The dynamic effects of infectious disease outbreaks: The case of pandemic influenza and human coronavirus

Physicochemical methods for disinfection of contaminated surfaces - a way to control infectious diseases

This paper represents the reviews of recent advancements in different physicochemical methods for disinfecting contaminated surfaces, which are considered to be responsible for transmitting different bacterial, viral, and fungal infectious diseases. Surface disinfection can be achieved by applying chemicals, UV-based processes, ionization radiation (gamma-ray, X-ray and electron beam), application of self-disinfecting surfaces, no-touch room disinfection methods, and robotic disinfection methods for built-in settings. Application of different chemicals, such as alcohols, hydrogen peroxide, peracetic acid, quaternary ammonium salts, phenol, and iodine solution, are common and economical. However, the process is time-consuming and less efficient. The use of UVC light (wavelength: 200-280 nm, generated by low vapor mercury lamps or pulse xenon light) has gained much attention for disinfecting fomites worldwide. In recent times, the combination of UV and H2O2, based on the principle of the advanced oxidation process, has been applied for disinfecting inanimate surfaces. The process is very efficient and faster than chemical and UV processes. Heavy metals like copper, silver, zinc, and other metals can inactivate microbes and are used for surface modification to produce self-disinfecting surfaces and used in healthcare facilities. In combination with UVB (280-315 nm) and UVA (315-400 nm), titanium oxide has been utilized for disinfecting contaminated surfaces. Ionization radiation, one of the advanced methods, can be used in disinfecting medical devices and drugs. Post-COVID-19 pandemic, the no-touch and robotic disinfection methods utilizing chemicals or UVC lights have received much importance in built-in settings. Among these methods, surface disinfection by applying chemicals by fogging/vaporization and UV radiation methods has been widely reported in the literature compared to other methods.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40201-024-00893-2.

Volatilomes of human infection

The human volatilome comprises a vast mixture of volatile emissions produced by the human body and its microbiomes. Following infection, the human volatilome undergoes significant shifts, and presents a unique medium for non-invasive biomarker discovery. In this review, we examine how the onset of infection impacts the production of volatile metabolites that reflects dysbiosis by pathogenic microbes. We describe key analytical workflows applied across both microbial and clinical volatilomics and emphasize the value in linking microbial studies to clinical investigations to robustly elucidate the metabolic species and pathways leading to the observed volatile signatures. We review the current state of the art across microbial and clinical volatilomics, outlining common objectives and successes of microbial-clinical volatilomic workflows. Finally, we propose key challenges, as well as our perspectives on emerging opportunities for developing clinically useful and targeted workflows that could significantly enhance and expedite current practices in infection diagnosis and monitoring.

Infection, Dysbiosis and Inflammation Interplay in the COVID Era in Children

For over three years, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in children and adolescents has generated repercussions, especially a few weeks after infection, for symptomatic patients who tested positive, for asymptomatic ones, or even just the contacts of an infected person, and evolved from severe forms such as multisystem inflammatory syndrome in children (MIS-C) to multifarious clinical manifestations in long COVID (LC). Referred to under the umbrella term LC, the onset of persistent and highly heterogeneous symptoms such as fatigue, post-exertion malaise, cognitive dysfunction, and others have a major impact on the child's daily quality of life for months. The first aim of this review was to highlight the circumstances of the pathophysiological changes produced by COVID-19 in children and to better understand the hyperinflammation in COVID-19 and how MIS-C, as a life-threatening condition, could have been avoided in some patients. Another goal was to better identify the interplay between infection, dysbiosis, and inflammation at a molecular and cellular level, to better guide scientists, physicians, and pediatricians to advance new lines of medical action to avoid the post-acute sequelae of SARS-CoV-2 infection. The third objective was to identify symptoms and their connection to molecular pathways to recognize LC more easily. The fourth purpose was to connect the triggering factors of LC with related sequelae following acute SARS-CoV-2 injuries to systems and organs, the persistence of the virus, and some of its components in hidden reservoirs, including the gut and the central nervous system. The reactivation of other latent infectious agents in the host's immune environments, the interaction of this virus with the microbiome, immune hyperactivation, and autoimmunity generated by molecular mimicry between viral agents and host proteins, could initiate a targeted and individualized management. New high-tech solutions, molecules, probiotics, and others should be discovered to innovatively solve the interplay between RNA persistent viruses, microbiota, and our immune system.

An integrated chance constraints approach for optimal vaccination strategies under uncertainty for COVID-19

Despite concerted efforts by health authorities worldwide to contain COVID-19, the SARS-CoV-2 virus has continued to spread and mutate into new variants with uncertain transmission characteristics. Therefore, there is a need for new data-driven models for determining optimal vaccination strategies that adapt to the new variants with their uncertain transmission characteristics. Motivated by this challenge, we derive an integrated chance constraints stochastic programming (ICC-SP) approach for finding vaccination strategies for epidemics that incorporates population demographics for any region of the world, uncertain disease transmission and vaccine efficacy. An optimal vaccination strategy specifies the proportion of individuals in a given household-type to vaccinate to bring the reproduction number to below one. The ICC-SP approach provides a quantitative method that allows to bound the expected excess of the reproduction number above one by an acceptable amount according to the decision-maker's level of risk. This new methodology involves a multi-community household based epidemiology model that uses census demographics data, vaccination status, age-related heterogeneity in disease susceptibility and infectivity, virus variants, and vaccine efficacy. The new methodology was tested on real data for seven neighboring counties in the United States state of Texas. The results are promising and show, among other findings, that vaccination strategies for controlling an outbreak should prioritize vaccinating certain household sizes as well as age groups with relatively high combined susceptibility and infectivity.

The moderating role of Covid-19-related support on urban livelihood capitals: Evidence from suburban Accra

In the Global South, the COVID-19 crisis has compelled varied efforts to quickly address the pandemic's impact on urban livelihoods. Families, friends as well as public, private, and civil society organizations have mobilized various resources to avert the pandemic's onslaught on the survival of the urban vulnerable. Indeed, there is a burgeoning ‘pandemic urban scholarship’ that shed insights on COVID-19 risks, local responses, and impacts on everyday urban life. Yet, it is unclear how many of these responses are affecting urban livelihoods. This paper thus investigates the impact of COVID-19 on urban livelihood capitals (financial, human, social, and physical) and analyses the moderating role of COVID-19-related support (from families, friends, government agencies, faith-based and non-governmental organizations) to address the pandemic's impact on these capitals. Drawing on a quantitative study in Adenta Municipality of the Greater Accra Region, Ghana, the study finds a negative association between COVID-19 impacts and all urban livelihood capitals. Crucially, COVID-19-related support only reduced the negative impact of the pandemic on financial capital, and not on the other forms of capital. The study suggests that building post-pandemic community resilience warrants the need to transition from the usual reactive, fragmented support to integrated, holistic, and contextually embedded long-term strategies that consider the multi-dimensionality of everyday urban life.

Structurally Different Yet Functionally Similar: Aptamers Specific for the Ebola Virus Soluble Glycoprotein and GP1,2 and Their Application in Electrochemical Sensing

The Ebola virus glycoprotein (GP) gene templates several mRNAs that produce either the virion-associated transmembrane protein or one of two secreted glycoproteins. Soluble glycoprotein (sGP) is the predominant product. GP1 and sGP share an amino terminal sequence of 295 amino acids but differ in quaternary structure, with GP1 being a heterohexamer with GP2 and sGP a homodimer. Two structurally different DNA aptamers were selected against sGP that also bound GP1,2. These DNA aptamers were compared with a 2'FY-RNA aptamer for their interactions with the Ebola GP gene products. The three aptamers have almost identical binding isotherms for sGP and GP1,2 in solution and on the virion. They demonstrated high affinity and selectivity for sGP and GP1,2. Furthermore, one aptamer, used as a sensing element in an electrochemical format, detected GP1,2 on pseudotyped virions and sGP with high sensitivity in the presence of serum, including from an Ebola-virus-infected monkey. Our results suggest that the aptamers interact with sGP across the interface between the monomers, which is different from the sites on the protein bound by most antibodies. The remarkable similarity in functional features of three structurally distinct aptamers suggests that aptamers, like antibodies, have preferred binding sites on proteins.

Impact of epidemic outbreaks (COVID-19) on global supply chains: A case of trade between Turkey and China

COVID-19 has negative impacts on supply chain operations between countries. The novelty of the study is to evaluate the sectoral effects of COVID-19 on global supply chains in the example of Turkey and China, considering detailed parameters, thanks to the developed System Dynamics (SD) model. During COVID-19 spread, most of the countries decided long period of lockdowns which impacted the production and supply chains. This had also caused decrease in capacity utilizations and industrial productions in many countries which resulted with imbalance of maritime trade between countries that increased the freight costs. In this study, cause and effect relations of trade parameters, supply chain parameters, demographic data and logistics data on disruptions of global supply chains have been depicted for specifically Turkey and China since China is the biggest importer of Turkey. Due to this disruption, mainly exports from Turkey to China has been impacted in food, chemical and mining sectors. This study is helpful to plan in which sectors; the actions should be taken by the government bodies or managers. Based on findings of this study, new policies such as onshore activities should consider to overcome the logistics and supply chain disruptions in global supply chains. This study has been presented beneficial implications for the government, policymakers and academia.

Bayesian estimation of a dynamic stochastic general equilibrium model with health disaster risk

Pandemics are not new, but they continue to prevail in the last three decades. A variety of reasons such as globalization, trade growth, urbanization, human behavior change, and the rise of the prevalence of viral diseases among animals can account for this issue. Outbreaks of COVID-19 indicated that viral diseases have spread easily among nations, influencing their economic stability. In this vein, the motivation behind the present study was to get an understanding of the effect of the rise of the health disaster risk on the dynamics of Iran's macroeconomic variables by using Bayesian Dynamic Stochastic General Equilibrium. As opposed to Computable General Equilibrium models, DSGE models can be evaluated in a stochastic environment. Since the duration of the virus outbreak and its effect on the economy is not known, it is more appropriate to use these models. The results demonstrated that increased health disaster risk has a remarkable negative effect on macroeconomic variables. According to the findings of the research and the significance of public vaccination as an essential solution for improving health status and quality of life, it was suggested that the government pave the path for the thriving of businesses and socio-economic activities as early as possible by employing specific policies such as tax exemption or budget allocation for vaccine manufacturing companies or importers.

Compact Camera Fluorescence Detector for Parallel-Light Lens-Based Real-Time PCR System

The polymerase chain reaction is an important technique in biological research. However, it is time consuming and has a number of disadvantages. Therefore, real-time PCR technology that can be used in real-time monitoring has emerged, and many studies are being conducted regarding its use. Real-time PCR requires many optical components and imaging devices such as expensive, high-performance cameras. Therefore, its cost and assembly process are limitations to its use. Currently, due to the development of smart camera devices, small, inexpensive cameras and various lenses are being developed. In this paper, we present a Compact Camera Fluorescence Detector for use in parallel-light lens-based real-time PCR devices. The proposed system has a simple optical structure, the system cost can be reduced, and the size can be miniaturized. This system only incorporates Fresnel lenses without additional optics in order for the same field of view to be achieved for 25 tubes. In the center of the Fresnel lens, one LED and a complementary metal-oxide semiconductor camera were placed in directions that were as similar as possible. In addition, to achieve the accurate analysis of the results, image processing was used to correct them. As a result of an experiment using a reference fluorescent substance and double-distilled water, it was confirmed that stable fluorescence detection was possible.

The sources of the Kuznets relationship between the COVID-19 mortality rate and economic performance

This paper discusses the findings of an empirical analysis of the Kuznets, or reverse U-shaped relationship, between the COVID-19 mortality rate and economic performance. In the early stages of economic development, the COVID-19 mortality rate is anticipated to rise with rising economic activity and urbanization. Eventually, the mortality rate decreases at higher economic development levels as people and the government are more capable of investing in disease abatement measures. The quality of political institutions, wealth distribution, urbanization, vaccination rate, and improvements in healthcare systems are hypothesized to affect the COVID-19 mortality rate. Examining this relationship can be effective in understanding the change in the COVID-19 mortality rate at different economic performance stages and in identifying appropriate preventive measures. This study employed the negative binomial regression to model a cross-sectional dataset of 137 countries. Results indicated that the relationship between the per-head gross domestic product (GDP) level and the COVID-19 mortality rate appeared to follow a pattern like the Kuznets curve, implying that changes in institutional quality, healthcare advancements, wealth distribution, urbanization, vaccination rate, and the percentage of the elderly population were significant in explaining the relationship. Improvement of the healthcare system has a notable effect on lowering the COVID-19 mortality rate under more effective government conditions. Additionally, the results suggested that a higher per-head GDP is required to reverse the rising trend of the mortality rate under higher income inequality. Based on these results, preventive measures, and policies to reduce COVID-19 mortalities were recommended in the conclusion section.

Modelling the persistence of Covid-19 positivity rate in Italy

The current Covid-19 pandemic is severely affecting public health and global economies. In this context, accurately predicting its evolution is essential for planning and providing resources effectively. This paper aims at capturing the dynamics of the positivity rate (PPR) of the novel coronavirus using the Heterogeneous Autoregressive (HAR) model. The use of this model is motivated by two main empirical features arising from the analysis of PPR time series: the changing long-run level and the persistent autocorrelation structure. Compared to the most frequently used Autoregressive Integrated Moving Average (ARIMA) models, the HAR is able to reproduce the strong persistence of the data by using components aggregated at different interval sizes, remaining parsimonious and easy to estimate. The relative merits of the proposed approach are assessed by performing a forecasting study on the Italian dataset. As a robustness check, the analysis of the positivity rate is also conducted by considering the case of the United States. The ability of the HAR-type models to predict the PPR at different horizons is evaluated through several loss functions, comparing the results with those generated by ARIMA models. The Model Confidence Set is used to test the significance of differences in the predictive performances of the models under analysis. Our findings suggest that HAR-type models significantly outperform ARIMA specifications in terms of forecasting accuracy. We also find that the PPR could represent an important metric for monitoring the evolution of hospitalizations, as the peak of patients in intensive care units occurs within 12-16 days after the peak in the positivity rate. This can help governments in planning socio-economic and health policies in advance.

Integrating GIS in reorganizing blood supply network in a robust-stochastic approach by combating disruption damages

As supplying adequate blood in multiple countries has failed due to the Covid-19 pandemic, the importance of redesigning a sensible protective-resilience blood supply chain is underscored. The outbreak-as an extensive disruption-has caused a delay in ordering and delivering blood and its by-products, which leads to severe social and financial loss to healthcare organizations. This paper presents a robust multi-phase optimization approach to model a blood supply network ensuring blood is collected efficiently. We evaluate the effectiveness of the model using real-world data from two mechanisms. Firstly, a Geographic Information System (GIS)-based method is presented to find potential alternative locations for blood donation centers to maximize availability, accessibility, and proximity to blood donors. Then, a protective mathematical model is developed with the incorporation of (a) blood perishability, (b) efficient collation centers, (c) multiple-source of suppliers, (d) back-up centers, (e) capacity limitation, and (f) uncertain demand. Emergency back-up for laboratory centers to supplement and offset the processing plants against the possible disorders is applied in a two-stage stochastic robust optimization model to maximize the level of hospitals' coverage. The results highlight the fraction cost of considering back-up facilities in the total costs and provide more resilient decisions with lower risks by examining resource limitations.

How did Italian diversified farms tackle Covid-19 pandemic first wave challenges?

The spread of the Covid-19 pandemic in Italy, in the period March-May 2020, quickly triggered a deep crisis, causing an immediate economic slowdown and consequently a strong contraction in domestic demand and trade. The food supply chain faced severe difficulties, although its anti-cyclical nature allowed for greater resilience compared to other economic sectors. In this framework of ongoing uncertainty, it is important to understand the response of farms to the crisis, and their role in the sustainability of the post-pandemic food supply chain, even for future policy interventions in the short and medium term. The purpose of the paper is to investigate how diversification affected the response of farms to the Covid-19 crisis, and explore whether the changes required by the post-crisis scenario can produce opportunities for their activities. The study investigates a sample of fifteen farms in central Italy through semi-structured interviews, performing a lexicon-based text and sentiment analysis. The results highlight the importance of farm diversification in dealing with the Covid-19 crisis, and emphasise the role of diversified farms for the sustainability of the agri-food system. These results have interesting policy implications, particularly regarding support for the competitiveness of farms by improving sustainable logistics, electronic commerce and exchanges of knowledge and innovations among farmers; these measures should be taken into account to target the future agricultural, rural and food policies, at both national and local level.

Evaluating the attitudes and behavior of Hong Kong medical students toward receiving the COVID-19 vaccine

Getting vaccinated against SARS-CoV-2 lowers the risk of severe infections. In Hong Kong, two vaccine types are offered: CoronaVac by Sinovac Biotech (Sinovac), and Comirnaty by BioNTech-Fosun Pharma (BioNTech). However, a low vaccine uptake rate is observed. This study primarily aimed to determine the population of medical students who underwent COVID-19 vaccination, and to identify factors associated with their decision on timing and vaccine type. Current medical students from The University of Hong Kong (HKU) were invited to participate in this cross-sectional survey study from 16 September to 31 December 2021. The main outcome measures were the vaccine uptake rate, primary reasons for vaccine-seeking behavior, vaccine hesitancy and vaccine preference, as well as information sources. All questions were of a multiple-choice format, with a free response option for questions pertaining to reason exploration. Overall, 214 medical students participated in the study, with all questionnaires analyzed. Amongst the 98.1% that completed 2 doses, 93.4% selected BioNTech and 6.6% selected Sinovac. Significant associations were observed between year groups and vaccine timing (p = 0.00989). The primary reason to seek vaccination was immunity against COVID-19 (53.5%), while the fear of potential side effects (61.6%) accounted for vaccine hesitancy. The BioNTech vaccine was favored for its higher efficacy against COVID-19 (87.4%). Information sources were mainly from HKU professors (64.6%) and social media (59.9%). The study found a high vaccine uptake rate amongst medical students, contrary to the situation observed in the Hong Kong general population at the time of the study.

Safety and Effectiveness of COVID-19 Vaccines: Results from a Cross-Sectional Survey among Staff, Workers and Students at an Egyptian University

Mass vaccination is the most effective strategy against the spread of the COVID-19 pandemic. However, concerns about the vaccine’s safety and effectiveness remain a huge obstacle to vaccine acceptance. The aim of the present study was to explore different COVID-19 vaccine outcomes, including the development of adverse events and/or COVID-19 infection following COVID-19 vaccination. A cross-sectional study was conducted by distributing an online survey targeting staff and students at the British university in Egypt. A total of 637 participants fully completed the survey. Of these, 609 (95.6%) participants received the COVID-19 vaccine. Only 12.6% of the total vaccinated participants reported COVID-19 infection after vaccination. Of these, only 2.8% reported having severe symptoms while 9.9% reported having no or mild symptoms. The most common side effects reported after the first vs. second dose were headache (36.3% vs. 14.6%), tiredness and fatigue (26.9% vs. 10.7), and fever (25.6% vs. 6.7%). In conclusion, the present study explored different COVID-19 vaccine outcomes where the overall incidence of side effects is higher after the first dose than after the second dose. There is a relationship between COVID-19 vaccines’ side effects and gastrointestinal disorders, gender, and the type of COVID-19 vaccine. Post-vaccination symptoms were more frequently reported in women compared to men and more frequent with viral vector vaccines compared to other types. The effectiveness of different types of COVID-19 vaccines was confirmed by the lower incidence rate of post-vaccination COVID-19 infection.

Implications of SARS-CoV-2 Infection in Systemic Juvenile Idiopathic Arthritis

Systemic juvenile idiopathic arthritis (sJIA) is a serious multifactorial autoinflammatory disease with a significant mortality rate due to macrophage activation syndrome (MAS). Recent research has deepened the knowledge about the pathophysiological mechanisms of sJIA-MAS, facilitating new targeted treatments, and biological disease-modifying antirheumatic drugs (bDMARDs), which significantly changed the course of the disease and prognosis. This review highlights that children are less likely to suffer severe COVID-19 infection, but at approximately 2–4 weeks, some cases of multisystem inflammatory syndrome in children (MIS-C) have been reported, with a fulminant course. Previous established treatments for cytokine storm syndrome (CSS) have guided COVID-19 therapeutics. sJIA-MAS is different from severe cases of COVID-19, a unique immune process in which a huge release of cytokines will especially flood the lungs. In this context, MIS-C should be reinterpreted as a special MAS, and long-term protection against SARS-CoV-2 infection can only be provided by the vaccine, but we do not yet have sufficient data. COVID-19 does not appear to have a substantial impact on rheumatic and musculoskeletal diseases (RMDs) activity in children treated with bDMARDs, but the clinical features, severity and outcome in these patients under various drugs are not yet easy to predict. Multicenter randomized controlled trials are still needed to determine when and by what means immunoregulatory products should be administered to patients with sJIA-MAS with a negative corticosteroid response or contraindications, to optimize their health and safety in the COVID era.

Data-driven test strategy for COVID-19 using machine learning: A study in Lahore, Pakistan

AIMS

We aimed at giving a preliminary analysis of the weakness of a current test strategy, and proposing a data-driven strategy that was self-adaptive to the dynamic change of pandemic. The effect of driven-data selection over time and space was also within the deep concern.

METHODS

A mathematical definition of the test strategy were given. With the real COVID-19 test data from March to July collected in Lahore, a significance analysis of the possible features was conducted. A machine learning method based on logistic regression and priority ranking were proposed for the data-driven test strategy. With performance assessed by the area under the receiver operating characteristic curve (AUC), time series analysis and spatial cross-test were conducted.

RESULTS

The transition of risk factors accounted for the failure of the current test strategy. The proposed data-driven strategy could enhance the positive detection rate from 2.54% to 28.18%, and the recall rate from 8.05% to 89.35% under strictly limited test capacity. Much more optimal utilization of test resources could be realized where 89.35% of total positive cases could be detected with merely 48.17% of the original test amount. The strategy showed self-adaptability with the development of pandemic, while the strategy driven by local data was proved to be optimal.

CONCLUSIONS

We recommended a generalization of such a data-driven test strategy for a better response to the global developing pandemic. Besides, the construction of the COVID-19 data system should be more refined on space for local applications.

Compliance with COVID-19-preventive behaviours among employees returning to work in the post-epidemic period

BACKGROUND

The COVID-19 pandemic has underscored the importance of behaviours such as social distancing in controlling pandemics. Currently, the epidemic is under control in China and production has resumed in various industries. This study investigates the behavioural compliance and related factors for COVID-19 prevention among employees returning to the workplace and provide strategic recommendations for improving individual-level preventive behaviour to prevent a new outbreak.

METHODS

A cross-sectional study design was used. Data were gathered from returning employees in China using an online questionnaire survey, from March to May, 2020. The questionnaire covered participants' COVID-19-related knowledge, compliance with recommended preventive behaviours, and levels of depression and anxiety. Univariate and multi-factor methods were used to analyse the data and identify factors influencing behaviour compliance.

RESULTS

Of the 1300 participants completing the full survey, more than half were male (71.92%) and 61% were aged between 31 and 50 years. Six hundred and ninety-eight (53.7%) participants showed high compliance, while 602 (46.3%) showed low compliance. In models adjusted for demographic and socio-economic factors, high education level (odds ratio [OR] = 0.23, 95% confidence interval [CI]: 0.07-0.70), office staff (OR = 0.51, 95% CI: 0.33-0.78), higher knowledge of COVID-19 (OR = 0.74, 95% CI: 0.67-0.81), and quarantining (OR = 0.74, 95% CI: 0.57-0.96) predicted better compliance with preventive behaviours (P <  0.05), while high anxiety levels (OR = 1.55, 95% CI: 1.10-2.18) predicted lower compliance with preventive behaviours (P <  0.05).

CONCLUSION

For employees returning to work during the post-COVID-19-epidemic period, compliance with recommended preventive behaviours requires improvement. Consequently, comprehensive intervention measures, including the provision of health education and psychological counselling, as well as the continuance of a strict isolation policy, could enhance such compliance.

The Impacts of COVID-19 and Policies on Spatial and Temporal Distribution Characteristics of Traffic: Two Examples in Beijing

The global closure policy to limit the spread of the new coronavirus (COVID-19) in 2020 was based on public safety and health considerations. In the implementation of arrangements to prevent the epidemic, the function of the transportation system as a basis for securing cities has been severely affected. After summarizing the domestic and international literature on epidemic policies and travel, this study analyzes the changes of the spatial and temporal distribution characteristics of people’s travel and the impacts in the context of the two epidemic phases in Beijing and abroad. During the epidemic, traffic volume into and out of Beijing showed a downward trend. In our study, we found that total travel volume in Beijing during the Spring Festival in 2020 was down by about 70% year-on-year, the distribution of daily traffic trips during the day was not affected by the outbreak, and six urban areas in the center of Beijing experienced greater declines in travel volume compared to other urban areas. The conclusions of the study can provide a reference for the sustainability and recovery of urban areas and formulation of policies in the subsequent pandemic era in terms of the relationship between public travel and epidemic control.

A Literature Review of Pandemics and Development: the Long-Term Perspective

Pandemics have been a long-standing object of study by economists, albeit with declining interest, that is until COVID-19 arrived. We review current knowledge on the pandemics' effects on long-term economic development, spanning economic and historical debates. We show that all economic inputs are potentially affected. Pandemics reduce the workforce and human capital, have mixed effects on investment and savings, but potentially positive consequences for innovation and knowledge development, depending on accompanying institutional change. In the absence of an innovative response supporting income redistribution, pandemics tend to increase income inequalities, worsening poverty traps and highlighting the distributional issues built into insurance-based health insurance systems. We find that the effects of pandemics are asymmetric over time, in space, and among sectors and households. Therefore, we suggest that the research focus on the theoretical plausibility and empirical significance of specific mechanisms should be complemented by meta-analytic efforts aimed at reconstructing the resulting complexity. Finally, we suggest that policymakers prioritize the development of organizational learning and innovative capabilities, focusing on the ability to adapt to emergencies rather than developing rigid protocols or mimicking solutions developed and implemented in different contexts.

Changing self-concept in the time of COVID-19: a close look at physician reflections on social media

BACKGROUND

The COVID-19 pandemic has changed the healthcare landscape drastically. Stricken by sharp surges in morbidity and mortality with resource and manpower shortages confounding their efforts, the medical community has witnessed high rates of burnout and post-traumatic stress amongst themselves. Whilst the prevailing literature has offered glimpses into their professional war, no review thus far has collated the deeply personal reflections of physicians and ascertained how their self-concept, self-esteem and perceived self-worth has altered during this crisis. Without adequate intervention, this may have profound effects on their mental and physical health, personal relationships and professional efficacy.

METHODS

With mentions of the coronavirus pervading social media by the millions, this paper set out to collate and thematically analyse social media posts containing first-person physician reflections on how COVID-19 affected their lives and their coping mechanisms. A consistent search strategy was employed and a PRISMA flowchart was used to map out the inclusion/exclusion criteria.

RESULTS

A total of 590 social media posts were screened, 511 evaluated, and 108 included for analysis. Salient themes identified include Disruptions to Personal Psycho-Emotional State, Disruptions to Professional Care Delivery, Concern for Family, Response from Institution, Response from Society and Coping Mechanisms.

CONCLUSION

It is evident that the distress experienced by physicians during this time has been manifold, multi-faceted and dominantly negative. Self-concepts were distorted with weakened self-esteem and perceived self-worth observed. The Ring Theory of Personhood (RToP) was adopted to explain COVID-19's impact on physician personhood as it considers existential, individual, relational and social concepts of the self. These entwined self-concepts serve as 'compensatory' to one another, with coping mechanisms buffering and fortifying the physician's overall personhood. With healthcare institutions playing a vital role in providing timely and targeted support, it was further proposed that a comprehensive assessment tool based on the RToP could be developed to detect at-risk physicians and evaluate the presence and effectiveness of established support structures.

Business Cycle and Public Health: The Moderating Role of Health Education and Digital Economy

The cyclicality of public health in the emerging market is underexplored in existing literature. In this study, we used a fixed effect model and provincial data to document how public health varies with the business cycle in China over the period of 2010-2019. The estimated results showed that the business cycle is negatively correlated with the mortality of infectious disease, a proxy variable of public health, thus indicating that public health exhibits a countercyclical pattern in China. Furthermore, we investigated the potential moderating role of public health education and digital economy development in the relationship between business cycle and public health. Our findings suggested that public health education and digital economy development can mitigate the damage of economic conditions on public health in China. Health education helps the public obtain more professional knowledge about diseases and then induces effective preventions. Compared with traditional economic growth, digital economy development can avoid environmental pollution which affects public health. Also, it ensures that state-of-the-art medical services are available for the public through e-health. In addition, digitalization assures that remote working is practicable and reduces close contact during epidemics such as COVID-19. The conclusions stand when subjected to several endogeneity and robustness checks. Therefore, the paper implies that these improvements in public health education and digitalization can help the government in promoting public health.

The impact of the COVID-19 pandemic on adolescents and young adults living with type 2 diabetes

Objectives

The aim of this study was to assess the impacts of the COVID-19 pandemic on adolescents and young adults living with type 2 diabetes (T2D) involved in the national Improving Renal Complications in Adolescents with T2D through REsearch (iCARE) study.

Methods

The Environmental influences on Child Health Outcomes (ECHO) COVID-19 Questionnaire developed by the National Institutes of Health ECHO COVID-19 Task Force was administered to participants (n=85) from the iCARE study between June 2020 and October 2020. Children 12 years old (via parent report) and adolescents and young adults ≥13 years old (via self-report) participated. The questionnaire assessed the impact of the pandemic on health-care appointments, lifestyle, internet use, social connections and mental health.

Results

Participants were 17.0±3.1 (range, 12 to 27) years of age and predominantly female (61.3%). During the pandemic, 69.4% were able to attend their health-care appointments by telephone or virtual platforms, 31.7% ate more, 45.1% slept more and 29.3% spent less time on physical activities. There was an increase in internet use for both educational (42.0%) and noneducational purposes (54.9%). Participants felt less socially connected (64.6%). Participants also felt sometimes (59.2%), often (19.7%) and very often (6.7%) satisfied with their lives.

Discussion

Our study revealed that the COVID-19 pandemic has had various impacts on the daily lives of adolescents and young adults living with T2D. Future research should include longitudinal studies of the health burden of the COVID-19 pandemic on this population, with a more in-depth evaluation of mental health outcomes and clinical outcomes.

Dynamic impact of negative public sentiment on agricultural product prices during COVID-19

The COVID-19 pandemic has had a significantly negative impact on public sentiment, which has resulted in panic and some irrational buying behavior, which in turn has had a complex impact on agricultural product prices. This study quantified online negative sentiment using micro-blog text mining and a time-varying parameter vector autoregressive model (TVP-VAR) to empirically analyze the dynamic impact of negative public emotions on agricultural product prices during the COVID-19 pandemic in China. It was found that the online negative sentiment impacted agricultural products prices during COVID-19 and had significant time-varying, lag, and life cycle characteristics, with the responses being most significant in the spread and recession periods. Differences were found in the price responses for different agricultural products and in different risk areas. The online negative sentiment was found to have the greatest impact on vegetable prices, with livestock products and vegetable prices being mainly positively impacted, fruit prices being mainly negatively impacted, and aquatic product prices being negatively impacted in the early stage and positively impacted in the middle and late stages. The online negative sentiment had the greatest impact on medium-risk area agricultural product prices, followed by low-risk areas, with the lowest impact found on the high-risk area agricultural product prices. Three policy suggestions for epidemic monitoring, public opinion guidance and control, and the timely release of agricultural product information are given based on the results.

Impact of COVID-19 pandemic on routine immunization

The current COVID-19 global pandemic continues to impact healthcare services beyond those directly related to the management of SARS-CoV-2 transmission and disease. We reviewed the published literature to assess the pandemic impact on existing global immunization activities and how the impact may be addressed. Widespread global disruption in routine childhood immunization has impacted a majority of regions and countries, especially in the initial pandemic phases. While data indicate subsequent recovery in immunization rates, a substantial number of vulnerable people remain unvaccinated. The downstream impact may be even greater in resource-limited settings and economically poorer populations, and consequently there are growing concerns around the resurgence of vaccine-preventable diseases, particularly measles. Guidance on how to address immunization deficits are available and continue to evolve, emphasizing the importance of maintaining and restoring routine immunization and necessary mass vaccination campaigns during and after pandemics. In this, collaboration between a broad range of stakeholders (governments, industry, healthcare decision-makers and frontline healthcare professionals) and clear communication and engagement with the public can help achieve these goals.Key messagesThe COVID-19 pandemic has a substantial impact on essential immunization activities.Disruption to mass vaccination campaigns increase risk of VPD resurgence.Catch-up campaigns are necessary to limit existing shortfalls in vaccine uptake.Guidance to mitigate these effects continues to evolve.

The Impact of the COVID-19 Pandemic on the Global Value Chain of the Manufacturing Industry

This paper adopts the GDYN model to estimate the dynamic impact of the COVID-19 pandemic on global manufacturing industry and the value chain. Our simulation finds that (1) In the short run, the low-tech manufacturing industries will suffer greater shocks, with a decline of output growth in 2021 by 6.0%. The growth rate of the high-tech manufacturing industry showed an increasing trend of 3.7% in 2021. (2) In the post-epidemic period, the total manufacturing output will return to the baseline level, from which the growth rate of low-tech manufacturing will rebound, demonstrating a V-shaped development trajectory. (3) From the perspective of Global Value Chain (GVC), the participation in GVCs of manufacturers in countries along the Belt and Road, the European Union and the United States will weaken, while China’s manufacturing industry has witnessed an obvious improvement in export competitiveness. The import added value of China has decreased, which shows that its ability to meet domestic demand has been improving. This indicates that the COVID-19 pandemic is providing a crucial opportunity for China to upgrade its manufacturing value chain, which contributes to the accelerated construction of a new dual-cycle development pattern.

Spatio-temporal characteristics and control strategies in the early period of COVID-19 spread: a case study of the mainland China

COVID-19 has caused huge impacts on human health and the economic operation of the world. Analyzing and summarizing the early propagation law can help reduce the losses caused by public health emergencies in the future. Early data on the spread of COVID-19 in 30 provinces (autonomous regions and municipalities) of mainland China except for Hubei, Hong Kong, Macao, and Taiwan were selected in this study. Spatio-temporal analysis, inflection point analysis, and correlation analysis are used to explore the spatio-temporal characteristics in the early COVID-19 spread. The results suggested that (1) the total confirmed cases have risen in an "S"-shaped curve over time, and the daily new cases have first increased and finally decreased; (2) the spatial distributions of both total and daily new cases show a trend of more in the east and less in the west, with a "multi-center agglomeration distribution" around Hubei Province and some major cities; (3) the spatial agglomeration of total confirmed cases has been increasing over time, while that of the daily new cases shows much more obvious in the mid-stage; and (4) timely release of the first-level public health emergency response can accelerate the emergence of the epidemic inflection point. The above analysis results have a specific reference value for the government's policy-making and measures to face public health emergencies.

Sustainable Determinants That Affect Tourist Arrival Forecasting

This study considers diversification effects and significant influences on tourist arrivals as a vital export direction. Different quantitative methods, namely a cointegrated-autoregressive model, panels, sentiment and sensitivity analysis, were used in this study. The time-series data for Croatia and Slovenia were isolated from several secondary sources. The variables examined in this approach are tourist arrivals, precipitations, sunny days, earthquakes, microbes and CO2 emissions. The study results showed that there is a severe negative effect on tourist arrivals defined by viruses. Moreover, there is a significant decisive effect of weather conditions on tourist arrivals. Nevertheless, it is necessary to move past Covid-19 pandemic discussions to yield more accurate tourism supply forecasts, while demand is already somehow low since the beginning of 2020. The primary significance is to develop a broader thinking about the impacts of CO2 emissions on the tourism escorted to official tourist websites.

The Impact of the First Wave of the COVID-19 Pandemic on Patients' Perceptions of Chronic Pain

PURPOSE

On 10 March 2020, Greece entered an increasingly restrictive 42-day lockdown, in order to contain the first wave of the COVID-19 pandemic. All scheduled appointments and activities of the pain clinics around the country were postponed indefinitely. The aim of this prospective study was to assess the perceived impact of the first wave of the pandemic on pain, quality of life, and access to treatment, during the first austere lockdown in Greece.

PATIENTS AND METHODS

In this cross-sectional study, 101 patients suffering from chronic pain completed a structured questionnaire. Levels of depression, anxiety, stress, personal wellbeing, optimism and personality traits were also evaluated, using the Depression, Anxiety and Stress Scale (DASS42), the Ten Item Personality Index (TIPI), the Life Orientation Test-Revised (GrLOT-R) and the Personal Wellbeing Index (PWI).

RESULTS

Despite the dramatic decrease in health care visitations before, during and after the imposed lockdown, most patients did not feel that access to pain physicians and medication was significantly affected. Higher levels of stress, anxiety, depression, neuroticism, openness to experience and general satisfaction with life seemed to be important determinant factors in how patients experienced their level, intensity and duration of pain, quality of life and response to medication.

CONCLUSION

The effects of the lockdown had a more severe impact on patients than the pandemic itself. For most, the level of their pain was not affected by the pandemic and was affected only slightly by the lockdown. Quality of life, however, was affected formost participants. Both the necessity and the complications of introducing the use of telemedicine to Greek chronic pain patients became evident during the study.

Agricultural land resource allocation to develop food crop commodities: lesson from Indonesia

This study estimates agricultural land resource allocation to develop food-crop commodities in order to safeguard food security in Indonesia in the middle of the coronavirus pandemic. The recommended commodities to be developed in Indonesia are corn, soybean, mungbean, peanut, and rice that are produced with advanced technology and input-output coefficient. There are five introduced scenarios namely, basic scenario, I, II, III, and IV. There are problems related to resource allocation such as limited resources, the ways of using it, and time constraints. In order to maintain and improve the comparative advantage of agricultural production as well as to broaden the agricultural activities, agricultural development is directed to increase business efficiency, improvements in agricultural science, technology, and human resource quality. The utilization of agricultural land resources should be well-planned for better development.

COVID-19 and energy: Influence mechanisms and research methodologies

Considering the important role of energy in modern society, it is imperative to study the current situation and future development of energy under the influence of COVID-19. This paper identifies the current research hotspots, proposes future research directions accordingly, and summarizes the methodologies via a bibliometric analysis. Five research hotspots include COVID-19 and the changes of energy consumption, COVID-19 and the fluctuation of the energy market, COVID-19 and the development of renewable energy, COVID-19 and climate impacts caused by energy consumption, and COVID-19 and the energy policy. According to the influence mechanism of COVID-19 on each hotspot, the pandemic has exerted short-term influencs on energy consumption, energy price, and air pollution. Meanwhile, the pandemic could have a far-reaching impact on the renewable energy sector, climate, and energy policy. In addition, the main methodologies are reviewed, revealing that regression analysis and scenario analysis are commonly used as the quantitative and qualitative methods, respectively. Moreover, given the nonlinear relations between the pandemic and energy, an artificial neural networks model is used to enhance the prediction efficiency of energy demand and price. Finally, policy implications for obtaining clean, low-carbon, safe, and efficient energy in the context of COVID-19 are proposed.

How Do Economic Fluctuations Affect the Mortality of Infectious Diseases?

This paper uses the mixed frequency vector autoregression model to explore the impact of economic fluctuations on infectious diseases mortality (IDM) from China perspective. We find that quarterly gross domestic product (GDP) fluctuations have a negative impact on the annual IDM, indicating that the mortality of infectious diseases varies counter-cyclically with the business cycle in China. Specifically, IDM usually increases with deterioration in economic conditions, and vice versa. The empirical results are consistent with the hypothesis I derived from the theoretical analysis, which highlights that economic fluctuations can negatively affect the mortality of infectious diseases. The findings can offer revelations for the government to consider the role of economic conditions in controlling the epidemic of infectious diseases. Policymakers should adopt appropriate and effective strategies to mitigate the potential negative effects of macroeconomic downturns on the mortality of infectious diseases. In the context of the COVID-19 pandemic, these analyses further emphasize the importance of promoting economic growth, increasing public health expenditure, and preventing and controlling foreign infectious diseases.

Socio-economic and environmental impacts of COVID-19 pandemic in Pakistan-an integrated analysis

The COVID-19 pandemic has affected about 210 countries with more than 67 million confirmed cases and over 1.5 million deaths across the globe including Pakistan. Considering the population density, health care capacity, existing poverty and environmental factors with more than 420,000 infected people and about 8300 plus mortalities, community transmission of the coronavirus happened rapidly in Pakistan. This paper analyses the short- and long-term effects of COVID-19 peak on the socio-economic and environmental aspects of Pakistan. According to the estimates, an economic loss of about 10%, i.e. 1.1 trillion PKR, will be observed in the FY 2021. Certain pandemic impediment measures like lockdowns, social distancing and travel restrictions taken by the Government have been thoroughly analysed to determine how they impacted the livelihoods of nearly 7.15 million workers. Consequently, a rise of 33.7% of poverty level is projected. While many negative impacts on primary, secondary and tertiary sectors of the economy such as agriculture, education and health care are observed, a drastic improvement in air quality index of urban centres of the country has been recorded amid lockdowns. With current economic crisis, fragile health care system and critical health literacy, a well-managed and coordinated action plan is required from all segments of the society led by the public authorities. Thorough assessment of COVID-19 scenario, management and control measures presented in this study can be assistive for the provision of policy guidelines to governments and think tanks of countries with similar socio-economic and cultural structure.

Effects of Pandemic Outbreak on Economies: Evidence From Business History Context

The coronavirus pandemic has highlighted the capitalist dysfunction showing that considering profit over people can be deadly. The study reveals the LME economies were more responsive toward the impact of the disease outbreaks as compared to the CME economies wherein the impact of the disease was moderated by the government involvement. This allows us to draw that the impact of the disease outbreaks can be moderated by increasing the involvement of the government authorities.

A Study on the Behavioral Change of Passengers on Sustainable Air Transport after COVID-19

From the perspective of the sustainability of aviation demand, we investigated passenger perceptions with regards to whether or not Korean people will resume the use of air transport after COVID-19. Based on five factors—the prevalence of COVID-19, requirements for self-isolation, circumstances at the destination, social atmosphere with regards to overseas travel, and level of preventative measures employed in the aviation service sector—a structured questionnaire was developed using confirmatory factor analysis. Based on these, the main levels of determination per factor were derived and a structured path for the recovery of aviation demand via structural equation analysis between factors was analyzed. The five factors established above were found to have a significant impact on passenger perceptions with regards to the restart of using air transport. It was found that people may consider resuming overseas travel with air transport, prior to the development of a COVID-19 cure or vaccine, corresponding to relaxed requirements for self-isolation if there is a fall in the number of confirmed cases. In addition, it was determined that the unconditional lifting of self-isolation requirements without considerations for the hygienic conditions of the destination has limitations in how much it will lead to the resumption of air travel. We hope that this study will serve as a starting point for other studies monitoring passenger behavior in the future and that it will lead to the development of sustainable strategies for recovering aviation demand.