Identifying competitive position for sixteen major Asia-Pacific hubs after the COVID-19 pandemic

Worry, avoidance, and coping during the COVID-19 pandemic: A comprehensive network analysis

The global aviation logistics network, a critical artery for high-value and time-sensitive supply chains, exhibits significant vulnerability to disruptive shocks. Traditional risk management models, often static and linear, fail to capture the dynamic, non-linear, and cascading nature of such disruptions. This paper proposes a novel methodological framework that integrates the principles of resilience engineering into a Bayesian Network (BN) to quantitatively assess and enhance the resilience of aviation logistics systems. The core innovation lies in structurally embedding the three capacities of resilience—absorptive, adaptive, and restorative—into the BN's topology. A real-world case study of a major Asian air cargo hub (Shanghai Pudong International Airport) during the COVID-19 pandemic is conducted to validate the model. Through predictive, diagnostic, and sensitivity analysis, the model identifies ground staff availability, aircraft redeployment flexibility, and regulatory adaptability as the most critical resilience enablers. The study concludes with strategic, data-driven suggestions for stakeholders to transition from reactive risk mitigation to proactive resilience building, emphasizing investment in human capital, digitalization, and collaborative ecosystem planning.

In addition to vaccine and impactful treatments, mitigation strategies represent an effective way to combat the COVID-19 virus and an invaluable resource in this task is numerical modeling that can reveal key factors in COVID-19 pandemic development. On the other hand, it has become evident that regional infection curves of COVID-19 exhibit complex patterns which often differ from curves predicted by forecasting models. The wide variations in attack rate observed among different social strata suggest that this may be due to social heterogeneity not accounted for by regional models. We investigated this hypothesis by developing and using a new Stochastic Heterogeneous Epidemic Model that focuses on subpopulations that are vulnerable in the sense of having an increased likelihood of spreading infection among themselves. We found that the isolation or embedding of vulnerable sub-clusters in a major population hub generated complex stochastic infection patterns which included multiple peaks and growth periods, an extended plateau, a prolonged tail, or a delayed second wave of infection. Embedded vulnerable groups became hotspots that drove infection despite efforts of the main population to socially distance, while isolated groups suffered delayed but intense infection. Amplification of infection by these hotspots facilitated transmission from one urban area to another, causing the epidemic to hopscotch in a stochastic manner to places it would not otherwise reach; whereas vaccination only in hotspot populations stopped geographic spread of infection. Our results suggest that social heterogeneity is a key factor in the formation of complex infection propagation patterns. Thus, the mitigation and vaccination of vulnerable groups is essential to control the COVID-19 pandemic worldwide. The design of our new model allows it to be applied in future studies of real-world scenarios on any scale, limited only by computing memory and the ability to determine the underlying topology and parameters.

To the Editor, In a recent editorial, Leopold and Dobbs [1] compiled worldwide experiences with the coronavirus-19 (COVID-19) pandemic. It was a raw but much-needed collection of perspectives from the frontline as we rally together against the challenges ahead. The first author of this letter (SS) reflects on his own journey, which began not even 4 months ago. Nothing was more exhilarating than being accepted to a foot and ankle fellowship at the National University Hospital, Singapore. After almost a year of planning, the day finally arrived for me to commence my fellowship. Apart from the usual beginner’s apprehension, each day was like a dream come true, with early-morning academic sessions followed by rounds to review inpatients and a subsequent rush to the operating room for the long list of procedures scheduled for the day. All of this, however, changed within 2 weeks, when the news of COVID-19 in China hit the shores of Singapore. Little did I realize that Singapore, being a major hub in Asia, would be thrown into this impending pandemic because of the large number of people traveling in and out of Singapore. The first patient with COVID-19 was confirmed on January 23, 2020, when a tourist from Wuhan, China travelled to Singapore [2]. The first instance of local transmission was confirmed on February 4, 2020. My hospital responded immediately. Team segregation was instituted, and interhospital deployment was also suspended with immediate effect. The change that affected me the most is that my mentor (SDD) was deployed to lead the orthopaedics team in a sister hospital and was not allowed to return to the National University Hospital until the situation improved. Adding to my dismay, a stepwise reduction in the elective surgery load was also instituted. Originally, only nonurgent elective procedures necessitating more than 23 hours of admission were postponed. Fortunately, for me, this meant that most of the foot and ankle procedures could continue. However, as the number of patients with COVID-19 continued to surge during the “second wave” of the virus in April 2020, additional stepwise reduction of elective surgery was performed, including the suspension of day surgery. This meant a lot to a fellow whose main objective was to learn as much about surgical interventions as possible. The silver lining was that while the decrease in the number of elective surgeries limited my exposure, the newly assigned attending surgeon (CCH) on my team ensured that each procedure’s educational value was maximized. More time was devoted to discussing the procedures, and the surgical procedures were reviewed in detail before and during the surgery. As trauma, infection, and tumor took the front seat in the pandemic, I also had more opportunities to participate and perform these procedures under the guidance of the attending surgeon. There is now more quality than quantity in the learning process than there was previously because the additional time and exposure allowed me to have a greater understanding of the procedures. Through the pandemic, I felt more involved in departmental academic and research efforts. Because members of the department were segregated into teams and not allowed to meet, video conferencing replaced the traditional in-person teachings. I had more opportunities to present several teachings and journal clubs over video conferencing, which further enhanced my learning. Beyond the clinical hours, time was also devoted to honing my research skills amid the pandemic [3, 4]. In addition, as part of my hospital’s befrienders and ambassadors initiative, I had the chance to connect with migrant workers who were COVID-19-positive and to reach out to this group of scared and worried people isolated from their usual support networks during this trying period. It was an eye-opening experience and a privilege to provide a listening ear and encouragement to them. While of course I wish that the virus outbreak had never occurred, especially not during my tenure as an overseas fellow, I feel at the same time blessed and privileged to be in Singapore during this pandemic because I have forged many valuable friendships over time. The numerous lessons I have learned because of the pandemic will serve as a blueprint for dealing with future pandemics in my native country, India. These experiences gleaned from my fellowship will indeed last forever.

Long Covid (LC) is a multisystem condition leading to a wide range of symptoms and often requiring treatment by several different clinical specialties. Patients with LC have reported difficulties in accessing care and a lack of coordination of their care, particularly in a hospital setting. To determine the extent to which the intensity and continuity of hospital care changes for patients after they receive an LC diagnosis. Retrospective observational cohort study using a linked primary and secondary care dataset. Routine healthcare data from North West London Integrated Care System of patients with a recorded diagnosis of LC who had attended a secondary care hospital Trust from 1 January 2019 to 30 September 2023. The intensity of utilisation of secondary care was calculated, and the continuity of care with respect to hospitals and specialties was computed using the sequential continuity score (SeCon) before the Covid-19 pandemic, before and after an LC diagnosis. 5611 out of 6270 (90.1%) patients diagnosed with LC had a recorded secondary care interaction in the study period. Intensity of secondary care utilisation increased markedly in outpatient, inpatient and Emergency Department pathways after a diagnosis of LC but peaked in the week of diagnosis. Average hospital SeCon fell significantly after an LC diagnosis from 1.00 to 0.83, while specialty SeCon remained unchanged from after diagnosis (0.40) and before the pandemic (0.44). A notable shift in specialty activity was observed with a focus on respiratory medicine as a major hub in a densely connected patient-sharing network with cardiology and other medical and surgical specialties. A recorded LC diagnosis was associated with increases in the intensity of hospital activity and a reduction in hospital-level care continuity, but no change in specialty continuity, which remains low. Collectively, this indicates a significant need to support LC patients as they navigate fragmented secondary care pathways. This study was co-designed with, conducted with and written in conjunction with people with long Covid.

The COVID-19 virus has hit the economy around the world. In Poland, SMEs have the greatest problems with doing business. Border blockades and the quarantine for enterprises in virtually all industries throughout Poland greatly complicated the supply systems and the inventory management process. Up to now, SMEs have acted in group purchasing organizations to improve their competitive position. This form of activity also positively affects their financial security. Therefore, in this paper, the inventory management among this group of companies during the COVID-19 pandemic was analyzed. The purpose of the paper was to show how inventory management strategies changed during the COVID-19 pandemic in SMEs operating in industry GPOs. The analysis was carried out on a group of 88 Polish commercial enterprises operating in purchasing groups. The research period covered the years 2017–2019 and March–June 2020. The research showed a change in inventory management strategy in SMEs during the pandemic time of COVID-19. For the first four months, managers of enterprises tried to pursue a conservative policy and to accumulate stocks in the event of a shortage of supplies. This article also presents the form of security that was applied for SMEs operating in group purchasing organizations (GPOs) to avoid forced downtime caused by the COVID-19 pandemic.

The use of big data by large food retailers is increasing their bargaining power against the agri-food cooperative sector. The aim of this study was to determine the social media behaviour of food retailers in Spain and the UK, and to identify significant changes pre- and post-COVID-19 pandemic. The study analysed Twitter data collected from 16 food retailers; a total of 102,200 valid tweets were extracted from their official Twitter accounts. A term frequency analysis and a social network analysis of food retailers’ Twitter behaviour were carried out. The results obtained show differences for both UK and Spanish retailers before and during the COVID-19 pandemic. For agri-food cooperatives with little bargaining power in the supply chain of fresh produce, data analysis is a key factor in improving their competitive positioning. These findings should be of value to data scientists as well as managers responsible for forming strategies in agri-food firms that have large food retailers as clients. Finally, the study also confirms that, for agri-food cooperatives, analysing tweet content is a cheap and useful tool for understanding customer behaviour.

BackgroundThe role of health-related disparities including sociodemographic, environmental, and critical care capacity in the COVID-19 pandemic are poorly understood. In the present study, we characterized vulnerable populations located in areas at higher risk of COVID-19 related mortality and low critical healthcare capacity in the U.S.MethodsUsing Bayesian multilevel analysis and small area disease risk mapping, we assessed the spatial variation of COVID-19 related mortality risk for the U.S. in relation with healthcare disparities including race, ethnicity, poverty, air quality, and critical healthcare capacity.ResultsOverall, highly populated, regional air hub areas, and minorities had an increased risk of COVID-19 related mortality. We found that with an increase of only 1 ug/m3 in long term PM2.5 exposure, the COVID-19 mortality rate increased by 13%. Counties with major air hubs had 18% increase in COVID-19 related death compared to counties with no airport connectivity. Sixty-eight percent of the counties with high COVID-19 related mortality risk were also counties with lower critical care capacity than national average. These counties were primary located at the North- and South-Eastern regions of the country.ConclusionThe existing disparity in health and environmental risk factors that exacerbate the COVID-19 related mortality, along with the regional healthcare capacity, determine the vulnerability of populations to COVID-19 related mortality. The results from this study can be used to guide the development of strategies for the identification and targeting preventive strategies in vulnerable populations with a higher proportion of minority groups living in areas with poor air quality and low healthcare capacity.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, continues to impact the world even three years after its outbreak. International border closures and health alerts severely affected the air transport industry, resulting in substantial financial losses. This study analyzes the global data on infected individuals alongside aircraft types, flight durations, and passenger flows. Using a Bayesian framework, we forecast the risk of infection during commercial flights and its potential spread across an air transport network. Our model allows us to explore the effect of mitigation measures, such as closing individual routes or airports, reducing aircraft occupancy, or restricting access for infected passengers, on disease propagation, while allowing the air industry to operate at near-normal levels. Our novel approach combines dynamic network modeling with discrete event simulation. A real-case study at major European hubs illustrates our methodology.

This editorial presents a commentary on COVID-19 and mental health in Hong Kong. We outline the current measures being used to contain the outbreak and how the experience of the SARS epidemic may have influenced the response in Hong Kong. We also discuss the potential mental health ill-effects of the pandemic and its impact on mental health nursing locally.

BackgroundThe rapid development of modern transportation networks, coupled with increasing urbanization and population mobility, presents a dual challenge for global public health systems: while enhancing connectivity and economic integration, these networks also accelerate the spatial dissemination of infectious diseases. The COVID-19 pandemic, which emerged in Wuhan, China, in late 2019, starkly illustrated this paradox. As a major national transportation hub with dense high-speed rail (HSR) connectivity, Wuhan exemplifies how modern transport infrastructure can facilitate the rapid intercity transmission of pathogens. The unprecedented lockdown of Wuhan on January 23, 2020, along with nationwide transportation controls, constituted a critical natural experiment for assessing the effectiveness of mobility restrictions in containing epidemic spread. This study provides timely empirical evidence on this pivotal public health intervention.MethodsUtilizing a multi-source dataset encompassing daily confirmed COVID-19 cases from 294 Chinese cities, HSR operational records, Baidu migration big data, and urban socioeconomic indicators, this study employs an econometric framework to evaluate the impact of transportation networks and controls on epidemic dynamics. Our empirical strategy involves cross-sectional and panel data analyses, with a focus on comparing cities with and without HSR connectivity before and after the Wuhan lockdown. We control for confounding factors such as city-level economic development, existing transportation infrastructure, and pre-lockdown population inflows from Wuhan. A series of robustness checks, including alternative model specifications, sample restrictions, placebo tests, and permutation simulations, are conducted to ensure the reliability of causal inferences.ResultsOur analysis reveals that HSR connectivity served as a primary channel for the early intercity transmission of COVID-19. Cities connected to the HSR network, particularly those with direct links to Wuhan, experienced significantly higher numbers of confirmed cases. On January 30, 2020, HSR-connected cities (excluding Wuhan) had an average of 12.62 more cases than non-HSR cities, which accounted for an estimated excess of 2,852 cases nationally. The correlation between pre-lockdown population outflows from Wuhan and subsequent case distribution in destination cities was strongly positive. Importantly, the implementation of the Wuhan lockdown and associated transportation suspensions effectively disrupted this transmission pathway. The estimated effect of HSR on case counts diminished sharply immediately after the lockdown, underscoring the efficacy of mobility restrictions in curbing epidemic spread.ImplicationsThis study demonstrates that large-scale transportation controls, exemplified by the Wuhan lockdown, can be a highly effective non-pharmaceutical intervention for containing emerging infectious diseases in their initial stages. The findings validate the scientific rationale behind China's containment strategy, which centered on source control and transmission route interruption. Beyond the immediate pandemic context, this research highlights the critical interplay between transportation planning and public health preparedness. It underscores the necessity for policymakers worldwide to integrate epidemic response mechanisms into the governance of highly mobile, interconnected urban systems. The evidence presented here offers a robust, data-driven rebuttal to politicized critiques of China's early response and provides valuable insights for designing coordinated, evidence-based mobility policies to mitigate future global health threats.

Introduction Standard operating procedures and patient pathways in healthcare have been greatly influenced by the Covid-19 pandemic. The aim of this study is to understand the impact of changes in discharge practices by comparing hospital length of stay and rates of failed discharge in selected common vascular procedures in the pre-Covid-19 and post-Covid-19 periods. Methods A single consultant surgeon’s logbook at a major vascular hub was used to identify all patients who underwent common vascular procedures in the pre-Covid-19 period (January to December 2017), and post-Covid-19 period (January 2021 to August 2022). Basic demographic data was recorded, as well as post-operative length of stay (LOS), failed discharge rates (re-admission within 24-hours) and re-admission within 30-days of the index procedure. Results 65 cases were identified in the pre-Covid-19 period. 71 cases identified in the Post-covid-19 period. For each of the surgical procedures, patient demographics were comparable. There has been a reduction in the median post- operative LOS for each of the surgical procedures. Common femoral endarterectomy from 3-days to 2-days, femoral-popliteal bypass from 10-days to 5-days, major limb amputation from 29-days to 18-days, endovascular aneurysm repair from 4-days to 2-days and fenestrated endovascular aneurysm repair from 4-days to 2- days. There were no recorded failed discharges. There was no increase in re-admission at 30-days. Conclusion We have demonstrated a reduction in the median duration of hospital stay in the post-Covid-19 period, without an increase in any readmissions. Early mobilisation and a prompt discharge policy is thought to be relevant.

The COVID-19 pandemic is one of the rarest events of global crises where a viral pathogen infiltrates every part of the world, leaving every country face an inevitable threat of having to lock down major cities and economic hubs and put firm restrictions on citizens thus slowing down the economy. The risk of removal of lockdowns is the emergence of new waves of a pandemic causing a surge in new cases. These facts necessitate the containment of the virus when the lockdowns end. Wearing masks in crowded places can help restrict the spread of the virus through minuscule droplets in the air. Through the automatic detection, enumeration, and localisation of masks from closed-circuit television footage, it is possible to keep violations of post-COVID regulations in check. In this paper, we leverage the Single-Shot Detection (SSD) framework through different base convolutional neural networks (CNNs) namely VGG16, VGG19, ResNet50, DenseNet121, MobileNetV2, and Xception to compare performance metrics attained by the different variations of the SSD and determine the efficacies for the best base network model for automatic mask detection in a post COVID world. We find that Xception performs best among all the other models in terms of mean average precision.

This research examines the shifting geography of small firm innovation in the U.S. by tracking the location of small business innovation research (SBIR) and small business technology transfer (STTR) awardees between 2010 and 2024. The SBIR and STTR are “seed fund” awards coordinated by the Small Business Administration (SBA) and funded through 11 U.S. federal agencies. Of particular interest is whether the number of individual SBA awards, awarded firms, and/or funding amounts are (1) becoming increasingly concentrated within regional innovation hubs and (2) exhibiting a shift toward or away from urban centers and other walkable, transit-accessible urban neighborhoods, particularly since 2020 and the COVID-19 pandemic. While the rise of remote work and pandemic-related fears may have reduced the desirability of urban spaces for both living and working, there remain significant benefits to spatial agglomeration that may be especially crucial for startups and other small firms in the knowledge- or information-intensive industries. The results suggest that innovative activity of smaller firms has indeed trended toward more centralized, denser, and walkable urban areas in recent years while also remaining fairly concentrated within major metropolitan innovation hubs. The pandemic appears to have resulted in a measurable, though potentially short-lived, cessation of these trends.

This study investigates price elasticity of demand and its pricing effect on revenue performance of hotels during the COVID-19 pandemic. Using annual operating performance data on over 2,500 hotels from 2018 to 2021, this study provides empirical evidence of a relatively inelastic demand for the lodging sector. Price, income, cross-price, and lagged demand are positive and inelastic in their relationships with demand. Price has a significant and negative effect on lodging demand while a hotel’s competitive position has a significant influence on RevPAR performance with both negatively affected by COVID-19. More important, the results show a significantly greater positive impact of pricing on RevPAR penetration for hotels that raised rates relative to hotels that dropped rates. The findings suggest that it may be best for hotels to maintain or raise room rates to maximize revenue performance in the midst of an external shock.