel demand for all trip purposes across all modes. • Sizeable shift to working from home by those who can. • Public transport will face the largest hurdles in regaining confidence. • Retail and food logistics will need to examine distribution processes • The aviation sector will likely need to restart with a heavy focus on domestic travel. • Public transport will need to take overt measures to restore confidence. • The dominance of the car is further enforced in the context of biosecurity concerns. • Active transport is a viable option for short inner-city trips. • Infrastructure investment should be carefully considered. • Flexible working arrangements are perhaps the biggest policy lever available to governments. [ABSTRACT FROM AUTHOR]

This paper formulates a Model Predictive Control (MPC) policy to mitigate the COVID-19 contagion in Brazil, designed as optimal On-Off social isolation strategy. The proposed optimization algorithm is able to determine the time and duration of social distancing policies in the country. The achieved results are based on data from the period between March and May of 2020, regarding the cumulative number of infections and deaths due to the SARS-CoV-2 virus. This dataset is assumably largely sub-notified due to the absence of mass testing in Brazil. Thus, the MPC is based on a SIR model which is identified using an uncertainty-weighted Least-Squares criterion. Furthermore, this model includes an additional dynamic variable that mimics the response of the population to the social distancing policies determined by the government, which affect the COVID-19 transmission rate. The proposed control method is set within a mixed-logical formalism, since the decision variable is forcefully binary (existence or the absence of social distance policy). A dwell-time constraint is included to avoid too frequent shifts between these two inputs. The achieved simulation results illustrate how such optimal control method would operate in practice, pointing out that no social distancing should be relaxed before mid August 2020. If relaxations are necessary, they should not be performed before this date and should be in small periods, no longer than 25 days. This paradigm would proceed roughly until January/2021. The results also indicate a possible second peak of infections, which has a forecast to the beginning of October. This peak can be reduced if the periods of days with relaxed social isolation measures are shortened. [ABSTRACT FROM AUTHOR]

Urban streets, especially curbside spaces, are increasingly complex and often contested. The Coronavirus pandemic created a new demand for street space to enable physical distancing. The urgency of the pandemic and the fear of covid exposure suspended traditional community engagement opportunities, opposition from residents and business owners, and considerations over the privatization of public street space. This exploratory paper uses the case studies of Toronto and Chicago to trace the past and present regulations and programs affecting curbside parking spaces. Through these cases, this paper addresses larger questions that relate the historical conceptions around curbside parking use with those put forward in response to the pandemic. Given the popularity of pandemic-related curbside space programs and their potential to become long-term interventions, this paper also raises several questions around privatization, access and social equity that must be addressed in future iterations of programs affecting curbside space. • Cities are rapidly reimagining curbside space as a result of the pandemic. • Cities are reducing barriers to accessing curbside parking space by eateries. • Shifts in curb space use raise questions around privatization, access and social equity. • Long-term curb space interventions need to be more equitable and public. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has severely impacted human activities in a way never documented in modern history. The prevention policies and measures have abruptly changed well-established urban mobility patterns. In this context, we exploit different sources of urban mobility data to gain insights into the effects of restrictive policies on the daily mobility and exhaust emissions in pandemic and post-pandemic periods. Manhattan, the most densely populated borough in New York City, is chosen as the study area. We collect data generated by taxis, sharing bikes, and road detectors between 2019 and 2021, and estimate exhaust emissions using the COPERT (Computer Programme to calculate Emissions from Road Transport) model. A comparative analysis is conducted to identify important changes in urban mobility and emission patterns, with a particular focus on the lockdown period in 2020 and its counterparts in 2019 and 2021. The results of the paper fuel the discussion on urban resilience and policy-making in a post pandemic world. • A comparative analysis is conducted to identify important changes in urban mobility and emission patterns due to the COVID-19. • Remarkable reductions in taxi trips and exhaust emissions are witnessed during the lockdown period. • The need for social distancing has encouraged the utilization of bike-sharing services. • Evidence on the resilience of bike sharing systems during this pandemic has been found. [ABSTRACT FROM AUTHOR]

In this paper we investigate the public transport trip frequency variations, as well as the reasons that led to the shift away from public transport means, due to the COVID-19 pandemic. We studied relevant data from the Moovit platform, and we compared operational and trip frequency characteristics of public transport systems before and after the outbreak of the pandemic in 87 cities worldwide. On average, waiting times at public transport stops/stations increased while trip distances decreased, apparently due to the mobility restriction and social distancing measures implemented in 2020. Most of the Moovit users who said that they abandoned public transport in 2020 were found in Italy and Greece. We developed linear regression analysis models to investigate (among the 35 variables examined in the study) the relationship between public transport abandonment rates and socioeconomic factors, quality of service characteristics, and indicators of pandemic's spread. Empirical findings show that public transport dropout rates are positively correlated with the COVID-19 death toll figures, the cleanliness of public transport vehicles and facilities, as well as with the income inequality (GINI) index of the population, and thus reconfirm previous research findings. In addition, the waiting time at stops/stations and the number of transfers required for commute trips appeared to be the most critical public transport trip segments, which significantly determine the discontinuation of public transport use under pandemic circumstances. Our research findings indicate specific aspects of public transport services, which require tailored adjustments in order to recover ridership in the post-pandemic period. • COVID-19 effect on public transport abandonment is studied in 87 cities worldwide. • Regression analyses assessed abandonment on socioeconomic, COVID-19 and Moovit data. • High abandonment rates were found in Thessaloniki, San Francisco, and Palermo. • COVID-19 deaths, vehicle hygiene conditions, income inequality affected abandonment. • Long waiting times at stops and higher transfer rates account for higher abandonment rates. [ABSTRACT FROM AUTHOR]

• This paper provides an overview of options for the design and implementation of national phone surveys. • The discussion draws on the experience with high-frequency phone surveys on COVID-19 in Africa. • Recommendations are provided for phone surveys to be the mainstay in routine and crisis monitoring efforts. Following the onset of the COVID-19 pandemic, face-to-face survey data collection efforts came to a halt due to lockdowns, limitations on mobility and social distancing requirements. What followed was a surge in phone surveys to fulfill rapidly evolving needs for timely and policy-relevant microdata for understanding the socioeconomic impacts of and responses to the pandemic. Even as the face-to-face survey data collection efforts are resuming in different parts of the world with COVID-19 safety protocols, the rapidly-acquired experience with phone surveys on the part of national statistical offices and survey practitioners in low- and middle-income countries appears to have formed the foundation for phone surveys to be more commonly implemented in the post-pandemic era, in response to other shocks and as complementary efforts to face-to-face surveys. Informed by the practical experience with the high-frequency phone surveys that have been implemented with support from the World Bank Living Standards Measurement Study (LSMS) to monitor the socioeconomic impacts of the COVID-19 pandemic, this paper provides an overview of options for the design and implementation of phone surveys to collect representative data from households and individuals. Further, the discussion identifies the requirements for phone surveys to be a mainstay in the toolkits of national statistical offices and the directions for future research on the design and implementation of phone surveys. [ABSTRACT FROM AUTHOR]

The complex dynamics of human mobility, combined with sporadic cases of local outbreaks, make assessing the impact of large-scale social distancing on COVID-19 propagation in China a challenge. In this paper, with the travel big dataset supported by Baidu migration platform, we develop a reactive–diffusion epidemic model on human mobility networks to characterize the spatio-temporal propagation of COVID-19, and a novel time-dependent function is incorporated into the model to describe the effects of human intervention. By applying the system control theory, we discuss both constant and time-varying threshold behavior of proposed model. In the context of population mobility-mediated epidemics in China, we explore the transmission patterns of COVID-19 in city clusters. The results suggest that human intervention significantly inhibits the high correlation between population mobility and infection cases. Furthermore, by simulating different population flow scenarios, we reveal spatial diffusion phenomenon of cases from cities with high infection density to cities with low infection density. Finally, our model exhibits acceptable prediction performance using actual case data. The localized analytical results verify the ability of the PDE model to correctly describe the epidemic propagation and provide new insights for controlling the spread of COVID-19. • A reaction–diffusion epidemic model on human mobility networks is studied. • The constant and time-varying threshold behavior of the model is discussed. • Human intervention inhibits the high correlation between migration and pandemics. • The spatial diffusion of cases among cities is numerically simulated. • The predictive performance of the model is validated by using real case data. [ABSTRACT FROM AUTHOR]

• Willingness to pay is estimated for four measures to reduce COVID-19 spread in transport. • Public transport and paratransit are considered, in the capitals of Uganda and Bangladesh. • WTP for an innovative barrier for motorcycle taxis is estimated. • Respondents are willing to pay extra for each of the mitigation measures. • COVID-19 related safety factors became more important in mode choice than travel time or costs. • WTP for capacity reduction in buses were larger than the actual fare increases in both cities. In order to combat the spread of COVID-19, various measures were taken in most countries to make public transit and paratransit safer. These additional measures, which include restrictions on number of passengers, provision of hand sanitisers and face coverings, and more frequent cleaning, add to the costs of operations or reduce profitability. The resulting financial pressure on the transport operators raises an important question on who pays for these additional measures. In most countries, this has been covered by one-time government bailouts to operators or strategies to increase fare, the latter of which directly affects the users. However, even without these interventions, there could be a demand and as such willingness to pay (WTP) for some of these intervention measures from the consumers concerned about safety. Knowing such WTP will not only help operators set their fare, but also help the governments decide the appropriate bailout needed. This paper addresses the issue by estimating the user's willingness to pay for selected COVID-19 mitigation measures in public transport and paratransit (motorcycle taxis) using survey data collected from two cities in low-income countries as case studies – Kampala, Uganda and Dhaka, Bangladesh. For public transport, these measures are - (1) social distancing (passenger loading at half capacity), and (2) mandatory hand sanitisation and increased cleaning of surfaces, while for paratransit, they are - (1) provision of a transparent shield between the rider and the passenger, and (2) provision of cleaned helmets at the start of each trip. The study analyses stated preference data using the utility maximisation framework and finds that the implementation or provision of COVID-19 mitigation measures improves the attractiveness of the associated public transport or paratransit alternatives, and transport users make trade-offs between safety and cost when making travel decisions. We find positive willingness to pay for all four mitigation measures, suggesting potential existence of a market for these measures. We also find that the typical mode choice factors such as costs, travel time and convenience became less important during the pandemic and the safety measures became more important considerations. [ABSTRACT FROM AUTHOR]

The COVID-19 crisis has become the most intense and long-lasting in the history of aviation. There is already a significant literature on the immediate impact of the outbreak, as well as on speculation on the future evolution of the industry. This paper seeks to contribute to this discussion by assessing a year into the crisis the demand related aspects and passenger behavioural impacts of the pandemic. Specifically, the paper aims to identify discrete market segments of air passengers according to their shared attitudes and preferences about air travel in light of the COVID-19 crisis, as well as past behaviour and future travel intentions. To achieve this, we analyse data from a large (n = 2096) online questionnaire survey of air passengers in Norway. The cluster analysis identifies four distinct passenger segments, with each displaying varying attitudes, behaviours, and levels of concern about air travel. One of these groups, described as the ' Apprehensive Elders', were identified as having the highest level of concern about flying, and subsequently showed a sharp decline in their intention to travel in the future. Another group, termed the 'Cautious Commuters', showed similarly enhanced levels of concerns about flying, but maintained a high propensity to fly following the pandemic despite these concerns. Regarding possible interventions to increase confidence in flying in the future, across all segments the data shows a clear preference for more 'traditional' active interventions, including wearing of face masks and enforcement of physical distancing, over and above passive or technological interventions. Norway represents a valuable case as a possible signal for future policy and practice in relation to the recovery of air travel following the pandemic. The findings have important implications for air transport managers and decision makers in terms of managing the perceptions and expectations of different passenger groups as air travel begins to return. • For younger passengers, concern about flying does not reduce their propensity to fly. • Older passengers showed greater concern and reduction in air travel after COVID-19. • Regular travellers were more concerned onboard the aircraft than in the airport. • Traditional methods increase flyer confidence more than technological tools. • Safe Travel certification alone is not enough to increase passenger confidence. [ABSTRACT FROM AUTHOR]

Understanding the effects of COVID-19 mitigation for persons in group living environments is of critical importance to limiting the spread of the virus. In the U.S., residential recovery homes for persons with alcohol and drug disorders are good examples of high-risk environments where virus mitigation procedures are essential. The National Alliance for Recovery Residences (NARR) has taken recommendations developed by the Center for Disease Control (CDC) and applied them to recovery home settings. This paper describes how COVID-19 mitigation efforts in recovery homes may be influenced by two factors. First, while some houses are licensed by states with rigorous health and safety standards, others are not licensed and are subject to less oversight. These homes may be more inconsistent in adhering to mitigation standards. Second, to varying degrees, recovery homes use a social model approach to recovery that contrasts with mitigation procedures such as social distancing and stay-at-home orders. This paper provides examples of ways recovery homes have been forced to adjust to the competing demands of mitigation efforts and social model recovery. The paper also identifies multiple questions that could be addressed by provider-researcher coalitions to inform how social model recovery can navigate forward during the era of COVID-19. As we move forward during the era of COVID-19, providers are encouraged to remember that recovery homes have a history of resilience facing adversity and in fact have their origins in grassroots responses to the challenges of their times. [ABSTRACT FROM AUTHOR]

• Describes the mechanical design and installation of the ST40 divertor. • Describes the associated development trials. • Describes the compressed timescales and project management needed to install the divertor. Tokamak Energy's ST40 spherical tokamak, operating in a double null diverted configuration, has a design basis of toroidal field B t = 3 T on-axis (R = 40 cm), and plasma current I p = 2MA. The procurement and installation of the top and bottom divertors for installation into ST40 was anticipated to be completed on a quick timescale of approximately ten weeks. The difficulties inherent in a tight deadline were exacerbated by the necessary social distancing measures introduced to combat the global crisis of COVID-19. This paper describes the procurement and installation of the divertors, the design is described in the sister paper [1], authored by Daniel Iglesias. [ABSTRACT FROM AUTHOR]

The outbreak of the COVID-19 pandemic revealed the crucial role of social distancing and hygiene practices in reducing virus transmission and thus revealed the high risk of infection in urban informal housing. Through an empirical study of Singapore's infectious situation and antiepidemic measures, this paper shows that the number of infected migrant workers living in dormitories was three hundred times greater than the number of infected local urban residents, not only because of the migrants' 'vulnerable' position but also because their living conditions fostered widespread transmission of the virus. The dwelling conditions of migrant dormitories, such as overcrowded living spaces, widely shared sanitation facilities, and poor hygiene practices, present great challenges to standard prevention strategies and control measures. Adverse health impacts resulting from the lockdown of dormitories during the COVID-19 pandemic suggest the importance of planning intervention in the dwelling conditions of informal housing, and indicate a need for the governments' active reforms of building codes and health care systems to promote the health of disadvantaged groups and then create more inclusive and healthy cities for all the society. [ABSTRACT FROM AUTHOR]

• This paper is the first to compare the impacts of government policies and national culture on social distancing. • This paper is the first to investigate the relationship between social distancing and all six of Hofstede's national culture dimensions. • This paper focus on the first wave of the COVID-19 outbreak since it isolates the impact of culture and government policies better than in the second wave. We assess the impact of national culture and government policies on social distancing to fight COVID-19 across major economies during the first wave of the pandemic. To do so, we regress government stringency index from Oxford COVID-19 government response tracker together with Hofstede's national culture scores on social distancing data from Google mobility reports. We find that government stringency has a far larger impact on social distancing than national culture. Social distancing increases with government stringency. We find two cultural dimensions matter: social distancing decreases with 'Long-term Orientation'; the opposite is true for 'Indulgence'. Our results convey that policymakers must act decisively rather than blaming the culture. [ABSTRACT FROM AUTHOR]

This paper looks into the impact of the recent COVID-19 epidemic on the daily mobility of people. Existing research into the epidemic travel patterns points at transport as a channel for disease spreading with especially long-distance travel in the centre of interest. We adopt a different approach looking into the effects that epidemic has on the transport system and specifically in relation to short-distance daily mobility activities. We go beyond simple travel avoidance behaviours and look into factors influencing change in travel times and in modal split under epidemic. This leads to the research problems we posit in this paper. We look into the overall reduction of daily travel and into the factors impacting peoples' decisions to refrain from daily traveling. This paper focuses on modes affected and explores differences between various societal groups. We use a CATI survey with a representative sample size of 1069 respondents from Poland. The survey was carried out between March, 24th and April, 6th2020, with a start date one week after the Polish government introduced administrative measures aimed at slowing down the COVID-19 epidemic. For data analysis, we propose using the GLM (general linear model), allowing us to include all the qualitative and quantitative variables which depict our sample. We observe significant drops in travel times under epidemic conditions. Those drops are similar regardless of the age group and gender. The time decrease depended on the purpose of travels, means of transport, traveller's household size, fear of coronavirus, main occupation, and change in it caused by the epidemic. The more the respondent was afraid of coronavirus, the more she or he shortened the travel time. • CATI survey reveals significant drops in daily travel times during epidemic. • The research confirms the effectiveness of mobility restrictions. • Travel time drops are similar regardless of the age group and gender. • Main occupation is the key factor affecting travel time change. • The more one was afraid of coronavirus, the bigger the travel time reduction was. [ABSTRACT FROM AUTHOR]

• We explore the problem of capacity for social distancing across various retail environments. • We provide guidance to managers as lockdown eases and establishments are allowed to reopen. • The paper identifies the minimum amount of space needed per person in different scenarios. • We estimate the optimal capacity for retailers to provide a safe environment for shoppers. COVID-19 has had a devastating effect on towns and cities throughout the world. However, with the gradual easing of lockdown policies in most countries, the majority of non-essential retail businesses are trying their best to bounce back both economically and socially. Nevertheless, the efforts of retail traders are hampered by uncertainty regarding what capacity measures need to be taken, and there is an urgent need to understand how social distancing can be safely followed and implemented in these spaces. This paper draws from retail space allocation, crowd science, operational research and ergonomics/biomechanics to develop a method for identifying the minimum amount of space an individual needs to socially distance in shops, markets, shopping centres and open commercial spaces, when there are other people present. The area required per person is calculated for both static space (where people are seated, standing or queuing, for example) and dynamic space (where people need to walk freely). We propose our method as a step forward in understanding the very practical problem of capacity, which can hopefully allow retail spaces to operate safely, and minimise the risk of virus transmission. [ABSTRACT FROM AUTHOR]

This paper is the first to examine the role of the cultural dimension in practising social distancing across the world. By drawing the data from the Google COVID-19 community mobility reports and the Hofstede cultural factors for 58 countries over the period from 16 February to 29 March 2020, we find that countries with higher 'Uncertainty Avoidance Index' predict the lower proportion of people gathering in public such as retail and recreation, grocery and pharmacy, parks, transit stations, workplaces. However, we do not find any predictive factor in having a relationship with the percentage of citizens staying in their residential areas. Our results are robust by adding the control variable as the wealth status, GDP per capita. Hence, this paper suggests some effective communications to contain the COVID-19 pandemic by emphasizing the role of uncertainties. [ABSTRACT FROM AUTHOR]

One approach to understand people's efforts to reduce disease transmission, is to consider the effect of behaviour on case rates. In this paper we present a spatial infection-reducing game model of public behaviour, formally equivalent to a Hopfield neural network coupled to SIRS disease dynamics. Behavioural game parameters can be precisely calibrated to geographical time series of Covid-19 active case numbers, giving an implied spatial history of behaviour. This is used to investigate the effects of government intervention, quantify behaviour area by area, and measure the effect of wealth on behaviour. We also demonstrate how a delay in people's perception of risk levels can induce behavioural instability, and oscillations in infection rates. • A flexible spatial model of infection-reducing behaviour based on a public goods game. • Model calibration to high resolution spatial Covid-19 case data provided by the NHS. • Population's behavioural response to governmental restriction levels can be measured. • Wealth significantly influences infection-reducing behaviour at population level. • Case reporting delays induce behavioural and disease instability. [ABSTRACT FROM AUTHOR]

• To prevent COVID-19 contagion, it is essential to detect suspect people as soon as possible. • Model-based Compressive sensing can determine affected individuals with a lower number of test • Group testing is not applicable is the condition that the ratio of affected/non-affected persons is high, such as COVID-19 test. • The contextual information (background disease, lifestyle, age, fever, etc.) can be used to build a graph model which using in model-based compressive sensing. The COVID-19 pandemic is threatening billions of people's life all over the world. As of March 6, 2021, covid-19 has confirmed in 115,653,459 people worldwide. It has also a devastating effect on businesses and social activities. Since there is still no definite cure for this disease, extensive testing is the most critical issue to determine the trend of illness, appropriate medical treatment, and make social distancing policies. Besides, testing more people in a shorter time helps to contain the contagion. The PCR-based methods are the most popular tests which take about an hour to make the output result. Obviously, it makes the number of tests highly limited and consequently, hurts the efficiency of pandemic control. In this paper, we propose a new approach to identify affected individuals with a considerably reduced No. of tests. Intuitively, saving time and resources is the main advantage of our approach. We use contextual information to make a graph-based model to be used in model-based compressive sensing (CS). Our proposed model makes the testing with fewer tests required compared to traditional testing methods and even group testing. We embed contextual information such as age, underlying disease, symptoms (i.e. cough, fever, fatigue, loss of consciousness), and social contacts into a graph-based model. This model is used in model-based CS to minimize the required test. We take advantage of Discrete Graph Signal Processing on Graph (DSP G) to generate the model. Our contextual model makes CS more efficient in both the number of samples and the recovery quality. Moreover, it can be applied in the case that group testing is not applicable due to its severe dependency on sparsity. Experimental results show that the overall testing speed (individuals per test ratio) increases more than 15 times compared to the individual testing with the error of less than 5% which is dramatically lower than that of traditional compressive sensing. [ABSTRACT FROM AUTHOR]

In this paper we investigate feedback control techniques for the COVID-19 pandemic which are able to guarantee that the capacity of available intensive care unit beds is not exceeded. The control signal models the social distancing policies enacted by local policy makers. We propose a control design based on the bang–bang funnel controller which is robust with respect to uncertainties in the parameters of the epidemiological model and only requires measurements of the number of individuals who require medical attention. Simulations illustrate the efficiency of the proposed controller. [ABSTRACT FROM AUTHOR]

• Distribution network reconfiguration considering losses, reliability and power quality. • Network reconfiguration based on new fuzzy multi-criteria approach. • Using of a new Improved Corona-virus Herd Immunity Optimizer Algorithm (ICHIOA) • Investigation of load variations impact on unbalanced network reconfiguration. • Superiority of ICHIOA compared to CHIO, PSO, GWO, MFO, BA and ALO. Reconfiguration of the distribution network to determine its optimal configuration is a technical and low-cost method that can improve different characteristics of the network based on multi-criteria optimization. In this paper reconfiguration of unbalanced distribution networks is presented with the objective of power loss minimization, voltage unbalance minimization, voltage sag improvement, and minimizing energy not supplied by the customers based on fuzzy multi-criteria approach (FMCA) using new improved corona-virus herd immunity optimizer algorithm (ICHIOA). The voltage unbalances and voltage sag is power quality criteria and also the ENS refers to the reliability index. Conventional CHIOA is inspired based on herd immunity against COVID-19 disease via social distancing and is improved using nonlinearly decreasing inertia weight strategy for global and local exploration improvement. The methodology is implemented as single and multi-objective optimization on 33 and 69 bus IEEE standard networks. Moreover, the performance of the ICHIOA in problem-solving is compared with some well-known algorithms such as particle swarm optimization (PSO), grey wolf optimizer (GWO), moth flame optimizer (MFO), ant lion optimizer (ALO), bat algorithm (BA) and also conventional CHIOA. The simulation results based on the FMCA showed that all criteria are improved with reconfiguration due to compromising between them while in single-objective optimization, some criteria may be weakened. Also, the obtained results confirmed the superiority of the ICHIOA in comparison with the other algorithms in achieving better criteria with lower convergence tolerance and more convergence accuracy. Moreover, the results cleared that the ICHIOA based on FMCA is capable to determine the best network configuration optimally to improve the power loss, voltage sag, voltage unbalance, and ENS in different loading conditions. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, the collapse of the public transit ridership led to significant budget deficits due to dramatic decreases in fare revenues. Additionally, public transit agencies are facing challenges of reduced vehicle capacity due to social distancing requirements, additional costs of cleaning and protective equipment, and increased downtime for vehicle cleaning. Due to these constraints on resources and budgets, many transit agencies have adopted essential service plans with reduced service hours, number of routes, or frequencies. This paper studies the resiliency during a pandemic of On-Demand Multimodal Transit Systems (ODMTS), a new generation of transit systems that combine a network of high-frequency trains and buses with on-demand shuttles to serve the first and last miles and act as feeders to the fixed network. It presents a case study for the city of Atlanta and evaluates ODMTS for multiple scenarios of depressed demand and social distancing representing various stages of the pandemic. The case study relies on an optimization pipeline that provides an end-to-end ODMTS solution by bringing together methods for demand estimation, network design, fleet sizing, and real-time dispatching. These methods are adapted to work in a multimodal setting and to satisfy practical constraints. In particular, a limit is imposed on the number of passenger transfers, and a new network design model is introduced to avoid the computational burden stemming from this constraint. Real data from the Metropolitan Atlanta Rapid Transit Authority (MARTA) is used to conduct the case study, and the results are evaluated with a high-fidelity simulation. The case study demonstrates how ODMTS provide a resilient solution in terms of cost, convenience, and accessibility for this wide range of scenarios. • On-Demand Multimodal Transit Systems (ODMTS) are resilient during pandemic response. • An end-to-end pipeline is presented to design and evaluate ODMTS. • A new network design model is introduced to limit the number of passenger transfers. • The study considers various scenarios of depressed demand and constrained capacity. • Findings are demonstrated on MARTA, the transit system of the city of Atlanta. [ABSTRACT FROM AUTHOR]

• COVID-19 pandemic examined. • COVID-19-stimulated innovations explored. • The concept of "CoviNovation" advanced. • Innovative practices are examined. Despite the valuable contributions of scholars to the COVID-19 pandemic, limited scholarly attention has been paid to the opportunities unleashed by the crisis. As many industries have been turned upside down and markets rendered uncertain, the crisis is also propelling waves of innovation activities. In this paper, we developed the concept of "CoviNovation" to denote the firm's innovation emerging from, rooted in or accelerated by the crisis. Our analysis yielded insights on innovations inspired by COVID-19 across the global airline industry, including inflight social distancing, utilizing touchless technologies at airports, disinfecting aircraft with UV, open-middle-seat policy, accelerated use of biometrics in check-in and COVID-19 insurance. The theoretical and practical implications of the COVID-19-inspired innovations examined. [ABSTRACT FROM AUTHOR]

Much attention on the spread and impact of the ongoing pandemic has focused on institutional factors such as government capacity along with population-level characteristics such as race, income, and age. This paper draws on a growing body of evidence that bonding, bridging, and linking social capital - the horizontal and vertical ties that bind societies together - impact public health to explain why some U.S. counties have seen higher (or lower) excess deaths during the COVID19 pandemic than others. Drawing on county-level reports from the Centers for Disease Control and Prevention (CDC) since February 2020, we calculated the number of excess deaths per county compared to 2018. Starting with a panel dataset of county observations over time, we used coarsened exact matching to create smaller but more similar sets of communities that differ primarily in social capital. Controlling for several factors, including politics and governance, health care quality, and demographic characteristics, we find that bonding and linking social capital reduce the toll of COVID-19 on communities. Public health officials and community organizations should prioritize building and maintaining strong social ties and trust in government to help combat the pandemic. • This study examines excess death rates during the COVID19 pandemic among US counties. • We use a panel dataset of counties over 6 time-steps from February to September 2020. • We identified more comparable samples using coarsened exact matching, different only by social capital. • Bonding and linking social capital were associated with fewer excess deaths in US counties. • Bonding social capital was effective in spring, and linking social capital in summer. [ABSTRACT FROM AUTHOR]

Electric vehicle development is critical to achieve the sustainable goals, while the hit of COVID-19 strikes the market and brings challenges to the whole industry. China, among one of the earliest regions affected by COVID-19 and takes a great part in the global electric vehicle market, is attracting growing attention on its post-pandemic trends in the electric vehicle industry. This paper provides a comprehensive analysis of COVID-19 impacts on China's electric vehicle industry from both the demand side and the supply side. Both challenges and opportunities for China's electric vehicle development are revealed with emerging trend analysis. It is found that the COVID-19 outbreak has reduced electric vehicle sales in the short-term, but may also stimulate future electric vehicle demand especially for large electric cars with better performance. Meanwhile, travel restrictions caused by COVID-19 have interrupted electric vehicle material supplies that relying on imports, accelerating domestic substitute exploitation and inventory improvement for critical parts. Additionally, massive lockdowns for controlling COVID-19 have disrupted productions and operations, which tends to expel small brands out of the competitive market, concentrating China's electric vehicle industry to the leading brands. Finally, the social distancing trend after pandemic is bringing challenges to traditional EV distribution channels with dealers, pushing automakers to develop innovative online selling channels. These impacts are likely to lead to a reformation of China's electric vehicle industry towards a more advanced and reliable future. • Impacts of COVID-19 on China's EV market and supply chain are analyzed. • COVID-19 outbreak may shift consumer demand to large EVs with better performance. • Supply interruption by travel restrictions may promote domestic R&D and reserves. • Suspension caused by lockdown may expel SMEs and concentrate China's EV industry. • Post-pandemic social distancing may lead to innovative online EV selling models. [ABSTRACT FROM AUTHOR]

• Even though 85% of respondents knew physical distancing helps curb the spread of COVID-19, over a third did not practice it. • Increasing the salience of social or material costs of not practicing physical distancing had no effect on expected behavior. • Respondents underestimated others' support for lockdown policies. Updating these beliefs may help encourage compliance. • 54% of respondents wrote a message encouracing physical distancing, suggesting a potential tool for creating common knowledge. Health behaviors to prevent the spread of infectious diseases are often subject to collective action problems, and social norms can play an important role in inducing compliance. In this paper, we study knowledge, beliefs, and behavior related to one such practice during the COVID-19 pandemic – physical distancing – using an online survey of social media users in Kenya, Nigeria, and Uganda. We find that, while there is widespread knowledge that physical distancing reduces the spread of the virus, respondents underestimate their peers' support for policies designed to enforce physical distancing, expect others not to practice physical distancing, and do not maintain physical distance themselves. However, more than half of respondents wrote a message to encourage others to practice physical distancing. Findings from survey experiments suggest that making salient the social and material costs for not keeping physical distance were insufficient to encourage compliance, suggestive of the absence of a social norm of physical distancing at the time. Given the large gap between own attitudes and expectations of others' attitudes toward lockdown policies, we propose that providing information on the extent of public support for physical distancing in citizens' own words may encourage compliance in the future. [ABSTRACT FROM AUTHOR]

Personal safety has had a renewed focus throughout the COVID-19 pandemic, which has led to behavioral change. The adoption of E-wallets facilitates social distancing and thereby helps prevent the spread of the COVID-19 virus. This paper aims to investigate the potential for consumers' continued usage of an E-wallet service through an integrated framework based on two established models: the Health Belief Model (HBM) and Technology Continuous Theory (TCT). An electronic survey was distributed to a sample of 1080 individuals from academic society in three different Hungarian universities who had used an electronic wallet during the pandemic COVID-19. Structural equation modelling (SEM) was applied in the study and explained the 55.9% variance in consumers' continuous intention towards E-wallet usage. This study found that while the COVID-19 pandemic strongly influenced the current use of e-wallets; the pivotal factor affecting their continued use is based on consumer self-efficacy. The study has both short and long-term implications; in the short-term, decisionmakers should utilize health threat constructs (as an element of the protective behaviors taken during the COVID-19 pandemic) to motivate consumers to use E-wallets; in the longer-term, banks should develop further strategies that encourage consumer loyalty regarding E-wallets by reassuring customers that these financial services achieve the value and benefits that they expect, resulting in self-efficacy. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic is producing significant economic and social cost globally. As a cure or a treatment is yet unavailable, social distancing is considered the key way to prevent it. Mobility restrictions and confinement measures implemented across the world are considered to help reduce air pollution. However, empirical examination of the link between public mobility changes and air pollution during the COVID-19 period remains unavailable. This paper examines the short and long run impacts of mobility changes on carbon monoxide (CO) emissions by employing three dynamic estimators on a panel of 35 countries covering daily data from 15 February to April 17, 2020 - a period when most countries went into strict lockdowns. Findings show a consistent evidence at the all-countries level and across regions that long-run indoor mobility increases reduce CO emissions, while outdoor mobility increases across places such as transit stations, workplaces, grocery & pharmacies, retail & recreation, and parks drive up emissions. Among the regions studied, Europe excluding the EU and the UK (−8.4%), followed by East Asia and the Pacific (−4.3%), sees a larger emissions reduction from increased indoor mobility. While short-run effects are limited in general, emissions in US-Canada respond to indoor and outdoor mobility changes in both the short (1.1%) and long run (−1.4%). Findings overall indicate that reducing unnecessary outdoor mobility could help in maintaining air quality in the post-pandemic world. [Display omitted] • Longer term lockdowns and mobility restrictions slow down CO emissions globally. • Europe experiences the largest declines in air pollution due to mobility restrictions in the long run. • Emissions decline due to mobility restrictions in the US and Canada in both short and long run. • Curbing people movement through more work-from-home could save the environment. [ABSTRACT FROM AUTHOR]

• A big-data-driven analytical framework assessing human mobility during COVID-19. • Location-based evidence from large-scale and privacy-protected samples in the US. • County-level human mobility metrics are made publicly available via an open platform. • Comprehensive assessment of human mobility using generalized additive mixed models. • The policy effect of "Stay-at-home" order on restricting travel is found limited. During the unprecedented coronavirus disease 2019 (COVID-19) challenge, non-pharmaceutical interventions became a widely adopted strategy to limit physical movements and interactions to mitigate virus transmissions. For situational awareness and decision-support, quickly available yet accurate big-data analytics about human mobility and social distancing is invaluable to agencies and decision-makers. This paper presents a big-data-driven analytical framework that ingests terabytes of data on a daily basis and quantitatively assesses the human mobility trend during COVID-19. Using mobile device location data of over 150 million monthly active samples in the United States (U.S.), the study successfully measures human mobility with three main metrics at the county level: daily average number of trips per person; daily average person-miles traveled; and daily percentage of residents staying home. A set of generalized additive mixed models is employed to disentangle the policy effect on human mobility from other confounding effects including virus effect, socio-demographic effect, weather effect, industry effect, and spatiotemporal autocorrelation. Results reveal the policy plays a limited, time-decreasing, and region-specific effect on human movement. The stay-at-home orders only contribute to a 3.5%-7.9% decrease in human mobility, while the reopening guidelines lead to a 1.6%-5.2% mobility increase. Results also indicate a reasonable spatial heterogeneity among the U.S. counties, wherein the number of confirmed COVID-19 cases, income levels, industry structure, age and racial distribution play important roles. The data informatics generated by the framework are made available to the public for a timely understanding of mobility trends and policy effects, as well as for time-sensitive decision support to further contain the spread of the virus. [ABSTRACT FROM AUTHOR]

2020 in the United States was marked by two converging crises—the COVID-19 pandemic and the large-scale uprisings in support of Black lives. These crises were met with both a counterproductive and inadequate response from the federal government. We examine these converging crises at the individual, social, and political scales. The biological realities of COVID-19 impact different populations in widely varied ways—the poor, the elderly, Black, Indigenous, and people of color, and those living with comorbidities get sick and die at the highest rates. Social distancing guidelines shifted millions of people to work-from-home and millions more lost their jobs, even as care laborers, preponderantly women, Black, Indigenous, and people of color, were asked to put their and their loved ones' lives on the line for the continuation of all of our lives. These biological, social, and economic crises have been punctuated by civil unrest, as millions took to the streets for racial justice, noting the unequal impacts of the pandemic. These converging crises have laid bare decades of neoliberal and neoconservative policies and ideologies, undergirded as they have been by racial capitalism, for their fundamental uncaringness. In this paper, we argue that this pandemic not only made a wider population more acutely aware of the necessity and importance of the need to care and for caring labors, but also that we stand at the precipice of potentiality--of producing a more caring society. To frame our argument, we draw on Nancy Scheper-Hughes and Margaret Lock's (1987) framework of three bodies—individual, social, and political—to unpack the multi-scalar entanglements in the differential impacts of COVID-19, questions of care, and their articulation in the current political-economic context. [ABSTRACT FROM AUTHOR]

Background: The aim was to examine the correlates of increased alcohol consumption during the COVID-19 pandemic-related restrictions that were implemented in a sample of UK adults.Methods: This paper presents analyses of data from a cross-sectional study. Adults aged 18 years and over, residing in the UK and self-isolating from others outside their own household were eligible to participate. Participants reported increase or no increase in their level of alcohol consumption from before to during lockdown, as well as symptoms of anxiety, depression and mental wellbeing. Socio-demographic characteristics were compared between adults with and without reported increased alcohol consumption. The associations between reported increased alcohol consumption and mental health outcomes were investigated using logistic and linear regression analyses.Results: 691 adults (61.1 % women; 48.8 % aged 35-64 years) were included in the analysis. Of these, 17 % reported increased alcohol consumption after lockdown. A higher proportion of 18-34-year olds reported increased alcohol consumption compared to older groups. The prevalence of poor overall mental health was significantly higher in individuals with increased alcohol consumption (vs. no increase) (45.4 % versus 32.7 %; p-value = 0.01). There was a significant association between increased alcohol consumption and poor overall mental health (OR = 1.64; 95 % CI = 1.01, 2.66), depressive symptoms (unstandardized beta = 2.93; 95 % CI = 0.91, 4.95) and mental wellbeing (unstandardized beta=-1.38; 95 % CI=-2.38, -0.39).Conclusions: More than one in six UK adults increased their alcohol consumption during lockdown and a higher proportion of these were younger adults. Increased alcohol consumption was independently associated with poor overall mental health, increased depressive symptoms and lower mental wellbeing. These findings highlight the importance of planning targeted support as we emerge from lockdown and plan for potential second and subsequent waves. [ABSTRACT FROM AUTHOR]