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With the rise of the Internet of Things (IoT) architectures and protocols, new video analytics systems and surveillance applications have been developed. In conventional systems, all the streams produced by cameras are sent to a centralized node where they can be seen by human operators whose task is to identify uncommon on abnormal situations. However, this way, much bandwidth is necessary for the system to work, and the number of necessary resources is proportional to the number of cameras and streams involved. In this paper, we propose an interesting approach to this problem: transforming any IP camera into a cognitive object. A cognitive camera (CC) can be considered a classic connected camera with onboard computational power for intelligent video processing. A CC can understand and interact with the surroundings, intelligently analyze complex scenes, and interact with the users. The IoT Edge Computing approach decreases latency in the decision-making process and consumes a tiny portion of bandwidth concerning the stream of a video, even in low resolution. CCs can help to address COVID-19. As a preventive measure, proper crowd monitoring and management systems must be installed in public places to limit sudden outbreaks and improve healthcare. The number of new infections can be significantly reduced by adopting physical distancing measures earlier. Motivated by this notion, a real-time crowd monitoring and management system for physical distance classification using CCs is proposed in this research paper. The experiment on Movidius board, an AI accelerator device, provides promising results of our proposed method in which the accuracies can achieve more than 85% from different datasets. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to put forward some evidence-based lessons that can be learned from how to respond to a Pandemic that relate to healthy living behaviours (HLB). A 4-step methodology was followed to conduct a narrative review of the literature and to present a professional practice vignette. The narrative review identified 8 lessons: 1) peer review; 2) historical perspectives; 3) investing in resilience and protection; 4) unintended consequences; 5) protecting physical activity; 6) school closures; 7) mental health; and 8) obesity. As in all probability there will be another Pandemic, it is important that the lessons learned over the last three years in relation to HLB are acted upon. Whilst there will not always be a consensus on what to emphasise, it is important that many evidence-based positions are presented. The authors of this paper recognise that this work is a starting point and that the lessons presented here will need to be revisited as new evidence becomes available. [ABSTRACT FROM AUTHOR]

• Sectors and linkages in economic system can be viewed as nodes and edges in network. And in this paper, network analysis method is adopted into input-output tables to evaluate the structural change of Chinese economy. • The modelling results indicate that the COVID-19 pandemic accelerates the undergoing structural transformation of Chinese economy. • Traditional strong sectors like petroleum and finance are severely attacked by pandemic and lag behind in structural status. • Sectors of digital service industries and scientific research expand their activities rapidly under social distancing policies. • Development strategies for China in the post-pandemic era regarding old and new growth engines are proposed. Recognizing the impact of COVID-19 on economic structure is an urgently required task for the post-pandemic era. However, studies have been hampered in undertaking this task by a lack of current data and the use of inappropriate methods. This paper fills the gap in the literature by applying a network analysis method using the newly released input–output tables of China and evaluating the structural impacts on the economy, including the changes in the sectoral closeness, betweenness, risk condition, and network backbone. The modelling results demonstrate that the pandemic has accelerated the structural transformation process of the Chinese economy: the traditional growth engines, such as the petroleum and finance industries, have lagged, whereas new growth engine sectors, including the digital services and scientific research industries, have expanded rapidly. Accordingly, we propose that the government formulate policies to stabilize old growth engine industries and foster new drivers to promote a sustainable economic recovery in China. [ABSTRACT FROM AUTHOR]

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]

The effects on human health and life have been catastrophic and its adverse economic effects have been profound, as many countries are engaged in lockdowns, social distancing, mobility, and other restrictions. These have caused unprecedented disruptions in production, distribution, consumption, supply chains, tourism, trade, investments, among others. This paper utilises a simple conceptual framework to anticipate the potential adverse impacts of the pandemic on the economy focussing specifically on output, employment, and prices. The anticipated potential outcomes on the above-mentioned global indicators are assessed utilising publicly available data and information. Both qualitative and quantitative information are utilised which are obtained from various primary and secondary sources. Consistent with the potential outcomes, the paper finds and reports severe adverse impact of the pandemic on global production, employment, and prices. Finally, the paper discusses policy responses to combat the crisis by governments and international organisations and discusses some business implications. [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]

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]

The world was taken aback when the Covid-19 pandemic hit in 2019. Ever since precautions have been taken to prevent the spreading or mutating of the virus, but the virus still keeps spreading and mutating. Scientists predict that the virus is going to stay for a long time but with reduced effectiveness. Recognizing the symptoms of the virus is essential in order to provide proper treatment for the virus. Visiting hospitals for consultation becomes quite difficult when people are supposed to maintain social distancing. Recently neural network generative models have shown impressive abilities in developing chatbots. However, using these neural network generative models that lack the required Covid specific knowledge to develop a Covid consulting system makes them difficult to be scaled. In order to bridge the gap between patients and a limited number of doctors we have proposed a Covid consulting agent by integrating the medical knowledge of Covid-19 with the neural network generative models. This system will automatically scan patient's dialogues seeking for a consultation to recognize the symptoms for Covid-19. The transformer and pretrained systems of BERT-GPT and GPT were fine-tuned CovidDialog-English dataset to generate responses for Covid-19 which were doctor-like and clinically meaningful to further solve the problem of the surging demand for medical consultations compared to the limited number of medical professionals. The results are evaluated and compared using multiple evaluation metrics which are NIST- n , perplexity, BLEU- n , METEOR, Entropy- n and Dist- n. In this paper, we also hope to prove that the results obtained from the automated dialogue systems were significantly similar to human evaluation. Furthermore, the evaluation shows that state-of-the-art BERT-GPT performs better. [ABSTRACT FROM AUTHOR]

The Global Novel Coronavirus Disease-2019 (COVID-19) pandemic has forced social distancing norms that have been followed worldwide. Thus, traditional biometric-based attendance marking systems are replaced with contactless attendance marking schemes. However, there are limitations of manufacturing cost, spoofing attacks, and security vulnerabilities. Thus, the paper proposes a contactless camera-based attendance system with the equipped functionalities of anti-spoofing. The proposed scheme can detect liveliness, so fake attendance marking is eliminated. The proposed scheme is also scalable and cost-effective, with generic solutions adaptable to schools, colleges, or other places where attendance is required. The system also eliminates the limitation of one-entry by multiple face-marking systems that allow simultaneous attendance marking. In performance analysis, parameters like image precision, storage cost, retrieval latency, and analysis of the anti-spoofing module is presented against existing schemes. An accuracy of 95.85% is reported for the model, with a significant improvement of 33.52% in storage cost through the Firebase database, which outperforms existing state-of-the-art schemes. [ABSTRACT FROM AUTHOR]

Many countries have imposed a set of non-pharmaceutical health policy interventions in an effort to slow the spread of the COVID-19 pandemic. The objective of this paper is to examine the effects of the interventions, drawing on evidence from the OECD countries. A special feature here is the mechanism that underlies the impact of the containment policies. To this end, a causal mediation analysis decomposing the total effect into a direct and an indirect effect is conducted. The key finding is a dual cause-effect channel. On the one hand, there is a direct effect of the non-pharmaceutical interventions on the various health variables. Beyond this, a quantitatively dominant indirect impact of non-pharmaceutical interventions operating via voluntary changes in social distancing is shown. [ABSTRACT FROM AUTHOR]

Aim: To establish contact lens wear and care practices during the COVID-19 pandemic in Spain.Method: A 58-item anonymous online survey was distributed during the period 30th April to 10th May via Qualtrics. The survey explored: a) demographic characteristics (age, sex, general health and where they were living during lockdown), b) changes in their contact lens use during lockdown, c) hygiene and contact lens compliance and d) concerns associated with contact lens wear and ways to support wearers during the pandemic.Results: Two hundred and sixty responses were analysed (38.8 ± 11.4 years old, 75% female). Three-quarters of participants reported that they were self-isolating or rigorously following social distancing advice. Sixty-seven percent of participants reported using their contact lenses less during the pandemic. Respondents were found to be compliant with handwashing prior to inserting and removing contact lenses (in both cases 97% doing this 'most times' or 'every time'). However, only 44 % complied with the '20 s rule' and 48 % used a shared towel to dry their hands. A higher proportion of hydrogen peroxide users replaced the lens case monthly compared to multi-purpose users (64% vs.49%; p < 0.001). Twenty-four percent admitted wearing lenses whilst showering and 16% did not consider ceasing lens wear if feeling unwell with flu/cold symptoms.Conclusion: Eye care practitioners should continue to educate contact lens wearers to ensure safe contact lens wear to minimise the chance of developing contact lens related complications during the pandemic. Modifiable factors that need particular attention in Spain include: handwashing for at least 20s before lens handling, drying hands with single use paper towels, including a rub-and-rinse step for reusable lenses, lens case cleaning and renewal, avoidance of water exposure and when to cease lens wear during the pandemic. [ABSTRACT FROM AUTHOR]

Under the background that asymptomatic virus carriers are contagious and the virus in the infected individuals has mild pathogenicity and enhanced transmissivity for an infectious disease, the phenomenon appears that the majority of infected people do not show any symptoms, but can infect others. Multiple population-wide testing can screen out asymptomatic virus carriers in time. Thus, we develop an infectious disease transmission dynamics model that includes three stages: non-testing period, testing period and testing interval, with multiple population-wide testing and social distancing to study the effects of the first testing time, total testing number, and testing interval time on the transmission of infectious diseases in this paper. The existence, uniqueness, boundedness and positivity of the solution, as well as the formulas of the basic reproduction number and the control reproduction number of the established model are established The numerical results show that the earlier the population-wide testing measure is implemented, the fewer the final size and necessary testing frequency. In the initial stage of the larger-scale spread of infectious disease, the existing virus carriers are not the most. But if population-wide testing measure is implemented during this period, the strongest testing force is required to contain the spread of the epidemic. Besides, population-wide testing combined with restrictive social distancing will significantly reduce the final size, necessary testing frequency, and duration of the epidemic. The testing interval time should be no longer than the incubation period of the virus to prevent and control the epidemic accurately. Therefore, the paper provides a theoretic basis for developing and implementing scientific testing strategies. • A three-stage SEIR model with the multiple population-wide testing is proposed. • Minimum of testing is related to the start time of the first test and test interval. • The choice of test interval should no longer than the incubation period of the virus. • In this case, no obvious difference in the minimum of test and the final size appear. [ABSTRACT FROM AUTHOR]

This paper presents two studies which address an underdeveloped area within acculturation research: majority members' perceptions of cultural change. Specifically, drawing on the theory of cultural inertia, we explored how majority members react to perceptions of recent majority culture and minority cultures change. A path model was hypothesised whereby British and English majority members' perceptions that their British (Study 1, N = 266) and English (Study 2, N = 292) cultures are changing due to the presence of minority cultures was positively associated with symbolic threat, and through this with greater prejudice towards minorities living in the UK/England. However, participants' perceptions that minority cultures are changing due to influence from the majority culture were negatively associated with symbolic threat, and through this with less prejudice towards minorities. These findings were supported across different operationalizations of prejudice (i.e., social distance and positive/negative affect) and even when controlling for another recently introduced concept of meta-perceptions – that is, majority members' perceptions of whether minority members prefer majority members to maintain their culture and/or adopt to the minority cultures. Findings call for a greater focus on studying the intergroup consequences of majority members' perceptions of cultural change. [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]

The development of techniques and systems for indicating routes in outdoor and indoor spaces has received a great deal of attention. While outdoor route planning is based on criteria such as the shortest, fastest route, and the least number of turns, indoor route planning is primarily focused on accessibility and safety. Routing systems for indoor spaces have become the focus of many researchers due to significant differences that make indoor routing is more complex than outdoor routing. An indoor environment is complex, which makes it difficult to find a route due to closed corridors, multiple floors, and other indoor features. Because of the present global scenario following the advent of the COVID-19 pandemic, indoor routing has become increasingly crucial. Wi-Fi, Bluetooth, and RFID are among the technologies used for indoor routing. For these technologies to help and guide users to the optimal route to their chosen destinations, they require accurate information, appropriate processing and modeling, and route density monitoring to ensure social distancing. In this paper, a new multi-user routing algorithm for indoor spaces is proposed. It has been adapted to the need for social distancing, and is based on multiple users, allowing more than one user to take the route or separate routes at one time without causing congestion on the same route. Despite the complexity of the system, the evaluation indicated that the proposed algorithm successfully controlled the flow of moving objects while ensuring social distancing and maintaining low costs. [ABSTRACT FROM AUTHOR]

• Behavioural study investigated transmission risks and mitigations for UK mass events in 2021. • Explored non-pharmaceutical interventions (NPIs); e.g. social distancing and face coverings. • 21 events observed. Data collection method presented with overview of data. The Events Research Programme (ERP) was a multi-disciplinary study undertaken during the COVID-19 pandemic to investigate SARS-CoV-2 transmission risks and mitigations around the reopening of mass events in the UK in 2021 – including a behavioural study, exploring how non-pharmaceutical interventions (NPIs), such as social distancing, pre-event virus testing, and the use of face coverings might enable people to attend events safely. This behavioural study is discussed here. A total of 21 pilot events were involved in the study between April and July 2021. The venues used for the pilots varied in size, layout, occupancy level, and crowd management approaches. Data was extracted from manual qualitative observations and venue CCTV cameras which recorded routinely at venues. In addition, 890 cameras were installed during the events to capture attendee movement outside the venues, during arrival, in event areas, circulation spaces, bars and restaurants, and on exiting. A mixed method approach was adopted to ensure locations and activities of interest were captured, quantitative data gathered, and that this data could be placed in context. This enabled a behavioural study, quantifying crowd performance behaviours for comparison between and within events. This paper describes the background to this work, the method adopted and provides a brief overview of the data collected, relating primarily to (i) crowd densities, (ii) social distancing (captured here as contact distancing), and (iii) the use of face coverings. [ABSTRACT FROM AUTHOR]

This paper studies the effectiveness of several pandemic restriction measures adopted in Singapore during the COVID-19 outbreak. To this end, the classical Susceptible-Exposed-Infectious-Recovered (SEIR) model widely used to describe the dynamic process of epidemic propagation is extended to an area-based SEIR model with the consideration of exposure to infections during commute and quarantine. The proposed model considers infections within areas and infections occurred during the commute of individuals. A case study of the Singapore MRT system is presented to show the effectiveness of pandemic restriction policies implemented in Singapore, namely social distancing, work shift and Circuit Breaker (CB) and phase advisories. A long-term investigation of COVID-19 pandemic in Singapore is performed, and the disease transmission dynamics in 2020–2021 (which covers the first wave and second wave of COVID-19 pandemic in Singapore) is modelled. [ABSTRACT FROM AUTHOR]

This paper presents a data-driven approach for COVID-19 modeling and forecasting, which can be used by public policy and decision makers to control the outbreak through Non-Pharmaceutical Interventions (NPI). First, we apply an extended Kalman filter (EKF) to a discrete-time stochastic augmented compartmental model to estimate the time-varying effective reproduction number (R t). We use daily confirmed cases, active cases, recovered cases, deceased cases, Case-Fatality-Rate (CFR), and infectious time as inputs for the model. Furthermore, we define a Transmission Index (TI) as a ratio between the instantaneous and the maximum value of the effective reproduction number. The value of TI indicates the "effectiveness" of the disease transmission from a contact between a susceptible and an infectious individual in the presence of current measures, such as physical distancing and lock-down, relative to a normal condition. Based on the value of TI, we forecast different scenarios to see the effect of relaxing and tightening public measures. Case studies in three countries are provided to show the practicability of our approach. [ABSTRACT FROM AUTHOR]

The SARS-CoV-2 virus was first registered in Brazil by the end of February 2020. Since then, the country counts over 150000 deaths due to COVID-19 and faces a profound social and economic crisis; there is also an ongoing health catastrophe, with the majority of hospital beds in many Brazilian cities currently occupied with COVID-19 patients. Thus, a Nonlinear Model Predictive Control (NMPC) scheme used to plan appropriate social distancing measures (and relaxations) in order to mitigate the effects of this pandemic is formulated in this paper. The strategy is designed upon an adapted data-driven Susceptible–Infected–Recovered–Deceased (SIRD) model, which includes time-varying auto-regressive immunological parameters. A novel identification procedure is proposed, composed of analytical regressions, Least-Squares optimization and auto-regressive model fits. The adapted SIRD model is validated with real data and able to adequately represent the contagion curves over large forecast horizons. The NMPC strategy is designed to generate piecewise constant quarantine guidelines, which can be reassessed (relaxed/strengthened) each week. Simulation results show that the proposed NMPC technique is able to mitigate the number of infections and progressively loosen social distancing measures. With respect to a "no-control" condition, the number of deaths could be reduced in up to 30% if the proposed NMPC coordinated health policy measures are enacted. [ABSTRACT FROM AUTHOR]

• Focus on community work for the betterment of floating children. • Use social network analysis within a Bourdieusian lens. • Analyse social groupings and the structures behind them. • Look at "small things" that are sociologically meaningful for social change. Drawing on Bourdieu's sociology, the concept of space in particular, this paper discussed the positions and dispositions of floating children in the urban space. It used social network analysis to test the homophily hypothesis that socially similar agents are physically proximate. Data were collected from 45 floating children and urban children in a community school in China. The results rejected the homophily hypothesis, calling for collective activism for small-scale but sociologically meaningful change to disrupt the correspondence between the physical and social distance established through the "site effects" of the hukou (household registration) system. [ABSTRACT FROM AUTHOR]

• Numerical investigation of human breathing zones in a semi-outdoor environment. • Local flow characteristics and BZs were studied using different crowded human-block arrays. • Crowd level significantly influenced the airflow field and BZ configuration. • Air temperature and wind direction affected the horizontal and vertical propagation of the BZs. This paper presents a comprehensive numerical investigation to predict the human breathing zones (BZs) in crowded semi-outdoor environments. The computational domain consisted of a nine-human block array with integrated nasal cavities subjected to the lower part of the atmospheric boundary layer. Five crowding levels, seven wind directions, and inflow ambient air temperatures (ranging from 10 to 31 °C) were tested to examine the horizontal and vertical formations of the BZs. Validation and verification tests were performed through comparisons with experimental results, a grid independence test, and an evaluation of various randomized distribution scenarios to minimize the uncertainties of the computational fluid dynamics analyses. The horizontal extension of the BZs tripled as the crowding level increased from 0.325 to 4.0 m2/capita. However, the lateral extension was insensitive and remained within 10 cm of the nostrils. Human models can inhale air close to the cheek, neck, and shoulders when an oblique flow is assumed. As the air temperature increased, individuals tended to inhale air from the upper regions, which was influenced by the interrelated thermal properties of the human body. Consequently, under high-temperature conditions, there may be an increased probability of gas-phase contaminant inhalation over greater horizontal distances. [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]

During the COVID-19 pandemic, public transport in many cities faces dramatic reduction of passenger demand. Various countermeasures such as social distancing and in-vehicle disinfection have been implemented to reduce the potential risks concerning infection, the effectiveness in promoting the use of public transport however remains unclear. Unlike the usual situation where time and cost are the main factors affecting travel decisions, the uncertainty hiding behind the behavior change of public transport users in a pandemic might be greatly affected by the control measures and the perception of people. This paper therefore aims to examine the effects of COVID-19 related countermeasures implemented in public transport on individuals' travel decisions. We explore the extent to which do policy countermeasures influence different groups of people on the use of public transport. An error component latent class choice model was estimated using the data collected in the Netherlands. Results show that the restrictions policy lifted by the Dutch central government have significant effect on individuals' transportation mode choice decision during the pandemic. The related measures adopted by the public transport sector, by contrast, present different effects on different people. The older and highly educated people are more susceptible to enforcement measures, whereas young and single Dutch citizens are more accessible to non-compulsory measures. Moreover, compared with other private modes, public transport is generally identified as a riskier option, and the average willingness to travel descends. Findings of this study are helpful for the authorities in designing and promoting effective policies in the context of pandemics. [ABSTRACT FROM AUTHOR]

• The impact of the COVID-19 pandemic may be especially potent for individuals with PTSD. • PE is a well-established and efficacious treatment for PTSD. • Clinical practice strategies aid in implementation of PE during the COVID-19 pandemic. The unprecedented effects and duration of the COVID-19 crisis are likely to elevate the population's level of anxiety due to psychological stress, economic hardship, and social isolation. This effect may be especially potent for individuals with preexisting mental health conditions, such as posttraumatic stress disorder (PTSD). Prolonged Exposure (PE) therapy is a highly effective treatment for PTSD across trauma-exposed populations, and has been implemented effectively via telehealth. Nevertheless, PE implementation via telehealth may require specific adaptations during the COVID-19 crisis due to public health mandates calling for sheltering in place and physical distancing. This paper discusses strategies for implementing PE for PTSD during the COVID-19 pandemic, which may also be applied to other situations in which physical distancing must be considered. [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]

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]

In March of 2020, the COVID-19 pandemic upended the world and changed the way people worked, lived and coped. In addition to pandemic restrictions and social distancing measures, academic libraries suffered budget cuts, layoffs, and closures. This paper explores the effect the pandemic had on New Jersey academic librarians during the Fall 2021 semester re-openings. Respondents were asked questions pertaining to their experiences working during the Fall 2021 semester: if they had returned to campus, if they were experiencing challenges, if they were affected by austerity measures, and if their view of the profession–and their intention to stay–had changed. [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 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 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]

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]

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]

• Illinois counties with more online or hybrid K-12 pupils had fewer new COVID-19 cases. • Illinois counties with more in-person K-12 pupils had more new COVID-19 cases. • New county COVID-19 cases were similar for online and hybrid K-12 instruction types. • New county COVID-19 hospital admissions were similar for all K-12 instruction types. • New county COVID-19 deaths were similar for all K-12 instruction types. One of the most difficult public policy decisions associated with the COVID-19 pandemic has been about how to offer K-12 instruction. We sought to determine whether differences in instruction types at the beginning of the 2020-2021 school year were related to differences in COVID-19 cases, hospitalizations, and deaths in Illinois counties during the first 3 weeks of the school year. We divided Illinois counties into 3 groups based on the instruction type used for a majority of K-12 students at the start of the school year: in-person, hybrid, or online-only. We used synthetic control analysis to match counties between the 3 groups. Both majority hybrid and majority online-only counties had significantly fewer new cases than majority in-person counties. There were no significant differences in new cases between majority hybrid counties and majority online-only counties or in new hospital admissions or deaths between any of the 3 county groups. This paper adds to the growing scientific consensus that at least some forms of in-person K-12 instruction have not contributed significantly to the spread of the pandemic. However, our results suggest that there may be an important difference between fully in-person instruction and hybrid instruction. [ABSTRACT FROM AUTHOR]

Mathematical modeling of epidemic spreading has been widely adopted to estimate the threats of epidemic diseases (i.e., the COVID-19 pandemic) as well as to evaluate epidemic control interventions. The indoor place is considered to be a significant epidemic spreading risk origin, but existing widely-used epidemic spreading models are usually limited for indoor places since the dynamic physical distance changes between people are ignored, and the empirical features of the essential and non-essential travel are not differentiated. In this paper, we introduce a pedestrian-based epidemic spreading model that is capable of modeling indoor transmission risks of diseases during people's social activities. Taking advantage of the before-and-after mobility data from the University of Maryland COVID-19 Impact Analysis Platform, it's found that people tend to spend more time in grocery stores once their travel frequencies are restricted to a low level. In other words, an increase in dwell time could balance the decrease in travel frequencies and satisfy people's demands. Based on the pedestrian-based model and the empirical evidence, combined non-pharmaceutical interventions from different operational levels are evaluated. Numerical simulations show that restrictions on people's travel frequency and open hours of indoor places may not be universally effective in reducing average infection risks for each pedestrian who visit the place. Entry limitations can be a widely effective alternative, whereas the decision-maker needs to balance the decrease in risky contacts and the increase in queue length outside the place that may impede people from fulfilling their travel needs. The results show that a good coordination among the decision-makers can contribute to the improvement of the performance of combined non-pharmaceutical interventions, and it also benefits the short-term and long-term interventions in the future. [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]

During infectious outbreaks like COVID-19, it is essential that every healthcare personnel (HCP) strictly adheres to infection prevention and control (IPC) policies. To boost IPC measures, training to reinforce preventive practices, which are pertinent to needs and encompass the expectations of the HCP, is indispensable. Thus, these expectations of the HCP should be explored. In this cross-sectional descriptive survey, we used convenience sampling technique to ask the participants to list their expectations on of covid-19 IPC training paper based forms. Using the category construction approach, we organised the expectations and grouped the participants on the basis of their work and place of work to analyse the association using the chi-square test. Many participants expected to learn about the use of PPE and masks, hand hygiene, physical distancing, cleaning and disinfection, basic precautions for personal protection during the training. Expectations also included various administrative queries, sample collection and clinical skills for diagnosis and management. There was significant association of many categories of expectations with the nature and place of work in the hospital. When planning IPC training, these expectations of the HCP may be carefully addressed. Information about causative agent, transmission and clinical aspects may will give a contextual meaning to IPC training. Some important preventive measures, which few participants expected to learn must be analysed in detail to understand the attitude of the HCP towards them. Efforts to appraise the HCP for the importance of these measures and promoting its practice may play a vital role to curb the spread of infectious diseases. [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 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]

• 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]

Searching for an available parking space is a time-consuming and frustrating task for drivers, which also leads to huge amounts of fuel waste. Far from being solved, as the COVID-19 crisis slowly resolves, we can expect an increase in the use of private cars in comparison with public transportation, which will further aggravate the problem. Therefore, the use of smart parking solutions that help drivers to find an available parking space will become key to alleviate this problem. Moreover, existing solutions should be extended and adapted to incorporate the concept of social distancing, which is the only prevention measure (along with proper hygiene) which has been able to stop the virus so far. In this paper, we present an approach for the recommendation of parking spaces that considers social distance metrics to decide which parking spaces should be suggested to each driver. As far was we know, this problem has not been considered before in the literature. We illustrate the proposal with a use case scenario of a parking lot. Our experimental evaluation shows its feasibility and benefits. [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 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]