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1.
Kocaeli Universitesi Saglik Bilimleri Dergisi ; 8(1):6-17, 2022.
Article in Turkish | GIM | ID: covidwho-2081484

ABSTRACT

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) was identified as the agent of COVID-19, and genomic data was first shared by China on January 10, 2020. Since then, tremendous effort has been devoted to sequencing the viral genome from samples collected around the world. In the recent past, next-generation sequencing (NGS) strategies have been used successfully to trace the origins, understand the evolution of infectious agents, to investigate the chains of the spread of epidemics, to facilitate the development of effective and rapid molecular diagnostic tests, and to contribute to the research of treatments and vaccines. Recent advances in technology and science have allowed the genomes of SARS-CoV-2, the agent of COVID-19, to be sequenced within hours or days after a case is identified. In this way, for the first time, the public health and epidemic size of a pandemic can be monitored in real-time. The early sharing of SARS-CoV-2 genome sequences has allowed the rapid development of molecular diagnostic tests, contributing to global preparedness and the design of countermeasures. Rapid, large-scale sequencing of the virus genome is essential in understanding the dynamics of viral outbreaks and assessing the effectiveness of control measures. SARS-CoV-2 gene sequencing can be used in many different areas, including improved diagnosis, development of countermeasures, and investigation of disease epidemiology. The development of effective and rapid sequencing methods to fully identify the genomic sequence of the etiologic agent of COVID-19 has been fundamental to the design of diagnostic molecular tests and the determination of effective measures and strategies to reduce the spread of the pandemic. Different approaches and sequencing methods can be applied to SARS-CoV-2 genomes, as evidenced by the number of sequences available. However, each technology and sequencing approach has its advantages and limitations. In this review, current platforms and methodological approaches for sequencing SARS-CoV-2 genomes will be discussed.

2.
Chinese Journal of Virology ; 37(6):1292-1301, 2021.
Article in Chinese | GIM | ID: covidwho-2081015

ABSTRACT

Kashgar is a prefecture in Xinjiang Uygur Autonomous Region. China. Kashgar Prefecture (KP) is a land-cargo port connecting China with central Asian countries and Europe. Frequent transportation of cargo has increased the risk of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) introduction into China, which has increased the pressure on coronavirus disease-2019 (COVID-19) prevention and control. In November 2020, an imported virus-induced COVID-19 outbreak occurred in KP. To investigate the genetic characterization of SARS-CoV-2 that contaminated the trucks and containers, and the potential of border rapid logistics system to serve as carriers for SARS-CoV-2 transmission, thirty-five SARS-CoV-2-positive nucleic-acid samples collected from KP cross-border trucks and containers from 6-10 November 2020 were subjected into SARS-CoV-2 genomic sequencing and comparative analyses. The results showed that the median (minimum to maximum) Ct value of ORF1ab was 37.64 (28.91-39.81) . and that of the N gene was 36.50 (26.35-39.30), and the median (minimum to maximum) of the reads mapping ratio to SARS-CoV-2 was 51.95% (0.86%-99.31%), which indicated low viral loads in these environmental samples. Eighteen of 35 samples had genomic coverage >70%. According to the Pango nomenclature, 18 SARS-CoV-2 sequences belonged to six lineages (B.1, B.I.1, B.1.9. B.1.1.220, B.1.153 and B.1.465), three of which (B.I. B.1.1 and 8.1.153) were found in case samples from the same period of four China-neighboring countries. Analyses of nucleotide mutations and phylogenetic trees showed that the genome sequences of SARS-CoV-2 collected from the same location were similar. Four of 18 sequences were in a sub-lineage with the representative strain of COVID-19 outbreak in KP, one of which had 1 or 2 differences in nucleotide mutation sites with the strain that caused the COVID-19 outbreak in KP, which indicated high homology in the viral genome. We showed that cross-border trucks and containers were contaminated by various genotypes of SARS-CoV-2 from other countries during the outbreak in KP. and in which contained the parental virus of the KP cases. These trucks and containers served as carriers for SARS-CoV-2 introduction from other countries to cause local transmission. Our results provide important references for COVID-19 prevention-and-control strategies in border ports and tracing of outbreak sources in China.

3.
Working Paper Series National Bureau of Economic Research ; 11(15), 2022.
Article in English | GIM | ID: covidwho-2080109

ABSTRACT

Political affiliation has emerged as a potential risk factor for COVID-19, amid evidence that Republican-leaning counties have had higher COVID-19 death rates than Democrat- leaning counties and evidence of a link between political party affiliation and vaccination views. This study constructs an individual-level dataset with political affiliation and excess death rates during the COVID-19 pandemic via a linkage of 2017 voter registration in Ohio and Florida to mortality data from 2018 to 2021. We estimate substantially higher excess death rates for registered Republicans when compared to registered Democrats, with almost all of the difference concentrated in the period after vaccines were widely available in our study states. Overall, the excess death rate for Republicans was 5.4 percentage points (pp), or 76%, higher than the excess death rate for Democrats. Post- vaccines, the excess death rate gap between Republicans and Democrats widened from 1.6 pp (22% of the Democrat excess death rate) to 10.4 pp (153% of the Democrat excess death rate). The gap in excess death rates between Republicans and Democrats is concentrated in counties with low vaccination rates and only materializes after vaccines became widely available.

4.
International Journal of Public Health ; 67(June), 2022.
Article in English | GIM | ID: covidwho-2072638

ABSTRACT

This special issue contains 12 articles on COVID-19 health crisis management of different countries. Topics on different countries' responses in the management and control of the pandemic includes coping strategies, non-pharmaceutical intervention, health care management, mobility and policy response, contact tracing and health policy.

5.
Journal of Advanced Medical and Dental Sciences Research ; 8(5):71-74, 2020.
Article in English | ProQuest Central | ID: covidwho-2067484

ABSTRACT

The pandemic of Coronavirus disease (COVID-19) is matter of concern. Social stigma in the situation of health is the negative association between a person or group of people who share certain characteristics and a specific disease. The present article highlighted impact of social stigma on health and way to prevent it.

6.
Atmospheric Chemistry and Physics ; 22(19):13183-13200, 2022.
Article in English | ProQuest Central | ID: covidwho-2067020

ABSTRACT

Emission inventories are essential for modelling studies and pollution control, but traditional emission inventories are usually updated after a few years based on the statistics of “bottom-up” approach from the energy consumption in provinces, cities, and counties. The latest emission inventories of multi-resolution emission inventory in China (MEIC) was compiled from the statistics for the year 2016 (MEIC_2016). However, the real emissions have varied yearly, due to national pollution control policies and accidental special events, such as the coronavirus disease (COVID-19) pandemic. In this study, a four-dimensional variational assimilation (4DVAR) system based on the “top-down” approach was developed to optimise sulfur dioxide (SO2) emissions by assimilating the data of SO2 concentrations from surface observational stations. The 4DVAR system was then applied to obtain the SO2 emissions during the early period of COVID-19 pandemic (from 17 January to 7 February 2020), and the same period in 2019 over China. The results showed that the average MEIC_2016, 2019, and 2020 emissions were42.2×106, 40.1×106, and 36.4×106 kg d-1. The emissions in 2020 decreased by 9.2 % in relation to the COVID-19 lockdown compared with those in 2019. For central China, where the lockdown measures were quite strict, the mean 2020 emission decreased by 21.0 % compared with 2019 emissions. Three forecast experiments were conducted using the emissions of MEIC_2016, 2019, and 2020 to demonstrate the effects of optimised emissions. The root mean square error (RMSE) in the experiments using 2019 and 2020 emissions decreased by 28.1 % and 50.7 %, and the correlation coefficient increased by 89.5 % and 205.9 % compared with the experiment using MEIC_2016. For central China, the average RMSE in the experiments with 2019 and 2020 emissions decreased by 48.8 % and 77.0 %, and the average correlation coefficient increased by 44.3 % and 238.7 %, compared with the experiment using MEIC_2016 emissions. The results demonstrated that the 4DVAR system effectively optimised emissions to describe the actual changes in SO2 emissions related to the COVID lockdown, and it can thus be used to improve the accuracy of forecasts.

7.
Nonlinear Engineering ; - (1):549-557, 2022.
Article in English | ProQuest Central | ID: covidwho-2065197

ABSTRACT

There are many factors that can lead to the transmission of coronavirus disease 2019 (COVID-19), one of which is the lack of knowledge on the virus and its prevention, notably in Indonesia. This study was focused to design and build an interactive learning app for COVID-19 education. The design of this study was research and development, and in terms of the app development, it utilized the analysis, design, development, implementation, and evaluation model. The project was carried out from July to December 2021, and it involved 25 study participants. The findings of this study confirmed that the educational app consisted of education, a symptom checker, a list of vaccine information links, the latest news, and COVID-19 statistics. The validity assessment showed that the educational app in this study was very appropriate to be utilized as a digital medium for patient education. In addition, it was also confirmed that all the functions of the app worked well, and participants strongly agreed that the educational materials and features of the app were interesting and helped them to learn COVID-19 prevention easily. It could be concluded that the app could be used as a learning medium for patient education. Further studies, however, were needed to prove its effectiveness in the real clinical world.

8.
Advances in Civil Engineering ; 2022, 2022.
Article in English | ProQuest Central | ID: covidwho-2064336

ABSTRACT

Coronavirus disease (COVID-19) is a viral infection caused by the SARS-CoV-2 virus that first surfaced in December 2019. According to the World Health Organization, most persons infected with this virus suffer from mild to severe respiratory infections and recover without specific treatment or hospitalization. Some people, however, may acquire serious illnesses that need medical attention and isolation facilities. This paper investigates the use of multi-criteria decision analysis (MCDA) based on GIS technology to determine the optimal site selection for isolation hospitals for coronavirus patients in Nile Delta region in Egypt using the fuzzy analytical hierarchy process (F-AHP) and the weighted overlay tool analysis method (WOA). The research of isolation hospital site selection in Nile Delta governorates in Egypt is one of the areas that have received insufficient attention due to the current global coronavirus epidemic. Several criteria are applied to identify and select the isolation hospital location, including World Health Organization regulations, Egyptian Ministry of Health conditions, previous research studies, and field visits. Geodatabase is created using ArcGIS Pro software, and manual digitization is done. As a conclusion of the study, numerous additional optimal sites for isolated hospitals have been found and chosen. There are around 29 proposed ideal sites for isolated hospitals utilizing F-AHP and approximately 24 sites using WOA approach in Nile Delta region. These planned hospital locations might be permanent as a central hospital or temporary, to be relocated after the epidemic is over. The paper emphasizes the need to use the study criteria while selecting and defining the location of coronavirus isolation hospitals.

9.
Complexity ; 2022, 2022.
Article in English | ProQuest Central | ID: covidwho-2064333

ABSTRACT

We propose a theoretical study to investigate the spread of the SARS-CoV-2 virus, reported in Wuhan, China. We develop a mathematical model based on the characteristic of the disease and then use fractional calculus to fractionalize it. We use the Caputo-Fabrizio operator for this purpose. We prove that the considered model has positive and bounded solutions. We calculate the threshold quantity of the proposed model and discuss its sensitivity analysis to find the role of every epidemic parameter and the relative impact on disease transmission. The threshold quantity (reproductive number) is used to discuss the steady states of the proposed model and to find that the proposed epidemic model is stable asymptotically under some constraints. Both the global and local properties of the proposed model will be performed with the help of the mean value theorem, Barbalat’s lemma, and linearization. To support our analytical findings, we draw some numerical simulations to verify with graphical representations.

10.
Discrete Dynamics in Nature and Society ; 2022, 2022.
Article in English | ProQuest Central | ID: covidwho-2064325

ABSTRACT

Africa’s first COVID-19 case was recorded in Egypt on February 14, 2020. Although it is not as expected by the World Health Organization (WHO) and other international organizations, currently a large number of Africans are getting infected by the virus. In this work, we studied the trend of the COVID-19 outbreak generally in Africa as a continent and in the five African regions separately. The study also investigated the validity of the ARIMA approach to forecast the spread of COVID-19 in Africa. The data of daily confirmed new COVID-19 cases from February 15 to October 16, 2020, were collected from the official website of Our World in Data to construct the autoregressive integrated moving average (ARIMA) model and to predict the trend of the daily confirmed cases through STATA 13 and EViews 9 software. The model used for our ARIMA estimation and prediction was (3, 1, 4) for Africa as a continent, ARIMA (3, 1, 3) for East Africa, ARIMA (2, 1, 3) for West Africa, ARIMA (2, 1, 3) for Central Africa, ARIMA (1, 1, 4) for North Africa, and ARIMA (4, 1, 5) for Southern Africa. Finally, the forecasted values were compared with the actual number of COVID-19 cases in the region. At the African level, the ARIMA model forecasted values and the actual data have similar signs with slightly different sizes, and there were some deviations at the subregional level. However, given the uncertain nature of the current COVID-19 pandemic, it is helpful to forecast the future trend of such pandemics by employing the ARIMA model.

11.
Journal of Mathematics ; 2022, 2022.
Article in English | ProQuest Central | ID: covidwho-2064324

ABSTRACT

The major goal of this study is to create an optimal technique for managing COVID-19 spread by transforming the SEIQR model into a dynamic (multistage) programming problem with continuous and discrete time-varying transmission rates as optimizing variables. We have developed an optimal control problem for a discrete-time, deterministic susceptible class (S), exposed class (E), infected class (I), quarantined class (Q), and recovered class (R) epidemic with a finite time horizon. The problem involves finding the minimum objective function of a controlled process subject to the constraints of limited resources. For our model, we present a new technique based on dynamic programming problem solutions that can be used to minimize infection rate and maximize recovery rate. We developed suitable conditions for obtaining monotonic solutions and proposed a dynamic programming model to obtain optimal transmission rate sequences. We explored the positivity and unique solvability nature of these implicit and explicit time-discrete models. According to our findings, isolating the affected humans can limit the danger of COVID-19 spreading in the future.

12.
IOP Conference Series. Materials Science and Engineering ; 1254(1):012028, 2022.
Article in English | ProQuest Central | ID: covidwho-2062811

ABSTRACT

Some of the most common chronic respiratory diseases, incapacitating the development and quality of life of patients and directly correlated with oro-dental cavity are represented by asthma and chronic obstructive pulmonary disease (CPOD), a chronic inflammatory disease affecting the airways, in which mast cells, eosinophils and T lymphocytes, play an important role [1]. A better understanding of the diagnosis and treatment of these pathology became possible by accepting that the existence of chronic inflammation, with its variations, is reflected in the clinical condition of the elderly patients, with implications on the dental status. Therefore, the present research, using respiratory biomedical explorations, wants to establish a clinical and functional correlation in the case of elderly patients with respiratory diseases and who associate oro-dental pathologies. In the current conditions, in which the predominant viral damage is SARS-COV 2 infection, it is necessary to develop a clinical-functional algorithm to quickly establish a subsequent evolution and prognosis of elderly patients, which involve an increased predisposition to morbidity and mortality.

13.
IOP Conference Series. Materials Science and Engineering ; 1253(1):012013, 2022.
Article in English | ProQuest Central | ID: covidwho-2062810

ABSTRACT

Desertion can be understood as the withdrawal and subsequent abandonment of school activity by students, due to different family, economic, social and other factors. All educational levels are affected by this scourge, being the university one of the most affected, especially during this time of pandemic caused by the SARS-CoV 19 virus. Due to the complexity of this problem, and the great impact it has generated at the educational level, many universities have proposed different intervention strategies to reduce dropout rates. The difficulty is that many of these strategies lack effectiveness, since they do not take into account the different causes, which are different for each case. On the other hand, it is important to have accurate and reliable information to determine the population in order to identify possible cases of dropout, and to take preventive actions to reduce the student dropout rate. In this sense, the purpose of this study is to analyze different predictive algorithms based on Machine Learning that enable early detection of possible cases of desertion in the Faculty of Engineering at the Corporación Universitaria Antonio José De Sucre. Among such algorithms we can mention decision trees, logistic regression and support vector machines. These will be trained with historical data and then tested to determine their performance, to finally choose the most appropriate within the context of the current problem.

14.
IOP Conference Series. Earth and Environmental Science ; 1083(1):012027, 2022.
Article in English | ProQuest Central | ID: covidwho-2062802

ABSTRACT

Covid-19 virus began in December 2019, and the coronavirus (COVID-19) has impacted several countries, affecting more than 90,000 patients and making it a global pandemic. Where health workers include doctors, nurses, and other health workers, play a role in treating infected patients and become the vanguard in the handling of coronavirus. Based on data Indonesia positive cases of Covid-19 as many as 3,872,738 people and patients recovered 3,381,884 people and patients who died as many as 118,883 people and 48.3% of the cases of COVID-19 patients in Indonesia are elderly. The actual SARS-CoV-2 outbreak caused a highly transmissible disease with a tremendous impact on elderly people. This study focused on very elderly patients (over 80 years old) was created with the aim of analyzing the relationship of some diseases in the elderly that affect covid-19 at Royal Prima Hospital Medan in 2020, And the conclusion of this study based statistically shows that there is no link between DM, heart and kidney diseases in the elderly that affect covid-19, as well as the presence of hypertensive disease and ARI in the elderly that affects covid-19.

15.
CAB Abstracts; 2022.
Preprint in English | CAB Abstracts | ID: ppcovidwho-345451

ABSTRACT

Background: Over 50 million cases of COVID-19 have been confirmed globally as of November 2020. Evidence is rapidly emerging on the epidemiology of COVID-19, and its impact on individuals and potential burden on health services and society. Between 10-35% of people with COVID-19 may experience post-acute long Covid. This currently equates to between 8,129 and 28,453 people in Scotland. Some of these people will require rehabilitation to support their recovery. Currently, we do not know how to optimally configure community rehabilitation services for people with long Covid.

16.
International Journal of Innovation and Applied Studies ; 37(4):882-889, 2022.
Article in Urdu | ProQuest Central | ID: covidwho-2058006

ABSTRACT

Coronavirus 2019 is considered the disease of the century. It has caused worldwide panic. The practices of health professionals have been a challenge to cope with this disease and stop the spread of the pandemic. Objectives: The present study aims to describe the preventive measures applied by health professionals and their experience in dealing with COVID-19. Methods: This study was conducted in April and May 2020 in central Morocco, at the «Sidi Said» hospital in Meknes, which is reserved for the care of people affected by COVID-19. An exploratory survey was conducted among all the caregivers working in this hospital. A self-administered questionnaire was used to collect the data, which were processed and statically analysed by Epi-info. Results: A total of 104 (73.5%) participants took part in the study. Most of them (70%) were women. More than half were nurses (59%). The majority (84%) received the COVID-19 vaccine. We found that the majority of caregivers had good knowledge about COVID-19 and about 43% of them received clinical simulation coaching. The most commonly used preventive measures to combat the pandemic were wearing masks (100%), hand washing and disinfection (96%), wearing gloves (81%) and face shields (64%). Conclusions: Health professionals have a good knowledge of Covid19, the correct use of protective equipment, hand hygiene and maintenance of the premises where the approach adopted by health care workers to control Covid19. However, raising awareness among citizens remains a key strategy for eliminating this pandemic.

17.
Journal of Clinical and Basic Research ; 6(1):37-45, 2022.
Article in English | GIM | ID: covidwho-2057220

ABSTRACT

Background and objectives: The coronavirus disease 2019 (COVID-19) pandemic is one of the most important healthcare and social challenges. The aim of this study was to evaluate the effect of acceptance and commitment therapy (ACT) on depression and quality of life among women with chronic pain during the COVID-19 pandemic lockdown.

18.
Journal of Clinical and Basic Research ; 6(1):11-27, 2022.
Article in English | CAB Abstracts | ID: covidwho-2057219

ABSTRACT

Coronavirus disease 2019 (COVID-19) is a severe acute respiratory disease with a high prevalence. According to the research and statistical data, in January 2021, there have been 92,262,621 confirmed cases of COVID-19 and more than two million deaths. Infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the main cause of this disease. In addition to the respiratory system, the disease affects the gastrointestinal tract, central-peripheral nervous system, circulatory system, and kidneys. Therefore, any therapeutic action to reduce COVID-19-related symptoms and complications is essential. In this study, we conducted a systematic review of the published literature and preprints on the efficacy of erythropoietin (EPO) and recombinant human EPO as a safe stimulant and tissue protector in the treatment of COVID-19. We also briefly described the structure of coronavirus, its pathogenesis, and the structure of EPO and recombinant human EPO. All relevant articles published in the Science Direct, PubMed, and Google Scholar databases were searched. According to the results, EPO is a cytoprotective cytokine induced by hypoxia. The pleiotropic effects of EPO are associated with its erythrocyte-forming, anti-apoptotic, anti-inflammatory activities. It also exerts protective effects on the heart, lungs, kidneys, arteries, and central and peripheral nervous systems. It has been demonstrated that EPO can increase hemoglobin levels, thereby increasing oxygen delivery to the tissues. Therefore, recombinant human EPO therapy can be used for counteracting the adverse effects of COVID-19 including hypoxic myocarditis, acute renal failure, pulmonary edema, and brain-spinal cord ischemic injury. Overall, the use of EPO and recombinant human EPO therapy increases blood coagulation, tumor growth, thromboembolism, and purification of red blood cells, which must be accompanied by anticoagulants such as heparin.

19.
Journal of Guilan University of Medical Sciences ; 30(2), 2021.
Article in Persian | CAB Abstracts | ID: covidwho-2057029

ABSTRACT

The current study sought to examine the clinical, laboratory, and imaging aspects of COVID-19-positive critically sick patients who were admitted to the intensive care units (ICUs) at three hospitals in Rash City, Iran. The goal of this retrospective study was to examine 138 COVID-19 patients who had been hospitalized to the intensive care unit. Data on the study participants' demographics, underlying diseases, laboratory and imaging results, and prognosis of the diseases were taken from their medical records. 138 COVID-19 patients who were hospitalised to the intensive care unit were the subject of this retrospective analysis. Patient records were used to extract information about the patient, including demographic details, underlying diseases, laboratory and imaging results, and disease outcomes. The majority of the patients in this study were male and between the ages of 55 and 69. The most prevalent underlying conditions were diabetes mellitus, hypertension, and chronic heart disease;the most prevalent symptoms were shortness of breath, fever, and cough. The most prevalent lung Computer Tomography (CT) scan finding was ground glass opacities, and the most frequent laboratory findings in the study participants were an increase in LDH, ESR, CRP, neutrophil percentage, and lymphopenia. A 90.58% fatality rate was recorded. This study showed that the majority of patients with severe disease presentations were older, had a history of underlying disease, symptoms of shortness of breath, cough, and fever, substantial lung involvement in imaging, and altered laboratory findings. Despite medical treatment and mechanical ventilation, mortality remained high.

20.
International Journal of Advances in Intelligent Informatics ; 8(2):224-236, 2022.
Article in English | ProQuest Central | ID: covidwho-2056919

ABSTRACT

Coronavirus disease 19 (Covid-19) is a pandemic disease that has already killed hundred thousands of people and infected millions more. At the climax disease Covid-19, this virus will lead to pneumonia and result in a fatality in extreme cases. COVID-19 provides radiological cues that can be easily detected using chest X-rays, which distinguishes it from other types of pneumonic disease. Recently, there are several studies using the CNN model only focused on developing binary classifier that classify between Covid-19 and normal chest X-ray. However, no previous studies have ever made a comparison between the performances of some of the established pre-trained CNN models that involving multi-classes including Covid-19, Pneumonia and Normal chest X-ray. Therefore, this study focused on formulating an automated system to detect Covid-19 from chest X-Ray images by four established and powerful CNN models AlexNet, GoogleNet, ResNet-18 and SqueezeNet and the performance of each of the models were compared. A total of21,252 chest X-ray images from various sources were pre-processed and trained for the transfer learning-based classification task, which included Covid-19, bacterial pneumonia, viral pneumonia, and normal chest x-ray images. In conclusion, this study revealed that all models successfully classify Covid-19 and other pneumonia at an accuracy of more than 78.5%, and the test results revealed that GoogleNet outperforms other models for achieved accuracy of 91.0%, precision of 85.6%, sensitivity of 85.3%, and F1 score of 85.4%.

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