Prevention and control of COVID-19 in public transportation: Experience from China

Assessing the impact of COVID-19 non-pharmaceutical interventions and relaxation policies on Class B respiratory infectious diseases transmission in China

This study investigates the incidence of Class B respiratory infectious diseases (RIDs) in China under the Coronavirus disease 2019 (COVID-19) epidemic and examines variations post-epidemic, following the relaxation of non-pharmaceutical interventions (NPIs). Two-stage evaluation was used in our study. In the first stage evaluation, we established counterfactual models for the pre-COVID-19 period to estimate expected incidences of Class B RIDs without the onset of the epidemic. In the second stage evaluation, we constructed seasonal autoregressive integrated moving average intervention (SARIMA-Intervention) models to evaluate the impact on the Class B RIDs after NPIs aimed at COVID-19 pandemic were relaxed. The counterfactual model in the first stage evaluation suggested average annual increases of 10.015%, 78.019%, 70.439%, and 67.799% for tuberculosis, scarlet fever, measles, and pertussis respectively, had the epidemic not occurred. In the second stage evaluation, the total relative reduction in 2023 of tuberculosis, scarlet fever, measles and pertussis were - 35.209%, - 59.184%, - 4.481%, and - 9.943% respectively. The actual incidence declined significantly in the first stage evaluation. However, the results of the second stage evaluation indicated that a rebound occurred in four Class B RIDs after the relaxation of NPIs; all of these showed a negative total relative reduction rate.

Public transportation means as seen by citizens: Approaching the case of the Dominican Republic

and middle-income countries, key constraints such as dense traffic flows, jams, and pollution constitute frequent issues that potentially explain many negative consequences in terms of (e.g.) efficiency, sustainability, and mobility safety. In this regard, recent evidence supports the idea that fostering public transportation is crucial to offering solutions for this difficult panorama. However, transport mode-related choices and shifts have been proven to depend highly on key perceptions and needs of potential users. The aim of this study was to analyze a set of key users' perceptions, usage, and perceived quality of public transportation in the Dominican Republic, as well as to explore the most relevant features for Dominicans from the "desired quality" paradigm. For this research at a national level, data retrieved from a nationwide sample of 1254 inhabitants of the Dominican Republic was used, proportional to the ONE census in terms of sex, age, habitat, and region. Overall, the results show that the general quality of transportation is 6.70 points out of 10. The use of public transportation in the Dominican Republic has a medium-low rating and is very focused on urban buses (41 %) and public cars (27.1 %). Nonetheless, the metro remains the most highly rated means of transport (M = 8.75). Concerning the quality variables analyzed, the highest scores are for accessibility (M = 7.08) and frequency of service (M = 6.99). Further, Dominicans focus on improving comfort, vehicle conditions, and safety. This study constitutes a first approximation to the desired quality of public transportation for Dominican Citizens, which may help policymakers scope user-based needs in public transportation systems and encourage a more frequent (and friendlier) public transport use in the country.

An overview for monitoring and prediction of pathogenic microorganisms in the atmosphere

Corona virus disease 2019 (COVID-19) has exerted a profound adverse impact on human health. Studies have demonstrated that aerosol transmission is one of the major transmission routes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Pathogenic microorganisms such as SARS-CoV-2 can survive in the air and cause widespread infection among people. Early monitoring of pathogenic microorganism transmission in the atmosphere and accurate epidemic prediction are the frontier guarantee for preventing large-scale epidemic outbreaks. Monitoring of pathogenic microorganisms in the air, especially in densely populated areas, may raise the possibility to detect viruses before people are widely infected and contain the epidemic at an earlier stage. The multi-scale coupled accurate epidemic prediction system can provide support for governments to analyze the epidemic situation, allocate health resources, and formulate epidemic response policies. This review first elaborates on the effects of the atmospheric environment on pathogenic microorganism transmission, which lays a theoretical foundation for the monitoring and prediction of epidemic development. Secondly, the monitoring technique development and the necessity of monitoring pathogenic microorganisms in the atmosphere are summarized and emphasized. Subsequently, this review introduces the major epidemic prediction methods and highlights the significance to realize a multi-scale coupled epidemic prediction system by strengthening the multidisciplinary cooperation of epidemiology, atmospheric sciences, environmental sciences, sociology, demography, etc. By summarizing the achievements and challenges in monitoring and prediction of pathogenic microorganism transmission in the atmosphere, this review proposes suggestions for epidemic response, namely, the establishment of an integrated monitoring and prediction platform for pathogenic microorganism transmission in the atmosphere.

The spatiotemporal trend of human brucellosis in China and driving factors using interpretability analysis

Human brucellosis has reemerged in China, with a distinct change in its geographical distribution. The incidence of human brucellosis has significantly risen in inland regions of China. To gain insights into epidemic characteristics and identify factors influencing the geographic spread of human brucellosis, our study utilized the Extreme Gradient Boosting (XGBoost) algorithm and interpretable machine learning techniques. The results showed a consistent upward trend in the incidence of human brucellosis, with a significant increase of 8.20% from 2004 to 2021 (95% CI: 1.70, 15.10). The northern region continued to face a serious human situation, with a gradual upward trend. Meanwhile, the western and southern regions have experienced a gradual spread of human brucellosis, encompassing all regions of China over the past decade. Further analysis using Shapley Additive Explanations (SHAP) demonstrated that higher Gross Domestic Product (GDP) per capita and increased funding for education have the potential to reduce the spread. Conversely, the expansion of human brucellosis showed a positive correlation with bed availability per 1000 individuals, humidity, railway mileage, and GDP. These findings strongly suggest that socioeconomic factors play a more significant role in the spread of human brucellosis than other factors.

Global lineage evolution pattern of sars-cov-2 in Africa, America, Europe, and Asia: A comparative analysis of variant clusters and their relevance across continents

Objective

The objective of this study is to provide a comparative analysis of variant clusters and their relevance across Africa, America, Europe, and Asia, in order to understand the evolutionary patterns of the virus across different regions and to inform the development of targeted interventions and genomic surveillance eforts.

Methods

The study analyzed the global lineage evolution pattern of 74, 075 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from 32 countries across four continents, focusing on variant clusters and their relevance across regions. Variants were weighted according to their hierarchical level. The correlation between variants was visualized through Dimensionality reduction analysis and Pairwise Pearson's correlation. We presented a reconstructed phylogenetic tree based on correlation analysis and variant weights.

Results

The analysis revealed that each continent had distinct variant clusters and different evolutionary patterns. The Americas had two clustered variants before lineage divergence and a downstream confluence lineage, Europe had bifurcation into two global lineages with an early occurrence of certain cluster while Asia had a downstream confluence of two large lineages diverging by two distinct clusters. Based on the cluster patterns of shared variants of the SARS-CoV-2 virus, Africa demonstrated a relatively clear distinction among three distinct regions.

Conclusions

The study provides insights into the evolutionary patterns of SARS-CoV-2 and highlights the importance of international collaboration in tracking and responding to emerging variants. The study found that the global pandemic was driven by Omicron variants that evolved with significant differences between countries and regions, and with different patterns across continents.

Big data sentiment analysis of business environment public perception based on LTP text classification --Take Heilongjiang province as an example

At present, the research of business environment is limited to conducting surveys on specific groups or measuring data from official databases. The assessment of the business environment largely depends on public perception. Aiming to explore the public perception of business environment, this paper organically combines the big data text mining and sentiment analysis (SA). The results show that the combination of big data text mining and SA can reflect the theme characteristics, reduce the bias of sentiment and text analysis, and clearly show the public perception of the business environment. The empirical study found that the public perception of business environment depends on not only the four dimensions of business environment, but also the influence of public opinion that cannot be ignored. The public's low recognition of the business environment in Heilongjiang Province mainly includes backward economic development, serious brain drain, low government efficiency, imperfect policies, administrative law enforcement, regional climate and urban construction. In order to solve these problems, it is necessary to improve the high-standard market system to promote economic development, enhance the efficiency of government services, improve government policies, effectively enhance law enforcement, strengthen infrastructure construction and promote cultural innovation.

[Study analysis evaluating the management and epidemiological aspects of the COVID-19 pandemic in Senegal one year on]

Introduction

after a year of evolution, the COVID-19 pandemic continues to be a burden. The African continent has not had the high case and death rates from COVID-19 as was predicted early in the pandemic. However, coronavirus is placing severe strains on Africa´s health and economic sectors. Senegal, like other African countries, continues to face this pandemic. The purpose of this study is to evaluate the management strategy and the epidemiological profile of the pandemic in Senegal one year on.

Methods

we listed all patients who tested positive for COVID-19 by RT-PCR throughout the country during the first year of the pandemic, from 2 March 2020 (first case date) to 1st March 2021. Epidemiological data were analysed.

Results

a total of 34,732 positive cases were diagnosed and recorded in one year, with a case-fatality rate of 2.5%. All the country´s administrative regions had been affected. Dakar, the capital, was the epicentre of the pandemic. Male predominance was established on the basis of the number of positive cases and deaths. The average age of subjects was 47 years and the cure rate was 83.5%. People over 60 were the most vulnerable, particularly those with cardiovascular co-morbidities.

Conclusion

Senegal´s strategy for managing COVID-19 has received international recognition. It has been dynamic, drawing on experience from previous management of public health events such as Ebola. The COVID-19 pandemic has put a strain on our fragile health systems. However, the response and the results achieved highlight the significant progress made by our country, helping to ensure the resilience of the health system.

[Risk management system to reduce COVID-19 infection in health personnelSistema de gestão de riscos para reduzir o contágio de COVID-19 em profissionais de saúde]

Objective

To assess the occupational factors associated with the occurrence of COVID-19 in health personnel who were exposed to different magnitudes of risk and who followed the United Nations crisis management policy for COVID-19.

Methods

Cross-sectional survey conducted between April and May 2021. The low-risk group (LRG) were considered to be those who had minimal contact with patients; the medium-risk group (MRG) had contact with non-COVID-19 patients and did not perform instrumental airway intervention; and the high-risk group (HRG) were those who cared for COVID-19 patients and performed instrumental intervention with aerosol generation. Diagnosed COVID-19 disease and the presence of positive IgG antibodies for SARS-CoV-2 measured with Elecsys® anti-SARS-CoV-2 were considered as outcomes.

Results

Outcome recorded in 43.8% of the LRG, versus 46.7% in the MRG (odds ratio [OR]: 1.125; 95% confidence interval [CI 95% ]: 0.896-1.414; p = 0.311), and 48.6% in the HRG (OR: 1,214; CI 95%: 0.964-1.530; p= 0.10).

Conclusion

Belonging to the high-risk group and the medium-risk group, based on the degree of exposure to confirmed COVID-19 patients in the work area, was not associated with a higher occurrence of disease or seroconversion.

Cost-effectiveness of Paxlovid in reducing severe COVID-19 and mortality in China

Objectives

To assess the cost-effectiveness of Paxlovid in reducing severe COVID-19 and its associated morality, and to investigate the affordable price of Paxlovid in China.

Materials and methods

Using a Markov model, two interventions by Paxlovid prescription (with and without prescription) were compared in terms of COVID-19-related clinical outcomes and economic loss. COVID-related costs were collected from the societal perspective. Effectiveness data were obtained from literature. The primary outcomes were total social cost, disability adjusted life-years (DALYs) and net monetary benefit (NMB). Scenario analyses were performed to investigate the affordable price of Paxlovid in China. Deterministic sensitivity analyses (DSA) and probabilistic sensitivity analysis (PSA) were performed to verify the model robustness.

Results

Compared with the non-Paxlovid cohort, the NMBs of the Paxlovid cohort were only higher in the subgroup of patients aged over 80 years old, regardless of their vaccination status. Our scenario analysis found that, the price ceiling of Paxlovid/box for it to be cost-effective was RMB 8,993 (8,970-9,009) in those aged over 80 years old who were not vaccinated, which is the highest; and was RMB 35 (27-45) in those aged 40-59 years old who were vaccinated, which is the lowest. Sensitivity analyses found that the incremental NMB for the vaccinated people aged over 80 years was most sensitive to the efficacy of Paxlovid and the cost-effectiveness probability of Paxlovid increased with its decreasing price.

Conclusion

Under the current marketing price of Paxlovid/box (RMB 1,890), using Paxlovid was only cost-effective in people aged over 80 years old regardless of their vaccination status.

Evaluating public transit agency responses to the Covid-19 pandemic in seven U.S. regions

The Covid-19 pandemic's impacts on public transit will be felt for years, if not longer. In a few short weeks in 2020, the nature of day-to-day travel shifted around the world. Many of those who were able to stay at home did so while a large majority of those who needed to continue traveling moved away from public transit if they had alternatives available. For their part, public transit agencies responded with rapid service adjustments during March 2020, making varying efforts to communicate with riders and the public during this time so that users could understand how service was changing and how it would affect them. The impacts of the pandemic were dramatic-public transit ridership dropped by nearly 80% in April 2020 across the United States as the unemployment rate reached 14%-worse than any month during the Great Recession. But agency responses were nonuniform. In this paper, we characterize how seven public transit operators in the United States-those responsible for 55% of all unlinked trips in 2019-adapted service during the pandemic using quantitative performance information and a review of agency press releases. We also assess impacts on riders for whom public transit is essential. We find that pandemic-era changes largely did not change existing disparities between groups, suggesting that baseline inequities did not worsen as overall service levels fell. Understanding transit agency behaviors using different data sources is a first step towards linking agency responses with outcomes. This type of analysis that blends quantitative performance analysis with qualitative data can also provide insight into how agencies can adapt to future crises.

Social and spatial heterogeneities in COVID-19 impacts on individual's metro use: A big-data driven causality inference

While mobility intervention policies implemented during the early stages of the COVID-19 outbreak had a significant impact on public transit use, few studies have investigated the individual-level responses in metro transit riding behaviors. Using long time-series cellphone big data from frequent metro users in Shenzhen, China, we developed a quasi-experimental interrupted time series (ITS) design to estimate the treatment effects of mobility intervention policies on people's daily shares of metro transit use (SMU). The results indicate that the first-level emergency response (FLR) and the public transit restriction (PTR) policy yielded abrupt drops in SMU of 8.0% and 17.6%, respectively, whereas the return-to-work (RTW) order had an immediate recovery effect of 14.5%. The effect of the FLR is time-decreasing while those effects of the PTR and the RTW are time-increasing. Females and elderly people living in neighborhoods near the city center with low population density and fewer transit stations are more adaptable to policy interventions for reducing SMUs, while the recovery effect of RTW is relatively low for the elderly living in less mixed-use neighborhoods with reduced transit service. These findings can help policymakers design more socially- and spatially-precise and equity mobility intervention policies during a pandemic.

India's public transportation system: the repercussions of COVID-19

The COVID-19 pandemic has left scars on the Indian public transportation system. In order to regain its original momentum, policymakers will need to assess the barriers hindering the effectiveness of the public transportation sector. In this regard, this article analyzes the various factors affecting the public transportation sector in India and determines their interrelationships. The research is presented in three steps. First, we review the literature to identify the factors that affect the public transportation system in India. Next, we propose an integrated model of grey-DEMATEL and ANP, grey-DANP, to calculate the priority ranking and weight of the factors. The grey-DEMATEL method is used to find the interrelationships among the factors, while ANP determines the local and global weights of the factors to form a priority order. Then, we present the interrelationships in the form of influential relation maps. Furthermore, we provide a sensitivity analysis to enhance the credibility of our study. The paper reveals that governmental regulations are the most influential factors in India's public transportation system. The transportation authorities and policymakers must also focus on improving the financial stability and enhancing the customer's trust in the public transportation system. The framework provided in this paper can be applied to other countries where similar hindrances in the public transportation system have been caused by COVID-19.

Understanding individual-level travel behavior changes due to COVID-19: Trip frequency, trip regularity, and trip distance

Understanding different mechanisms in trip changes depending on transportation modes due to COVID-19 pandemic is the key to providing practical insights for healthy communities. This study aimed to investigate the impact of the COVID-19 pandemic on individual-level travel behavior in Daejeon Metropolitan City, South Korea. Using smart card and private vehicle records, we explored different travel behaviors exhibited while using buses and private vehicles. An individual's travel behavior was represented in trip frequency, trip regularity, and trip distance and was compared weekly for about three months, including the initial period of pandemic. A significant decrease in trip frequency during non-peak hours on weekdays and during weekends indicates that people reduced non-mandatory trips more than commuter trips. This was also verified in that, as the number of infection cases increased, trip regularity with 24-hour intervals intensified. People maintained the size of their activity boundaries but reduced their daily trip distances. The interesting point is that private vehicle usage increased for shorter trip distances while bus usage dropped regardless of the ranges of trip distances under the pandemic. The findings provide evidence of possible inequality issues in transportation during the pandemic and can help make precautionary policies for future pandemics.

Evaluation and improvement of the resilience of a transportation system against epidemic diseases: A system dynamics approach

The influential role of health protocols in preventing the spread of the COVID-19 disease has led governments to seek effective methods for implementing these protocols in the society. Considering the importance of public transportation system in spread of viruses, this paper introduces and analyzes some methods of inspecting urban public transportation companies using system dynamics approach. First, the base model, which represents the status of a public transportation terminal, was created and validated using a system dynamics simulation approach. Then the impact of two penalty policies, including fixed penalty policy (FPP) and variable penalty policy (VPP) on the violations within the terminal was investigated. The simulation results show that the variable penalty policy significantly reduces the violations of passenger terminal drivers. Next, the extended model was developed which considered several terminals. Finally, by presenting two policies of fixed inspector assignment (FIA) and variable inspector assignment (VIA), the effect of four scenarios of combining inspection and penalties policies was investigated. The simulation results showed that combining the variable penalty and variable inspector assignment policies could significantly reduce terminal violations. Also, the implementation of this policy does not require an additional inspector. The results can help city managers to adopt appropriate inspection policies.

Dynamic model of respiratory infectious disease transmission in urban public transportation systems

During the epidemics of respiratory infectious diseases, the use of public transportation increases the risk of disease transmission. Therefore, we established a dynamic model to provide an in-depth understanding of the mechanism of epidemic spread via this route. We designed a computer program to model a rail transit system including four transit lines in a small town in which assumed 70% of the residents commute via these trams in weekdays and the remaining residents take the tram at random. The model could identify the best travel route for each passenger and the specific passengers onboard when the tram passed through each station, and simulate the dynamic spread of a respiratory pathogen as the passengers used the rail transit system. Based on the program operating, we estimated that all residents in the town were ultimately infected, including 86.6% who were infected due to the public transportation system. The remaining individuals were infected at home. As the infection rate increased, the number of infected individuals increased more rapidly. Reducing the frequency of trams, driving private cars or riding bicycles, showing nucleic acid certificates and wearing masks for passengers, etc., are effective measures for the prevention of the spread of epidemic diseases.

The global dynamic transmissibility of COVID-19 and its influencing factors: an analysis of control measures from 176 countries

OBJECTIVE

To summarise the dynamic characteristics of COVID-19 transmissibility; To analyse and quantify the effect of control measures on controlling the transmissibility of COVID-19; To predict and compare the effectiveness of different control measures.

METHODS

We used the basic reproduction number ([Formula: see text]) to measure the transmissibility of COVID-19, the transmissibility of COVID-19 and control measures of 176 countries and regions from January 1, 2020 to May 14, 2022 were included in the study. The dynamic characteristics of COVID-19 transmissibility were summarised through descriptive research and a Dynamic Bayesian Network (DBN) model was constructed to quantify the effect of control measures on controlling the transmissibility of COVID-19.

RESULTS

The results show that the spatial transmissibility of COVID-19 is high in Asia, Europe and Africa, the temporal transmissibility of COVID-19 increases with the epidemic of Beta and Omicron strains. Dynamic Bayesian Network (DBN) model shows that the transmissibility of COVID-19 is negatively correlated with control measures. Restricting population mobility has the strongest effect, nucleic acid testing (NAT) has a strong effect, and vaccination has the weakest effect.

CONCLUSION

Strict control measures are essential for controlling the COVID-19 outbreak; Restricting population mobility and nucleic acid testing (NAT) have significant impacts on controlling the COVID-19 transmissibility, while vaccination has no significant impact. In light of these findings, future control measures may include the widespread use of new NAT technology and the promotion of booster immunization.

Humanitarian management strategy for interstate movement of migrant workers in India during COVID-19 pandemic: an optimization based approach

India faced a unique situation during the ongoing COVID-19 pandemic when millions of migrant workers, in different states had to be transported to their home states as workplaces shut down. The governments in respective states faced challenges of minimizing economic impact while ensuring that the risk of infection was also kept under control. This paper develops models based on various secondary data from governmental and relevant non-governmental sources, trying to minimize the economic impact while keeping the rate of infection low and determining whether the migrant workforce should be allowed to stay in their workplace state or allowed to return to their home state. We found that the number of days of lockdown had a significant impact on the results. Fewer days of lockdown resulted in workers remaining in their work state as the preferred outcome, while a higher number of days of lockdown implied that people traveled to their home state and remain there. The proportion of workers who were willing to return to their work state played an important role on the results too. Beyond the threshold percentages of migrant workers returning to their work state, it became optimal for the government to encourage the workers to travel to their home state. However, this was mostly visible for moderate number of lockdown days as the effects on results were dominated by the impact from the number of lockdown days for too high or too low number of lockdown days. There is also an important trade-off between the budget and infection rate 'R' for the governments to consider. Minimizing the risk of infection requires an additional budget.

Two-year impact of COVID-19 pandemic on hospitalized patients with skin diseases in China

To investigate the clinical characteristics of skin disorders among hospitalized patients before and during the coronavirus disease 2019 (COVID-19) pandemic, a retrospective study was conducted based on hospitalized patients with skin diseases from Xiangya Hospital of Central South University, the largest hospital in the south-central region of China, between January 1, 2018, and December 31, 2021. A total of 3039 hospitalized patients were enrolled in the study, including 1681 patients in the prepandemic group and 1358 patients in the pandemic group. The total number of hospitalized patients in the pandemic group decreased by 19.2%, with an increased proportion of patients over 60 years of age (39.8% vs. 35.8%). Moreover, compared with the prepandemic group, there were decreases in the occurrence of most skin diseases in the pandemic group, but the proportions of keratinolytic carcinoma (6.6% vs. 5.2%), dermatitis (24.0% vs. 18.9%), and psoriasis (18.0% vs. 14.8%) were higher in the pandemic group. In addition, longer hospital stays (β = 0.07, SE = 0.02, P = 1.35 × 10^-3 ) and higher hospital costs (β = 0.06, SE = 0.03, p = 0.031) were found in the pandemic group through general linear models, even after the corresponding adjustment. In summary, the COVID-19 pandemic has had a lasting impact on patients with skin diseases, with fewer hospitalized patients, increased proportions of older patients, longer hospital stays, and increased hospital costs. These findings will facilitate better preparation for the most effective response to future pandemics.

The impact of COVID-19 lockdown on cases and deaths of AIDS, gonorrhea, syphilis, hepatitis B, and hepatitis C in China: an interrupted time series analysis

BACKGROUND

China has implemented nationwide lockdown to contain COVID-19 from an early stage. Previous studies of the impact of COVID-19 on sexually transmitted diseases (STDs) and diseases caused by blood-borne viruses (BBVs) in China have yielded widely disparate results, and study on deaths attributable to STDs and BBVs are scarce.

OBJECTIVE

We aimed to elucidate the impact of COVID-19 lockdown on the cases, deaths, and case-fatality ratios of STDs and BBVs.

METHODS

We extracted the monthly cases and deaths data for AIDS, gonorrhea, syphilis, hepatitis B, and hepatitis C between January 2015 and December 2021 from the notifiable disease reporting database on the official website of the National Health Commission of China. We used descriptive statistics to summarize the number of cases and deaths, and calculated incidence and case-fatality ratios before and after implementing nationwide lockdown (January 2020). We used negative binominal segmented regression models to estimate the immediate and long-term impacts of lockdown on cases, deaths, and case-fatality ratios in January 2020 and December 2021, respectively.

RESULTS

A total of 14,800,330 cases and 127,030 deaths of AIDS, gonorrhea, syphilis, hepatitis B, and hepatitis C were reported from January 2015 to December 2021, with an incidence of 149.11/100,000 before lockdown and 151.41/100,000 after lockdown , and a case-fatality ratio of 8.21/1000 before lockdown and 9.50/1000 after lockdown . In the negative binominal model, AIDS cases (-23.4%; 0.766, 0.626-0.939) and deaths (-23.9%; 0.761, 0.647-0.896), gonorrhea cases (-34.3%; 0.657, 0.524-0.823), syphilis cases (-15.4%; 0.846, 0.763-0.937), hepatitis B cases (-17.5%; 0.825, 0.726-0.937) and hepatitis C cases (-19.6%; 0.804, 0.693-0.933) showed significant decreases in January 2020. Gonorrhea, syphilis and hepatitis C showed small increases in the number of deaths or case-fatality ratios in January 2020. By December 2021, the cases, deaths, and case-fatality ratios for each disease had either reached or remained below expected levels.

CONCLUSIONS

COVID-19 lockdown may have contributed to fewer reported cases of AIDS, gonorrhea, syphilis, hepatitis B, and hepatitis C, and more reported deaths or case-fatality ratios of gonorrhea, syphilis and hepatitis C in China.

CLINICALTRIAL

COVID-19 epidemic and public health interventions in Shanghai, China: Statistical analysis of transmission, correlation and conversion

Background

The Shanghai COVID-19 epidemic is an important example of a local outbreak and of the implementation of normalized prevention and disease control strategies. The precise impact of public health interventions on epidemic prevention and control is unknown.

Methods

We collected information on COVID-19 patients reported in Shanghai, China, from January 30 to May 31, 2022. These newly added cases were classified as local confirmed cases, local asymptomatic infections, imported confirmed cases and imported asymptomatic infections. We used polynomial fitting correlation analysis and illustrated the time lag plot in the correlation analysis of local and imported cases. Analyzing the conversion of asymptomatic infections to confirmed cases, we proposed a new measure of the conversion rate (C _r ). In the evolution of epidemic transmission and the analysis of intervention effects, we calculated the effective reproduction number (R _t ). Additionally, we used simulated predictions of public health interventions in transmission, correlation, and conversion analyses.

Results

(1) The overall level of R _t in the first three stages was higher than the epidemic threshold. After the implementation of public health intervention measures in the third stage, R _t decreased rapidly, and the overall R _t level in the last three stages was lower than the epidemic threshold. The longer the public health interventions were delayed, the more cases that were expected and the later the epidemic was expected to end. (2) In the correlation analysis, the outbreak in Shanghai was characterized by double peaks. (3) In the conversion analysis, when the incubation period was short (3 or 7 days), the conversion rate fluctuated smoothly and did not reflect the effect of the intervention. When the incubation period was extended (10 and 14 days), the conversion rate fluctuated in each period, being higher in the first five stages and lower in the sixth stage.

Conclusion

Effective public health interventions helped slow the spread of COVID-19 in Shanghai, shorten the outbreak duration, and protect the healthcare system from stress. Our research can serve as a positive guideline for addressing infectious disease prevention and control in China and other countries and regions.

Passengers' self-protective intentions while using ride-hailing services during the COVID-19 pandemic

In the transport context, there has been limited research examining passengers' health-protective behaviour while travelling during a health-related crisis such as COVID-19. This study develops a conceptual model aiming to explore determinants associated with passengers' self-protective intentions using the context of ride-hailing services in Vietnam. Ride-hailing services are popular in countries where public transport is underdeveloped. The conceptual model is based on perceived risk and self-efficacy as the main predictor of self-protective intentions when using ride-hailing services. In addition, the proposed conceptual model explores the direct and indirect impact of subjective knowledge and the perceived effectiveness of preventive measures on self-protective intentions. The proposed conceptual model was tested on a large sample of ride-hailing users in Vietnam (n = 527). The structural equation modelling (SEM) analysis results indicate that self-efficacy has the highest total impact on self-protective behaviour, followed by subject knowledge and perceived effectiveness of preventive measures. Self-efficacy also plays a fully mediating role in the linkage between the perceived effectiveness of preventive measures implemented by ride-hailing organisations and the intention to engage in self-protective behaviour. The results of this study expand the current understanding of ride-hailing passengers' health-protective behaviour and contribute to the transport and public health literature.

Public Health Measures and the Control of COVID-19 in China

In December 2019, the COVID-19 pandemic quickly spread throughout China and beyond, posing enormous global challenges. With prompt, vigorous, and coordinated control measures, mainland China contained the spread of the epidemic within two months and halted the epidemic in three months. Aggressive containment strategy, hierarchical management, rational reallocation of resources, efficient contact tracing, and voluntary cooperation of Chinese citizens contributed to the rapid and efficient control of the epidemic, thus promoting the rapid recovery of the Chinese economy. This review summarizes China's prevention and control strategies and other public health measures, which may provide a reference for the epidemic control in other countries.

Changes on local travel behaviors under travel reduction-related interventions during COVID-19 pandemic: a case study in Hong Kong

The emerging Omicron variant poses a serious threat to human health. Public transports play a critical role in infection spread. Based on the data of nearly 4 billion smartcard uses, between January 1, 2019 and January 31, 2021 from the Mass Transit Railway Corporation of Hong Kong, we analyzed the subway travel behavior of different population groups (adults, children, students and senior citizens) due to the COVID-19 pandemic and human travel behavior under different interventions (e.g. work suspension, school closure). Due to the pandemic, the number of MTR passengers (the daily number of passengers in close proximity in subway carriages) decreased by 37.4% (40.8%) for adults, 80.3% (78.5%) for children, 71.6% (71.6%) for students, and 33.5% (36.1%) for senior citizens. Due to work from home (school suspension), the number of contacted adults (students/children) in the same carriage during the rush hours decreased by 39.6% (38.6%/43.2%). If all workers, students, and children were encouraged to commute avoiding rush hours, the possible repeated contacts during rush hour of adults, children and students decreased by 73.3%, 77.9% and 79.5%, respectively. Since adults accounted for 87.3% of the total number of subway passengers during the pandemic, work from home and staggered shift pattern of workers can reduce the infection risk effectively. Our objective is to find the changes of local travel behavior due to the pandemic. From the perspective of public transports, the results provide a scientific support for COVID-19 prevention and control in cities.

A data-driven interpretable ensemble framework based on tree models for forecasting the occurrence of COVID-19 in the USA

This prevalence of coronavirus disease 2019 (COVID-19) has become one of the most serious public health crises. Tree-based machine learning methods, with the advantages of high efficiency, and strong interpretability, have been widely used in predicting diseases. A data-driven interpretable ensemble framework based on tree models was designed to forecast daily new cases of COVID-19 in the USA and to determine the important factors related to COVID-19. Based on a hyperparametric optimization technique, we developed three machine learning algorithms based on decision trees, including random forest (RF), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM), and three linear ensemble models were used to integrate these outcomes for better prediction accuracy. Finally, the SHapley Additive explanation (SHAP) value was used to obtain the feature importance ranking. Our outcomes demonstrated that, among the three basic machine learners, the prediction accuracy was the following in descending order: LightGBM, XGBoost, and RF. The optimized LAD ensemble was the most precise prediction model that reduced the prediction error of the best base learner (LightGBM) by approximately 3.111%, while vaccination, wearing masks, less mobility, and government interventions had positive effects on the control and prevention of COVID-19.

Social distancing and revenue management-A post-pandemic adaptation for railways

The SARS-CoV-2 pandemic has had a significant impact on rail operations worldwide. Adopting control measures such as a 50% occupancy rate can contribute to a safer travel environment, though at the expense of operational efficiency. This paper addresses the issues of social distancing and revenue maximization for a train operating company in a post-pandemic world. Although the two objectives appear to be highly contradictory, we believe that judicious planning can optimize both to a great extent. Existing research on social distancing on public transport has only considered the risk of virus transmission during travel. This is the first attempt to recognize the risk of virus spread in different cities along with transmission risk as part of developing a social distancing plan. We study the problem of assigning seats to passenger groups on long-distance trains while ensuring social distancing within coaches. A novel seating assignment policy is proposed that takes into account several factors that govern the spread of virus. In an effort to reduce the spread of the virus and improve revenue simultaneously, a mixed-integer programming (MIP) model is proposed to assign seats to passengers. Several families of valid inequalities and preprocessing steps are proposed to strengthen the MIP formulation, which represents a substantial contribution to the literature on group seat assignment problem. The validity of the model and the effectiveness of the valid inequalities have been evaluated using real-life data from Indian Railways. The computational results demonstrate a significant reduction in the risk of contagion and an increase in seat utilization compared to the current approach employed by operators.

Assessment of Doubly Disadvantaged Neighborhoods by Healthy Living Environment Exposure

Good access to greenspace and healthy food has commonly been found to be positively associated with health outcomes, despite some studies finding no significant relationship between them. Examining inequalities in accessing greenspace and healthy food among different disadvantaged neighborhoods can help reveal the disadvantaged races/ethnicities in cities with a high level of residential segregation (i.e., population of the same race/ethnicity concentrated in the same neighborhoods). However, existing studies have mostly focused on measuring the inequalities in accessing either greenspace or healthy food alone, which can lead to the inaccurate depiction of disadvantaged neighborhoods in healthy living environments. Therefore, this paper aims at improving the assessment of doubly disadvantaged neighborhoods by considering accessibility to both greenspace and healthy food in the City of Chicago. Our results show that black-majority neighborhoods are the most doubly disadvantaged in terms of exposure to healthy living environments. This study can help guide policymakers to divert more resources towards the improvement of the urban environment for the most doubly disadvantaged neighborhoods.

Beyond fear and abandonment: Public transport resilience during the COVID-19 pandemic

The outbreak of the COVID-19 pandemic challenged urban public transport systems to maintain accessibility and service for daily users while adapting to local health and safety regulations. Developing sustainable and resilient urban policies under such crisis conditions requires understanding the different feelings, experiences and expectations of passengers and how these relate to socio-economic inequalities. Drawing on a mixed-method study in Berlin (Germany), Brussels (Belgium), Stockholm (Sweden) and Tallinn (Estonia), we show how the pandemic outbreak has changed both who uses public transport and how users experience their journeys. Challenging the narratives that portray public transport as a place of fear, we find that remaining passengers assess the risk of contagion lower than those who avoided it completely. We argue that promoting resilient public transport requires policies that address the needs of passengers relying on public transport services. Therefore, we question the current policies under the sustainable mobility paradigm for not taking sufficient account of the feelings, experiences and emotions and particularly of transport-dependent users.

Perceived risks of transit use during COVID-19: Correlates and strategies from a case study in El Paso, Texas

Introduction

COVID-19 has led to public transportation ridership plummeting and thus created fiscal crises and operational difficulties for transit operators. Although transit services remain essential for people with limited access to alternative transportation modes, the unfavorable public view keeps potential riders from transit. The public transportation industry is in dire need of restoring trust and recovering ridership.

Methods

In July 2020, we conducted an online survey in El Paso, Texas, to investigate COVID-19 risk perceptions related to transit use. A total of 712 valid responses, consisting of 613 English and 99 Spanish responses, were included in the analyses.

Results and conclusions

Descriptive and bivariate analyses showed many choice transit riders changed their mobility patterns by abandoning public transportation. Survey participants reported that social distancing and cleaning services were very important in encouraging them to return to transit. The free fare policy was also a stimulus for the existing riders to continue their transit use during the pandemic. The multivariable analysis results highlighted that public knowledge plays a vital role in COVID-19 risk perceptions and transit use decisions. Major opportunities exist in terms of public awareness campaigns that inform the public about the COVID-19 related safety measures transit operators are implementing. We further suggest some practical strategies to enhance public communication and help transit operators recover from COVID-19. This study offers timely insights for public policy stakeholders, including transit agencies, to better utilize their resources to protect public health, regain public confidence, and bring passengers back.

The impact of COVID-19 non-pharmaceutical interventions on HIV care continuum in China: An interrupted time series analysis

Background

China implemented strict non-pharmaceutical interventions to contain COVID-19 at the early stage. We aimed to evaluate the impact of COVID-19 on HIV care continuum in China.

Methods

Aggregated data on HIV care continuum between 1 January 2017 and 31 December 2020 were collected from centers for disease control and prevention at different levels and major infectious disease hospitals in various regions in China. We used interrupted time series analysis to characterize temporal trend in weekly numbers of HIV post-exposure prophylaxis (PEP) prescriptions, HIV tests, HIV diagnoses, median time intervals between HIV diagnosis and antiretroviral therapy (ART) initiation (time intervals, days), ART initiations, mean CD4+ T cell counts at ART initiation (CD4 counts, cells/μL), ART collections, and missed visits for ART collection, before and after the implementation of massive NPIs (23 January to 7 April 2020). We used Poisson segmented regression models to estimate the immediate and long-term impact of NPIs on these outcomes.

Findings

A total of 16,780 PEP prescriptions, 1,101,686 HIV tests, 69,659 HIV diagnoses, 63,409 time intervals and ART initiations, 61,518 CD4 counts, 1,528,802 ART collections, and 6656 missed visits were recorded during the study period. The majority of outcomes occurred in males (55·3-87·4%), 21-50 year olds (51·7-90·5%), Southwestern China (38·2-82·0%) and heterosexual transmission (47·9-66·1%). NPIs was associated with 71·5% decrease in PEP prescriptions (IRR 0·285; 95% CI 0·192-0·423), 36·1% decrease in HIV tests (0·639, 0·497-0·822), 32·0% decrease in HIV diagnoses (0·680, 0·511-0·904), 59·3% increase in time intervals (1·593, 1·270-1·997) and 17·4% decrease in CD4 counts (0·826, 0·746-0·915) in the first week during NPIs. There was no marked change in the number of ART initiations, ART collections and missed visits during the NPIs. By the end of 2020, the number of HIV tests, HIV diagnoses, time intervals, ART initiations, and CD4 counts reached expected levels, but the number of PEP prescriptions (0·523, 0·394-0·696), ART collections (0·720, 0·595-0·872), and missed visits (0·137, 0·086-0·220) were still below expected levels. With the ease of restrictions, PEP prescriptions (slope change 1·024/week, 1·012-1·037), HIV tests (1·016/week, 1·008-1·026), and CD4 counts (1·005/week, 1·001-1·009) showed a significant increasing trend.

Interpretation

HIV care continuum in China was affected by the COVID-19 NPIs at various levels. Preparedness and efforts to maintain the HIV care continuum during public health emergencies should leverage collaborations between stakeholders.

Funding

Natural Science Foundation of China.

Insight into the nonlinear effect of COVID-19 on well-being in China: Commuting, a vital ingredient

Background

COVID-19 had a devastating impact on people's work, travel, and well-being worldwide. As one of the first countries to be affected by the virus and develop relatively well-executed pandemic control, China has witnessed a significant shift in people's well-being and habits, related to both commuting and social interaction. In this context, what factors and the extent to which they contribute to well-being are worth exploring.

Methods

Through a questionnaire survey within mainland China, 688 valid sheets were collected, capturing various aspects of individuals' life, including travel, and social status. Focusing on commuting and other factors, a Gradient Boosting Decision Tree (GBDT) model was developed based on 300 sheets reporting working trips, to analyze the effects on well-being. Two indicators, i.e., the Relative Importance (RI) and Partial Dependency Plot (PDP), were used to quantify and visualize the effects of the explanatory factors and the synergy among them.

Results

Commuting characteristics are the most critical ingredients, followed by social interactions to explain subjective well-being. Commuting stress poses the most substantial effect. Less stressful commuting trips can solidly improve overall well-being. Better life satisfaction is linked with shorter confinement periods and increased restriction levels. Meanwhile, the switch from in-person to online social interactions had less impact on young people's life satisfaction. Older people were unsatisfied with this change, which had a significant negative impact on their life satisfaction.

Conclusions

From the synergy of commuting stress and commuting time on well-being, the effect of commuting time on well-being is mediated by commuting stress in the case of China. Even if one is satisfied with online communication, the extent of enhancement on well-being is minimal, for it still cannot replace face-to-face interaction. The findings can be beneficial in improving the overall well-being of society during the pandemic and after the virus has been eradicated.

Developing a conceptual framework for the health protection of United Nations peacekeepers against the COVID-19 pandemic from global health perspectives

The coronavirus disease 2019 (COVID-19) pandemic has posed particular health risks to United Nations peacekeepers, which require prompt responses and global attention. Since the health protection of United Nations peacekeepers against the COVID-19 pandemic is a typical global health problem, strategies from global health perspectives may help address it. From global health perspectives, and referring to the successful health protection of the Chinese Anti-Ebola medical team in Liberia, a conceptual framework was developed for the health protection of United Nations peacekeepers against the COVID-19 pandemic. Within this framework, the features include multiple cross-borders (cross-border risk factors, impact, and actions); multiple risk factors (Social Determinants of Health), multiple disciplines (public health, medicine, politics, diplomacy, and others), and extensive interdepartmental cooperation. These strategies include multiple phases (before-deployment, during-deployment, and post-deployment), multi-level cooperation networks (the United Nations, host countries, troop-contributing countries, the United Nations peacekeeping team, and United Nations peacekeepers), and concerted efforts from various dimensions (medical, psychological, and social).

COVID-19 Vehicle Based on an Efficient Mutual Authentication Scheme for 5G-Enabled Vehicular Fog Computing

The COVID-19 pandemic is currently having disastrous effects on every part of human life everywhere in the world. There have been terrible losses for the entire human race in all nations and areas. It is crucial to take good precautions and prevent COVID-19 because of its high infectiousness and fatality rate. One of the key spreading routes has been identified to be transportation systems. Therefore, improving infection tracking and healthcare monitoring for high-mobility transportation systems is impractical for pandemic control. In order to enhance driving enjoyment and road safety, 5G-enabled vehicular fog computing may gather and interpret pertinent vehicle data, which open the door to non-contact autonomous healthcare monitoring. Due to the urgent need to contain the automotive pandemic, this paper proposes a COVID-19 vehicle based on an efficient mutual authentication scheme for 5G-enabled vehicular fog computing. The proposed scheme consists of two different aspects of the special flag, SF = 0 and SF = 1, denoting normal and COVID-19 vehicles, respectively. The proposed scheme satisfies privacy and security requirements as well as achieves COVID-19 and healthcare solutions. Finally, the performance evaluation section shows that the proposed scheme is more efficient in terms of communication and computation costs as compared to most recent related works.

Latent profile analysis of security among patients with COVID-19 infection in mobile cabin hospitals and its relationship with psychological capital

Aim

COVID-19 patients' security is related to their mental health. However, the classification of this group's sense of security is still unclear. The aim of our research is to clarify the subtypes of security of patients infected with COVID-19, explore the factors affecting profile membership, and examine the relationship between security and psychological capital for the purpose of providing a reference for improving patients' sense of security and mental health.

Methods

A total of 650 COVID-19 patients in a mobile cabin hospital were selected for a cross-sectional survey from April to May 2022. They completed online self-report questionnaires that included a demographic questionnaire, security scale, and psychological capital scale. Data analysis included latent profile analysis, variance analysis, the Chi-square test, multiple comparisons, multivariate logistical regression, and hierarchical regression analysis.

Results

Three latent profiles were identified-low security (Class 1), moderate security (Class 2), and high security (Class 3)-accounting for 12.00, 49.51, and 38.49% of the total surveyed patients, respectively. In terms of the score of security and its two dimensions, Class 3 was higher than Class 2, and Class 2 was higher than Class 1 (all P < 0.001). Patients with difficulty falling asleep, sleep quality as usual, and lower tenacity were more likely to be grouped into Class 1 rather than Class 3; Patients from families with a per capita monthly household income <3,000 and lower self-efficacy and hope were more likely to be grouped into Classes 1 and 2 than into Class 3. Psychological capital was an important predictor of security, which could independently explain 18.70% of the variation in the patients' security.

Conclusions

Security has different classification features among patients with COVID-19 infection in mobile cabin hospitals. The security of over half of the patients surveyed is at the lower or middle level, and psychological capital is an important predictor of the patients' security. Medical staff should actively pay attention to patients with low security and help them to improve their security level and psychological capital.

A systematic review of COVID-19 transport policies and mitigation strategies around the globe

This paper reports a Scopus-based systematic literature review of a wide variety of transportation policies and mitigation strategies that have been conducted around the world to minimize COVID-19 contagion risk in transportation systems. The review offers a representative coverage of countries across all continents of the planet, as well as among representative climate regions - as weather is an important factor to consider. The readership interested in policies and mitigation strategies is expected to involve a wide range of actors, each involving a particular application context; hence, the literature is also characterized by key attributes such as: transportation mode; actor (users, operators, government, industry); jurisdiction (national, provincial, city, neighborhood); and area of application (planning, regulation, operations, research, incentives). An in-depth analysis of the surveyed literature is then reported, focusing first on condensing the literature into 151 distinct policies and strategies, which are subsequently categorized into 25 broad categories that are discussed at length. The compendium and discussion of strategies and policies reported not only provide comprehensive guidelines to inform various courses of action for decision-makers, planners, and social communicators, but also emphasize on future work and the potential of some of these strategies to be the precursors of meaningful, more sustainable behavioral changes in future mobility patterns.

Carpooling in times of crisis: Organizational identification as a safety belt

The purpose of this research is to understand how organizational identification and fear of Covid-19 influence individuals' attitudes, trust, and intention to carpool. For this study, 299 participants completed an online questionnaire in which we assessed their organizational identification, fear of Covid-19, perceived risks, attitude, trust, and intention to carpool. Results show that the relationship between individuals and their organization is an effective lever to promote carpooling. Our results confirm that individuals' trust level and attitude strongly determine carpooling intention. The results highlight a negative relationship between perceived risks and attitude, as well as trust; Covid-19 is also identified as an antecedent to perceived risks. Organizations implementing carpooling solutions should focus on developing organizational identification and address fears associated with Covid-19.

Measuring the customer satisfaction of public transportation in Tehran during the COVID-19 pandemic using MCDM techniques

The expeditiously spreading of coronavirus disease 2019 (COVID-19) has affected every facet of human lives, including transportation. Due to some characteristics of COVID-19, like high infectivity, people prefer to use their private cars more than before. On the one hand, this circumstance caused public transportation to face an unprecedented decrease in demand and, consequently, revenue. On the other hand, it could intensify traffic congestion during rush hours. This study provides a computational framework to assess public transportation's customer satisfaction in Tehran during the COVID-19 pandemic. To this end, a combined multi-criteria decision-making (MCDM) approach based on the best-worst method (BWM) and fuzzy technique for order performance by similarity to ideal solution (fuzzy TOPSIS) is introduced, which benefits from all the advantages of BWM and fuzzy TOPSIS procedure and consequently provides consistent and reliable outcomes. Outcomes of the implemented model provide precious insight for improving service quality during and after the pandemic; for example, it reveals the performance of each transport mode about each criterion which can help policymakers and transit agencies to allocate resources more intelligently. Final results indicate that during the pandemic, taxis had a better performance compared to other transportation modes.

Analysis of factors influencing public employees' work cognition under a public health crisis: A survey of China's response to COVID-19

The work cognition of public employees lays importance on tackling an escalating health crisis situation. At the micro-level and macro-level, different factors contribute to different degrees of public employees' work cognition. However, there are limited studies examining the work cognition of public employees and its influencing factors, particularly in situations such as a public health crisis. Our research takes China's response to COVID-19 as an example. The data have been taken from six Chinese provinces, Hunan, Hubei, Jiangsu, Shanxi, Henan, and Shandong, through a total of 738 questionnaires and telephonic interviews. Furthermore, this study used a logistic multiple regression model to analyze the factors that influenced the public employees' work cognition when working under a public health crisis. The results of our study showed that at a micro-level, the educational background, attitudes, and actions (initiative, responsibility, administrative capacity, and timeliness of feedback), and their level of concern with work influenced the work cognition of the public employees. At a macro-level, we found that it was the anti-epidemic measures that most influenced public employees' work cognition. Our findings provide important policy implications for emergency preparedness and handling of major emergencies, and have important reference value for the management of public employees and the improvement of national governance capabilities under similar major challenges in the future.

Has COVID-19 changed our loyalty towards public transport? Understanding the moderating role of the pandemic in the relationship between service quality, customer satisfaction and loyalty

COVID-19 has been associated with a decline in public transport ridership in many cities. However, the impact of the pandemic on passenger perceptions of public transport, particularly loyalty, has remained largely unexplored. Using a case study of Tehran's bus system, this paper aims to assess the moderating effect of COVID-19 on passenger loyalty. A cross-sectional survey of bus users was conducted in two similar periods, before and during COVID-19. The data was analysed using structural equation modelling, with the effect of observed heterogeneity evaluated using multiple indicators multiple causes models and multi-group analysis. The results indicate that during COVID-19, perceptions of service quality have improved, particularly in relation to comfort (including crowding), safety, reliability and information. While this has led to increased customer satisfaction, loyalty to the system has decreased. An increase in the perceived attractiveness of using private cars was found to be the primary factor for reducing passenger loyalty with the perceived monetary and psychological costs of using cars being less effective in encouraging people to use the bus. Taking into account the significant utility of private vehicles in urban transportation during COVID-19, the present study identifies feasible areas for improving the performance of bus services to increase satisfaction with this form of public transport among car owners.

A systematic review of the impacts of the coronavirus crisis on urban transport: Key lessons learned and prospects for future cities

The COVID-19 pandemic continues to have a significant impact on the transport sector worldwide. Lockdown and physical distancing requirements continue to be enforced in many cities leading to severe travel restrictions and travel demand reduction to limit the spread of the disease. This article provides bibliometric evidence-based insights into how the pandemic has exposed the vulnerability of established public transport systems and shared mobility solutions. It shows how some transport interventions can accelerate the shift to sustainable urban mobility practices such as micro-mobility and active transport. To accomplish this, the article examines recent studies (244 publications) from the Scopus database using a rigorous systematic literature review approach covering the period from January 2020 to February 2021. Importantly, the mapping of bibliographic coupling and co-citation analysis showed four heterogeneous clusters representing research efforts into "environment", "travel behavior and mode choice", "public transport", and "interventions". Inductive reasoning is used to analyze the disruptions that cities have encountered worldwide, the rapid interventions that were put in place, the aftershocks and the short and long-term impacts. Finally, the paper summarizes the lessons learned and opportunities ahead, and the challenges that must be overcome. The article also outlines pathways to build on the momentum of sustainable practices as part of a holistic approach for enabling resilient transport solutions for the new urban world.

Transmission and Cleaning Misconception During the COVID-19 Pandemic Time in Riyadh, Saudi Arabia

OBJECTIVES

 This study aimed to investigate the knowledge and attitude of the public in Saudi Arabia toward the concept of surface decontamination during the COVID-19 pandemic.

METHODS

 A cross-sectional, web-based study was conducted over six months, from February 2021 to July 2021. We included adult Saudi and non-Saudi males and females living in Riyadh, Saudi Arabia.  Results: Six hundred and twenty-six responses from Saudi (92.7%) and non-Saudi (7.3%) participants with a median age of 24 years and interquartile range (IQR) of 21-29 years were received. Regarding knowledge level, 32.10% of the participants had good knowledge of respiratory virus transmission, and only 3.4% had good knowledge of decontamination products. Overall, 58.1% of the participants had a positive attitude toward decontamination products, and 28% had a negative attitude. Older participants, females, and participants who received their information from the Ministry of Health had higher odds of having a positive attitude toward disinfectant (OR = 1.022, 95% CI: 1.004 to 1.039, p = 0.013), (OR = 3.05, 95% CI: 2.08 to 4.47, p < 0.001), and (OR = 2.95, 95% CI: 1.44 to 6.05, p = 0.003), respectively.  Conclusion: The current evidence suggests that the knowledge in the general population of Saudi Arabia is low regarding the transmission of COVID-19 infection and disinfectant products. The prevalence of using decontamination products and attitude toward it is average. Continuous awareness campaigns are required to increase the public's awareness toward such products to change the population's attitude and practice, improve the prevention, and reduce the spread of the infection and its related misconception.

Improving the adherence to COVID-19 preventive measures in the community: Evidence brief for policy

Objectives

To identify evidence-based strategies to improve adherence to the preventive measures against the coronavirus disease (COVID-19) at the community level.

Method

This is an evidence brief for policy, combining research evidence specific to contextual knowledge from stakeholders. A systematic search was performed in 18 electronic databases, gray literature, and a handle search, including only secondary and tertiary studies that focused on the adherence of the general population to COVID-19 preventive measures in the community. Two reviewers, independently, performed the study selection, data extraction, and assessment of the quality of the studies. Relevant evidence has been synthesized to draft evidence-based strategies to improve adherence. These strategies were circulated for external endorsement by stakeholders and final refinement. Endorsement rates >80%, 60-80% and <60% were considered high, moderate, and low respectively.

Results

Eleven studies, with varying methodological qualities were included: high (n = 3), moderate (n = 3), low (n = 1), and critically low (n = 4). Three evidence based strategies were identified: i. Risk communication; ii. Health education to the general public, and iii. Financial support and access to essential supplies and services. The rates of endorsement were: 83% for risk communication, 83% for health education, and 92% for financial support and access to essential supplies and services. The evidence showed that an increase in knowledge, transparent communication, and public awareness about the risks of COVID-19 and the benefits of adopting preventive measures results in changes in people's attitudes and behavior, which can increase adherence. In addition, the guarantee of support and assistance provides conditions for people to adopt and sustain such measures.

Conclusions

These strategies can guide future actions and the formulation of public policies to improve adherence to preventive measures in the community during the current COVID-19 pandemic and other epidemics.

Impacts of COVID-19 Travel Restriction Policies on the Traffic Quality of the National and Provincial Trunk Highway Network: A Case Study of Shaanxi Province

According to recent research, the COVID-19 pandemic has impacted road traffic quality. This study aims to analyze the impacts of COVID-19 travel restriction policies on the traffic quality of the national and provincial trunk highway network (NPTHN) in Shaanxi Province. We collected the traffic data of the NPTHN for three consecutive years (from 2019 to 2021), before and after the COVID-19 outbreak, including weekly average daily traffic, weekly traffic interruption times, weekly traffic control time, weekly traffic accidents, weekly traffic injuries, and weekly traffic deaths. Using descriptive statistics and dynamic analysis methods, we studied the safety and service levels of the NPTHN. We set up an assessment model of the NPTHN operational orderliness through dissipative structure theory and entropy theory to study the operational orderliness of the NPTHN. Results show that in 2020, the service level, safety level, and operational orderliness of the NPTHN dropped to the lowest levels. The pandemic was gradually brought under control, and the travel restriction policies were gradually reduced and lifted. The adverse impacts on the operational orderliness of the NPTHN decreased, but the operational orderliness did not yet recover to the pre-pandemic level. Meanwhile, the service and safety levels of the NPTHN did not recover. Taken together, the COVID-19 travel restriction policies had adverse impacts on the traffic quality of the NPTHN in Shaanxi Province.

Intentions to use ride-sourcing services in Vietnam: What happens after three months without COVID-19 infections?

The COVID-19 pandemic has brought new risks and stress for paid transport users worldwide. COVID-19 has changed mobility dynamics worldwide, including low- and middle-income countries (e.g., Vietnam). The present study aims to provide an in-depth understanding of ride-sourcing passengers' behavioural intentions when COVID-19 pandemic management successfully prevented community transmission by extending the TPB with two constructs: perceived virus infection risk and problem-focused coping. Using self-administered questionnaires, data were collected from ride-sourcing customers in Ho Chi Minh City (Vietnam). A total of 540 responses were used for validating the proposed theorethical model. The structural equation model results indicate that problem-focused coping is a multi-faceted construct with two dimensions: problem-solving and self-protection. Also, problem-focused coping has the highest total effect on the intention to use ride-sourcing services following a period of COVID-19 suppression (3 months without identified cases). The findings also reveal that attitude partially mediates the link between problem-focused coping and behavioural intention. The results of this study could be used to develop strategies to promote ride-sourcing services in the aftermath of the COVID-19 pandemic.

Satisfaction differences in bus traveling among low-income individuals before and after COVID-19

Although all cities in China have promulgated public transportation control measures to choke off the spread of COVID-19, it also has brought severe changes to low-income individuals' bus traveling. However, the study focusing on satisfaction differences in bus traveling before and after COVID-19 is far under-researched, this paper therefore explored satisfaction differences among low-income individuals under socioeconomic attributes, traveling attributes, and psychological attributes by using the data consist of interviews addressed to 930 individuals in Taiyuan, China. Furthermore, the relationship between satisfaction levels and modes of traveling alone and traveling with companions by bus has also been deeply analyzed to reduce single-person driving problem. As a result, many exciting phenomena were discovered: the significant factors affecting low-income individuals' satisfaction occur "shift" on a large scale after COVID-19; risk concern has a significant positive impact on risk perception, but risk concern and risk perception have only a minor impact on satisfaction before and after COVID-19; it was found that there is a significant relationship between satisfaction levels and modes of traveling alone and traveling with companions by bus. Understanding them can be a reference for improving the travel environment between low-income individuals.

Analysis of the Impacts on the Psychological Changes of Chinese Returning College Students After the Outbreak of the 2019 Coronavirus Disease

This work aims to analyze the impacts on the psychological changes of Chinese returning college students after the outbreak of the 2019 coronavirus disease (COVID-19). A questionnaire survey is used to take 1,482 college students who returned to school after the epidemic as the research objects. The Chinese college students' knowledge of the epidemic, alienation in physical education class, school happiness, and expectations for a healthy life in the future are investigated and analyzed. The research results manifest that Chinese returning college students have relatively poor awareness of COVID-19, and the overall degree of alienation in physical education classes after the epidemic is low, with an average score of 3.55 ± 1.018. The overall level of school happiness is high, with an average score of 4.94 ± 0.883; the overall level of expectation for a healthy life in the future is high, with an average score of 3.50 ± 0.840. It denotes that the epidemic has a great psychological impact on returning college students, and it is necessary to strengthen mental health education for college students after COVID-19. It provides a sustainable theoretical reference for the formulation of psychological intervention measures for returning college students.

Impact of the COVID-19 Epidemic on Population Mobility Networks in the Beijing–Tianjin–Hebei Urban Agglomeration from a Resilience Perspective

As an important symbol and carrier of regional social and economic activities, population mobility is a vital force to promote the re-agglomeration and diffusion of social and economic factors. An accurate and timely grasp on the impact of the COVID-19 epidemic on population mobility between cities is of great significance for promoting epidemic prevention and control and economic and social development. This study proposes a theoretical framework for resilience assessment, using centrality and nodality, hierarchy and matching, cluster, transmission, and diversity to measure the impact of the COVID-19 epidemic on population mobility in the Beijing–Tianjin–Hebei (BTH) urban agglomeration in 2020–2022, based on the migration data of AutoNavi and social network analysis. The results show that the COVID-19 epidemic had different impacts on the population network resilience of the BTH urban agglomeration based on the scale and timing. During the full-scale outbreak of the epidemic, strict epidemic prevention and control measures were introduced. The measures, such as social distancing and city and road closure, significantly reduced population mobility in the BTH urban agglomeration, and population mobility between cities decreased sharply. The population mobility network’s cluster, transmission, and diversity decreased significantly, severely testing the network resilience. Due to the refinement of the epidemic control measures over time, when a single urban node was impacted, the urban node did not completely fail, and consequently it had little impact on the overall cluster, transmission, and diversity of the population mobility network. Urban nodes at different levels of the population mobility network were not equally affected by the COVID-19 epidemic. The findings can make references for the coordination of epidemic control measures and urban development. It also provides a new perspective for the study of network resilience, and provides scientific data support and a theoretical basis for improving the resilience of BTH urban agglomeration and promoting collaborative development.

Spatio-Temporal Heterogeneity of the Relationships Between PM2.5 and Its Determinants: A Case Study of Chinese Cities in Winter of 2020

Fine particulate matter (PM2.5) poses threat to human health in China, particularly in winter. The pandemic of coronavirus disease 2019 (COVID-19) led to a series of strict control measures in Chinese cities, resulting in a short-term significant improvement in air quality. This is a perfect case to explore driving factors affecting the PM2.5 distributions in Chinese cities, thus helping form better policies for future PM2.5 mitigation. Based on panel data of 332 cities, we analyzed the function of natural and anthropogenic factors to PM2.5 pollution by applying the geographically and temporally weighted regression (GTWR) model. We found that the PM2.5 concentration of 84.3% of cities decreased after lockdown. Spatially, in the winter of 2020, cities with high PM2.5 concentrations were mainly distributed in Northeast China, the North China Plain and the Tarim Basin. Higher temperature, wind speed and relative humidity were easier to promote haze pollution in northwest of the country, where enhanced surface pressure decreased PM2.5 concentrations. Furthermore, the intensity of trip activities (ITAs) had a significant positive effect on PM2.5 pollution in Northwest and Central China. The number of daily pollutant operating vents of key polluting enterprises in the industrial sector (VOI) in northern cities was positively correlated with the PM2.5 concentration; inversely, the number of daily pollutant operating vents of key polluting enterprises in the power sector (VOP) imposed a negative effect on the PM2.5 concentration in these regions. This work provides some implications for regional air quality improvement policies of Chinese cities in wintertime.

Nudging physical distancing behaviors during the pandemic: a field experiment on passengers in the subway stations of shiraz, Iran

Background

The possibility of the emergence of new pandemics necessitates further research into using simple strategies to promote social distancing behaviors in public. Most of the current evidence on effectiveness of physical distancing interventions is based on self-report and measure of intention which will not necessarily predict actual behavior.

Methods

A field experimental study was conducted in the subway stations of Shiraz, Southern Iran. The interventions were based on intuitions from protection motivation theory and consisted of using environmental nudges to notify the passengers of the pandemic situation (threat appeal) and a verbal advice on keeping a safe physical distance as an effective method of protection against COVID-19 (coping message). Average physical distancing was estimated as the number of steps between two consecutive passengers and was compared between interventions (n = 1045) and the control (n = 855) groups.

Results

A total of 1900 people riding on subway escalators were directly observed during two intervention conditions and the control condition. Under either threat or coping-based interventions, passengers were two times more likely (OR 2.0, 95%CI 1.5–2.7, P <  0.001) to keep a physical distance of at least 1.2 m from the traveler in front compared with those who did receive no intervention. The Kruskal-Wallis test revealed that there was a significant improvement in physical distancing behaviors with coping advice compared with threat appeal and the control conditions (χ2 = 120.84, df = 2, p <  0.001).

Conclusions

Our findings suggest that simple and inexpensive theory-based interventions can be used in crowded public spaces to promote physical distancing within the context of the pandemic.

A knowledge graph-based method for epidemic contact tracing in public transportation

Contact tracing is an effective measure by which to prevent further infections in public transportation systems. Considering the large number of people infected during the COVID-19 pandemic, digital contact tracing is expected to be quicker and more effective than traditional manual contact tracing, which is slow and labor-intensive. In this study, we introduce a knowledge graph-based framework for fusing multi-source data from public transportation systems to construct contact networks, design algorithms to model epidemic spread, and verify the validity of an effective digital contact tracing method. In particular, we take advantage of the trip chaining model to integrate multi-source public transportation data to construct a knowledge graph. A contact network is then extracted from the constructed knowledge graph, and a breadth-first search algorithm is developed to efficiently trace infected passengers in the contact network. The proposed framework and algorithms are validated by a case study using smart card transaction data from transit systems in Xiamen, China. We show that the knowledge graph provides an efficient framework for contact tracing with the reconstructed contact network, and the average positive tracing rate is over 96%.

The Impact of COVID-19 Pandemic on Halting Sustainable Development in the Colca y Volcanes de Andagua UNESCO Global Geopark in Peru—Prospects and Future

Events, such as the COVID-19 pandemic, that rapidly impact global communication and travel have significant consequences for the tourism industry, which is one of the pillars of global development. We assess the impacts of the COVID-19 crisis on the Colca y Volcanes de Andagua UNESCO Global Geopark in Peru. The Colca y Volcanes de Andagua Geopark was established immediately prior to the pandemic in October 2019. The instability of the government in Peru during the pandemic and the difficult living conditions in the high Andes, such as the lack of drinking water, cleaning agents, medical care, and the high levels of poverty, particularly in the geopark region, has contributed to the significantly high COVID-19 infection rates. In addition, detrimental impacts faced by the local community are a direct result of a reduction in travellers to the area due to legislative restrictions, which have had negative consequences on the local tourism industry. There is an urgent need for the recovery of the local tourism industry to prevent the permanent closure of tourism facilities and to minimise poverty rates.