ABSTRACT
The COVID-19 outbreak has contributed to a tremendous global decline in international trade flows. The rapid spread of the disease and the control measures implemented by governments to contain the virus have led to serious consequences for the global economy. The pandemic has affected the international movement of people, goods, and services. Currently, the systematic quantitative research investigating the effects of specific non-pharmaceutical intervention policy clusters on country-level international trade flows, remains limited. In this study, the Panel Vector Autoregression (PVAR) method was conducted using country-level panel data collected from various international sources including the United Nations, World Bank, and University of Oxford. The results show that stringent COVID-19 closure, social distancing, and containment measures and health-related measures, had significant negative impacts on trade flows. In contrast, economic support measures showed significant positive effects on trade. In summary, the findings suggest that policymakers should maintain less stringent containment measures related to public closure and movement restrictions and stimulate economic activities through economic support policies in order to minimize losses in trade flows during the pandemic. © 2023,ABAC Journal. All Rights Reserved.
ABSTRACT
INTRODUCTION: Since the outbreak of the COVI D-19 pandemic in December 2019, public policy debate has been increasingly focusing on developing and implementing new disease prevention measures based on tracking of geographical location, in particular during the quarantine period. Limited studies have so far investigated possible public acceptance of such measures.METHODS: We analyzed a sample data of 1,000 respondents from the 2021 Korean Social Science Data Center using descriptive statistics and logistic regression modelling. The outcome variable was the binary variable measuring the public acceptance of COVID-19 related tracking devices for people subjected to quarantine, explanatory variable included socio-economic characteristics and subjective perception measures.RESULTS: The results suggest that subjective factors, such as perceived likelihood of virus contraction (OR=1.78) and severity of the disease (OR=2.21), rather than socio-economic factors, are key determinants of public acceptance of COVID-19 related location tracking technology. Elderly participants in the middle socio-economic class have shown the highest acceptance rate for tracking device implementationCONCLUSION: Although the use of location tracking devices has been increasing exponentially, there is still limited understanding in terms of public acceptance of such devices. The results of this study contribute to identifying such determinants, this contributing to policy design related to COVID-19 prevention.
ABSTRACT
The influence of Covid-19 still persists in the world. Air traffic recovery is slow. The recovery of air transport is also influenced by the emergence of new variants of Covid-19. The Asia-Pacific region was the first to be directly affected by the Covid-19 pandemic. After a relatively strong drop in air transport in early 2020, the situation in the region has stabilized. The research is focused on the economic parameters of airlines in the Asia-Pacific region. 14 airlines were included in the research. In the evaluation process, the research focused on operating revenue, operating costs and net profit or loss. By comparing the economic indicators of airlines in the years 2018-2020, a comprehensive view of the development of economic indicators before and during the Covid-19 pandemic was created. The research shows that most airlines in the region have experienced high financial losses compared to previous years. © 2021 IEEE.
ABSTRACT
Patients with long-term effects of coronavirus disease, the so-called “long-term COVID-19 syndrome” (long-COVID-19) after SARS-CoV-2 infection, have a postponed recovery lasting from 4 weeks and up to six months, spread worldwide. Physiological predictors based on human blood biomarkers and host-virus responses to SARS-CoV-2 are still unknown. There is growing evidence about the impact of micronutrients on improving lymphocyte proliferation and their essential roles for a functioning human immune system and regulating metabolic health. This paper aims to review information about micronutrients in patients with SARS-CoV-2 infection that determines long-COVID-19 outcomes and highlight the importance of diagnostics in predictors of long-COVID-19. We reviewed articles returned from searches on PubMed/SCOPUS/Web of Science/EMBASE databases using a combination of terms “long COVID-19”, “long-term effects of COVID-19”, “post-COVID-19 symptoms”, “COVID-19 associated stress”, “micronutrients”. Evidence indicates the relationship between lymphocyte proliferation improving micronutrient level and long-COVID-19 induction. Zinc, selenium, iron, manganese have an immunomodulatory function in innate and adaptive immune responses to viral infection. Anti-inflammatory functions of Vits A and B groups include the regulation of lymphocyte proliferation and metabolic health. Further research using sampling and artificial intelligence-assisted algorithms could assist in the recognition of the correlation of micronutrients and long-COVID-19 clinical outcomes. © Sofia-Maria Karkhut, Iryna Muzyka, Maryana Savytska, Yaryna Pohoretska, Nataliya Ivanchenko, Oksana Zayachkivska, John V. Schloss, Sandor Szabo 2021.
ABSTRACT
Objective: R0, the number of cases resulting from one infectious person in a susceptible population, is a common metric in infectious disease research. Newly-developed methods for real-time approximations (Rt) offer promise for monitoring COVID-19 trends using real-world data. The objective was to compare available methods of calculating Rt and understand drivers in variability, using available regional public surveillance data. Methods: Longitudinal public health data describing infections, recoveries, and deaths from New Jersey (NJ), British Columbia (BC), and Ontario were visualized. Two methods for calculating Rt, by Cori et al. (growth in cases) and Contreras et al. (cases, recoveries, deaths), were implemented and compared. The sensitivity of estimated Rt parameter to changes in infection rates, duration of infection, and mortality rates was investigated, and the relationship with public health measures explored visually. Results: Rates of COVID-19 infections per 100,000 residents from May to December ranged from 2,856 (NJ) to 622 (BC), and total cases ranged from 253,696 (NJ) to 31,782 (BC). Using Cori et al. method, Rt estimates ranged from 0.5 to 1.5 across jurisdictions;even with large rises in incidence, estimates remained relatively stable. In contrast, Rt estimates based on Contreras et al. markedly fluctuated. Estimates for BC and Ontario were generally 0.5 to 3, but exceeded 10 for NJ for much of the observation period due to limited reporting of recoveries. Conclusions: Rt estimates for COVID-19, calculated using two recent methods, vary;and each method considers different parameters in its derivation. The Cori et al. method may be better suited to tracking COVID-19 burden in jurisdictions with incomplete recovery data reported;the choice of measure should depend on accuracy and timing of the reporting of required metrics. Accurate estimates and visualizations of Rt will be informative for understanding changing COVID-19 burden and comparing the impact of interventions across jurisdictions.
ABSTRACT
The Covid‐19 pandemic has had a significant impact on air transport in various parts of the world. The impact of the pandemic has been and still is significant within the Member States of the European Union. The introduction focused on identifying and monitoring the pandemic spread in the individual Member States. The research focused on two periods that were compared with each other based on key indicators, i.e., reproduction rate, hospitalized patients, or ICU patients. Identification and monitoring of the above‐mentioned periods were performed by an observational study of collected data mentioned below. Subsequently, an algorithm was proposed, which was to determine an index number of a given country based on key indicators mentioned earlier. The index number is an assessment of the pandemic situation in a given country. The index number calculation in the monitored periods divided the countries into two groups: countries with the index number higher than one and countries with the index number lower than one. The latter can continue using air transport by pandemic situation assessment conducted by the algorithm. The air transport utili-zation rate depends on the second part of the algorithm, where the allowed number of routes is calculated for individual airlines. The use of an algorithm for calculating the index number of individual countries and at the same time monitoring the development of key indicators every 14 days is a suitable method for ensuring the sustainable use of air transport to minimize financial losses. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
ABSTRACT
The COVID-19 pandemic outbreak has affected all sectors worldwide including aviation industry and it will take years to return to pre-crisis levels. Thousands of jobs have been lost due to the shutdown. The traffic reduction has far exceeded the level observed in events such as terror attacks of 11. September 2001 and SARS. In the course of June after months of grounded planes and thousands of cancelled flights, several European airlines are restarting their routes. However, the recovery is proceeding at a slower pace. According to ACI Europe a full recovery in passenger traffic to 2019 is now expected for 2024. © 2020 IEEE.