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In the present paper, a reaction-diffusion epidemic mathematical model is proposed for the analysis of the transmission mechanism of the novel coronavirus disease 2019 (COVID-19). The mathematical model contains six-time and space-dependent classes, namely; Susceptible, Exposed, Asymptomatically infected, Symptomatic infected, Quarantine, and Recovered or Removed (SEQIaIsR). The threshold number R0 is calculated by utilizing the next-generation matrix approach. Values of the parameters are estimated with the help of the least square curve fitting tools. In addition to the simple explicit procedure, the mathematical epidemiological model with diffusion is simulated through the operator splitting approach based on finite difference and meshless methods. Stability analysis of the disease free and endemic equilibrium points of the model is investigated. Simulation results of the model with and without diffusion are presented in detail. A comparison of the obtained numerical results of both the models is performed in the absence of an exact solution. The correctness of the solution is verified through mutual comparison and partly, via theoretical analysis as well.
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The study of COVID-19 pandemic which paralyzed global economy of countries is a crucial research area for effective future planning against other epidemics. Unfortunately, we now have variants of the disease resulting to what is now known as waves of the pandemic. Several mathematical models have been developed to study this disease. While recent models incorporated control measures, others are without optimal control measures or demographic parameters. In this study, we propose a deterministic compartmental epidemiological model to study the transmission dynamic of the spread of the third wave of the pandemic in Nigeria, and we incorporated optimal control measures as strategies to reduce the burden of the deadly disease. Specifically, we investigated the transmission dynamics of COVID-19 model without demographic features. We then conducted theoretical analysis of the model with and without optimal control strategy. In the model without optimal control, we computed the reproduction number, an epidemiological threshold useful for bringing the third wave of the pandemic under check in Nigeria, and we proofed the disease stability and conducted sensitivity analysis in order to identify parameters that can impact the reproduction number tremendously. In a similar reasoning, for the model with control strategy, we check the necessary condition for the model. To validate our theoretical analyses, we illustrated the applications of the proposed model using COVID-19 data for Nigeria for a period when the country was under the yoke of the third wave of the disease. The data were then fitted to the model, and we derived a predictive tool toward making a forecast for the cumulative number of cases of infection, cumulative number of active cases and the peak of the third wave of the pandemic. From the simulations, it was observed that the presence of optimal control parameters leads to significant impact on the reduction of the spread of the disease. However, it was discovered that the success of the control of the disease relies on the proper and effective implementation of the optimal control strategies efficiently and adequately.
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A new co-infection model for the transmission dynamics of two virus hepatitis B (HBV) and coronavirus (COVID-19) is formulated to study the effect of white noise intensities. First, we present the model equilibria and basic reproduction number. The local stability of the equilibria points is proved. Moreover, the proposed stochastic model has been investigated for a non-negative solution and positively invariant region. With the help of Lyapunov function, analysis was performed and conditions for extinction and persistence of the disease based on the stochastic co-infection model were derived. Particularly, we discuss the dynamics of the stochastic model around the disease-free state. Similarly, we obtain the conditions that fluctuate at the disease endemic state holds if min ( R H s , R C s , R HC s ) > 1 . Based on extinction as well as persistence some conditions are established in form of expression containing white noise intensities as well as model parameters. The numerical results have also been used to illustrate our analytical results.
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This paper presents and investigates a new fractional discrete COVID-19 model which involves three variables: the new daily cases, additional severe cases and deaths. Here, we analyze the stability of the equilibrium point at different values of the fractional order. Using maximum Lyapunov exponents, phase attractors, bifurcation diagrams, the 0-1 test and approximation entropy (ApEn), it is shown that the dynamic behaviors of the model change from stable to chaotic behavior by varying the fractional orders. Besides showing that the fractional discrete model fits the real data of the pandemic, the simulation findings also show that the numbers of new daily cases, additional severe cases and deaths exhibit chaotic behavior without any effective attempts to curb the epidemic.
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This paper deals with the Bayesian estimation of the parameters of a discrete fractional epidemic model SEIRD as an extension of the classical SEIR model, describing the dynamics of disease propagation in a population. Equilibrium points are computed and the existence stability nature at these points are discussed. The basic reproduction number R0 is calculated using next generation matrix method. The estimation of the parameters is based on Bayesian inference. The numerical simulations were used to illustrate the stability of the discrete fractional order SEIRD epidemic model and to evaluate the performance of the estimation method. The model introduced is applied to real data concerning pandemic COVID-19 in Morocco. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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This paper developed a factor-based robust approach to improve the tracking fund's stability. Similar to the financial crisis, the recent coronavirus pandemic amplify the global market volatility significantly, which suggests that healthcare-based factor can be used to hedge against the jump risk. The index tracking fund is constructed by a developed cardinality constrained conic programming. To overcome the large-scale computational challenge, we decompose the problem into two simplified cases and quickly calculate the tighter lower bound and its feasible upper bound. In addition, a subgradient-based inequalities are derived to exclude the suboptimal points that have been traveled in previous iterations. It turns out that the proposed model, along with the designed solving technique, can be used as an alternative to build reliable tracking portfolios. We demonstrate the effectiveness and robustness of the proposed method by testing different large real data sets. © 2022 Elsevier Ltd
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A fast procedure obtained by the combination of fabric phase extraction (FPSE) with high performance liquid chromatography (HPLC) has been developed and validated for the quantification of favipiravir (FVP) in human plasma and breast milk. A sol-gel polycaprolactone-block-polydimethylsiloxane-block-polycaprolactone (sol-gel PCAP-PDMS-PCAP) coated on 100% cellose cotton fabric was selected as the most efficient membrane for FPSE in human plasma and breast milk samples. HPLC-UV analysis were performed using a RP C18 column under isocratic conditions. Under these optimezed settings, the overall chromatographic analysis time was limited to only 5 min without encountering any observable matrix interferences. Following the method validation procedure, the herein assay shows a linear calibration curve over the range of 0.2–50 µg/mL and 0.5–25 µg/mL for plasma and breast milk, respectively. The method sensitivities in terms of limit of detection (LOD) and limit of quantification (LOQ), validated in both the matrices, have been found to be 0.06 and 0.2 µg/mL for plasma and 0.15 and 0.5 µg/mL for milk, respectively. Intraday and interday precision and trueness, accordingly to the International Guidelines, were validated and were below 3.61% for both the matrices. The herein method was further tested on real samples in order to highlight the applicability and the advantage for therapeutic drug monitoring (TDM) applications. To the best of our knowledge, this is the first validated FPSE-HPLC-UV method in human plasma and breast milk for TDM purposes applied on real samples. The validated method provides fast, simple, cost reduced, and sensitive assay for the direct quantification of favipiravir in real biological matrices, also appliyng a well-known rugged and cheap instrument configuration. © 2022 Elsevier B.V.
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In this paper we demonstrate a new conceptual framework in the application of multilayer perceptron (MLP) artificial neural networks (ANNs) to bankruptcy risk prediction using different time-delay neural network (TDNN) models to assess Altman's EM Z″-score risk zones of firms for a sample of 100 companies operating in the hotel industry in the Republic of Serbia. Hence, the accuracies of 9580 forecasting ANNs trained for the period 2016 to 2021 are analyzed, and the impact of various input parameters of different ANN models on their forecasting accuracy is investigated, including Altman's bankruptcy risk indicators, market and internal nonfinancial indicators, the lengths of the learning periods of the ANNs and of their input parameters, and the K-means clusters of risk zones. Based on this research, 11 stability indicators (SIs) for the years under analysis are formulated, which represent the generalization capabilities of ANN models, i.e., differences in the generalization errors between the preceding period and the year for which zone assessment is given;these are seen as a consequence of structural changes at the industry level that occurred during the relevant year. SIs are validated through comparison with the relative strength index (RSI) for descriptive indicators of Altman's model, and high correlation is found. Special focus is placed on the identification of the stability in 2020 in order to assess the impact of the COVID-19 crisis during that year. It is established that despite the fact that the development of bankruptcy risk in the hotel industry in the Republic of Serbia is a highly volatile process, the largest changes in the analyzed period occurred in 2020, i.e., the potential applications of ANNs for forecasting zones in 2020 are limited. © 2022 by the authors.
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The main aim of this paper is to construct a mathematical model for the spread of SARS-CoV-2 infection. We discuss the modified COVID-19 and change the model to fractional order form based on the Caputo-Fabrizio derivative. Also several definitions and theorems of fractional calculus, fuzzy theory and Laplace transform are illustrated. The existence and uniqueness of the solution of the model are proved based on the Banach's unique fixed point theory. Moreover Hyers-Ulam stability analysis is studied. The obtained results show the efficiency and accuracy of the model. © 2023 the Author(s), licensee AIMS Press.
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This study examines the effects of the COVID-19 outbreak on the performance and stability of the banking sector. Our sample consists of 2073 banks in 106 countries from 2016Q1 to 2021Q2. We employ several alternative bank performance and stability measures for a comprehensive analysis and robustness. The findings show that the COVID-19 outbreak has significantly reduced bank performance and stability. These results are consistently observed across several geographical regions and countries' income classifications. Additional analysis shows that the adverse impact of COVID-19 depends on the characteristics of the bank and market structure. While a better regulatory environment, institutional quality, and financial development have significantly increased the strength and resilience of banks. These findings provide practical implications for regulators and policymakers in the face of unprecedented uncertainty caused by the COVID-19 pandemic. © 2023 Elsevier B.V.
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Our investigation of 46 conventional and 22 Islamic banks from the Gulf Cooperation Council (GCC) countries during 2008–2021 reveals that sectoral diversification effects on stability are nonlinear and different for the two bank types. While Islamic banks' stability is worsened only by moderate levels of diversification, conventional banks' stability is enhanced by high levels and impaired by low levels of diversification. Furthermore, diversification acted as a stabilizer during the global financial crisis but exacerbated the adverse effects of the Covid-19 pandemic. Although regulators usually call for bank diversification, our results imply that it can be a double-edged sword. © 2022
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This paper presents the three species mathematical models in which the interaction of two preys-one predator where the virus will affected the healthy species under some mutual interference with handling time using Beddington De Angelis FR. The motive of this work is to interaction among healthy (susceptible) prey, infected prey and predator to minimize the spread of disease. Boundedness, Equilibrium points, check the periodic solution and analyse the stability with numerical examples using maple software of Rossler type. Finally the result of this model prey predator of the SI type using numerical simulations.
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The study explores the dynamics of a COVID-19 epidemic in multiple susceptible populations, including the various stages of vaccination administration. In the model, there are eight human compartments: completely susceptible;susceptible with dose-1 vaccination;susceptible with dose-2 vaccination;susceptible with booster dose vaccination;exposed;infected with and without symptoms, and recovered compartments. The biological feasibility of the model is analysed. The threshold value, R0, is derived using the next-generation matrix. The stability analysis of the equilibrium points was performed locally and globally using the threshold parameter of the model. The conditions determining disease persistence is obtained. The model is subjected to sensitivity analysis, and the most sensitive parameters are identified. Also, MATLAB is used to verify the mathematical outcomes of the system's dynamic behaviour and suggests that necessary steps should be taken to keep the spread of the omicron variant infectious disease under control. The findings of this study could aid health officials in their efforts to combat the spread of COVID-19. © 2022 International Association for Mathematics and Computers in Simulation (IMACS)
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Several mathematical models have been developed to investigate the dynamics SARS-CoV-2 and its different variants. Most of the multi-strain SARS-CoV-2 models do not capture an important and more realistic feature of such models known as randomness. As the dynamical behavior of most epidemics, especially SARS-CoV-2, is unarguably influenced by several random factors, it is appropriate to consider a stochastic vaccination co-infection model for two strains of SARS-CoV-2. In this work, a new stochastic model for two variants of SARS-CoV-2 is presented. The conditions of existence and the uniqueness of a unique global solution of the stochastic model are derived. Constructing an appropriate Lyapunov function, the conditions for the stochastic system to fluctuate around endemic equilibrium of the deterministic system are derived. Stationary distribution and ergodicity for the new co-infection model are also studied. Numerical simulations are carried out to validate theoretical results. It is observed that when the white noise intensities are larger than certain thresholds and the associated stochastic reproduction numbers are less than unity, both strains die out and go into extinction with unit probability. More-over, it is observed that, for weak white noise intensities, the solution of the stochastic system fluctuates around the endemic equilibrium (EE) of the deterministic model. Frequency distributions are also studied to show random fluctuations due to stochastic white noise intensities. The results presented herein also reveal the impact of vaccination in reducing the co-circulation of SARS-CoV-2 variants within a given population. © 2022 International Association for Mathematics and Computers in Simulation (IMACS)
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One of society's major concerns that have continued for a long time is infectious diseases. It has been demonstrated that certain disease infections, in particular multiple disease infections, make it more challenging to identify and treat infected individuals, thus deteriorating human health. As a result, a COVID-19-malaria co-infection model is developed and analyzed to study the effects of threshold quantities and co-infection transmission rate on the two diseases' synergistic relation-ship. This allowed us to better understand the co-dynamics of the two diseases in the population. The existence and stability of the disease-free equilibrium of each single infection were first inves-tigated by using their respective reproduction number. The COVID-19 and malaria-free equilibrium are locally asymptotically stable when the individual threshold quantities RC and RM are below unity. Additionally, the occurrence of the malaria prevalent equilibrium is examined, and the requirements for the backward bifurcation's existence are provided. Sensitivity analysis reveals that the two main parameters that influence the spread of COVID-19 infection are the disease transmis-sion rate (bc) and the fraction of the exposed individuals becoming symptomatic (w), while malaria transmission is influenced by the abundance of vector population, which is driven by recruitment rate (pv) with an increase in the effective biting rate (b), probability of malaria transmission per mosquito bite (bm), and probability of malaria transmission from infected humans to vectors (bv). The findings from the numerical simulation of the model show that COVID-19 will predom-inate in the populace and drives malaria to extinction when RM < 1 < RC, whereas malaria will dominate in the population and drives COVID-19 into extinction when RC < 1 < RM. At the dis-ease's endemic equilibrium, the two diseases will coexist with the one with the highest reproduction number predominating but not eradicating the other. It was demonstrated in particular that COVID-19 will invade a population where malaria is endemic if the invasion reproduction number exceeds unity. The findings also demonstrate that when the two diseases are at endemic equilibrium,the prevalence of co-infection increases COVID-19's burden on the population while decreasing malaria incidence. (c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/ 4.0/).
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In this paper we analyze COVID-19 spread in Indonesia using an epidemio logical model. We consider symptomatic and asymptomatic infections in the model. We analyze the equilibria of the model and their stability which depend on the basic reproduction ratio for symptomatic and asymptomatic infections. Furthermore, we use optimal control in prevention and treatment in decreasing the number of positive COVID-19 patients in Indonesia. Furthermore, we analyze the existence of optimal control using the Pontryagin minimum principle. We also give numerical simulation of COVID-19 spread with and without the control. According to the simulation, COVID-19 spread could be reduced by using prevention and treatment control simultaneously. © 2023 JONNER NAINGGOLAN et al.
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Purpose: This study investigates the impact of the COVID-19 pandemic on financial stability in Vietnam, a developing country characterized by a bank-based financial system. Design/methodology/approach: Using a sample of daily data from January 23, 2020 to June 30, 2022, the VECM and NARDL models are employed to study Vietnam's financial stability in face of the COVID-19 disaster. Following the literature on COVID-19, the authors measure the impact of the pandemic by the number of daily infected cases and the national lockdown. Given the reliance of the Vietnamese government on the banking system to regulate the economy, the authors evaluate financial stability from the interbank market and stock market perspectives. Findings: The authors find that the pandemic imposes a destructive effect on financial stability during the early time of the pandemic;however, the analysis with an extended period indicates that this effect gradually fades in the long term. In addition, from the NARDL results, the authors reveal an asymmetric relationship between the financial market and the COVID-19 pandemic in both short term and long term. Research limitations/implications: An implication drawn from this study is that unprecedented health disasters should be resolved by unprecedented stringent countermeasures when conventional methods are ineffective. Although rigorous remedies may increase short-term liabilities, their implementation quickly ceases disease diffusion and helps an economy enter the recovery stage in a timelier manner. Originality/value: The study is the first to examine the impact of the COVID-19 pandemic on financial stability, via the interbank market lens, in a developing country that relies on the bank-based financial system. © 2023, Emerald Publishing Limited.
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With the emergence of the COVID-19, masks and protective clothing have been used in huge quantities. A large number of non-degradable materials have severely damaged the ecological environment. Now, people are increasingly pursuing the use of environmentally friendly materials to replace traditional chemical materials. Silk fibroin (SF) and Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) have received increasing attention because of their unique biodegradability and biocompatibility. In this paper, a series of biodegradable SF/PHBV nanofiber membranes with different PHBV content were fabricated by using electrospinning technology. The morphology of the electrospun SF/PHBV composite nanofiber was observed by scanning electron microscopy (SEM). The average diameters of the pure SF, SF/PHBV (4/1), SF/PHBV (3/1), and SF/PHBV (2/1) nanofibers were 55.16 ± 12.38 nm, 75.93 ± 21.83 nm, 69.35 ± 21.55 nm, and 61.40 ± 12.31 nm, respectively. Fourier transform infrared (FTIR) spectroscopy and X-ray diffraction (XRD) were used to explore the microstructure of the electrospun SF/PHBV composite nanofiber. The crystallization ability of the composite nanofiber was greatly improved with the addition of PHBV. The results of thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) indicated that the thermal stability of SF was better than PHBV obviously, so SF could improve the thermal stability of the composite materials within a certain range. The mechanical properties of the electrospun nanofiber membranes were evaluated by using a universal testing machine. In general, the elongation of the composite nanofiber membranes decreased, and the breaking strength increased with the addition of PHBV. The small pore size of the nanofiber membranes ensured that they had good application prospects in the field of filtration and protection. When the spinning time was 1 h, the filtration efficiency of SF/PHBV/PLA composite materials remained above 95%. © 2021 The Textile Institute.
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In July 2021, the European Central Bank (ECB) published a new monetary policy strategy, the first time in 17 years that it had undertaken a review of its monetary policy. In the intervening time, the world - and the economic challenges facing the ECB - have changed immensely but partly as a result of the ECB's own maneuvering. In particular, monetary policy has been relied upon for every single malaise facing the global economy, including and up to the coronavirus pandemic. This paper argues that a review of central banks as an institutional mechanism in general, and in particular the ECB, was overdue but should not have been limited to policies;instead, an opportunity was missed to have an institutional review to examine whether or not it has been performing as intended. In particular, the vast experiment of unconventional monetary policy/issuance should have been more scrutinized from an institutional level as it appears to have contributed to the current problems the European economy faces. Europe and the ECB would be well served by taking stock of its actions over the past two decades and especially during the era of unconventional monetary policy to find a sustainable route forward.
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A mathematical model revealing the transmission mechanism of COVID-19 is produced and theoretically examined, which has helped us address the disease dynamics and treatment measures, such as vaccination for susceptible patients. The mathematical model containing the whole population was partitioned into six different compartments, represented by the SVEIQR model. Important properties of the model, such as the nonnegativity of solutions and their boundedness, are established. Furthermore, we calculated the basic reproduction number, which is an important parameter in infection models. The disease-free equilibrium solution of the model was determined to be locally and globally asymptotically stable. When the basic reproduction number (Formula presented.) is less than one, the disease-free equilibrium point is locally asymptotically stable. To discover the approximative solution to the model, a general numerical approach based on the Haar collocation technique was developed. Using some real data, the sensitivity analysis of (Formula presented.) was shown. We simulated the approximate results for various values of the quarantine and vaccination populations using Matlab to show the transmission dynamics of the Coronavirus-19 disease through graphs. The validation of the results by the Simulink software and numerical methods shows that our model and adopted methodology are appropriate and accurate and could be used for further predictions for COVID-19. © 2022 by the authors.