The Economic Effects of COVID-19 Containment Measures

A novel comparison framework for epidemiological strategies applied to age-based restrictions versus horizontal lockdowns

During an epidemic, such as the COVID-19 pandemic, policy-makers are faced with the decision of implementing effective, yet socioeconomically costly intervention strategies, such as school and workplace closure, physical distancing, etc. In this study, we propose a rigorous definition of epidemiological strategies. In addition, we develop a scheme for comparing certain epidemiological strategies, with the goal of providing policy-makers with a tool for their systematic comparison. Then, we put the suggested scheme to the test by employing an age-based epidemiological compartment model introduced in Bitsouni et al. (2024), coupled with data from the literature, in order to compare the effectiveness of age-based and horizontal interventions. In general, our findings suggest that these two are comparable, mainly at a low or medium level of intensity.

The optimal spatially-dependent control measures to effectively and economically eliminate emerging infectious diseases

Non-pharmaceutical interventions (NPIs) are effective in mitigating infections during the early stages of an infectious disease outbreak. However, these measures incur significant economic and livelihood costs. To address this, we developed an optimal control framework aimed at identifying strategies that minimize such costs while ensuring full control of a cross-regional outbreak of emerging infectious diseases. Our approach uses a spatial SEIR model with interventions for the epidemic process, and incorporates population flow in a gravity model dependent on gross domestic product (GDP) and geographical distance. We applied this framework to identify an optimal control strategy for the COVID-19 outbreak caused by the Delta variant in Xi'an City, Shaanxi, China, between December 2021 and January 2022. The model was parameterized by fitting it to daily case data from each district of Xi'an City. Our findings indicate that an increase in the basic reproduction number, the latent period or the infectious period leads to a prolonged outbreak and a larger final size. This indicates that diseases with greater transmissibility are more challenging and costly to control, and so it is important for governments to quickly identify cases and implement control strategies. Indeed, the optimal control strategy we identified suggests that more costly control measures should be implemented as soon as they are deemed necessary. Our results demonstrate that optimal control regimes exhibit spatial, economic, and population heterogeneity. More populated and economically developed regions require a robust regular surveillance mechanism to ensure timely detection and control of imported infections. Regions with higher GDP tend to experience larger-scale epidemics and, consequently, require higher control costs. Notably, our proposed optimal strategy significantly reduced costs compared to the actual expenditures for the Xi'an outbreak.

Learning outcomes for participants in citizen science mosquito surveillance

Although citizen science initiatives have been increasing globally, there is still a gap in understanding how they can result in sustainable benefits for citizen scientists. This article addresses dual goals of (i) collecting relevant data on potential vector mosquitoes and (ii) delivering learning outcomes among participants in a citizen science mosquito surveillance program. Mozzie Monitors uses an e-entomology approach to collect and identify mosquitoes of medical importance. This study used quantitative, qualitative, and mixed method approaches, comprised of before and after longitudinal surveys, in-depth interviews and descriptive assessment of mosquito attributes to assess participants' educational gains and data collection scalability. Results showed that mosquito abundance and diversity differed in each study location, with Aedes notoscriptus (Skuse) being the most common mosquito reported in all areas. Citizen scientists were predominantly women over 50 and highly educated. The before-and-after analysis showed that participants learned how to identify the most common mosquito species after participating in the program. They also improved their technical skills in mosquito photography, increasing the rates of identifiable photos. Finally, participating in this citizen science program resulted in behavior changes, with participants starting to look for mosquito eggs and larvae in their backyards to manage mosquito populations. The mixed methods used in this research showed increased participants' confidence, self-efficacy, and engagement throughout the trial. Overall, this study demonstrated the potential of Mozzie Monitors to contribute to the dual goals of mosquito data contribution and citizen scientists' educational outcomes for improved public health.

Relationship between Exhaled Aerosol and Carbon Dioxide Emission Across Respiratory Activities

Respiratory particles produced during vocalized and nonvocalized activities such as breathing, speaking, and singing serve as a major route for respiratory pathogen transmission. This work reports concomitant measurements of exhaled carbon dioxide volume (VCO2) and minute ventilation (VE), along with exhaled respiratory particles during breathing, exercising, speaking, and singing. Exhaled CO2 and VE measured across healthy adult participants follow a similar trend to particle number concentration during the nonvocalized exercise activities (breathing at rest, vigorous exercise, and very vigorous exercise). Exhaled CO2 is strongly correlated with mean particle number (r = 0.81) and mass (r = 0.84) emission rates for the nonvocalized exercise activities. However, exhaled CO2 is poorly correlated with mean particle number (r = 0.34) and mass (r = 0.12) emission rates during activities requiring vocalization. These results demonstrate that in most real-world environments vocalization loudness is the main factor controlling respiratory particle emission and exhaled CO2 is a poor surrogate measure for estimating particle emission during vocalization. Although measurements of indoor CO2 concentrations provide valuable information about room ventilation, such measurements are poor indicators of respiratory particle concentrations and may significantly underestimate respiratory particle concentrations and disease transmission risk.

COVID-19 post-pandemic reflections from sub-Saharan Africa: what we know now that we wish we knew then

The commonly heard aphorism about history repeating itself suggests an endless cycle of recurring events. However, George Santayana offered a similar sentiment when he said, "Those who do not learn from history are doomed to repeat it". This emphasises that the responsibility for the recurrence of events lies not with history itself, but with humanity. It underscores that if we desire change, it is our responsibility to initiate it, rather than attributing it to external forces such as fate, luck, or time. With this thought in mind, here we offer a narrative view from sub-Saharan Africa, focusing primarily on our own experiences in Nigeria and Uganda, on what harsh lessons can be learnt from the COVID-19 pandemic regarding emergency preparedness to respond effectively to the next major infectious disease outbreak. Four strategies are suggested, the implementation of which may contribute substantially to safeguarding against an experience similar to the catastrophic public health, social and economic costs borne by African nations during COVID-19 and in its immediate aftermath.

The economic impact of international travel measures used during the COVID-19 pandemic: a scoping review

INTRODUCTION

Assessment of the use of travel measures during COVID-19 has focused on their effectiveness in achieving public health objectives. However, the prolonged use of highly varied and frequently changing measures by governments, and their unintended consequences caused, has been controversial. This has led to a call for coordinated decision-making focused on risk-based approaches, which requires better understanding of the broader impacts of international travel measures (ITMs) on individuals and societies.

METHODS

Our scoping review investigates the literature on the economic impact of COVID-19 ITMs. We searched health, social science and COVID-19-specific databases for empirical studies preprinted or published between 1 January 2020 and 31 October 2023. Evidence was charted using a narrative approach and included jurisdiction of study, ITMs studied, study design, outcome categories, and main findings.

RESULTS

Twenty-six studies met the inclusion criteria and were included for data extraction. Twelve of them focused on the international travel restrictions implemented in early 2020. Limited attention was given to measures such as entry/exit screening and vaccination requirements. Eight studies focused on high-income countries, 6 on low-income and middle-income countries and 10 studies were comparative although did not select countries by income. Economic outcomes assessed included financial markets (n=13), economic growth (n=4), economic activities (n=1), performance of industries central to international travel (n=9), household-level economic status (n=3) and consumer behaviour (n=1). Empirical methods employed included linear regression (n=17), mathematical modelling (n=3) and mixed strategies (n=6).

CONCLUSION

Existing studies have begun to provide evidence of the wide-ranging economic impacts resulting from ITMs. However, the small body of research combined with difficulties in isolating the effects of such measures and limitations in available data mean that it is challenging to draw general and robust conclusions. Future research using rigorous empirical methods and high-quality data is needed on this topic.

Economic evaluation of vaccination against COVID-19: A systematic review

Background and Aims

Coronavirus has burdened considerable expenditures on the different health systems. Vaccination programs, the critical solution against pandemic diseases, are known as safe and effective interventions to prevent and control epidemics. We aimed to perform a systematic review to provide economic evidence of the value of different types of vaccines available to combat the Covid-19 to all health policymakers worldwide.

Methods

Electronic searches conducted on Medline/PubMed, Cochrane Library, Web of Science, Scopus, Embase, and other economic evaluation databases. Related and published articles searched up to March 2022 by using keywords such as "Vaccination," "Covid-19," "Cost-benefit," "Cost-utility," "Cost-effectiveness," "Economic Assessment," and "Economic evaluation." Followed by choosing the most suitable articles according to inclusion and exclusion criteria, data captured and the results extracted. The quality assessment of the articles performed by the checklist of CHEERS 2022. Finally, 13 articles included in the review.

Results

All messenger RNA vaccines were dominant with approximately 70% coverage against no vaccination in the primary vaccination program except in one study that looked at booster effects. From a payer's perspective, a dollar invested in a vaccine would be less profitable than from a societal perspective. Therefore, primary mass vaccination can be considered a cost-effective intervention in primary vaccination to save more lives and produce more positive externalities. However, the cost-benefit ratio for all vaccines increases when statistical lifetime value and global economic and educational disadvantages are considered.

Conclusion

The COVID-19 primary vaccination programs in regional outbreaks, from a long-term perspective, will demonstrate substantial cost-effectiveness. It is suggested that due to the positive externalities of vaccination, primary mass vaccination, with the help of COVAX-19TM, could be considered a reliable way to combat viral epidemics compared to the loss of individual lives and economic and educational disturbances around the world.

Intention to leave among nurses during the COVID-19 outbreak: A rapid systematic review and Meta-Analysis

AIMS AND OBJECTIVES

The COVID-19 pandemic has caused an increase in the workload of nurses and changes in working conditions. Stress and the increase in workload during the COVID-19 pandemic had a negative effect on nurses' intention to leave. This study aimed to determine the current rate of intention to leave the job among nurses during the COVID-19 outbreak by conducting a rapid systematic review and meta-analysis.

METHODOLOGY/METHODS

The review procedure was conducted by the PRISMA criteria. The researchers searched PubMed and Web of Science databases for studies providing the rate of nurses' intent to leave, published until 31 December 2021. Heterogeneity was assessed using the I2 test, and publication bias was measured by Egger's test.

RESULTS

The estimated overall intent to leave the profession among nurses during the COVID-19 pandemic was 31.7% (95% CI: 25%-39%) with significant heterogeneity (Q test: 188.9; p = 0.0001; I2 : %95.2; Tau2 : 0.225). Additionally, Egger's regression test suggested no publication bias for estimating the pooled rate of nurses' intent to leave during the COVID-19 outbreak.

NO PATIENT OR PUBLIC CONTRIBUTION

Since the research is a meta-analysis study, a literature review model was used. Ethics committee approval was not obtained because the literature review did not directly affect humans and animals.

CONCLUSION

This study showed that approximately one-third of nurses working during the COVID-19 pandemic had thoughts about intending to leave their job. The findings indicate the need for strategies involving precautions and solutions to minimise the psychological impacts of COVID-19 among nurses.

RELEVANCE TO CLINICAL PRACTICE

In this period when the global nurse crisis exists, it is of great importance for institutions to retain their nurse workforce. There is an urgent need to prepare nurses to cope better with COVID-19 pandemic. Identification of risk factors for intention to leave could be a significant weapon giving nurses and healthcare systems the ability to response in a better way against the following COVID-19 waves in the near future.

Mental health effects of social distancing in Switzerland

This analysis examines the effect of COVID-19 on public mental health in Switzerland. Following an event-study framework, we compare helpline call volume and duration before and after the outbreak of the first and second wave. The use of administrative phone-level data allows us to i) decompose the total effects into an intensive and extensive margin and ii) calculate a measure of unmet need. For the first wave, our results show that callers with a history of helpline contacts increase calls substantially. We also identify capacity constraints leading to unmet need for psychological counseling. Finally, we find no effects in the second wave, which might be explained by a number of factors including the absence of a lockdown and less restrictive social distancing measures.

Global prevalence of COVID-19-induced acute respiratory distress syndrome: systematic review and meta-analysis

BACKGROUND

Acute respiratory distress syndrome (ARDS) is potentially a fatal form of respiratory failure among COVID-19 patients. Globally, there are inconsistent findings regarding ARDS among COVID-19 patients. Therefore, this study aimed to estimate the pooled prevalence of COVID-19-induced ARDS among COVID-19 patients worldwide.

METHODS

To retrieve relevant studies, the authors searched Embase, MEDLINE, PubMed, Web of Science, Cochrane Library, Google, and Google Scholar using a combination of search terms. The search was conducted for articles published from December 2019 to September 2022. Articles were searched and screened by title (ti), abstract (ab), and full-text (ft) by two reviewers independently. The quality of each included article was assessed using the Newcastle-Ottawa Assessment Scale. Data were entered into Microsoft Word and exported to Stata version 14 for analysis. Heterogeneity was detected using the Cochrane Q statistics and I-square (I2). Then the sources of variations were identified by subgroup and meta-regression analysis. A random effect meta-analysis model was used. The publication bias was detected using the graphic asymmetry test of the funnel plot and/or Egger's test (p value < 0.05). To treat the potential publication bias, trim and fill analysis were computed. The protocol has been registered in an international database, the Prospective Register of Systematic Reviews (PROSPERO) with reference number: CRD42023438277.

RESULTS

A total of 794 studies worldwide were screened for their eligibility. Of these 11 studies with 2845 participants were included in this systematic review and meta-analysis. The overall pooled prevalence of COVID-19-induced ARDS in the world was found to be 32.2% (95%CI = 27.70-41.73%), I2 = 97.3%, and p value < 0.001).

CONCLUSION

The pooled prevalence of COVID-19-induced ARDS was found to be high. The virus remains a global burden because its genetic causes are constantly changing or it mutated throughout the pandemic to emerge a new strain of infection. Therefore, interventions such as massive vaccination, early case detection, screening, isolation, and treatment of the cases need to be implemented to tackle its severity.

Behavioral Changes Associated With COVID-19 Vaccination: Cross-National Online Survey

BACKGROUND

During the initial phases of the vaccination campaign worldwide, nonpharmaceutical interventions (NPIs) remained pivotal in the fight against the COVID-19 pandemic. In this context, it is important to understand how the arrival of vaccines affected the adoption of NPIs. Indeed, some individuals might have seen the start of mass vaccination campaigns as the end of the emergency and, as a result, relaxed their COVID-safe behaviors, facilitating the spread of the virus in a delicate epidemic phase such as the initial rollout.

OBJECTIVE

The aim of this study was to collect information about the possible relaxation of protective behaviors following key events of the vaccination campaign in four countries and to analyze possible associations of these behavioral tendencies with the sociodemographic characteristics of participants.

METHODS

We developed an online survey named "COVID-19 Prevention and Behavior Survey" that was conducted between November 26 and December 22, 2021. Participants were recruited using targeted ads on Facebook in four different countries: Brazil, Italy, South Africa, and the United Kingdom. We measured the onset of relaxation of protective measures in response to key events of the vaccination campaign, namely personal vaccination and vaccination of the most vulnerable population. Through calculation of odds ratios (ORs) and regression analysis, we assessed the strength of association between compliance with NPIs and sociodemographic characteristics of participants.

RESULTS

We received 2263 questionnaires from the four countries. Participants reported the most significant changes in social activities such as going to a restaurant or the cinema and visiting relatives and friends. This is in good agreement with validated psychological models of health-related behavioral change such as the Health Belief Model, according to which activities with higher costs and perceived barriers (eg, social activities) are more prone to early relaxation. Multivariate analysis using a generalized linear model showed that the two main determinants of the drop of social NPIs were (1) having previously tested positive for COVID-19 (after the second vaccine dose: OR 2.46, 95% CI 1.73-3.49) and (2) living with people at risk (after the second vaccine dose: OR 1.57, 95% CI 1.22-2.03).

CONCLUSIONS

This work shows that particular caution has to be taken during vaccination campaigns. Indeed, people might relax their safe behaviors regardless of the dynamics of the epidemic. For this reason, it is crucial to maintain high compliance with NPIs to avoid hindering the beneficial effects of the vaccine.

Impact of the COVID-19 pandemic on the conduct of non-COVID-19 clinical trials: protocol for a scoping review

INTRODUCTION

The COVID-19 pandemic posed a detrimental impact on the conduct of non-COVID-19 related clinical trials, raising concerns about the completeness of these studies and waste of resources. While several measures and strategies have been suggested to address these issues, a thorough and timely summarisation is still lacking. Therefore, our aim is to conduct a scoping review to summarise the negative effects of COVID-19 on non-COVID-19 clinical trials, outline the effective measures for mitigating these impacts, and provide insights for future pandemics.

METHODS AND ANALYSIS

This scoping review will be conducted in line with the Joanna Briggs Institute's scoping review methodological framework, and the results will be reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. Relevant articles will be searched in PubMed, Embase and the Cochrane Library from 1 December 2019 to 1 July 2023. We will also screen the reference lists of the included studies manually to identify more potentially relevant articles. Articles focusing on the adverse impacts of COVID-19 on non-COVID-19 clinical trials and effective measures for mitigating them will be included. Two investigators will perform study selection and data extraction independently. A narrative summary as well as a descriptive analysis of the basic characteristics and key results of the included studies will be performed.

ETHICS AND DISSEMINATION

Ethical approval is not required, as this scoping review will be completed based only on published literature. The findings of this scoping review will be disseminated through a peer-reviewed publication and/or conference presentations.

Effect of COVID-19 on immunization coverage of children aged 0-11 months in the center region of Cameroon

The occurrence of epidemics is known to contribute in reducing the capacity of health facilities to deliver care and the predisposition of populations to seek care through several mechanisms. The objective was to assess the effect of the COVID-19 on vaccination coverage of the expanded program of immunization (EPI) vaccines in children aged 0-11 months. The study involved a descriptive and case control designs exhaustively targeting health facilities in health areas from selected health districts. The descriptive part explored the distribution of immunization coverage 12 months before and during COVID-19. Data were extracted from monthly EPI reports of health areas. Cases were months with immunization coverages of Bacille Calmette-Guerin (BCG), Measles Mumps-Rubella 1 (MMR1) or Diphtheria-Pertussis-Tetanus Hepatitis B + Hemophilus influenzae type b dose 3 (DPT-Hi+Hb3) less than 80%. The exposure were months belonging to the pandemic period. Of the 78 targeted health areas, 74 (94.87%) were reached. The monthly immunization coverage of BCG, RR1, DPT-Hi+Hb 1 and 3 decreased during the pandemic period by minimum 30%. Being a health-area month belonging to the COVID-19 pandemic period was found to be significantly associated to lower BCG [OR=2.00 (1.61; 2.50); P#x003C;0.001], MMR1 [OR=2.45 (1.76; 3.41); P#x003C;0.001] and DPT-Hi+Hb3 [OR=2.11 (1.68; 2.640); P#x003C;0.001] immunisation coverage. COVID-19 had a significant effect on the decrease of immunization coverages of antigens offered in the EPI program. This raises the need to develop interventions during health emergencies to prevent disruption of health services access.

The relationship between salivary Fibroblast Growth Factor-2 and cortisol reactivity and psychological outcomes prior to and during the COVID-19 pandemic

Background

Fibroblast growth factor-2 (FGF2) is a biomarker that is associated with depression, anxiety and stress in rodents. In humans, we have previously demonstrated that salivary FGF2 increased following stress in a similar pattern to cortisol, and FGF2 (but not cortisol) reactivity predicted repetitive negative thinking, a transdiagnostic risk factor for mental illness. The current study assessed the relationship between FGF2, cortisol, and mental health before and during the COVID-19 pandemic.

Methods

We employed a longitudinal correlational design using a convenience sample. We assessed whether FGF2 and cortisol reactivity following the Trier Social Stress Task (TSST) were associated with DASS-21 depression, anxiety and stress, measured at the time of the TSST in 2019-20 (n = 87; time 1), and then again in May 2020 during the first wave of COVID-19 in Sydney (n = 34 of the original sample; time 2).

Results

FGF2 reactivity (but not absolute FGF2 levels) at time 1 predicted depression, anxiety, and stress across timepoints. Cortisol reactivity at time 1 was associated with stress over timepoints, and absolute cortisol levels were associated with depression across timepoints.

Limitations

The sample was comprised of mostly healthy participants from a student population, and there was high attrition between timepoints. The outcomes need to be replicated in larger, more diverse, samples.

Conclusions

FGF2 and cortisol may be uniquely predictive of mental health outcomes in healthy samples, potentially allowing for early identification of at-risk individuals.

COVID-19 transmission dynamics and the impact of vaccination: modelling, analysis and simulations

Despite the lifting of COVID-19 restrictions, the COVID-19 pandemic and its effects remain a global challenge including the sub-Saharan Africa (SSA) region. Knowledge of the COVID-19 dynamics and its potential trends amidst variations in COVID-19 vaccine coverage is therefore crucial for policy makers in the SSA region where vaccine uptake is generally lower than in high-income countries. Using a compartmental epidemiological model, this study aims to forecast the potential COVID-19 trends and determine how long a wave could be, taking into consideration the current vaccination rates. The model is calibrated using South African reported data for the first four waves of COVID-19, and the data for the fifth wave are used to test the validity of the model forecast. The model is qualitatively analysed by determining equilibria and their stability, calculating the basic reproduction number R 0 and investigating the local and global sensitivity analysis with respect to R 0 . The impact of vaccination and control interventions are investigated via a series of numerical simulations. Based on the fitted data and simulations, we observed that massive vaccination would only be beneficial (deaths averting) if a highly effective vaccine is used, particularly in combination with non-pharmaceutical interventions. Furthermore, our forecasts demonstrate that increased vaccination coverage in SSA increases population immunity leading to low daily infection numbers in potential future waves. Our findings could be helpful in guiding policy makers and governments in designing vaccination strategies and the implementation of other COVID-19 mitigation strategies.

The spatial linkage mechanism: medical level, public health security, and economic climate from 19 OECD EU countries

Introduction

The global spread of the COVID-19 has brought about global changes, especially in terms of economic growth. Therefore, it has become a global issue to explore the impact of public health security on the economy.

Methods

Employing a dynamic spatial Durbin model, this study analyzes the spatial linkage mechanism of medical level, public health security, and economic climate in 19 countries as well as investigates the relationship between economic climate and COVID-19 by the panel data of 19 OECD European Union countries from March 2020 to September 2022.

Results

Results show that an improvement in the medical level can reduce the negative impact of public health security on the economy. Specifically, there is a significant spatial spillover effect. The degree of economic prosperity hurts the reproduction rate of COVID-19.

Discussion

Policymakers should consider both the severity of the public health security issues and the economic level when developing prevention and control policies. Given this, corresponding suggestions provide theoretical support for formulating policies to reduce the economic impact of public health security issues.

Modeling the effects of Prophylactic behaviors on the spread of SARS-CoV-2 in West Africa

Various general and individual measures have been implemented to limit the spread of SARS-CoV-2 since its emergence in China. Several phenomenological and mechanistic models have been developed to inform and guide health policy. Many of these models ignore opinions about certain control measures, although various opinions and attitudes can influence individual actions. To account for the effects of prophylactic opinions on disease dynamics and to avoid identifiability problems, we expand the SIR-Opinion model of Tyson et al. (2020) to take into account the partial detection of infected individuals in order to provide robust modeling of COVID-19 as well as degrees of adherence to prophylactic treatments, taking into account a hybrid modeling technique using Richard's model and the logistic model. Applying the approach to COVID-19 data from West Africa demonstrates that the more people with a strong prophylactic opinion, the smaller the final COVID-19 pandemic size. The influence of individuals on each other and from the media significantly influences the susceptible population and, thus, the dynamics of the disease. Thus, when considering the opinion of susceptible individuals to the disease, the view of the population at baseline influences its dynamics. The results are expected to inform public policy in the context of emerging and re-emerging infectious diseases.

The impact of the COVID-19 pandemic on global GDP growth

This paper describes one of the first attempts to gauge the effect of the COVID-19 pandemic on the global trajectory of real GDP over the course of 2020 and 2021. It is also among the first efforts to distinguish between the role of domestic variables and global trade in transmitting the economic effects of COVID-19. We estimate panel data regressions of the quarterly growth in real GDP on pandemic variables for 90 countries over the period 2020 Q1 through 2021 Q4. We find that readings on the number of COVID-19 deaths had a very small effect in our aggregate sample. On the other hand, changes in the stringency of the lockdown measures taken by governments to restrict the spread of the virus were an important influence on GDP. The economic effects of the pandemic differed between rich and poor countries: COVID-19 deaths exerted a somewhat greater drag on GDP in advanced economies, although this difference was not statistically significant, whereas lockdown restrictions were more injurious to economic activity in emerging and developing economies. In addition to these domestic pandemic effects, global trade represented a significant channel through which the economic effects of the pandemic spilled across national borders. This finding underscores how globalization makes each country vulnerable not only to medical contagion from the COVID-19 pandemic, but to economic contagion as well.

COVID-19, lockdowns and international trade: evidence from firm-level data

The COVID-19 pandemics and the lockdowns imposed to mitigate the rise of infections beyond manageable levels strongly affected international trade. Although the health crisis and the mobility restrictions associated with lockdowns are closely related, their impacts on international trade have a different nature. This paper uses monthly firm-level trade data for Portuguese firms to measure the impact of partner countries' lockdowns on nominal export and import flows during 2020 and the first half of 2021, while also assessing the impact of the health crisis. The high time frequency and granularity of the data contribute to the identification of the impact of these obstacles on trade. We conclude that the detrimental impact of lockdowns is sizeable and broadly similar in exports and imports, and the impact of the health conditions is slightly stronger in exports. There is evidence that the detrimental impact of lockdowns was stronger for larger firms, for those with higher geographical concentration of trade, more integrated in global value chains and in the upper quartiles of the trade unit value distribution. The negative impact is also estimated to be larger for industries with high import content and for trade partners that are more important as sources of value added to be embodied in Portuguese exports. Results also suggest that exports adapted to the prevailing circumstances as of June 2020, but such an effect is not clear in imports.

Stock market response to Covid-19, containment measures and stabilization policies—The case of Europe

Policymakers imposed constraints on public life to contain the Covid-19 pandemic. At the same time, fiscal, monetary and macroprudential policies implemented a large range of expansionary measures to limit the economic consequences of the pandemic and stimulate recovery. In this paper, we assess the response of the equity market as a high-frequency indicator of economic activity to containment and stabilization policies for 29 European economies. We construct indicators of containment and stabilization policies and estimate a range of panel VAR models. The main results are threefold. First, we find that stock markets are highly responsive to containment and stabilization policies. We show that domestic fiscal policy, macroprudential policy as well as monetary policy support the recovery as reflected in the stock market. Second, expansionary fiscal policy conducted at the European level reduces rather raises stock prices. Third, we estimate the model over subsamples and show that the counter-intuitive stock market response to EU policies is driven by the responses in medium- and high-debt countries. These countries’ stock markets are also particularly susceptible to monetary policy announcements.

Unintended consequences of COVID-19 public policy responses on renewable energy power: evidence from OECD countries in the EU

Since 2020, governments around the world have implemented many types of public policies in response to the outbreak of COVID-19. These dramatic public policies have substantially changed production and consumption activities, thereby temporarily lowering electricity use and greenhouse gas emissions. This study argues that pandemic-induced public policies have unintentionally slowed the transition to renewable energy use in the EU since the decline in greenhouse gas emissions due to the lockdowns helped countries temporarily reduce their total emissions. We employ a fixed-effect model to investigate the effects of different types of COVID-19 public policy responses on electricity production, consumption, and net imports in 12 OECD countries in the EU, and we mainly focus on the share of electricity production from renewable energy sources. Among several public policy responses, stringent lockdown policies, such as workplace closures, stay-at-home requirements, and restrictions on gathering size, have negative and statistically significant impacts on electricity generation and consumption. Furthermore, countries with stringent lockdown policies are more likely to import electricity from other countries to mitigate the electricity shortages in their domestic markets. Importantly, we find that lockdown events have negative and statistically significant effects on the share of renewables in electricity production while increasing the share of fossil fuels in electricity production. In contrast, economic support policies such as income support, debt relief, and economic stimulus programs help reduce the share of fossil fuels in electricity production and decrease the net import of electricity from other countries. Our results indicate that the public policies implemented in response to the outbreak of COVID-19 have mixed effects on the transition to renewable energy sources in the EU, suggesting that the current decline in greenhouse gas emissions comes from the reduction in electricity use due to lockdown events instead of the adoption of renewable energy use and discouraging the transition to renewable energy sources.

Fitting and validation of an agent-based model for COVID-19 case forecasting in workplaces and universities

COVID-19 forecasting models have been critical in guiding decision-making on surveillance testing, social distancing, and vaccination requirements. Beyond influencing public health policies, an accurate COVID-19 forecasting model can impact community spread by enabling employers and university leaders to adapt worksite policies and practices to contain or mitigate outbreaks. While many such models have been developed for COVID-19 forecasting at the national, state, county, or city level, only a few models have been developed for workplaces and universities. Furthermore, COVID-19 forecasting models have rarely been validated against real COVID-19 case data. Here we present the systematic parameter fitting and validation of an agent-based compartment model for the forecasting of daily COVID-19 cases in single-site workplaces and universities with real-world data. Our approaches include manual fitting, where initial model parameters are chosen based on historical data, and automated fitting, where parameters are chosen based on candidate case trajectory simulations that result in best fit to prevalence estimation data. We use a 14-day fitting window and validate our approaches on 7- and 14-day testing windows with real COVID-19 case data from one employer. Our manual and automated fitting approaches accurately predicted COVID-19 case trends and outperformed the baseline model (no parameter fitting) across multiple scenarios, including a rising case trajectory (RMSLE values: 2.627 for baseline, 0.562 for manual fitting, 0.399 for automated fitting) and a decreasing case trajectory (RMSLE values: 1.155 for baseline, 0.537 for manual fitting, 0.778 for automated fitting). Our COVID-19 case forecasting model allows decision-makers at workplaces and universities to proactively respond to case trend forecasts, mitigate outbreaks, and promote safety.

The unexpected consequences of the COVID-19 pandemic on maritime crime: Evidence from Indonesia and Nigeria

The economic fallout from the COVID-19 pandemic has been devastating. Job losses, negative growth rates, and increased poverty have all followed rising infection rates. The economic costs have been especially challenging for many piracy-prone countries. The international monetary fund anticipates sizable unemployment increases in many Indo-Pacific countries. Deeper and more durable economic damage may materialize in some West African countries. Often, negative economic shocks produce surges in crime, both on land and at sea. The present study evaluates the effects of COVID-19 on maritime pirate attacks in two countries, Nigeria, located in the Gulf of Guinea, and Indonesia, located in the Indo-Pacific. We employ monthly and quarterly data on government measures to prevent infection, sea-piracy incidents, and economic conditions to explore whether the subsequent economic fallout produced more maritime crime. We do not find clear evidence of this relationship in Indonesia. However, COVID-19-induced stringency measure does appear to have increased sea-piracy incidents in Nigeria.

Understanding Covid-19 Mobility Through Human Capital: A Unified Causal Framework

This paper seeks to identify the causal impact of educational human capital on social distancing behavior at workplace in Turkey using district-level data for the period of April 2020 - February 2021. We adopt a unified causal framework, predicated on domain knowledge, theory-justified constraints anda data-driven causal structure discovery using causal graphs. We answer our causal query by employing machine learning prediction algorithms; instrumental variables in the presence of latent confounding and Heckman's model in the presence of selection bias. Results show that educated regions are able to distance-work and educational human capital is a key factor in reducing workplace mobility, possibly through its impact on employment. This pattern leads to higher workplace mobility for less educated regions and translates into higher Covid-19 infection rates. The future of the pandemic lies in less educated segments of developing countries and calls for public health action to decrease its unequal and pervasive impact.

Mental Health System Responsiveness during COVID-19 in People with Pre-Existing Psychiatric Disorders: Experiences from Iran

Mental health system responsiveness (MHSR) is one of the important indicators in measuring the performance of mental health systems. Recognizing this function can be effective in responding appropriately to the needs of People with Pre-Existing Psychiatric Disorders (PPEPD). This study aimed to investigate MHSR during the COVID-19 period in PPEPD in Iran. Using stratified random sampling, 142 PPEPD who were admitted to a Psychiatric Hospital in Iran one year before the onset of the COVID-19 pandemic were recruited for this cross-sectional study. Participants completed a demographic and clinical characteristics questionnaire as well as a Mental Health System Responsiveness Questionnaire through telephone interviews. The results show that the indicators of prompt attention, autonomy, and access to care were reported as the worst-performing and the confidentiality indicator as the best-performing. The type of insurance affected the access to care and the quality of basic amenities. MHSR has been reported to be poor in Iran in general and this problem worsened during the COVID-19 pandemic. Considering the prevalence of psychiatric disorders in Iran and the degree of disability of these disorders, structural and functional changes are needed for adequate MHSR.

Infectious diseases, dividend policy, and independent directors: Evidence from textual analysis

We investigated the effect of uncertainty associated with infectious diseases on corporate dividend policy. We used a unique text-based measure of infectious diseases that includes not only the Covid-19, but also other important diseases, such as SARs, MERs, and Ebola. Based on a sample of 287,151 firm-year observations across four decades (from 1985 to 2021), our results show that a higher level of uncertainty associated with infectious diseases significantly reduce dividends. Interestingly, we also found that having more independent directors on the board mitigates the negative effect of uncertainty associated with infectious diseases on dividends which implies that the reduction in dividends was partly driven by agency conflicts. We performed several robustness checks which confirm that our findings are unlikely to be affected by endogeneity issues.

To open or not to open: the moderating effects of human mobility on the relationship between vaccination and COVID-19 transmission

COVID-19 vaccination is being used to control SARS-CoV-2 transmission globally, and many countries have relaxed some non-pharmaceutical interventions. It is unclear whether relaxing human mobility restrictions is proper and increases transmission risk. To fill this knowledge gap, we aim to examine if human mobility impairs the role of vaccination on COVID-19 transmission. We apply dynamic panel data models with three lag levels (i.e. 0 day, 7 days, and 14 days) to investigate the relationship between vaccination and COVID-19 transmission and the moderating effects of different kinds of human mobility. Our results show a negative relationship between the percentage of the vaccinated population and daily new COVID-19 cases after controlling for human mobility. We also observe that when people are only vaccinated with one dose, increased human mobility in retail and recreation, grocery and pharmacy, parks, transit stations, and workplaces could impair the role of vaccination on COVID-19 transmission, although their moderating effects appear at different lag levels. However, there are no moderating effects of human mobility in transit stations and workplaces at all lag levels when people are fully vaccinated. This finding does not mean that governments may relax restrictions in these two areas since mobility in transit stations and workplaces could affect COVID-19 transmission by themselves directly. Therefore, we recommend that governments still insist on implementing human mobility control measures from the perspective of transmission risk.

Workplace impact on employees: A Lifelines Corona Research Initiative on the return to work

A large proportion of the global workforce migrated home during the COVID-19 pandemic and subsequent lockdowns. It remains unclear what the exact differences between home workers and non-home workers were, especially during the pandemic when a return to work was imminent. How were building, workplace, and related facilities associated with workers' perceptions and health? What are the lessons to be learned? Lifelines Corona Research Initiative was used to compare employees' workplaces and related concerns, facilities, work quality, and health in a complete case analysis (N = 12,776) when return to work was imminent. Mann-Whitney U, logistic regression, and Wilcoxon matched-pairs were used for analyses. Notwithstanding small differences, the results show that home workers had less favourable scores for concerns about and facilities of on-site buildings and workplaces upon return to work, but better scores for work quality and health than non-home workers. However, additional analyses also suggest that building, workplace, and related facilities may have had the capacity to positively influence employees' affective responses and work quality, but not always their health.

District-level analysis of socio-demographic factors and COVID-19 infections in Greater Accra and Ashanti regions, Ghana

Since December 2019 when COVID-19 was detected, it took the world by surprise in terms of spread and morbidity/mortality. The high rate of spread and casualties recorded from COVID-19 called for research in all directions to find ways to contain and reverse the incidences. It is against this background that this paper sought to measure the association of the socio-demographic factors in the hard-hit districts in Greater Accra and Ashanti to analyze its relationship with the novel COVID-19 virus. Data on COVID-19 cases from 35 Districts in both Greater Accra and Ashanti Regions were collected from the Ghana Health Service and population data from Ghana Statistical Service. Descriptive statistics and regression analysis were generated using R. We found that some socio-demographic variables have an association with COVID-19 infections. For example, age and religion especially Christianity and Islam pose risk to COVID-19. The population aged 15-64 was particularly at high risk of infections due to the high level of movement of this age group. We, therefore, recommend that places of congregation such as Churches and Mosques be targeted for vigorous sensitization on COVID-19 protocols and prevention. Also, districts with a high population between the ages of 15-64 should step sensitization efforts to educate their inhabitants on the need to reduce travel and related activities to curb the spread of the virus.

Impact of economic policy uncertainty, energy intensity, technological innovation and R&D on CO2 emissions: evidence from a panel of 18 developed economies

This study examines the impact of economic policy uncertainty (EPU) and ecological innovation on carbon (CO₂) emissions in a panel of 18 developed countries from 2005 to 2018 using second-generation time-series panel data techniques. We use three robust long-run estimators, namely two-stage least squares (2SLS), panel generalised method of moments (GMM) and generalised least squares (GLS), to resolve heterogeneity, endogeneity and simultaneity in the panels. We further performed causality tests to ascertain the direction of causality between the variables. Our estimations suggest three innovative findings. First, economic growth contributes significantly and positively to CO₂ emissions; however, this happens at an optimal level of growth after which carbon emission reduces, indicating that our sample exhibits an inverted U-shaped environmental Kuznets curve (EKC) relationship. Second, the impact of EPU on CO₂ emissions is diverse: high levels of EPU have a significant influence on CO₂ emissions only in high-polluting countries but not in low-polluting ones. Thirdly, research and development (R&D), foreign direct investment (FDI), urbanisation and renewable energy (RE) usage were also found to have varying effects on CO₂ emissions. These findings highlight the heterogeneous relationship between carbon emissions and economic indicators even in advanced economies, as the pollution haven hypothesis (PHH) holds true in high-pollution countries while the pollution halo effect holds for low-pollution ones. A key policy implication of this work is that the quest to mitigate emissions should not be a one-size-fits-all approach because not every country's urbanisation rate, FDI inflows, R&D and renewable energy consumption directly affect CO₂ emissions in the face of economic policy uncertainties.

Data needs for integrated economic-epidemiological models of pandemic mitigation policies

The COVID-19 pandemic and the mitigation policies implemented in response to it have resulted in economic losses worldwide. Attempts to understand the relationship between economics and epidemiology has led to a new generation of integrated mathematical models. The data needs for these models transcend those of the individual fields, especially where human interaction patterns are closely linked with economic activity. In this article, we reflect upon modelling efforts to date, discussing the data needs that they have identified, both for understanding the consequences of the pandemic and policy responses to it through analysis of historic data and for the further development of this new and exciting interdisciplinary field.

Cost-Benefit Analysis of Interventions to Mitigate the Monkeypox Virus

When a viral outbreak occurs, governments are obligated to protect their citizens from the diverse adverse effects of the disease. Health policymakers often have several interventions to consider based on the health of the population, as well as the cascading social and economic consequences of the possible mitigation strategies. The current outbreak of the monkeypox virus has elicited debate on the best mitigation strategy, especially given that most world economies are still recovering from the harsh economic effects of the COVID-19 pandemic. This paper sought to analyze the costs and benefits of three possible strategies and determine which option has the best health outcomes and positive economic effects. A case study of Jeddah was performed, whereby a model was simulated to determine the number of infections over 28 days based on one case of the monkeypox virus. Findings reveal that the vaccination provides the best intervention, as it effectively reduces the transmission rate and prevents loss of lives in the city. From the model, only three people were infected over the research period, while no deaths were reported. Although vaccination incurs a huge direct cost at the beginning, in the long run, it saves the economy from the disease's financial burden in terms of productivity loss from work absenteeism and premature deaths.

Collaborating Across Organizational Boundaries to Co-Create a More Just, Resilient, and Thriving Society

In this editorial for our special issue on interorganizational collaboration (IOC), we position collaborative action in the context of the concurrent global crises that necessitate the bridging of interests, positions, competencies, and resources. We unpack the notion of IOC in terms of its conditions, phases, practices, and dynamics, and provide an overview of how the contributing authors support such understanding of cross-boundary collaboration. Through their action-oriented approaches to research and learning, they show a promising interplay of insight and impact. We underline their search for impact and aim to reinforce the potential of IOC not just to be successful, but also highly meaningful to address grand challenges. We therefore take a normative stance and describe how the intertwined notions of justice, resilience, and thriving can serve as a compass to legitimize, organize, facilitate, assess, and study IOC as an important pathway for the co-creation of a better world.

Risk perception, but also political orientation, modulate behavioral response to COVID-19: A randomized survey experiment

Prior work has shown that accurately perceiving the risk for COVID-19 is associated with higher adherence to protective health behaviors, like face mask use, and more acceptance of governmental restrictive measures such as partial or complete banning of indoor activities and social gatherings. In this study we explored these associations at the beginning of the second wave of COVID-19 in Argentina through a national representative probabilistic survey that evaluated personal and contextual risk perception, self-reported compliance with protective health behaviors, attitude to governmental restrictive measures, and political orientation and psychological distress as potential modulators. Also, going beyond measures of association, here we sought to test whether messages highlighting potential risks increased acceptance of restrictive measures. Three types of messages were randomized to the participants. Two messages conveyed risk-related content (either through emotional arousal or cognitive appraisal) and the third a prosocial, altruistic content. Between March 29th and 30th, 2021, 2,894 participants were recruited (57.57% female). 74.64% of those surveyed evaluated the current health situation as “quite serious” or “very serious” and 62.03% estimated that the situation will be “worse” or “much worse” in the following 3 months. The perception of personal risk and the level of adherence to protective behaviors gradually increased with age. Through a regression model, age, perceived personal risk, and contextual risk appraisal were the variables most significantly associated with protective behaviors. In the case of the acceptance of restrictive measures, political orientation was the most associated variable. We then found messages aimed at increasing risk perception (both emotionally or cognitively focused) had a significantly greater effect on increasing the acceptance of restrictive measures than the prosocial message, mainly for government supporters but also for non-supporters. However, the level of response was also modulated by the political orientation of the participants. We propose a mechanism of “ideological anchoring” to explain that participants were responsive to risk modulation, but within the limits established by their pre-existent political views. We conclude that messages highlighting risk can help reinforce the acceptance of restrictive measures even in the presence of polarized views, but must be calibrated by age and political orientation.

Psychosocial Functioning and the Educational Experiences of Students with ASD during the COVID-19 Pandemic in Poland

Due to their individual developmental and learning needs, adolescents with autism spectrum disorder (ASD) benefit from a variety of educational, medical, and therapeutic services. During the COVID-19 pandemic, these services were discontinued or significantly reduced, which may have resulted in increased difficulties in coping with various areas of life. The purpose of this study was to explore how the pandemic affected the psychosocial and educational functioning of students with ASD. A qualitative, problem-focused interview method was used. The obtained material was subjected to interpretive phenomenological analysis. The study involved 10 secondary school students diagnosed with ASD. The assessment of the effects of the pandemic on the functioning of people with ASD is inconclusive. The respondents noted both negative and positive effects of lockdown. On the positive side, they were able to spend time with their family, isolate themselves from difficult social relationships and feel better. Among the negative effects, adolescents point to difficulties in emotional functioning—increased levels of stress and anxiety, as well as increased feelings of loneliness and difficulties with online education. The study showed the varied experiences of young people with autism during the pandemic, highlighting the significant need to support some of them in terms of their emotional, social and educational functioning.

The Need for Smart Architecture Caused by the Impact of COVID-19 upon Architecture and City: A Systematic Literature Review

The recent pandemic era of COVID-19 has shown social adjustment on a global scale in an attempt to reduce contamination. In response, academic studies relating to smart technologies have increased to assist with governmental restrictions such as social distancing. Despite the restrictions, architectural, engineering and construction industries have shown an increase in budget and activity. An investigation of the adjustments made in response to the pandemic through utilizing new technologies, such as the internet of things (IoT) and smart technologies, is necessary to understand the research trends of the new normal. This study should address various sectors, including business, healthcare, architecture, education, tourism and transportation. In this study, a literature review was performed on two web-based, peer-reviewed journal databases, SCOPUS and Web of Science, to identify a trend in research for the pandemic era in various sectors. The results from 123 papers revealed a focused word group of IoT, smart technologies, architecture, building, space and COVID-19. Overlapping knowledges of IoT systems, within the design of a building which was designed for a specific purpose, were discovered. The findings justify the need for a new sub-category within the field of architecture called “smart architecture”. This aims to categorize the knowledge which is required to embed IoT systems in three key architectural topics—planning, design, and construction—for building design with specific purposes, tailored to various sectors.

Analysis of Spatio-Temporal Characteristics of Urban Economic Resilience and Influencing Factors in Guangdong-Hong Kong-Macao Greater Bay Area

Due to the changes in the domestic and international economic situation in the post-pandemic era, the economic development of the Guangdong-Hong Kong-Macao Greater Bay Area has become unstable in many aspects. The paper adopted the Pressure-State-Response (PSR) model to build a regional economic resilience evaluation system from the perspective of public health emergencies. Then, the spatial and temporal evolution of the economic resilience of the Guangdong-Hong Kong-Macao Greater Bay Area and the influencing factors were explored by using entropy weight method, GIS and gray correlation method. The conclusions show that: (1) Temporally, the economic resilience of the Guangdong-Hong Kong-Macao Greater Bay Area has generally increased from 2010 to 2021, and is divided into three main stages: rapid development, adjustment to fluctuations and stable development. (2) Spatially, the overall pattern of economic resilience in the Guangdong-Hong Kong-Macao Greater Bay Area is high in the middle and south and low in the northwest, and shows a "stochastic-equalized-polarized" pattern of transformation. (3) In terms of influencing factors, economic status and economic response are the main dimensions affecting the resilience level of the economic system in the Guangdong-Hong Kong-Macao region. The level of scientific research and innovation, medical governance, government regulation and the rationalization of the industrial system are the key factors.

Novel Insights in Spatial Epidemiology Utilizing Explainable AI (XAI) and Remote Sensing

The COVID-19 pandemic has affected many aspects of human life around the world, due to its tremendous outcomes on public health and socio-economic activities. Policy makers have tried to develop efficient responses based on technologies and advanced pandemic control methodologies, to limit the wide spreading of the virus in urban areas. However, techniques such as social isolation and lockdown are short-term solutions that minimize the spread of the pandemic in cities and do not invert long-term issues that derive from climate change, air pollution and urban planning challenges that enhance the spreading ability. Thus, it seems crucial to understand what kind of factors assist or prevent the wide spreading of the virus. Although AI frameworks have a very efficient predictive ability as data-driven procedures, they often struggle to identify strong correlations among multidimensional data and provide robust explanations. In this paper, we propose the fusion of a heterogeneous, spatio-temporal dataset that combine data from eight European cities spanning from 1 January 2020 to 31 December 2021 and describe atmospheric, socio-economic, health, mobility and environmental factors all related to potential links with COVID-19. Remote sensing data are the key solution to monitor the availability on public green spaces between cities in the study period. So, we evaluate the benefits of NIR and RED bands of satellite images to calculate the NDVI and locate the percentage in vegetation cover on each city for each week of our 2-year study. This novel dataset is evaluated by a tree-based machine learning algorithm that utilizes ensemble learning and is trained to make robust predictions on daily cases and deaths. Comparisons with other machine learning techniques justify its robustness on the regression metrics RMSE and MAE. Furthermore, the explainable frameworks SHAP and LIME are utilized to locate potential positive or negative influence of the factors on global and local level, with respect to our model’s predictive ability. A variation of SHAP, namely treeSHAP, is utilized for our tree-based algorithm to make fast and accurate explanations.

How Banks Were Chosen and Rated in Hungary before and during the COVID-19 Pandemic

Banks can be chosen based on multiple factors, such as location, security, and e-banking functions. The characteristics of customers such as gender and age can also affect this decision. Since the digitalization of banking sped up due to the COVID-19 pandemic, the factors that affect this decision may change as well. To assess this, a questionnaire was completed by 156 respondents, and the results were evaluated using Pearson’s correlation test. According to the results, personal visits to the banks declined after the COVID-19 pandemic started. Furthermore, the number of e-bankers rose. When choosing banks, no gender-related relationships were found based on location, while older people chose different banks than their younger counterparts. The security of internet banking functions was not associated with bank choice, while the security of the mobile banking application was. Regarding the ratings of banks, males and females did not rate banks differently, and younger people tended to be more critical in their ratings. Security, accessible location, and good customer service can lead to more positive ratings as well. The findings can be used by banks in Hungary to improve their services in order to attract customers and increase their satisfaction.

Contagion Effect of Financial Markets in Crisis: An Analysis Based on the DCC–MGARCH Model

Global crises have created unprecedented challenges for communities and economies across the world, triggering turmoil in global finance and economy. This study adopts the dynamic conditional correlation multiple generalized autoregressive conditional heteroskedasticity (DCC–MGARCH) model to explore contagion effects across financial markets in crisis. The main findings are as follows: (1) the financial crisis and COVID-19 pandemic intensified the connection between the Chinese and US stock markets in the short term; (2) the dynamic conditional correlations (DCCs) during the COVID-19 pandemic are higher than those during the 2008 financial crisis owing to the further opening of the Chinese capital market, and financial institutions’ investments in the European market are higher than those in the American markets; (3) a stepwise increase is observed in the dynamic conditional correlation between the returns on the S&P 500 Index and SSEC during and after the onset of a destructive crisis; and (4) a unidirectional contagion effect exists between the Chinese market and US market, and the Hong Kong stock market contributes to the risk spillover. Effective transmission channels of external negative shocks may be investors’ sentiments, financial institutions, and the RMB exchange rate in the stock markets. This study provides useful suggestions to authorities formulating financial regulations and investors diversifying risk investments.

Numerical Evaluation of a Novel Vertical Drop Airflow System to Mitigate Droplet Transmission in Trains

Owing to the outbreak of COVID-19, researchers are exploring methods to prevent contact and non-contact infections that occur via multiple transmission routes. However, studies on preventing infections caused by droplet transmission in public transportation are insufficient. To prevent the spread of infectious diseases, a new ventilation system in railway vehicles must be developed. In this study, a novel vertical drop airflow (VDA) system is proposed to mitigate the effect of droplet transmission in a high-speed train cabin. The droplet transmission route and droplet fate are investigated using three-dimensional fluid dynamics simulations, performed employing the Eulerian–Lagrangian model. Additionally, a porous model is adopted to simulate the effect of close-fitting masks. The results indicate that 120 s after coughing, the decrease in the droplet number in the VDA system is 72.1% of that observed in the conventional system. Moreover, the VDA system effectively suppresses droplet transmission because the maximum droplet travel distances of the VDA systems are 49.9% to 67.0% of those of the conventional systems. Furthermore, the effect of reducing droplet transmission by wearing a close-fitting mask is confirmed in all systems. Thus, the decrease in both droplet number and droplet transmission area in train cabins validate that the proposed VDA system has an effective airflow design to prevent droplet infection.

Which factors influence mobility change during COVID‐19 in Germany? Evidence from German county data

This study analyzes the role of regional demographic, socioeconomic, and political factors in mobility changes during the COVID‐19 pandemic in Germany. Spatial econometric models are applied using data from the 401 counties in Germany. The model incorporates measures to reduce potential endogeneity effects. Our results show that mobility change shows significant socioeconomic heterogeneity, which could affect future policy measures to contain the pandemic. For example, case numbers and the share of academics are negatively associated with changes in mobility. On the contrary, a region's mean age and rural location have a positive impact. Political and economic implications of the results are discussed. The findings point to a possible reorganization of spatial, economic, and social activities beyond the course of the pandemic.

Sustainability Development: Assessment of Selected Indicators of Sustainable Energy Development in Poland and in Selected EU Member States Prior to COVID-19 and Following the Third Wave of COVID-19

An important question in the literature on climate change and sustainable development is the relationship between countries’ economic growth, household electricity consumption and greenhouse gas emissions. Despite the ongoing COVID-19 pandemic and related economic restrictions, sustainable economic growth remains at the forefront of the global development agenda. However, given the strong relationship between the ever increasing electricity consumption and greenhouse gas CO2 emissions, an increasing number of scientists have been questioning the feasibility of the planned emission reduction. In my research, I strove to determine whether there exists a relationship between the change in the structure of electricity consumption of households in selected EU Member States (15 countries), the impact of innovation, changes in electricity prices and economic growth, and CO2 emissions in 2007–2019, prior to the outbreak of the COVID-19 pandemic, and following its third wave (2021). The aim of the article is to propose a synthetic index to assess the degree of sustainable energy development (SISED) in selected EU countries. Multiobjective decision analysis (MODA) was applied in order to assess the sustainable energy development of the selected European countries. Research findings may contribute to both literature and practice if they are applied by individual EU countries in the process of formulating directions aimed at achieving sustainable energy development.

Responses of the International Bond Markets to COVID-19 Containment Measures

Using an international sample during the COVID-19 outbreak, our study gives evidence that COVID-19 containment measures impact volatility in the international bond markets in different ways. We found that the positive effect of increasing new COVID-19 vaccinations markedly mitigates bond market volatility, while non-pharmaceutical government interventions resembling bad news increase volatility in bond markets. Besides this, changes in total COVID-19 cases and total deaths have co-movement and a significant relationship with this volatility. Our results imply that the investors’ responses to the trigger of increased uncertainty seem to differ in a way that depends on bad or good news as a reflection of the possibility of pandemic control and the health of the economy. The mass vaccinations not only signal a lower probability of stringent government responses to the pandemic but also stabilize investors’ behavior and mitigate compliance fears to open a period of safe living with coronavirus. Our findings are still robust when using alternative measures of independent variables and different forecasting models of conditional volatility.

Fostering participation in digital contact tracing

Digital contact tracing is a promising digital public health intervention to manage epidemics. However, in order to reach its full potential, the technology has to be widely adopted and used. During the SARS-CoV-2 pandemic, this has not necessarily been the case. We review the literature with a focus on how participation in digital contact tracing could be fostered and provide policy recommendations on how to increase its adoption and usage as well as recommendations for further research.