Parichehr Zamani Fard; Ahmad Goudarzi
Abstract
The high rate of outbreaks of the Coronavirus Disease 2019 (QUID-19) is a warning about health, economic, and social issues that are affecting the whole world. The COVID-19 pandemic has had many financial and economic implications worldwide. These economic turbulences, along with market uncertainty, ...
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The high rate of outbreaks of the Coronavirus Disease 2019 (QUID-19) is a warning about health, economic, and social issues that are affecting the whole world. The COVID-19 pandemic has had many financial and economic implications worldwide. These economic turbulences, along with market uncertainty, can affect investors' confidence in firms' financial performance and, consequently, may lead to various financial crises. Audit quality can affect the auditors' ability to detect material misstatements. This study is conducted to investigate the effect of COVID-19 on audit quality during social distancing in companies listed on the Tehran Stock Exchange. This is an applied study in terms of purpose and a descriptive-comparative one in terms of method. In the study, one main hypothesis and five sub-hypotheses were developed, and the Kruskal-Wallis test with SPSS software was used. The statistical population included companies listed on the Tehran Stock Exchange from 2017 to 2020. The findings suggest that COVID-19 affects audit quality during social distancing in companies listed on the Tehran Stock Exchange.
Mohammad Alipour-Vaezi; Reza Tavakkoli-Moghadaam; Mina Samieinasab
Abstract
Since human societies have endured massive financial disruptions and life losses after the outbreak of the COVID-19 pandemic, it is critical to eliminate this disease as soon as possible. Today, the invention of the COVID-19 vaccine made this objective more reachable. But unfortunately, the suppliant ...
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Since human societies have endured massive financial disruptions and life losses after the outbreak of the COVID-19 pandemic, it is critical to eliminate this disease as soon as possible. Today, the invention of the COVID-19 vaccine made this objective more reachable. But unfortunately, the suppliant of the vaccines is limited. Hence, to prevent further lethal harms, it seems rational to use a scientific method for vaccine allocation. This study proposes a method for prioritizing the patients based on their level of life-threatening danger according to the proven risk factors (e.g., age, sex, pregnancy, and underlying diseases) of the COVID-19. That is a new data-driven decision-making method for patients’ classification based on their health condition information using several machine learning algorithms. In this method, vaccine applicants are classified into four classes. The scheduling of vaccine distribution would be conducted based on the results of this classification. Furthermore, a real-life case study is also investigated through the proposed method for better illumination in this paper. The vaccine distribution schedule of the real-case study has been performed with 94% accuracy. It should be mentioned that the main achievement of this research is to design a new efficient method for a vaccine distribution schedule.
Nazila Adabavazeh; Mehrdad Nikbakht; Alireza Amirteimoori
Abstract
Communities are constantly seeking to manage the damages which are caused by crises. In this regard, health centers have become the most expensive unit of the health system as they provide quick and timely health care services to reduce the effects of unexpected accidents. So, their planning and preparation ...
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Communities are constantly seeking to manage the damages which are caused by crises. In this regard, health centers have become the most expensive unit of the health system as they provide quick and timely health care services to reduce the effects of unexpected accidents. So, their planning and preparation should be considered as an important part of strategic health policies. The purpose of this study is to investigate performance evaluation techniques for health units, which is helpful for WHO to identify the capabilities of crisis management and the limitations of world health units. This study evaluates the performance of the world health systems dealing with Corona-virus based on parametric and nonparametric statistical techniques according to "Population, GPD Per Capita, Total Recovered, Total Cases, and Total Deaths". This descriptive cross-sectional study is performed on the World Population Review, Worldometer, WHO data of Covid-19 from 1 March -11 April 2020. Based on the results, the efficient and inefficient health system units are identified. The results of this study show that 52 medical centers have not performed efficiently. The average efficiency of inefficient units is 0.30. On this basis, most of the studied countries do not operate efficiently due to the lack of optimal use of resources. Ineffective health system units call for greater attention of WHO in promoting health culture during the crisis management of common viruses. Therefore, there is a capacity to improve efficiency by 70%. By conducting this research, in addition to the introduction of functional patterns to the top health managers, it is possible to plan more accurately to develop the capacity of health care services and save resources.