The philosophy of the human person curriculum in the Philippines: Basis for COVID-19 Model of Curriculum Revision

Identifying gaps and overlaps in the Introduction of Philosophy of the Human Person (IPHP) curriculum in the Philippines is a great concern that makes it relevant. This ascertains its scopes based on sufficiency in terms of themes, goals, and aims;principles and criteria used for content selection;and proposing a COVID-19 Model for future revision. Using content analysis, it utilized pre-determined codes on the themes, goals, and aims of social studies;and the principles and criteria for content selection. Four clusters of themes were sufficiently integrated with the IPHP curriculum in a spiral progression;three other clusters showed gaps with no integration. The 10 social studies goals were sufficiently integrated that remains consistent in a semester with a decrease in distribution due to is spiraling complexities of contents. Six aims were sufficiently integrated with no existing gap with a negligible overlap in personal development. The principles of the curriculum were sufficiently used as well. As the semester progresses, the utilization of these principles decreases toward the second quarter, which needs attention for a future revision, using a COVID-19 Model. These results have a practical impact on curriculum makers to see the nitty-gritty in crafting or revising a curriculum to ensure the balance of content integration, realignment of concepts and skills, and continuity. These results also promote social impact in understanding our humanity as juxtaposed in the IPHP taught in the senior high school curriculum in the Philippines.

SIMULATIONS AND ANALYSIS OF COVID-19 AS A FRACTIONAL MODEL WITH DIFFERENT KERNELS

Recently, Atangana proposed new operators by combining fractional and fractal calculus. These recently proposed operators, referred to as fractal–fractional operators, have been widely used to study complex dynamics. In this paper, the COVID-19 model is considered via Atangana–Baleanu fractal-fractional operator. The Lyapunov stability for the model is derived for first and second derivative. Numerical results have developed through Lagrangian-piecewise interpolation for the different fractal–fractional operators. We develop numerical outcomes through different differential and integral fractional operators like power-law, exponential law, and Mittag-Leffler kernel. To get a better outcome of the proposed scheme, numerical simulation is made with different kernels having the memory effects with fractional parameters. [ FROM AUTHOR] Copyright of Fractals is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Fractional modeling and optimal control strategies for mutated COVID‐19 pandemic

As the COVID‐19 continues to mutate, the number of infected people is increasing dramatically, and the vaccine is not enough to fight the mutated strain. In this paper, a SEIR‐type fractional model with reinfection and vaccine inefficacy is proposed, which can successfully capture the mutated COVID‐19 pandemic. The existence, uniqueness, boundedness, and nonnegativeness of the fractional model are derived. Based on the basic reproduction number R0$$ {R}_0 $$, locally stability and globally stability are analyzed. The sensitivity analysis evaluate the influence of each parameter on the R0$$ {R}_0 $$ and rank key epidemiological parameters. Finally, the necessary conditions for implementing fractional optimal control are obtained by Pontryagin's maximum principle, and the corresponding optimal solutions are derived for mitigation COVID‐19 transmission. The numerical results show that humans will coexist with COVID‐19 for a long time under the current control strategy. Furthermore, it is particularly important to develop new vaccines with higher protection rates. [ FROM AUTHOR] Copyright of Mathematical Methods in the Applied Sciences is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

A Generalized Fractional Order Model for Cov-2 with Vaccination Effect Using Real Data

This work is devoted to studying the transmission dynamics of CoV-2 under the effect of vaccination. The aforesaid model is considered under fractional derivative with variable order of nonsingular kernel type known as Atangan-Baleanue-Caputo (ABC). Fundamental properties of the proposed model including equilibrium points and R0 are obtained by using nonlinear analysis. The existence and uniqueness of solution to the considered model are investigated via fixed point theorems due to Banach and Krasnoselskii. Also, the Ulam-Hyers (UH) approach of stability is used for the said model. Further numerical analysis is investigated by using fundamental theorems of AB fractional calculus and the iterative numerical techniques due to Adams-Bashforth. Numerical simulations are performed by using different values of fractional-variable order ?(??) for the model. The respective results are demonstrated by using real data from Saudi Arabia for graphical presentation.

Numerical Simulation for COVID-19 Model Using a Multidomain Spectral Relaxation Technique

The major objective of this work is to evaluate and study the model of coronavirus illness by providing an efficient numerical solution for this important model. The model under investigation is composed of five differential equations. In this study, the multidomain spectral relaxation method (MSRM) is used to numerically solve the suggested model. The proposed approach is based on the hypothesis that the domain of the problem can be split into a finite number of subintervals, each of which can have a solution. The procedure also converts the proposed model into a system of algebraic equations. Some theoretical studies are provided to discuss the convergence analysis of the suggested scheme and deduce an upper bound of the error. A numerical simulation is used to evaluate the approach's accuracy and utility, and it is presented in symmetric forms.

Modeling the competitive transmission of the Omicron strain and Delta strain of COVID-19.

Since November 2021, there have been cases of COVID-19's Omicron strain spreading in competition with Delta strains in many parts of the world. To explore how these two strains developed in this competitive spread, a new compartmentalized model was established. First, we analyzed the fundamental properties of the model, obtained the expression of the basic reproduction number, proved the local and global asymptotic stability of the disease-free equilibrium. Then by means of the cubic spline interpolation method, we obtained the data of new Omicron and Delta cases in the United States of new cases starting from December 8, 2021, to February 12, 2022. Using the weighted nonlinear least squares estimation method, we fitted six time series (cumulative confirmed cases, cumulative deaths, new cases, new deaths, new Omicron cases, and new Delta cases), got estimates of the unknown parameters, and obtained an approximation of the basic reproduction number in the United States during this time period as R 0 ≈ 1.5165 . Finally, each control strategy was evaluated by cost-effectiveness analysis to obtain the optimal control strategy under different perspectives. The results not only show the competitive transmission characteristics of the new strain and existing strain, but also provide scientific suggestions for effectively controlling the spread of these strains.

Analysis and simulation of a stochastic COVID-19 model with large-scale nucleic acid detection and isolation measures: A case study of the outbreak in Urumqi, China in August 2022.

In this paper, a stochastic COVID-19 model with large-scale nucleic acid detection and isolation measures is proposed. Firstly, the existence and uniqueness of the global positive solution is obtained. Secondly, threshold criteria for the stochastic extinction and persistence in the mean with probability one are established. Moreover, a sufficient condition for the existence of unique ergodic stationary distribution for any positive solution is also established. Finally, numerical simulations are carried out in combination with real COVID-19 data from Urumqi, China and the theoretical results are verified.

On Digital Models: Responding to Viral Metaphors in Pandemic Times

COVID-19 has been a crisis represented and interpreted through models. Models are metaphors that illustrate one phenomenon in and through another that is better understood or seemingly more transparent. In this article, we consider digitally driven COVID-19 models that draw on the certainty of data from smartphones and social networks to make predictions about a poorly understood virus. Network data normally used to model information spread drive models of an actually existing biological virus. A return to HIV network models of the 1980s helps map the social implications of this latest turn to modeling. These earlier models were used to hone stigmatizing viral metaphors about behavior, risk, and exposure, in the shadow of an emerging digital culture. Thinking across COVID-19 and HIV modeling demonstrates how models can support personal responsibilization, be used to blame "bad” actors, and justify the creep of new surveillance practices under the rubric of "Data for Good” programs. Drawing on critical HIV and queer studies, we argue that the people and behaviors that are opaque to viral models and their methods of capture present potential avenues for speaking back to digital virality's terms. We highlight these exceptions, which show how certain lives make trouble for models and their sensibilities, telling of queer forms of life, desire, and contact that evade modeling altogether.

Evaluating Prediction Models for Airport Passenger Throughput Using a Hybrid Method

This paper proposes a hybrid evaluation method to assess the prediction models for airport passenger throughput (APT). By analyzing two hundred three airports in China, five types of models are evaluated to study the applicability to different airports with various airport passenger throughput and developing conditions. The models were fitted using the historical data before 2014 and were verified by using the data from 2015–2019. The evaluating results show that the models employed for evaluating perform well in general except that there are insufficient historical data for modelling, or the APT of the airports changes abruptly owing to expansion, relocation or other kinds of external forces such as earthquakes. The more the APT of an airport is, the more suitable the models are for the airport. Particularly, there is no direct relation between the complexity and the predicting accuracy of the models. If the parameters of the models are properly set, time series models, causal models, market share methods and analogy-based methods can be utilized to predict the APT of 88% of studied airports effectively.

Multiversal Methods in Observational Studies: The Case of COVID-19

In the present study, 13 covariates have been selected as potentially associated with 3 metrics of the spread of COVID-19 in 20 European countries. Robustness of the linear correlations between 10 of the 13 covariates as main regressors and the 3 COVID-19 metrics as dependent variables have been tested through a methodology for sensitivity analysis that falls under the name of "Multiverse”. Under this methodology, thousands of alternative estimates are generated by a single hypothesis of regression. The capacity of identification of a robust causal claim for the 10 variables has been measured through 3 indicators over a Janus Confusion Matrix, which is a confusion matrix that assumes the likelihood to observe a True claim as the ratio between the absolute difference of estimates with a different sign and the total of estimates. This methodology provides the opportunity to evaluate the outcomes of a shift from the common level of significance to the alternative. According to the results of the study, in the dataset the benefits of the shifts come at a very high cost in terms of false negatives. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

COVID-19 Tracking Applications Acceptance among General Populace: An Overview in Malaysia

The COVID-19 pandemic forced governments to implement strategies for contact tracing due to the disease's ease of spread. The Malaysian government has sought to develop and implement a digital contact-tracking application to make it easier and faster to detect the spread;the system has become an integral part of the exit strategy from mandated lockdowns. These applications keep track of the user's proximity with others who are in the system to inform them early on if they are at a risk of infection. The effectiveness of these applications depends on the willingness of users to install and allow the application to track their location at all times. Therefore, this research aims to identify the factors that would stimulate or slow down the adoption of contact-tracing apps. © 2023 by the authors.

On the analysis of the fractional model of COVID-19 under the piecewise global operators.

An expanding field of study that offers fresh and intriguing approaches to both mathematicians and biologists is the symbolic representation of mathematics. In relation to COVID-19, such a method might provide information to humanity for halting the spread of this epidemic, which has severely impacted people's quality of life. In this study, we examine a crucial COVID-19 model under a globalized piecewise fractional derivative in the context of Caputo and Atangana Baleanu fractional operators. The said model has been constructed in the format of two fractional operators, having a non-linear time-varying spreading rate, and composed of ten compartmental individuals: Susceptible, Infectious, Diagnosed, Ailing, Recognized, Infectious Real, Threatened, Recovered Diagnosed, Healed and Extinct populations. The qualitative analysis is developed for the proposed model along with the discussion of their dynamical behaviors. The stability of the approximate solution is tested by using the Ulam-Hyers stability approach. For the implementation of the given model in the sense of an approximate piecewise solution, the Newton Polynomial approximate solution technique is applied. The graphing results are with different additional fractional orders connected to COVID-19 disease, and the graphical representation is established for other piecewise fractional orders. By using comparisons of this nature between the graphed and analytical data, we are able to calculate the best-fit parameters for any arbitrary orders with a very low error rate. Additionally, many parameters' effects on the transmission of viral infections are examined and analyzed. Such a discussion will be more informative as it demonstrates the dynamics on various piecewise intervals.

Stationary distribution and long-time behavior of COVID-19 model with stochastic effect

The coronavirus disease (COVID-19) is a dangerous pandemic and it spreads to many people in most of the world. In this paper, we propose a COVID-19 model with the assumption that it is affected by randomness. For positivity, we prove the global existence of positive solution and the system exhibits extinction under certain parametric restrictions. Moreover, we establish the stability region for the stochastic model under the behavior of stationary distribution. The stationary distribution gives the guarantee of the appearance of infection in the population. Besides that, we find the reproduction ratio R0S for prevail and disappear of infection within the human population. From the graphical representation, we have validated the threshold conditions that define in our theoretical findings. © 2023 World Scientific Publishing Company.

Multi-objective T-S fuzzy control of Covid-19 spread model: An LMI approach.

Due to the importance of control actions in spreading coronavirus disease, this paper is devoted to first modeling and then proposing an appropriate controller for this model. In the modeling procedure, we used a nonlinear mathematical model for the covid-19 outbreak to form a T-S fuzzy model. Then, for proposing the suitable controller, multiple optimization techniques including Linear Quadratic Regulator (LQR) and mixed H 2 - H ∞ are taken into account. The mentioned controller is chosen because the model of corona-virus spread is not only full of disturbances like a sudden increase in infected people, but also noises such as unavailability of the exact number of each compartment. The controller is simulated accordingly to validate the results of mathematical calculations, and a comparative analysis is presented to investigate the different situations of the problem. Comparing the results of controlled and uncontrolled situations, it can be observed that we can tackle the devastating hazards of the covid-19 outbreak effectively if the suggested approaches and policies of controlling interventions are executed, appropriately.

The fractional-order discrete COVID-19 pandemic model: stability and chaos.

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.

Dynamics of a fractional order mathematical model for COVID-19 epidemic transmission.

To achieve the aim of immediately halting spread of COVID-19 it is essential to know the dynamic behavior of the virus of intensive level of replication. Simply analyzing experimental data to learn about this disease consumes a lot of effort and cost. Mathematical models may be able to assist in this regard. Through integrating the mathematical frameworks with the accessible disease data it will be useful and outlay to comprehend the primary components involved in the spreading of COVID-19. There are so many techniques to formulate the impact of disease on the population mathematically, including deterministic modeling, stochastic modeling or fractional order modeling etc. Fractional derivative modeling is one of the essential techniques for analyzing real-world issues and making accurate assessments of situations. In this paper, a fractional order epidemic model that represents the transmission of COVID-19 using seven compartments of population susceptible, exposed, infective, recovered, the quarantine population, recovered-exposed, and dead population is provided. The fractional order derivative is considered in the Caputo sense. In order to determine the epidemic forecast and persistence, we calculate the reproduction number R 0 . Applying fixed point theory, the existence and uniqueness of the solutions of fractional order derivative have been studied . Moreover, we implement the generalized Adams-Bashforth-Moulton method to get an approximate solution of the fractional-order COVID-19 model. Finally, numerical result and an outstanding graphic simulation are presented.

Mathematical analysis of new variant Omicron model driven by Lévy noise and with variable-order fractional derivatives

In this paper, we study a variable-order fractional mathematical model driven by Lévy noise describing the new variant of COVID-19 (Omicron virus). Based on our analysis and discussion under a new set of sufficient conditions, we prove the existence and uniqueness of the related solution. Moreover, we discuss the stability analysis of the corresponding Omicron virus model by employing Ulam–Hyers and Ulam–Hyers–Rassias stabilities in Banach spaces. Finally, we present some numerical results and comparative studies to show clearly the importance of our results and its effects on behaviors of the new variant model.

Dynamics and simulations of stochastic COVID-19 epidemic model using Legendre spectral collocation method

The aim of this study is to investigate the dynamics of epidemic transmission of COVID-19 SEIR stochastic model with generalized saturated incidence rate. We assume that the random perturbations depends on white noises, which implies that it is directly proportional to the steady states. The existence and uniqueness of the positive solution along with the stability analysis is provided under disease-free and endemic equilibrium conditions for asymptotically stable transmission dynamics of the model. An epidemiological metric based on the ratio of basic reproduction is used to describe the transmission of an infectious disease using different parameters values involve in the proposed model. A higher order scheme based on Legendre spectral collocation method is used for the numerical simulations. For the better understanding of the proposed scheme, a comparison is made with the deterministic counterpart. In order to confirm the theoretical analysis, we provide a number of numerical examples. © 2023 the Author(s), licensee AIMS Press.

EXISTENCE RESULTS AND NUMERICAL STUDY ON NOVEL CORONAVIRUS 2019-NCOV/SARS-COV-2 MODEL USING DIFFERENTIAL OPERATORS BASED ON THE GENERALIZED MITTAG-LEFFLER KERNEL AND FIXED POINTS

The use of mathematical modeling in the exploration of epidemiological disorders has increased dramatically. Mathematical models can be used to forecast how viral infections spread, as well as to depict the likely outcome of an outbreak and to support public health measures. In this paper, we present useful ideas for finding existence of solutions of the novel coronavirus 2019-nCoV/SARS-CoV-2 model via fractional derivatives by using fuzzy mappings. Three classes of fractional operators were considered including Atangana-Baleanu, Caputo-Fabrizio and Caputo. For each case, we introduce the fuzzination in the study of the existence of a system of solutions. A fresh numerical scheme was proposed for each scenario, and then numerical simulations involving various parameters of Atangana-Baleanu fractional-order were shown utilizing numerical solutions. © 2022

A Novel Modeling and Analysis of Fractional-Order COVID-19 Pandemic Having a Vaccination Strategy

Recently, many illustrative studies have been performed on the mathematical modeling and analysis of COVID-19. Due to the uncertainty in the process of vaccination and its efficiency on the disease, there have not been taken enough studies into account yet. In this context, a mathematical model is developed to reveal the effects of vaccine treatment, which has been developed recently by several companies, on COVID-19 in this study. In the suggested model, as well as the vaccinated individuals, a five-dimensional ordinary differential equation system including the susceptible, infected, exposed and recovered population is constructed. This mentioned system is considered in the fractional order to investigate and point out more detailed analysis in the disease and its future prediction. Moreover, besides the positivity, existence and uniqueness of the solution, biologically feasible region are provided. The basic reproduction number, known as expected secondary infection which means that expected infection among the susceptible populations caused by this infection, is computed. In the numerical simulations, the parameter values taken from the literature and estimated are used to perform the solutions of the proposed model. In the numerical simulations, Adams-Bashforth algorithm which is a well-known numerical scheme is used to obtain the results. © 2022 American Institute of Physics Inc.. All rights reserved.