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1.
European Journal of Biology ; 81(2):206-216, 2022.
Article in English | Scopus | ID: covidwho-2218034

ABSTRACT

Viruses are the most abundant biological entities on our planet. On the basis of parameters like capsid structure, morphology, genetic material, etc., they are classified into different families. The Coronaviridae family of viruses includes a diverse group of positive strand RNA viruses and a subset of these viruses infects humans. Though some of these human-infecting coronaviruses cause minor respiratory ailments in healthy adults but three of them are responsible for major pandemics of the 21st century. These pandemics claimed thousands to several hundred thousands of human lives and have plunged the regional economies and even the global economy into an abyss. This work highlights the current research on human coronaviruses involving their diversity, evolution, clinical, and zoonotic attributes. An economic impact analysis of major coronaviruses is also presented to point out how these pathogens have claimed billions of dollars. © 2022 by the Author(s).

2.
ARS Medica Tomitana ; 27(4):209-213, 2021.
Article in English | EMBASE | ID: covidwho-2215106

ABSTRACT

The quality of dental services is an important component in the process of oral health care and requires constant evaluation for a possible increase in it. With the SARS-COV II pandemic, dental services have suffered. The restrictions applied successively led to the closure of the dental offices, offering services to urgent cases only. Thus, throurh the questionnaire method, we formed a representative sample of the population covering a variety of professions and ages, generating a general opinion about the evaluation of the dental patients satisfaction of the services received between January 2022 and February 2022. The study group involved 151 patients. Copyright © 2021 Rosu Elena Mirela, published by Sciendo.

3.
ACM Transactions on Multimedia Computing, Communications and Applications ; 18(2 S), 2022.
Article in English | Scopus | ID: covidwho-2214024

ABSTRACT

In this paper, a brownfield Internet of Medical Things network is introduced for imaging data that can be easily scaled out depending on the objectives, functional requirements, and the number of facilities and devices connected to it. This is further used to develop a novel Content-based Medical Image Retrieval framework. The developed framework uses DenseNet-201 architecture for generating the image descriptors. Then for classification, the optimized Deep Neural Network model has been configured through a population-based metaheuristic Differential Evolution. Differential Evolution iteratively performs the joint optimization of hyperparameters and architecture of Deep Neural Networks. The competence of the proposed model is validated on three publicly available datasets: Brain Tumor MRI dataset, Covid-19 Radiography database, and Breast Cancer MRI dataset, and by comparing it with selected models over different aspects of performance evaluation. Results show that the convergence rate of the proposed framework is very fast, and it achieves at least 97.28% accuracy across all the models. © 2022 Association for Computing Machinery.

4.
International Journal of Modern Physics C: Computational Physics & Physical Computation ; : 1, 2023.
Article in English | Academic Search Complete | ID: covidwho-2214015

ABSTRACT

Early warning signs of the outbreak of pandemic disease become a high profile from the beginning and they remind more susceptible individuals to keep social distance on social occasions. However, these signs have no way to the Susceptible–Infected–Recovered (SIR) models which have been concerned by medical scientists. Warning signs imply the risk level of the pandemic disease evaluated by the government. The response of susceptible population (S-population) to the warning signs is represented by a chicken game. In order to get a better payoff, the more beneficial behavior of the S-population may be induced in the autonomous society based on the SIR model. We emphasize that participants can choose their strategies whether to follow the health rules or not without coercion in the chicken game while the warning signs released by the policy makers can encourage S-population to choose beneficial behavior, instead of purely following the healthy rules or not. The agile policy helps S-population to make a choice on the basis of risk interests but without losing to protect themselves in a serious pandemic situation. Comparing the classic SIR model with our signal-SIR model, the serious pandemic signal released by the policy makers and the disease awareness to it together play an important role in the outbreak period of the pandemic disease. [ FROM AUTHOR]

5.
IEEE Potentials ; 42(1):21-26, 2023.
Article in English | Scopus | ID: covidwho-2213357

ABSTRACT

In December 2019, the world was shaken by the discovery of a novel type of pneumonia virus that had not been observed before. The disease was caused by severe acute respiratory syndrome coronavirus 2, and the disease was officially named COVID-19 by the World Health Organization (WHO) in March 2020. Also in that month, the WHO announced that COVID-19 could be categorized as a pandemic. © 1988-2012 IEEE.

6.
4th International Conference on Inventive Research in Computing Applications, ICIRCA 2022 ; : 459-466, 2022.
Article in English | Scopus | ID: covidwho-2213285

ABSTRACT

COVID-19 diagnosis has become a crucial task in today's world due to the rapid spread of the infectious Corona Virus disease caused by the SARS-CoV-2 virus. Analysis of COVID using CT scan images is shown to give better results but it requires expert radiologists and it consumes time. Hence there is a need for a diagnosis system to classify whether it's COVID positive or not for quick and early diagnosis. Deep Learning models are effective in handling classification problems but some models might lead to vanishing gradient problem. A Mixture Density Network (i.e.) Bidirectional Long Short-Term Memory((Bi-LSTM) with Mixture Network is used as the classifier to handle the vanishing gradient problem and to classify based on the probability distribution. Parameter tuning plays a major role in improving the overall efficiency of the classifier. An Enhanced Memetic Adaptive Differential Evolution (EMADE) algorithm is proposed for tuning the parameters of the classifier. Enhanced MADE is a memetic algorithm with proposed Elite chaotic local search (ECLS) which helps in addressing the issue of getting stuck at a local optimal solution and premature convergence. The use of Elitism in the chaotic local search directs the algorithm toward the optimal solution and increases the exploitation ability. Due to high false negatives in RT-PCR, CT scan images have been taken as the input. The dataset is labeled and it consists of 1252 CT scans that are positive for COVID-19, and 1230 CT scans that are negative for COVID-19. The dataset collected from patients in Sao Paulo, Brazil that is available on Kaggle is used [21]. A sample of the dataset is taken for experimentation and an accuracy of 75.83% is achieved. The precision is 80.32% indicating that there are fewer False positive than the existing methods. © 2022 IEEE.

7.
Communications Biology ; 5(1):1376, 2022.
Article in English | MEDLINE | ID: covidwho-2212034

ABSTRACT

Little is known about SARS-CoV-2 evolution under Molnupiravir and Paxlovid, the only antivirals approved for COVID-19 treatment. By investigating SARS-CoV-2 variability in 8 Molnupiravir-treated, 7 Paxlovid-treated and 5 drug-naive individuals at 4 time-points (Days 0-2-5-7), a higher genetic distance is found under Molnupiravir pressure compared to Paxlovid and no-drug pressure (nucleotide-substitutions/site mean+/-Standard error: 18.7 x 10-4 +/- 2.1 x 10-4 vs. 3.3 x 10-4 +/- 0.8 x 10-4 vs. 3.1 x 10-4 +/- 0.8 x 10-4, P = 0.0003), peaking between Day 2 and 5. Molnupiravir drives the emergence of more G-A and C-T transitions than other mutations (P = 0.031). SARS-CoV-2 selective evolution under Molnupiravir pressure does not differ from that under Paxlovid or no-drug pressure, except for orf8 (dN > dS, P = 0.001);few amino acid mutations are enriched at specific sites. No RNA-dependent RNA polymerase (RdRp) or main proteases (Mpro) mutations conferring resistance to Molnupiravir or Paxlovid are found. This proof-of-concept study defines the SARS-CoV-2 within-host evolution during antiviral treatment, confirming higher in vivo variability induced by Molnupiravir compared to Paxlovid and drug-naive, albeit not resulting in apparent mutation selection.

8.
Cell Reports Medicine ; : 100943, 2023.
Article in English | ScienceDirect | ID: covidwho-2211656

ABSTRACT

Summary The chronic infection hypothesis for novel SARS-CoV-2 variant emergence is increasingly gaining credence following the appearance of Omicron. Here we investigate intrahost evolution and genetic diversity of lineage B.1.517 during a SARS-CoV-2 chronic infection lasting for 471 days (and still ongoing) with consistently recovered infectious virus and high viral genome copies. During the infection, we find an accelerated virus evolutionary rate translating to 35 nucleotide substitutions per year, approximately two-fold higher than the global SARS-CoV-2 evolutionary rate. This intrahost evolution result in the emergence and persistence of at least three genetically distinct genotypes suggesting the establishment of spatially structured viral populations continually reseeding different genotypes into the nasopharynx. Finally, we track the temporal dynamics of genetic diversity to identify advantageous mutations and highlight hallmark changes for chronic infection. Our findings demonstrate that untreated chronic infections accelerate SARS-CoV-2 evolution, providing an opportunity for the emergence of genetically divergent variants.

9.
Journal of Water Process Engineering ; 50, 2022.
Article in English | Web of Science | ID: covidwho-2211024

ABSTRACT

The outbreak of COVID-19 has led to the increase in face mask waste globally. In this study, face mask-derived carbocatalysts doped with nitrogen (N-Mask) were fabricated through one-step pyrolysis of 1:5 w/w mixture of face mask and urea at different temperatures to activate peroxymonosulfate (PMS) for gatifloxacin (GAT) degradation. The N-Mask prepared at 800 degrees C (N-Mask800) exhibited the highest GAT degradation rate with k(app) = 0.093 min(-1) which could be attributed to its high N doping level (17.1 wt%) and highest specific surface area (237.13 m(2) g(-1)). The relationship between k(app), catalyst loading and PMS dosage at various pHs on GAT degradation were successfully established. It was also found that the GAT degradation rate was inhibited in the sequential operating mode compared to the simultaneous operating mode. It was construed that adsorption and catalysis share the same active sites. Deterioration in catalytic performance was observed over successive cycles due to the surface chemistry change during catalysis, and difficulty in catalyst recovery after treatment. Radical scavenger study revealed that both radical and nonradical pathways were involved during GAT degradation, with nonradical pathway playing a dominant role. XPS analysis revealed that pyrrolic N and graphitic N can facilitate PMS activation via radical and nonradical pathways. Based on the LC-MS/MS analysis, the GAT degradation intermediates were identified, and the possible degradation pathways were tentatively proposed. Overall, this study demonstrated that carbocatalyst derived from face mask could be transformed into costeffective and environmentally friendly PMS activator for environmental wastewater treatment applications.

10.
Heliyon ; 8(5): e09449, 2022 May.
Article in English | MEDLINE | ID: covidwho-2178994

ABSTRACT

Pandemics are global challenges that lead to total disruption of human activities. From the inception of human existence, all pandemics have resulted in loss of human lives. The coronavirus disease caused by SAR-CoV-2 began in China and is now at the global scale with an increase in mortality and morbidity. Numerous anthropogenic activities have been implicated in the emergence and severity of pandemics, including COVID-19. These activities cause changes in microbial ecology, leading to evolution due to mutation and recombination. This review hypothesized that an understanding of these anthropogenic activities would explain the dynamics of pandemics. The recent coronavirus model was used to study issues leading to microbial evolution, towards preventing future pandemics. Our review highlighted anthropogenic activities, including deforestation, mining activities, waste treatment, burning of fossil fuel, as well as international travels as drivers of microbial evolution leading to pandemics. Furthermore, human-animal interaction has also been implicated in pandemic incidents. Our study recommends substantial control of such anthropogenic activities as having been highlighted as ways to reduce the frequency of mutation, reduce pathogenic reservoirs, and the emergence of infectious diseases.

11.
Computers in Biology and Medicine ; 152, 2023.
Article in English | Web of Science | ID: covidwho-2177832

ABSTRACT

The widespread of SARS-CoV-2 presents a significant threat to human society, as well as public health and economic development. Extensive efforts have been undertaken to battle against the pandemic, whereas effective approaches such as vaccination would be weakened by the continuous mutations, leading to considerable attention being attracted to the mutation prediction. However, most previous studies lack attention to phylo-genetics. In this paper, we propose a novel and effective model TEMPO for predicting the mutation of SARS-CoV-2 evolution. Specifically, we design a phylogenetic tree-based sampling method to generate sequence evolution data. Then, a transformer-based model is presented for the site mutation prediction after learning the high-level representation of these sequence data. We conduct experiments to verify the effectiveness of TEMPO, leveraging a large-scale SARS-CoV-2 dataset. Experimental results show that TEMPO is effective for mutation prediction of SARS-CoV-2 evolution and outperforms several state-of-the-art baseline methods. We further perform mutation prediction experiments of other infectious viruses, to explore the feasibility and robustness of TEMPO, and experimental results verify its superiority. The codes and datasets are freely available at https://github. com/ZJUDataIntelligence/TEMPO.

12.
Indian J Clin Biochem ; : 1-8, 2022.
Article in English | Web of Science | ID: covidwho-2175134

ABSTRACT

Human Coronaviruses (hCoVs) belongs to the enormous and dissimilar family of positive-sense, non-segmented, single-stranded RNA viruses. The RNA viruses are prone to high rates of mutational recombination resulting in emergence of evolutionary variant to alter various features including transmissibility and severity. The evolutionary changes affect the immune escape and reduce effectiveness of diagnostic and therapeutic measures by becoming undetectable by the currently available diagnostics and refractory to therapeutics and vaccines. Whole genome sequencing studies from various countries have adequately reported mosaic recombination between different lineage strain of SARS-CoV-2 whereby RNA dependent RNA polymerase (RdRp) gene reconnects with a homologous RNA strand at diverse position. This all lead to evolutionary emergence of new variant/ lineage as evident with the emergence of XBB in India at the time of writing this review. The continuous periodical genomic surveillance is utmost required for understanding the various lineages involved in recombination to emerge into hybrid variant. This may further help in assessing virus transmission dynamics, virulence and severity factor to help health authorities take appropriate timely action for prevention and control of any future COVID-19 outbreak.

13.
Current topics in microbiology and immunology ; 439:305-339, 2023.
Article in English | EMBASE | ID: covidwho-2173657

ABSTRACT

Coronaviruses have a broad host range and exhibit high zoonotic potential. In this chapter, we describe their genomic organization in terms of encoded proteins and provide an introduction to the peculiar discontinuous transcription mechanism. Further, we present evolutionary conserved genomic RNA secondary structure features, which are involved in the complex replication mechanism. With a focus on computational methods, we review the emergence of SARS-CoV-2 starting with the 2019 strains. In that context, we also discuss the debated hypothesis of whether SARS-CoV-2 was created in a laboratory. We focus on the molecular evolution and the epidemiological dynamics of this recently emerged pathogen and we explain how variants of concern are detected and characterised. COVID-19, the disease caused by SARS-CoV-2, can spread through different transmission routes and also depends on a number of risk factors. We describe how current computational models of viral epidemiology, or more specifically, phylodynamics, have facilitated and will continue to enable a better understanding of the epidemic dynamics of SARS-CoV-2. Copyright © 2023. The Author(s), under exclusive license to Springer Nature Switzerland AG.

14.
Springer Protocols Handbooks ; : 189-198, 2022.
Article in English | EMBASE | ID: covidwho-2173513

ABSTRACT

Canine coronavirus (CCoV) is usually the cause of mild gastroenteritis in dogs and is known to have spread worldwide. In the last decade, as a consequence of the extraordinary large RNA genome, novel recombinant variants of CCoV have been found that are closely related to feline and porcine strains. Moreover highly virulent pantropic CCoV strains were recently identified in dogs. The molecular characterization of the CCoV circulating in canine population is essential for understanding viral evolution. Copyright © Springer Science+Business Media New York 2016.

15.
16.
African Journal of Hospitality, Tourism and Leisure ; 11(SpecialEdition2):1698-1706, 2022.
Article in English | Scopus | ID: covidwho-2206487

ABSTRACT

This study's objective is to explore advertising dynamics and destination evolution in tourism promotion for Africa. A literature review approach using integrative literature method and content analysis were deployed. The results have indicated that as destinations evolve across different countries in Africa, the advertising dynamics exhibit either path dependency or path creation while other destinations display double trajectories of both path dependency and path creation in tourism promotion. The implication is for tourism stakeholders particularly destination marketing organisations to consider the advertising dynamics as their destinations evolve in the Coronavirus Disease 2019 (COVID-19) era so that repeat visitors fall back in love with tourism in Africa as well as attract first time visitors. The novelty of this paper is the contribution to knowledge in the scope of tourism in Africa by exploring advertising dynamics and destination evolution in the context of Africa tourism promotion and specifically explores forms of advertising dynamics and destination evolution in Africa's tourism promotion guided by the Evolutionary Economic Geography (EEG) theory. © 2022 AJHTL /Author(s)

17.
Journal of Engineering Research ; 10(4A):114-131, 2022.
Article in English | Web of Science | ID: covidwho-2206364

ABSTRACT

Recently, the coronavirus pandemic has caused widespread panic around the world. Modern technologies can be used to monitor and control this highly contagious disease. A plausible solution is to equip each patient who is diagnosed with or suspected of having COVID-19 with sensors that can monitor various healthcare and location parameters and report them to the desired facility to control the spread of the disease. However, the simultaneous communication of numerous sensors installed in most of an area's population results in a massive burden on existing Long-Term Evolution (LTE) networks. The existing network becomes oversaturated because it has to manage two more kinds of traffic in addition to regular traffic (text, voice, and video). Healthcare traffic is generated by many sensors deployed over a huge population, and extra traffic is generated by people contacting their family members via video or voice calls. In pandemics, e-healthcare traffic is critical and should not suffer packet loss or latency due to network overload. In this research, we studied the performance of existing networks under various conditions and predicted the severity of network degradation in an emergency scenario. We proposed and evaluated three schemes (doubling bandwidth, combining LTE-A and LTE-M networks, and request queuing) for ensuring the quality of service (QoS) of healthcare sensor (HCS) network traffic without perturbation from routine human-to-human or machine-to-machine communications. We simulated all proposed schemes and compared them with existing network scenarios. Although it is observed from the results that doubling the bandwidth serves the purpose, it is a time-consuming and expensive solution that seems non-practical in case a sudden peak occurs during an emergency. We can conclude by analyzing the simulations that the proposed queuing scheme is best-suitable under all studied scenarios where QoS for HCS traffic is never compromised, which is the ultimate goal of this research.

18.
Progress in Biochemistry and Biophysics ; 49(10):1827-1847, 2022.
Article in Chinese | Web of Science | ID: covidwho-2204240

ABSTRACT

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has posed a serious threat to international public health. The SARS-COV-2 gene continues to mutate in COVID-19 outbreaks. Mutation mainly manifests in 3 forms: point mutation, gene recombination and epigenetic modification. Viral mutations are driven by multiple factors, with mutation rates modulated at 3 levels, the nature of virus, host-virus interactions and natural selection. Therefore, it is particularly important to strengthen the monitoring of the global novel coronavirus genome and the protection of immunosuppressed populations. In the early stage of virus evolution, the mutant strains exhibit greater transmissibility and less virulence than the wild-type strain, although 5 variants of concern (VOCs) showed different stability, transmission capacity, adaptability and pathogenicity. So physical interventions need to be further strengthened. As herd immunity is established, novel mutant strains tend to mutate against vaccines and antibodies. In that case, VOCs, especially the prevailing Omicron variant, bring challenges to the prevention and control of COVID-19 worldwide. The existing and potential prevention, diagnosis and treatment approaches for COVID-19 were summarized. In the vaccination part, the protective efficacy of COVID-19 vaccine against VOCs and the factors influencing the efficacy of COVID-19 vaccine were analyzed. In the detection part, the detection methods based on nucleic acid, antigen and antibody were summarized in order to satisfy the requirements for point-of-care testing and timely recognition of novel variants. And in the treatment part, the potential therapeutic drugs and targets of SARS-CoV-2 were summarized. Drug targets are generally divided into extracellular targets and intracellular targets. In general, this review proposes possible countermeasures by analyzing the impact of mutations on global epidemic prevention and control, hoping to provide theoretical basis for possible large-scale epidemic prevention and control in the future.

19.
Journal of Applied Mathematics & Informatics ; 40(3-4):633-656, 2022.
Article in English | Web of Science | ID: covidwho-2203918

ABSTRACT

Many regions of the world are now facing the second wave of boomed cases of COVID-19. This time, the second wave of this highly infectious disease (COVID-19) is becoming more devastating. To control the existing situation, more mass testing, and tracing of COVID-19 positive individuals are required. Furthermore, practicing to wear a face mask and maintenance of physical distancing are strongly recommended for everyone. Taking all these into consideration, an optimal control problem has been reformulated in terms of nonlinear ordinary differential equations in this paper. The aim of this study is to explore the control strategy of coronavirus-2 disease (COVID-19) and thus, minimize the number of symptomatic, asymptomatic and infected individuals as well as cost of the controls measures. The optimal control model has been analyzed analytically with the help of the necessary conditions of very well-known Pontryagin's maximum principle. Numerical simulations of the optimal control problem are also performed to illustrate the results.

20.
Journal of Chinese Agricultural Mechanization ; 43(9):165-173, 2022.
Article in Chinese | Scopus | ID: covidwho-2203863

ABSTRACT

In the context of the complex international situation and novel Coronavirus pandemic, the issue of food security in China has become more important. Shaanxi province is an important agricultural production base in northwest China. It is of great significance to explore and analyze the spatial-temporal evolution characteristics and driving factors of cultivated land pressure in Shaanxi Province. This study is based on the number and distribution situation of cultivated land from 1995 to 2019 in Shaanxi, the minimum area of cultivated land per capita Sminand cultivated land pressure index P measure, to integrate the traditional difference index, establish the overall differentiation measure index of GDI, reference gravity mobile model and overall differentiation measure index of GDI describe the spatial and temporal variation characteristics of cultivated land pressure in the area. The driving factors of cultivated land pressure change were analyzed and discussed by using grey correlation analysis method. The results showed that the cultivated land area in Shaanxi province decreased firstly and then increased from 1995 to 2019. The cultivated land pressure index showed a downward trend, and remained at the level of "warning pressure" for a long time, with a small variation range. The center of cultivated land pressure in Shaanxi province was located in Guanzhong area, and moved northwestward first, then southward year by year. The spatial differentiation of cultivated land pressure in Shaanxi province was not obvious before 2003, and the state was relatively stable, and the differentiation pattern became more and more obvious after 2003. Frost-free period, precipitation, grain yield per unit, fertilizer use, income of rural residents, income of urban residents, economic development level and industrial level had significant effects on cultivated land pressure in Shaanxi Province from 1995 to 2019. © 2022 Journal of Chinese Agricultural Mechanization Editorial Office. All rights reserved.

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