The Predictive Capacity of Air Travel Patterns During the Global Spread of the COVID-19 Pandemic: Risk, Uncertainty and Randomness

Assessment of epidemic risk state and its change trend of public hospital in underdeveloped area in different stages

Objective

Epidemics are sudden and rapidly spreading. Hospitals in underdeveloped areas are particularly vulnerable in case of an outbreak. This paper aims to assess the epidemic risk state and its change trend of hospitals in different epidemic stages, identify the key factors affecting hospital epidemic risk change, provide priority reference for hospital epidemic risk control, and enhance the hospital's ability to respond to sudden epidemics.

Methods

Based on Grounded theory, the epidemic risk indicators that affect hospital safety are summarized. The concept of epidemic risk state and its random state space is proposed according to Markov chain theory. The impact of each indicator on the random risk state and its change is comprehensively assessed from two aspects: risk occurrence probability and risk loss. Finally, the assessment of the hospital epidemic risk state and its change at different stages is achieved.

Results

The stable risk states of public hospitals in underdeveloped areas in non-epidemic stage t0, early epidemic stage t1, and outbreak stage t2 areP ^ t 0 ( S n ) = { 0 . 142 , 0 . 546 , 0 . 220 , 0 . 093 } ,P ^ t 1 ( S n ) = { 0 . 025 , 0 . 364 , 0 . 254 , 0 . 357 } , andP ^ t 2 ( S n ) = { 0 . 020 , 0 . 241 , 0 . 191 , 0 . 548 } , respectively. In non-epidemic stage, the key factor in improving the hospital epidemic risk state is emergency funding. In early epidemic stage, the key factors in improving the hospital epidemic risk state are the training of medical staff in epidemic prevention skills and the management of public health. In outbreak state, the key factor in improving the hospital epidemic risk state is the training of medical staff in epidemic prevention skills and psychological awareness.

Conclusion

This paper proposes the concept of epidemic risk state, providing an effective assessment method for the epidemic risk state and its change trend in public hospitals. According to the assessment, public hospitals in underdeveloped areas in different epidemic stages should adopt different risk control strategies to improve their current risk state. Blind risk control is inefficient and may even cause the epidemic risk to transition toward a more dangerous state.

What can we learn from severity index on flight data monitoring? Analysis of safety resilience in flight operations during COVID-19 disruptions

The unexpected spread of the pandemic raised concerns regarding pilots' skill decay resulting from the significant drops in the frequency of flights by about 70%. This research retrieved 4761 Flight Data Monitoring (FDM) occurrences based on the FDM programme containing 123,140 flights operated by an international airline between June 2019 and May 2021. The FDM severity index was analysed by event category, aircraft type, and flight phase. The results demonstrate an increase in severity score from the pre-pandemic level to the pandemic onset on events that occurred on different flight phases. This trend is not present in the third stage, which indicates that pilots and the safety management system of the airline demonstrated resilience to cope with the flight disruptions during the pandemic. Through the analysis of event severity, FDM enables safety managers to recommend measures to increase safety resilience and self-monitoring capabilities of both operators and regulators.Practitioner summary: The onset of the pandemic led to a rise in the severity of flight data monitoring events in a large airline, likely linked to a lack of operational practice and skills decay. This was demonstrated across different flight phases and aircraft types. In the settled pandemic period, the severity index returned to pre-pandemic levels, indicating that the resilience of individual pilots and safety management systems is critical to operational safety.HIGHLIGHTSThe FDM event severity scores significantly increased following the pandemic onset, especially for event categories involving pilot core competencies.The FDM event severity scores stagnated or decreased during the later pandemic stage indicating resilience among the airline pilots and the airline's safety management system.The airline and pilots demonstrated resilience by effectively mitigating the effects of proficiency decay which took place as the pandemic started.FDM analysis has shown to be effective in establishing a proactive SMS programme to mitigate the negative impacts of the pandemic on aviation safety.

Assessing self-reported public health emergency competencies for civil aviation personnel in China: a pilot study

INTRODUCTION

COVID-19 has demonstrated the importance of competent staff with expertise in public health emergency preparedness and response in the civil aviation system. The civil aviation system is a critical sentinel and checkpoint to prevent imported cases and slow the spread of communicable diseases. Understanding the current competencies of staff to deal with public health emergencies will help government agencies develop targeted training and evidence-based policies to improve their public health preparedness and response capabilities.

METHODS

This cross-sectional pilot study was conducted from November 2022 to October 2023, involving 118 staff members from various positions within China's civil aviation system. A 59-item questionnaire was translated and developed according to a competency profile. Data were collected using the self-report questionnaire to measure the workforce's self-perceptions of knowledge and skills associated with public health emergency proficiency, categorized into (1) general competency, (2) preparedness competency, (3) response competency, and (4) recovery competency. KMO & Bartlett test and Cronbach's α reliability analysis were used to test the reliability and validity of the questionnaire. Descriptive statistics, independent sample T-test, ANOVA, and linear regression models were performed to analyze the competencies.

RESULTS

A total of 107 staff members from the aviation system were surveyed in this study. The KMO & Bartlett test, (KMO = 0.919, P < 0.001) and Cronbach's α coefficients (α = 0.985) for this questionnaire were acceptable. The results suggested that respondents scored a mean of 6.48 out of 9 for the single question. However, the staff needed to acquire more knowledge in investigating epidemic information (5.92) and case managing (5.91) in the response stage. Overall, males scored higher (409.05 ± 81.39) than females (367.99 ± 84.97), with scores in the medical department (445.67 ± 72.01) higher than management (387.00 ± 70.87) and general department (362.32 ± 86.93). Additionally, those with completely subjective evaluation (425.79 ± 88.10) scored higher than the general group (374.39 ± 79.91). To predict the total score, female medical workers were more likely to have lower scores (β = -34.5, P = 0.041). Compared with those in the medical department, the management workers (β = -65.54, P = 0.008) and general workers (β = -78.06, P < 0.001) were associated with a lower total score.

CONCLUSIONS

There was still a gap between the public health emergency competencies of the civil aviation system and the demand. Staff in China's civil aviation systems demonstrated overall competence in public health emergency preparedness and response. However, there was a need to enhance the accumulation of practical experience. Implementing effective training programs for public health emergencies was recommended to mitigate knowledge gaps. Meanwhile, regular training evaluations were also recommended to give comprehensive feedback on the value of the training programs.

Inferring country-specific import risk of diseases from the world air transportation network

Disease propagation between countries strongly depends on their effective distance, a measure derived from the world air transportation network (WAN). It reduces the complex spreading patterns of a pandemic to a wave-like propagation from the outbreak country, establishing a linear relationship to the arrival time of the unmitigated spread of a disease. However, in the early stages of an outbreak, what concerns decision-makers in countries is understanding the relative risk of active cases arriving in their country-essentially, the likelihood that an active case boarding an airplane at the outbreak location will reach them. While there are data-fitted models available to estimate these risks, accurate mechanistic, parameter-free models are still lacking. Therefore, we introduce the 'import risk' model in this study, which defines import probabilities using the effective-distance framework. The model assumes that airline passengers are distributed along the shortest path tree that starts at the outbreak's origin. In combination with a random walk, we account for all possible paths, thus inferring predominant connecting flights. Our model outperforms other mobility models, such as the radiation and gravity model with varying distance types, and it improves further if additional geographic information is included. The import risk model's precision increases for countries with stronger connections within the WAN, and it reveals a geographic distance dependence that implies a pull- rather than a push-dynamic in the distribution process.

Investigating the impacts of COVID-19 on aviation safety based on occurrences captured through flight data monitoring

The COVID-19 pandemic led to growing concerns about pilots' proficiency due to the significant decrease in flight operations. The objective of this research is to provide a proactive approach to mitigate potential risks in flight operations associated with the impact of the COVID-19 pandemic using flight data monitoring (FDM). The results demonstrated significant associations between the pandemic impacts and FDM exceedance categories, flight phases and fleets. Manual flying skill decay, lack of practice effects on use of standard operating procedures and knowledge of flight deck automation should be considered by airlines when preparing for the return to normal operations. An FDM Programme allows prediction of the probability and severity of occurrences for developing an effective SMS within an airline. To mitigate the impacts of the pandemic, tailored training sessions must be implemented, and airlines should strive to avoid additional optional procedures where practicable. Practitioner summary: The COVID-19 pandemic has raised concerns regarding pilot proficiency due to lack of practice effects. Results from the Flight Data Monitoring Programme show significant associations between the pandemic impacts and occurrence categories, fleets, and flight phases. FDM can be applied to mitigate the probability and severity of occurrences for airlines developing effective safety management systems.HIGHLIGHTSThere is a significant association between the COVID-19 pandemic stages and FDM events in different flight phases, FDM categories, and aircraft typesThe COVID-19 pandemic led to a significant increase in FDM exceedances, especially for precursors on runway excursion and go-aroundsAirlines should carefully plan training sessions for pilots as the disruptions due to the pandemic led to a lack of practice effect in flight operationsReviewing FDM data may have contributions to establish proactive SMS and mitigate COVID-19 impacts to aviation safety.

Urban public health emergencies and the COVID-19 pandemic. Part 1: Social and spatial inequalities in the COVID-city

COVID-19 has had unprecedented impacts on urban life on a global scale, representing the worst pandemic in living memory. In this introduction to the first of two parts of a Special Issue on urban public health emergencies, we suggest that the COVID-19 outbreak, and associated attempts to manage the pandemic, reproduced and ultimately exacerbated the social and spatial divides that striate the contemporary city. Here, we draw on evidence from the papers in Part 1 of the Special Issue to summarise the uneven urban geographies of COVID-19 evident at the inter- and intra-urban level, emphasising the particular vulnerabilities and risks borne by racialised workers who found it difficult to practise social distancing in either their home or working life. Considering the interplay of environmental, social and biological factors that conspired to create hotspots of COVID-19 infection, and the way these are connected to the racialised capitalism that underpins contemporary urban development, this introduction suggests that reflection on public health emergencies in the city is not just essential from a policy perspective but helps enrich theoretical debates on the nature of contemporary urbanisation in its 'planetary' guise.

Airline strategies during the pandemic: What worked?

An examination is conducted of airline strategies during the covid-19 pandemic using data from the United States. Our findings show that airlines pursued diverse strategies in terms of route entry and retention, pricing, and load factors. At the route level, a more detailed examination is conducted of the performance of a middle-seat blocking strategy designed to increase the safety of air travel. We show that this strategy (i.e., not making middle seats available to passengers) likely resulted in revenue losses for carriers, an estimated US $3,300 per flight. This revenue loss provides an indication as to why the middle seat blocking strategy was discontinued by all US airlines despite ongoing safety concerns.

Scenarios for a post-COVID-19 world airline network

The airline industry was severely hit by the COVID-19 crisis with an average demand decrease of about 64 % (IATA, April 2020), which triggered already several bankruptcies of airline companies all over the world. While the robustness of the world airline network (WAN) was mostly studied as a homogeneous network, we introduce a new tool for analyzing the impact of a company failure: the "airline company network" where two airlines are connected if they share at least one route segment. Using this tool, we observe that the failure of companies well connected with others has the largest impact on the connectivity of the WAN. We then explore how the global demand reduction affects airlines differently and provide an analysis of different scenarios if it stays low and does not come back to its pre-crisis level. Using traffic data from the Official Aviation Guide and simple assumptions about customer's airline choice strategies, we find that the local effective demand can be much lower than the average one, especially for companies that are not monopolistic and share their segments with larger companies. Even if the average demand comes back to 60 % of the total capacity, we find that between 46 % and 59 % of the companies could experience a reduction of more than 50 % of their traffic, depending on the type of competitive advantage that drives customer's airline choice. These results highlight how the complex competitive structure of the WAN weakens its robustness when facing such a large crisis.

COVID-19 public transit precautions: Trade-offs between risk reduction and costs

Public transit has received scrutiny as a vector for spreading COVID-19 with much of the literature finding correlations between transit ridership and COVID-19 rates by assessing the role that transportation plays as a vector for human mobility in COVID-19 spread. However, most studies do not directly measure the risk of contracting COVID-19 inside the public transit vehicle. We fill a gap in the literature by comparing the risk and social costs across several modes of transportation. We develop a framework to estimate the spread of COVID-19 on transit using the bus system in Pittsburgh. We find that some trips have demand that exceed their COVID-19 passenger limit, where the driver must decide between: (1) leaving a passenger without a ride or (2) allowing them on the bus and increasing COVID-19 risk. We consider five alternatives for alleviating overcapacity: allow crowding, additional buses, longer buses as substitutes, Transportation Network Company (TNC) rides, or Autonomous Vehicles (AVs) for passed-by passengers. We use transit ridership and COVID-19 data from the spring of 2020 by combining transportation data and an epidemiological model of COVID-19 stochastically in a Monte Carlo Analysis. Our results show that 4% of county cases were contracted on the bus or from a bus rider, and a disproportionate amount (52%) were from overcapacity trips. The risk of contracting COVID-19 on the bus was low but worth mitigating. A cost-benefit analysis reveals that dispatching AVs or longer buses yield the lowest societal costs of $45 and $46 million, respectively compared to allowing crowding ($59 million).

A numerical study of COVID-19-laden droplets dispersion in aircraft cabin ventilation system

Ventilation systems for aircraft cabins are mainly used to maintain a comfortable environment in the cabin and ensure the health of passengers. This study evaluates the decontamination performance of two cabin ventilation systems, the displacement ventilation (DV) system and the mixing ventilation (MV) system, in preventing contamination by virus (COVID-19)-laden droplets. The Euler-Lagrange method was used to computationally model droplet dispersion of different diameters and their behavior in the two systems was contrastively analyzed. Statistics on droplet suspension ratios and duration as well as the infection probability of each passenger were also computed. It was found that11.07% fewer droplet remained suspended in the DV system were than those in the MV system 10s from droplet release. In addition, the number of droplets extracted from the exhausts in the DV system was 13.15% more than the MV system at the 400s mark. In the DV system, higher ambient wind velocities were also found to locally increase infection probability for passengers in certain locations.

Predictive analytics of COVID-19 cases and tourist arrivals in ASEAN based on covid-19 cases

Purpose

Research into predictive analytics, which helps predict future values using historical data, is crucial. In order to foresee future instances of COVID-19, a method based on the Seasonal ARIMA (SARIMA) model is proposed here. Additionally, the suggested model is able to predict tourist arrivals in the tourism business by factoring in COVID-19 during the pandemic. In this paper, we present a model that uses time-series analysis to predict the impact of a pandemic event, in this case the spread of the Coronavirus pandemic (Covid-19).

Methods

The proposed approach outperformed the Autoregressive Integrated Moving Average (ARIMA) and Holt Winters models in all experiments for forecasting future values using COVID-19 and tourism datasets, with the lowest mean absolute error (MAE), mean absolute percentage error (MAPE), mean squared error (MSE), and root mean squared error (RMSE). The SARIMA model predicts COVID-19 and tourist arrivals with and without the COVID-19 pandemic with less than 5% MAPE error.

Results

The suggested method provides a dashboard that shows COVID-19 and tourism-related information to end users. The suggested tool can be deployed in the healthcare, tourism, and government sectors to monitor the number of COVID-19 cases and determine the correlation between COVID-19 cases and tourism.

Conclusion

Management in the tourism industries and stakeholders are expected to benefit from this study in making decisions about whether or not to keep funding a given tourism business. The datasets, codes, and all the experiments are available for further research, and details are included in the appendix.

The impact of air travel on the precocity and severity of COVID-19 deaths in sub-national areas across 45 countries

Human travel fed the worldwide spread of COVID-19, but it remains unclear whether the volume of incoming air passengers and the centrality of airports in the global airline network made some regions more vulnerable to earlier and higher mortality. We assess whether the precocity and severity of COVID-19 deaths were contingent on these measures of air travel intensity, adjusting for differences in local non-pharmaceutical interventions and pre-pandemic structural characteristics of 502 sub-national areas on five continents in April-October 2020. Ordinary least squares (OLS) models of precocity (i.e., the timing of the 1st and 10th death outbreaks) reveal that neither airport centrality nor the volume of incoming passengers are impactful once we consider pre-pandemic demographic characteristics of the areas. We assess severity (i.e., the weekly death incidence of COVID-19) through the estimation of a generalized linear mixed model, employing a negative binomial link function. Results suggest that COVID-19 death incidence was insensitive to airport centrality, with no substantial changes over time. Higher air passenger volume tends to coincide with more COVID-19 deaths, but this relation weakened as the pandemic proceeded. Different models prove that either the lack of airports in a region or total travel bans did reduce mortality significantly. We conclude that COVID-19 importation through air travel followed a 'travel as spark' principle, whereby the absence of air travel reduced epidemic risk drastically. However, once some travel occurred, its impact on the severity of the pandemic was only in part associated with the number of incoming passengers, and not at all with the position of airports in the global network of airline connections.

The effects of air transport mobility and global connectivity on viral transmission: Lessons learned from Covid-19 and its variants

We investigate the impact of air travel mobility and global connectivity on viral transmission by tracing the announced arrival time of COVID-19 and its major variants in countries around the world. We find that air travel intensity to a country, "effective distance" as measured by international air traffic, is generally a significant predictor for the announced viral arrival time. The level of healthcare infrastructure in a country is less important at predicting the initial transmission and detection time of a virus. A policy variable, notably the percentage reduction of total inbound seats in response to a viral outbreak, is largely ineffective at delaying viral transmission and discovery time. These findings suggest that air network connectivity is a major contributor to the speed of viral transmission. However, government attempts to delay viral transmission by reducing air network connectivity after the virus is first discovered are largely ineffective.

Examining COVID-19-triggered changes in spatial connectivity patterns in the European air transport network up to June 2021

The integrity of international supply chain operations heavily relies on air transport services to facilitate the movement of goods and enable human interactions between its stakeholders. With the outbreak of COVID-19 in Europe around March 2020, air transport networks have been subject to profound alterations. Although the link between variations in air transport service levels and changes in user costs for network-wide travel has been analysed extensively, few studies have examined the extent to which severe network shrinkage events lead to a reduction in network connectivity, which is therefore difficult to predict. This paper investigates how the COVID-19 pandemic has structurally altered the European air transport network in 2020/21 and how these changes have deteriorated users' ease when utilising network-wide air transport services. To do this, the paper estimates the change in average quickest path length at the airport level during different stages of this period. Results indicate there is strong heterogeneity in airports' susceptibility to pandemic-induced network changes, with both regional variations and variations in the airline type serving individual airports. Furthermore, topological features of individual airports are found to determine airport susceptibility. The findings are discussed in terms of their implications for locational decisions in supply chain designs.

Relationship between the Chinese Main Air Transport Network and COVID-19 Pandemic Transmission

The COVID-19 pandemic had an unprecedented impact on the civil aviation passenger transport industry. This study analyzes the scale change and spatial distribution of the Chinese main air transport network (CMATN) and its role in the early spread of the pandemic using a complex network analysis method and econometric model. The result shows that CMATN is mainly located in the economically developed and densely populated central and eastern regions of China. The normalized degree, closeness, and betweenness centralities of CMATN node cities show an overall increasing trend, indicating that the air transport network is constantly improving. There was a significant positive relationship between the centrality of node cities, the duration of the COVID-19 pandemic, and the number of confirmed cases, indicating that air transport networks were crucial in the pandemic’s early spread. Furthermore, social and economic variables such as GDP and population had a significant positive impact on the duration of the pandemic, indicating that higher levels of social and economic development increased the seriousness of the pandemic. Our findings are expected to supplement existing research and serve as a point of reference for pandemic prevention and control.

COVID-19 Vulnerability Mapping of Asian Countries

OBJECTIVE

The objective of this study is to map vulnerability of Asian countries to the COVID-19 pandemic.

METHOD

According to the Intergovernmental Panel on Climate Change (IPCC) 2007 framework for natural hazards, vulnerability is a function of exposure, sensitivity, and adaptive capacity. From an extensive literature review, we identified 16 socioeconomic, meteorological, environmental, and health factors that influence coronavirus disease 2019 (COVID-19) cases and deaths. The underlying factors of vulnerability were identified using principal component analysis.

RESULTS

Our findings indicate that the percentage of the urban population, obesity rate, air connectivity, and the population aged 65 and over, diabetes prevalence, and PM_2.5 levels all contributed significantly to COVID-19 sensitivity. Subsequently, governance effectiveness, human development index (HDI), vaccination rate, and life expectancy at birth, and gross domestic product (GDP) all had a positive effect on adaptive capacity. The estimated vulnerability was corroborated by a Pearson correlation of 0.615 between death per million population and vulnerability.

CONCLUSION

This study demonstrates the application of universal indicators for assessing pandemic vulnerability for informed policy interventions such as the COVAX vaccine roll-out priority. Despite data limitations and a lack of spatiotemporal analysis, this study's methodological framework allows for ample data incorporation and replication.

Air transportation as a puzzle piece of COVID-19 in Africa?

COVID-19 has hit our society hard, with more than 242 million cases reported worldwide and more than 4.9 million directly related fatalities. The role of Africa throughout the pandemic has been puzzling, since the African continent seems to have gone through the pandemic better than other continents; clearly better than predicted by the public during the emergence of COVID-19 one year ago. While several factors have been proposed in the literature to explain the unexpected role of Africa, including a relatively young population, more historical-driven preparedness to other types of coronavirus and diseases, and a limited amount of testing, the puzzle is not considered to be solved. In this study, we aim to answer the question whether air transportation indicators can support us in explaining the evolution of COVID-19 in Africa? Using flight data for the year 2020, we explore how changes in the air transportation system correlate with evolution of epidemiological indicators. Our results suggest that air transportation could indeed play a critical role for the spread of COVID-19 in Africa as well. Overall, we hope that our analysis contributes towards a better understanding of COVID-19 and the role air transportation plays in an under-researched region of the world.

The Impact of COVID-19 Pandemic on Air Transport Passenger Markets-Implications for Selected EU Airports Based on Time Series Models Analysis

The COVID-19 pandemic caused a drastic reduction in air traffic passengers, especially during the period when the EU countries introduced a lockdown. Even after the relaunch of airline operators, passenger traffic did not return to the pre-pandemic trend. The aim of the study was to estimate the difference between the demand that was observed during the pandemic, and the demand that was forecast based on the pre-pandemic trend. The calculations were made for airports in selected EU countries. The first method was seasonality indicators, using quarterly data for 2015–2021. In the multiplicative model of seasonal fluctuations, the method of determining the seasonality indicators was used, based on the quotient of empirical values and the value of the trend. The one-name period trend method was used in the next step, then Fourier spectral analysis was applied. In the context of forecasts for the individual quarters of 2020 and 2021, all models indicate a further growing trend in the demand for passenger transport, which could have been observed if the COVID-19 pandemic had not occurred. As a result of the pandemic, the number of passengers handled at airports has significantly decreased. In the third quarter of 2021, freight growth was already noticeable, with the exception of Netherland, where a marked decline was recorded.

Epidemiological geography at work: An exploratory review about the overall findings of spatial analysis applied to the study of CoViD-19 propagation along the first pandemic year

The present work aims to give an overview on the international scientific papers related to the territorial spreading of SARS-CoV-2, with a specific focus upon applied quantitative geography and territorial analysis, to define a general structure for epidemiological geography research. The target publications were based on GIS spatial analysis, both in the sense of topological analysis and descriptive statistics or lato sensu geographical approaches. The first basic purpose was to organize and enhance the vast knowledge developments generated hitherto by the first pandemic that was studied "on-the-fly" all over the world. The consequent target was to investigate to what extent researchers in geography were able to draw scientifically consistent conclusions about the pandemic evolution, as well as whether wider generalizations could be reasonably claimed. This implied an analysis and a comparison of their findings. Finally, we tested what geographic approaches can say about the pandemic and whether a reliable spatial analysis routine for mapping infectious diseases could be extrapolated. We selected papers proposed for publication during 2020 and 209 articles complied with our parameters of query. The articles were divided in seven categories to enhance existing commonalities. In some cases, converging conclusions were extracted, and generalizations were derived. In other cases, contrasting or inconsistent findings were found, and possible explanations were provided. From the results of our survey, we extrapolated a routine for the production of epidemiological geography analyses, we highlighted the different steps of investigation that were attained, and we underlined the most critical nodes of the methodology. Our findings may help to point out what are the most critical conceptual challenges of epidemiological mapping, and where it might improve to engender informed conclusions and aware outcomes.

Regional mobility during the Covid-19 pandemic: Analysis of trends and repercussions using mobile phones data across the EU

The analysis of mobile phones data at regional level in the EU reveals varying patterns in mobility trends during the Covid-19 pandemic. These depend on the temporal evolution of the pandemic in each EU Member State, the measures taken at local or national level to limit the growth of the pandemic, as well as the level of urbanization and type of economic activity in each region. During the first phase of the pandemic (March- April 2020) the decrease in mobility was in general uniform among regions in the same Member State, especially in Italy, Spain and France, where national level measures were adopted. A relaxation of the measures and a resulting rebound of mobility was evident during the summer period (July- August 2020). At the same time, a shift from urban to rural areas during the summer vacation period is evident, with especially touristic areas increasing the number of movements in the same Member State. The variance in mobility trends during the second wave of the pandemic (October- November 2020) was higher, a result of the predominantly local and regional level measures applied in each Member State. Those insights suggest a certain correlation between the level of mobility and the evolution of the pandemic at regional level. The association with high levels of Covid-19 prevalence is particularly strong in urban regions with high mobility levels.

The COVID-19 pandemic and the "Plague of Athens": comparable features 25 centuries apart

Motivated by the up to now disastrous outcomes of the COVID-19 pandemic, we attempted a flashback to the so-called "Plague of Athens," which indicated a serious contagious disease, having taken place between 430 and 426 BC. The ancient pandemic was meticulously described by the Athenian historian and general Thucydides. We compared, as much as possible, the following parameters: background conditions, spreading of the pandemics, preceded and concurrent adverse events, duration and waves of the pandemics, symptoms, implicated infectious agents/diseases and mental/psychosocial consequences. The current pandemic was preceded by a global economic crisis, which particularly affected deprived population groups, while the ancient one started on the second year of a catastrophic civil war. Rivalry and different political systems between now (US/China) and then (Athens/Sparta) superpowers were the basis for conspiracy scenarios, concerning origins of the pandemics, which resulted to huge numbers of deaths, particularly in overcrowded and poor areas/cities. Both pandemics not sparing any age, sex, nationality, social group, may have had a zoonotic component, besides being air-born. However, their spreading is/was remarkably rapid, presenting 3-4 waves and lasting for several years. Some somatic signs and symptoms of the diseases coincide. Although for COVID-19, SARS-CoV-2 has been identified as causing agent, the antique pandemic has most probably been attributed to typhoid fever, although this is still a matter of debate. Additionally, both pandemics affected mental health and psychosocial behavior in close similarity. It is noteworthy, that in both eras physicians and healthcare workers, despite physical and psychological exhaustion, in the majority, presented admirable resilience and willingness to help suffering fellow people, often at the expense of their own lives. The considerable number of comparable features between COVID-19 and the "Plague of Athens" confirms that pandemics may present over time important similarities in their origin, evolution and outcomes.

Investigating the Impact of the External Environment and Benchmark Characteristics on the China-Pakistan Economic Corridor's Construction: A COVID-19 Perspective

The economic stability of a country, such as Pakistan is dependent on the construction of mega-projects, such as the China-Pakistan Economic Corridor (CPEC). However, certain external factors and project characteristics may delay the construction of infrastructure projects; scholars have not investigated the development of CPEC from this perspective. In addition, the COVID-19 outbreak has hindered CPEC initiatives. This analysis will examine the effect of external environment factors on CPEC, and benchmark the project's effects on economic stability through CPEC's development by incorporating 523 samples obtained from employees of various CPEC projects. Structural equation modeling was used to analyze all hypotheses proposed here on AMOS 21.0 tools. According to the findings of this study, the CPEC external environment and project benchmark characteristics have a negative effect on the construction of CPEC development. Furthermore, the development of CPEC is found to have a significant effect on economic stability. However, fear of COVID-19 has weakened the relationship between CPEC development and economic stability. Finally, we also discuss the implications and limitations of the study.

Evaluation of different air distribution systems in a commercial airliner cabin in terms of comfort and COVID-19 infection risk

The air distribution system in an airliner plays a key role in maintaining a comfortable and healthy environment in the aircraft cabin. To evaluate the performance of a novel displacement ventilation (DV) system and a traditional mixing ventilation (MV) system in an airliner cabin, this study conducted experiments and simulations in a seven-row cabin mockup. This investigation used ultrasonic anemometers and T-thermocouples to measure the air velocity, temperature and distribution of 1 μm and 5 μm particles. Simulation verifications were performed for these operating conditions, and additional scenarios with different occurrence source locations were also simulated. This study combined the Wells-Riley equation with a real case based on a COVID-19 outbreak among passengers on a long-distance bus to obtain the COVID-19 quanta value. Through an evaluation of the airflow organization, thermal comfort, and risk of COVID-19 infection, the two ventilation systems were compared. This investigation found that polydisperse particles should be used to calculate the risk of infection in airliner cabins. In addition, at the beginning of the pandemic, the infection risk with DV was lower than that with MV. In the middle and late stages of the epidemic, the infection risk with MV can be reduced when passengers wear masks, leading to an infection risk approximately equal to that of DV.

Travel Bubbles in Air Transportation: Myth or Reality?

Aviation has been hit hard by COVID-19, with passengers stranded in remote destinations, airlines filing for bankruptcy, and uncertain demand scenarios for the future. Travel bubbles are discussed as one possible solution, meaning countries which have successfully constrained the spread of COVID-19 gradually increase their mutual international flights, returning to a degree of normality. This study aims to answer the question of whether travel bubbles are indeed observable in flight data for the year 2020. We take the year 2019 as reference and then search for anomalies in countries’ flight bans and recoveries, which could possibly be explained by having successfully implemented a travel bubble. To the best of our knowledge, this study is the first to try to address the identification of COVID-19 travel bubbles in real data. Our methodology and findings lead to several important insights regarding policy making, problems associated with the concept of travel bubbles, and raise interesting avenues for future research.

Religion, social interactions, and COVID-19 incidence in Western Germany

This paper investigates how social interactions, as shaped by religious denomination, are related to COVID-19 incidence and associated mortality in Western Germany. We observe that the number of infections and deaths during the early pandemic phase were much higher in predominantly Catholic counties with arguably stronger family and social ties. The relationship was confirmed at the county level through numerous robustness checks, and after controlling for a series of characteristics and county fixed effects. At the individual level, we confirmed that Catholics, relative to non-Catholics, have tighter and more frequent interactions with their family and friends. Moreover, the intensity of social interaction was able to partially explain the relationship between COVID-19 incidence and share of Catholics at the county level. Our results highlight the number of dimensions that have to be taken into account when designing and implementing mitigation measures in the early stages of disease outbreaks.

COVID-19 and bailout policy: The case of Virgin Australia

The impact of COVID-19 on air transport is unprecedented and some well-known airline brands may disappear as a result. Governments around the world have responded swiftly to cushion the financial impact by offering direct wage subsidies, tax relief, loans, etc. This paper explores the government's appropriate responses to failing airlines' bailout request by examining the case of Virgin Australia. Following the bailout policy principles established in the literature, we suggest that bankruptcy protection should be considered as the first solution to a failing carrier. A bailout decision should be guided by a set of principles and procedures, which should not be taken lightly. Our analysis also shows that the government cannot take a hands-off approach in the absence of private lenders and investors, as the costs to consumers and regional residents would be huge if the carrier could not get through the COVID-19 pandemic. A minimum level of assistance with conditions might be needed to maintain market competition.

The disruptive impact of COVID-19 on air transportation: An ITS econometric analysis☆

This paper provides estimates of the destructive impact of the COVID-19 outbreak on air transport at the macro-regional level. To this end, weekly data on the air service volumes are analyzed through an ITS SARIMA model and a counterfactual analysis covering the 2016–2020. We find that the real effect of COVID-19 was a reduction above 80% in all world's macro-regions in May 2020, and still a decrease of about 70% at the end of the Summer 2020, with the only exception of China and Eastern Asia, and North America, where the reductions are, respectively, −29% and −54%. The empirical evidence confirms that the impact of the pandemic crisis and of the subsequent lockdown has been dramatic, much higher than any previous crisis. We also find that the impact is greater for intercontinental connections and for FSCs, while LCCs appear to be slightly more resilient. These results confirm that airline economic sustainability is currently at high risk, and that the unequal resources of the various countries in subsidizing national airlines could generate a competitive imbalance in the future.

"What should be computed" for supporting post-pandemic recovery policymaking? A life-oriented perspective

The COVID-19 pandemic has caused various impacts on people's lives, while changes in people's lives have shown mixed effects on mitigating the spread of the SARS-CoV-2 virus. Understanding how to capture such two-way interactions is crucial, not only to control the pandemic but also to support post-pandemic urban recovery policies. As suggested by the life-oriented approach, the above interactions exist with respect to a variety of life domains, which form a complex behavior system. Through a review of the literature, this paper first points out inconsistent evidence about behavioral factors affecting the spread of COVID-19, and then argues that existing studies on the impacts of COVID-19 on people's lives have ignored behavioral co-changes in multiple life domains. Furthermore, selected uncertain trends of people's lives for the post-pandemic recovery are described. Finally, this paper concludes with a summary about "what should be computed?" in Computational Urban Science with respect to how to catch up with delays in the SDGs caused by the COVID-19 pandemic, how to address digital divides and dilemmas of e-society, how to capture behavioral co-changes during the post-pandemic recovery process, and how to better manage post-pandemic recovery policymaking processes.

COVID-19 Pandemic—Financial Consequences for Polish Airports—Selected Aspects

The COVID-19 pandemic has reduced the mobility of urban residents on an international level. Tourist air traffic was suspended as one of many activities. As a result, the aviation industry has suffered losses at various levels. In addition to carriers, airports are also suffering due to the effects of the pandemic. Their income comes mainly from charges for take-offs and landings of airplanes, passenger charges, and commercial and restaurant activity. In this paper, the authors attempt to estimate the level of losses incurred by six Polish airports in relation to passenger charges. Based on the data for the years 2015–2019, the forecasts of passenger flows for the year 2020 were estimated using the seasonality indicator method, the method of one-name period trends, and models of linear trends with seasonality. Research has shown that the total losses of the examined airports for the year 2020 amounted to approximately 290 million EUR, and these are losses resulting only from the lack of fees charged for servicing passengers at the airports.

COVID-19 impacts on general aviation - Comparative experiences, governmental responses and policy imperatives

This article catalogues experiences of the general aviation sector as it progressively encountered the challenges of COVID-19 in the early part of 2020. The article focuses primarily on the Australian marketplace as a contribution to the body of knowledge in an under-researched industry sector. The article draws on literature pertaining to prior pandemic experience to enquire about the level of precursory preparedness in the sector, and then utilises data from 12 semi-structured interviews with experienced industry participants locally and internationally. The key findings suggest that there has been a lack of applied learning by policy makers in the past, and that generic support on offer now does not address the long term resilience of the sector nor does it address a pathway for future sudden moments of dislocation. Policies which purport to support aviation should be crafted in a way that engages all levels of industry rather than be airline centric.

Open Business Model of COVID-19 Transformation of an Urban Public Transport System: The Experience of a Large Russian City

Dialectics, or developmental transformation, would eventually cause any system to change. The level and depth of these changes vary and depend on the power of external influence and system reservation mechanisms. The art of managing system processes consists of two main aspects. The first aspect involves the sagacity of managers and predicting general environmental change trends (and their impacts on the managed system). The second involves adjusting to these trends, maximizing possible benefits, and minimizing the negative manifestations of this process. Innovation plays an important role, contributing to system transformations with maximal effect and minimal loss. Public transport systems are important elements in cities, as they provide spatial mobility for at least half of the citizens of a city who cannot use individual transportation. Modern urbanization and peculiarities of the social–economic statuses of many citizens contribute to the fact that organized public transportation is unprofitable. The low solvency of citizens who use public transportation services means that passenger transport systems do not work with enough profitability. As a result, governing institutions often choose to subsidize unprofitable transporter activities, thereby prolonging the functioning of unprofitable routes. This is possible only in conditions of sustainability (in regards to a non-optimal system), when the environment is calm, and its negative impact is low. “Black swans” (according to N. Taleb) are bifurcation factors that break the sustainability of non-optimal system. Urban public transport (UPT) of a large Russian city, Tyumen, experienced it in 2020, in connection with the COVID-19 lockdown. The sharp decrease in population mobility in Tyumen, in 2020–2021, caused the need for a complete transformation of the transport service system. However, managers did not want to fundamentally change a system that consensually suited most counterparties. The search for new balances in a system that demands transformation is one way for sustainable provision. This article looks at the transformation and sustainability of a UPT system in the large Russian city of Tyumen, under conditions affected by the negative impact of COVID-19. Results of a comparative (i.e., pre-crisis (2019) and crisis (2020)) Pareto analysis of the contributions of different UPT routes are presented. Transformation of the structure of the UPT route system can overcome the “crisis” COVID-19 period and minimize its financial-economic costs.

Influence of transportation network on transmission heterogeneity of COVID-19 in China

In this paper, we propose a novel approach to model spatial heterogeneity for epidemic spreading, which combines the relevance of transport proximity in human movement and the excellent estimation accuracy of deep neural network. We apply this model to investigate the effects of various transportation networks on the heterogeneous propagation of COVID-19 in China. We further apply it to predict the development of COVID-19 in China in two scenarios, i.e., i) assuming that different types of traffic restriction policies are conducted and ii) assuming that the epicenter of the COVID-19 outbreak is in Beijing, so as to illustrate the potential usage of the model in generating various policy insights to help the containment of the further spread of COVID-19. We find that the most effective way to prevent the coronavirus from spreading quickly and extensively is to control the routes linked to the epicenter at the beginning of the pandemic. But if the virus has been widely spread, setting restrictions on hub cities would be much more efficient than imposing the same travel ban across the whole country. We also show that a comprehensive consideration of the epicenter location is necessary for disease control.

Understanding small Chinese cities as COVID-19 hotspots with an urban epidemic hazard index

Multiple small- to middle-scale cities, mostly located in northern China, became epidemic hotspots during the second wave of the spread of COVID-19 in early 2021. Despite qualitative discussions of potential social-economic causes, it remains unclear how this unordinary pattern could be substantiated with quantitative explanations. Through the development of an urban epidemic hazard index (EpiRank) for Chinese prefectural districts, we came up with a mathematical explanation for this phenomenon. The index is constructed via epidemic simulations on a multi-layer transportation network interconnecting local SEIR transmission dynamics, which characterizes intra- and inter-city population flow with a granular mathematical description. Essentially, we argue that these highlighted small towns possess greater epidemic hazards due to the combined effect of large local population and small inter-city transportation. The ratio of total population to population outflow could serve as an alternative city-specific indicator of such hazards, but its effectiveness is not as good as EpiRank, where contributions from other cities in determining a specific city's epidemic hazard are captured via the network approach. Population alone and city GDP are not valid signals for this indication. The proposed index is applicable to different epidemic settings and can be useful for the risk assessment and response planning of urban epidemic hazards in China. The model framework is modularized and the analysis can be extended to other nations.

COVID-19 pandemic and air transportation: Successfully navigating the paper hurricane

This paper aims to analyze and understand the impact of the corona virus disease (COVID-19) on aviation and also the role aviation played in the spread of COVID-19, by reviewing the recent scientific literature. We have collected 110 papers on the subject published in the year 2020 and grouped them according to their major application domain, leading to the following categories: Analysis of the global air transportation system during COVID-19, the impacts on the passenger-centric flight experience, and the long-term impacts on broad aviation. Based on the aggregated reported findings in the literature, this paper concludes with a set of recommendations for future scientific directions; hopefully helping aviation to prepare for a post-COVID-19 world.

Assessing regional risk of COVID-19 infection from Wuhan via high-speed rail

This paper demonstrates that transportation networks may be used to assess and predict the regional risk of COVID-19 infection from the outbreak. We use China's high-speed rail (HSR) network at the scale of prefecture level to assess, based on a probabilistic risk model, the risk of COVID-19 infection from Wuhan to the country's 31 province-level regions at the early stage of domestic spread. We find that the high-risk regions are mainly distributed along the southern half of Beijing-Hong Kong HSR line, where a large number of infection cases have been confirmed at the early stage. Furthermore, the two components of the infection risk, namely, the probability (proxied by the region's correlation with Wuhan through HSR) and the impact (proxied by the region's population with mobility), can play different roles in the risk ranking for different regions. For public health administrators, these findings may be used for better decision making, including the preparation of emergency plans and supplies, and the allocation of limited resources, before the extensive spread of the epidemic. Moreover, the administrators should adopt different intervention measures for different regions, so as to better mitigate the epidemic spread according to their own risk scenarios with respect to the probability of occurring and, once occurred, the impact.

The effect of the synchronized multi-dimensional policies on imported COVID-19 curtailment in China

As countries are lifting restrictions and resuming international travels, the rising risk of COVID-19 importation remains concerning, given that the SARS-CoV-2 virus could be transmitted unintentionally through the global transportation network. To explore and assess the effective strategies for curtailing the epidemic risk from international importation nationwide, we evaluated "the joint prevention and control" mechanism, which made up of 19 containment policies, on how it impacted the change of medical observation and detection time from border arrival to laboratory confirmation of COVID-19 in its burst in China. Based on 1,314 epidemiological-survey cases from February 29 to May 25, 2020, we found that the synchronized approach of implementing multi-dimensional interventional policies, such as a centralized quarantine and nucleic acid testing (NAT), flight service adjustment and border closure, effectively facilitate early identification of infected case. Specifically, the implementation of the international flight service reduction was found to be associated with a reduction of the mean intervals of diagnosis from arrival to lab-confirmation by 0.44 days maximally, and the border closure was associated with a reduction of the diagnosis interval of imported cases by 0.69 days, from arrival to laboratory confirmation. The study suggests that a timely and synchronized implementation of multi-dimensional policies is compelling in preventing domestic spreading from importation.

Understanding the Spread of COVID-19 in China: Spatial–Temporal Characteristics, Risk Analysis and the Impact of the Quarantine of Hubei Province on the Railway Transportation Network

The rapid spread of COVID-19 and its global growth constitutes an international public-health emergency, posing a serious threat to global health, safety, and social economy. In this paper, we systematically studied the temporal and spatial characteristics of COVID-19, infectivity, and the impact of Hubei province’s quarantine on the national railway system on the basis of epidemic and national train data. This study found the following: (1) The overall growth of the epidemic was exponential, and the outbreak of Hubei had a strong spread in the eastern and southern directions. The epidemic was generally more serious in the capital or developed cities in each province, and the epidemic outside Hubei was under control after the imported growth ended. (2) On the basis of analyzing the disturbance of the spread of the epidemic by traffic control, the average incubation period of COVID-19 was approximately 4 days. The ratio of the number of cured people to the number of deaths gradually increased, indicating that, given sufficient medical service, the cure rate can be greatly improved. (3) The quarantine of Hubei had greater impact on cities with higher centrality, especially in the Yangtze River Delta region, and smaller impact on the overall connectivity of the national railway network. For local people, quarantine had great impact on the outflow of local people to neighboring provinces.

Exploring spatiotemporal effects of the driving factors on COVID-19 incidences in the contiguous United States

Since December 2019, the world has witnessed the stringent effect of an unprecedented global pandemic, coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of January 29,2021, there have been 100,819,363 confirmed cases and 2,176,159 deaths reported. Among the countries affected severely by COVID-19, the United States tops the list. Research has been conducted to discuss the causal associations between explanatory factors and COVID-19 transmission in the contiguous United States. However, most of these studies focus more on spatial associations of the estimated parameters, yet exploring the time-varying dimension in spatial econometric modeling appears to be utmost essential. This research adopts various relevant approaches to explore the potential effects of driving factors on COVID-19 counts in the contiguous United States. A total of three global spatial regression models and two local spatial regression models, the latter including geographically weighted regression (GWR) and multiscale GWR (MGWR), are performed at the county scale to take into account the scale effects. For COVID-19 cases, ethnicity, crime, and income factors are found to be the strongest covariates and explain most of the variance of the modeling estimation. For COVID-19 deaths, migration (domestic and international) and income factors play a critical role in explaining spatial differences of COVID-19 deaths across counties. Such associations also exhibit temporal variations from March to July, as supported by better performance of MGWR than GWR. Both global and local associations among the parameters vary highly over space and change across time. Therefore, time dimension should be paid more attention to in the spatial epidemiological analysis. Among the two local spatial regression models, MGWR performs more accurately, as it has slightly higher Adj. R2 values (for cases, R2 = 0.961; for deaths, R2 = 0.962), compared to GWR's Adj. R2 values (for cases, R2 = 0.954; for deaths, R2 = 0.954). To inform policy-makers at the nation and state levels, understanding the place-based characteristics of the explanatory forces and related spatial patterns of the driving factors is of paramount importance. Since it is not the first time humans are facing public health emergency, the findings of the present research on COVID-19 therefore can be used as a reference for policy designing and effective decision making.

The heterogeneity of the COVID-19 pandemic and national responses: an explanatory mixed-methods study

BACKGROUND

The coronavirus disease of 2019 (COVID-19) has quickly spread to all corners of the world since its emergence in Wuhan, China in December of 2019. The disease burden has been heterogeneous across regions of the world, with Americas leading in cumulative cases and deaths, followed by Europe, Southeast Asia, Eastern Mediterranean, Africa and Western Pacific. Initial responses to COVID-19 also varied between governments, ranging from proactive containment to delayed intervention. Understanding these variabilities allow high burden countries to learn from low burden countries on ways to create more sustainable response plans in the future.

METHODS

This study used a mixed-methods approach to perform cross-country comparisons of pandemic responses in the United States (US), Brazil, Germany, Australia, South Korea, Thailand, New Zealand, Italy and China. These countries were selected based on their income level, relative COVID-19 burden and geographic location. To rationalize the epidemiological variability, a list of 14 indicators was established to assess the countries' preparedness, actual response, and socioeconomic and demographic profile in the context of COVID-19.

RESULTS

As of 1 April 2021, the US had the highest cases per million out of the nine countries, followed by Brazil, Italy, Germany, South Korea, Australia, New Zealand, Thailand and China. Meanwhile, Italy ranked first out of the nine countries' total deaths per million, followed by the US, Brazil, Germany, Australia, South Korea, New Zealand, China and Thailand. The epidemiological differences between these countries could be explained by nine indicators, and they were 1) leadership, governance and coordination of response, 2) communication, 3) community engagement, 4) multisectoral actions, 5) public health capacity, 6) universal health coverage, 7) medical services and hospital capacity, 8) demography and 9) burden of non-communicable diseases.

CONCLUSION

The COVID-19 pandemic manifests varied outcomes due to differences in countries' vulnerability, preparedness and response. Our study rationalizes why South Korea, New Zealand, Thailand, Australia and China performed better than the US, Italy and Brazil. By identifying the strengths of low burden countries and weaknesses of hotspot countries, we elucidate factors constituting an effective pandemic response that can be adopted by leaders in preparation for re-emerging public health threats.

On the degree of synchronization between air transport connectivity and COVID-19 cases at worldwide level

COVID-19 is one of the most impactful pandemics in recent history, not only in terms of direct casualties but also regarding socio-economic impact. The goal of our study is to investigate the degree of synchronization between the number of confirmed cases in specific countries, on one hand, and how/at which stage these countries adapted their air transportation operations, on the other hand. We investigate the global air transportation system as a network of countries whose edges represent the existence of direct flights. Aggregated analysis of this country network and its evolving dynamics leads to novel insights regarding the synchronization with the number of confirmed cases; finding that most country borders were likely closed too late. We believe and hope that our analysis leads to a more efficient/effective prevention and control of future epidemics.

Does International Travel Frequency Affect COVID-19 Biosecurity Behavior in the United States?

High-quality biosecurity practices are critical to restarting international tourism. Effective market segmentation improves the communication and efficacy of health advice. Travel frequency is an important basis for health-related consumer segmentation, as it is closely related to risk of greater exposure to infectious diseases. Theoretically grounded studies of tourist biosecurity behavior and travel frequency have largely been neglected, although insights into practices and attitudes are especially relevant for coronavirus disease of 2019 (COVID-19 (coronavirus disease of 2019) health responses. Therefore, this research constructed and tested a conceptual model applying Value–Attitude–Behavior theory to US travelers to see whether the frequency of international travel affected tourist COVID-19 related biosecurity behavior. US respondents were drawn from a panel using a quota sampling technique according to the age and gender of American outbound tourists. An online survey was administered in September 2020. The responses (n = 395) of those who traveled internationally within five years were analyzed utilizing partial least squares-structural equation modeling (PLS-SEM) with multi-group analysis. Travel frequency significantly affects biosecurity behavior. High travel frequency (≥8 trips) has the strongest effect of value on biosecurity attitudes, personal norms, social norms, and biosecurity social norms, leading to biosecurity behaviors. Biosecurity behaviors pertaining to medium travel frequency (4–7 trips) are significantly influenced by personal norms. At low travel frequency (1–3 trips) levels, biosecurity behaviors are stimulated by biosecurity attitudes and social norms, showing the highest predictive power among the three groups. This work provides insights into international travel consumer biosecurity practices and behavior. From a market segmentation perspective, the levels of international travel frequency have various influences on biosecurity values, attitudes, personal norms, social norms, and behaviors. The biosecurity behaviors of low-frequency travelers are found to be the most significant of the three groups, suggesting that individuals who travel less frequently are more likely to practice responsible COVID-19 biosecurity behavior.

Emergency preparedness for public health threats, surveillance, modelling & forecasting

In the interconnected world, safeguarding global health security is vital for maintaining public health and economic upliftment of any nation. Emergency preparedness is considered as the key to control the emerging public health challenges at both national as well as international levels. Further, the predictive information systems based on routine surveillance, disease modelling and forecasting play a pivotal role in both policy building and community participation to detect, prevent and respond to potential health threats. Therefore, reliable and timely forecasts of these untoward events could mobilize swift and effective public health responses and mitigation efforts. The present review focuses on the various aspects of emergency preparedness with special emphasis on public health surveillance, epidemiological modelling and capacity building approaches. Global coordination and capacity building, funding and commitment at the national and international levels, under the One Health framework, are crucial in combating global public health threats in a holistic manner.

Global mobility, travel and migration health: clinical and public health implications for children and families

Exponential growth of the world's population combined with increased travel has dramatically increased the spread of infectious diseases. Although there has been significant focus on migration, the major contributors to the transmission of communicable diseases are travel and tourism not migration. Given that children represent up to 10% of international travellers, it is critical to the health of all age groups to ensure that tailored guidance for children is considered in public health policy and guidelines, and pandemic responses. To further support pandemic preparedness, public health systems need to strengthen ties with communities and health systems. In addition, travel and migration issues need to be included as core competencies in medical education. Ensuring that clinicians who care for children have knowledge of travel and migration health will foster a better health outcome in an increasingly mobile population at risk of emerging infectious diseases.Abbreviations CDC: Centers for Disease Control and Prevention; DGMQ: CDC Division of Global Migration and Quarantine; EID: emerging infectious diseases; EU: European Union; VFR: visiting friends and relatives; IOM: United Nations International Organization for Migration; LPR: lawful permanent resident; US: United States of America; WHO: World Health Organization.

Do pandemics have an asymmetric effect on tourism in Italy?

In this study, the asymmetric Granger causality relationship between tourist arrivals and world pandemic uncertainty index is examined by controlling inflation, consumer confidence index, and industrial production for the period 2000M1 and 2020M1 in Italy. To the best of our knowledge, the current study is one of the few studies to investigate the relationship between tourist arrivals and world pandemic uncertainty in an asymmetric framework. The empirical results show that using the Granger causality test in a linear framework causes bias results due to misspecification. Therefore, the study relies on asymmetric Granger causality test results which reveal that the positive shock of world pandemic uncertainty Granger causes a negative shock of tourist arrivals. It is suggested that international tourist arrivals are sensitive to external shocks such as pandemics and in such instances the government of the concerned country can insulate the tourism-service and hospitality industry against the shocks by developing strategies to promote full information between all stakeholders.

Applications of GIS and geospatial analyses in COVID-19 research: A systematic review

Background: Geographic information science (GIS) has established itself as a distinct domain and incredibly useful whenever the research is related to geography, space, and other spatio-temporal dimensions. However, the scientific landscape on the integration of GIS in COVID-related studies is largely unknown. In this systematic review, we assessed the current evidence on the implementation of GIS and other geospatial tools in the COVID-19 pandemic. Methods: We systematically retrieved and reviewed 79 research articles that either directly used GIS or other geospatial tools as part of their analysis. We grouped the identified papers under six broader thematic groups based on the objectives and research questions of the study- environmental, socio-economic, and cultural, public health, spatial transmission, computer-aided modeling, and data mining. Results: The interdisciplinary nature of how geographic and spatial analysis was used in COVID-19 research was notable among the reviewed papers. Geospatial techniques, especially WebGIS, have even been widely used to visualize the data on a map and were critical to informing the public regarding the spread of the virus, especially during the early days of the pandemic. This review not only provided an overarching view on how GIS has been used in COVID-19 research so far but also concluded that geospatial analysis and technologies could be used in future public health emergencies along with statistical and other socio-economic modeling techniques. Our review also highlighted how scientific communities and policymakers could leverage GIS to extract useful information to make an informed decision in the future. Conclusions:  Despite the limited applications of GIS in identifying the nature and spatio-temporal pattern of this raging pandemic, there are opportunities to utilize these techniques in handling the pandemic. The use of spatial analysis and GIS could significantly improve how we understand the pandemic as well as address the underserviced demographic groups and communities.

Applications of GIS and geospatial analyses in COVID-19 research: A systematic review

Background: Geographic information science (GIS) has established itself as a distinct domain and incredibly useful whenever the research is related to geography, space, and other spatio-temporal dimensions. However, the scientific landscape on the integration of GIS in COVID-related studies is largely unknown. In this systematic review, we assessed the current evidence on the implementation of GIS and other geospatial tools in the COVID-19 pandemic. Methods: We systematically retrieved and reviewed 79 research articles that either directly used GIS or other geospatial tools as part of their analysis. We grouped the identified papers under six broader thematic groups based on the objectives and research questions of the study- environmental, socio-economic, and cultural, public health, spatial transmission, computer-aided modeling, and data mining. Results: The interdisciplinary nature of how geographic and spatial analysis was used in COVID-19 research was notable among the reviewed papers. Although GIS has substantial potential in planning to slow down the spread, surveillance, contact tracing, and identify the trends and hotspots of breakdowns, it was not employed as much as it could have been. This review not only provided an overarching view on how GIS has been used in COVID-19 research so far but also concluded that this geospatial analysis and technologies could be used in future public health emergencies along with statistical and other socio-economic modeling techniques. Our systematic review also provides how both scientific communities and policymakers could leverage GIS to extract useful information to make an informed decision in the future. Conclusions:  Despite the limited applications of GIS in identifying the nature and spatio-temporal pattern of this raging pandemic, there are opportunities to utilize these techniques in handling the pandemic. The use of spatial analysis and GIS could significantly improve how we understand the pandemic as well as address the underserviced demographic groups and communities.

How did COVID-19 impact air transportation? A first peek through the lens of complex networks

The current outbreak of COVID-19 is an unprecedented event in air transportation. This is probably the first time that global aviation contributed to the planet-wide spread of a pandemic, with casualties in over two hundred countries. As of August 23rd, 2020, the number of infected cases has topped 23 million, reportedly relating to more than 800,000 deaths worldwide. However, there is also a second side of the pandemic: it has led to an unmatched singularity in the global air transportation system. In what could be considered a highly uncoordinated, almost chaotic manner, countries have closed their borders, and people are reluctant/unable to travel due to country-specific lock-down measures. Accordingly, aviation is one of the industries that has been suffering most due to the consequences of the pandemic outbreak, despite probably being one of its largest initial drivers. In this study, we investigate the impact of COVID-19 on global air transportation at different scales, ranging from worldwide airport networks where airports are nodes and links between airports exist when direct flights exist, to international country networks where countries are contracted as nodes, and to domestic airport networks for representative countries/regions. We focus on the spatial-temporal evolutionary dynamics of COVID-19 in air transportation networks. Our study provides a comprehensive empirical analysis on the impact of the COVID-19 pandemic on aviation from a complex system perspective using network science tools.

Factors Associated with Mental Health Results among Workers with Income Losses Exposed to COVID-19 in China

The outbreak and worldwide spread of COVID-19 has resulted in a high prevalence of mental health problems in China and other countries. This was a cross-sectional study conducted using an online survey and face-to-face interviews to assess mental health problems and the associated factors among Chinese citizens with income losses exposed to COVID-19. The degrees of the depression, anxiety, insomnia, and distress symptoms of our participants were assessed using the Chinese versions of the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder-7 (GAD-7), the Insomnia Severity Index-7 (ISI-7), and the revised 7-item Impact of Event Scale (IES-7) scales, respectively, which found that the prevalence rates of depression, anxiety, insomnia, and distress caused by COVID-19 were 45.5%, 49.5%, 30.9%, and 68.1%, respectively. Multivariable logistic regression analysis was performed to identify factors associated with mental health outcomes among workers with income losses during COVID-19. Participants working in Hubei province with heavy income losses, especially pregnant women, were found to have a high risk of developing unfavorable mental health symptoms and may need psychological support or interventions.