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Rabies remains a pressing global public health issue, demanding effective modeling and control strategies. This study focused on developing a mathematical model using ordinary differential equations (ODEs) to estimate parameters and assess uncertainties related to the transmission dynamics of rabies in humans and dogs. To determine model parameters and address uncertainties, next-generation matrices were utilized to calculate the basic reproduction number ${\cal R}_{0}$. Furthermore, the Partial Rank Correlation Coefficient was used to identify parameters that significantly influence model outputs. The analysis of equilibrium states revealed that the rabies-free equilibrium is globally asymptotically stable when $R_0<1$, whereas the endemic equilibrium is globally asymptotically stable when ${\cal R}_{0}\geq 1$. To reduce the severity of rabies and align with the Global Rabies Control (GRC) initiative by 2030, the study recommends implementing control strategies targeting indoor domestic dogs., Comment: This is a preprint whose final form is published in 'Chaos, Solitons & Fractals' at [https://doi.org/10.1016/j.chaos.2024.115633]

We propose a nonstandard finite difference scheme for the Susceptible-Infected-Removed (SIR) continuous model. We prove that our discretized system is dynamically consistent with its continuous counterpart and we derive its exact solution. We end with the analysis of the long-term behavior of susceptible, infected and removed individuals, illustrating our results with examples. In contrast with the SIR discrete-time model available in the literature, our new model is simultaneously mathematically and biologically sound., Comment: This is a preprint published Open Access in 'Applied Numerical Mathematics' [https://doi.org/10.1016/j.apnum.2024.09.014]

This paper presents a mathematical model to understand how rabies spreads among humans, free-range, and domestic dogs. By analyzing the model, we discovered that there are equilibrium points representing both disease-free and endemic states. We calculated the basic reproduction number, $\mathcal{R}_{0}$, using the next generation matrix method. When $\mathcal{R}_{0}<1$, the disease-free equilibrium is globally stable, whereas when $\mathcal{R}_{0}>1$, the endemic equilibrium is globally stable. To identify the most influential parameters in disease transmission, we used the normalized forward sensitivity index. Our simulations revealed that the contact rates between the infectious agent and humans, free-range dogs, and domestic dogs have the most significant impact on rabies transmission. The study also examines how periodic changes in transmission rates affect the disease dynamics, emphasizing the importance of transmission frequency and amplitude on the patterns observed in rabies spread. Therefore, the study proposes that to mitigate the factors most strongly linked to disease sensitivity, effective disease control measures should primarily prioritize on reducing the population of both free-range and domestic dogs in open environments., Comment: This is a preprint whose final form is published open access in 'Heliyon' at [https://doi.org/10.1016/j.heliyon.2024.e32012]

We propose and analyze a deterministic mathematical model for the transmission of food-borne diseases in a population consisting of humans and flies. We employ the Caputo operator to examine the impact of governmental actions and online food delivery services on the transmission of food-borne diseases. The proposed model investigates important aspects such as positivity, boundedness, disease-free equilibrium, basic reproduction number and sensitivity analysis. The existence and uniqueness of a solution for the initial value problem is established using Banach and Schauder type fixed point theorems. Functional techniques are employed to demonstrate the stability of the proposed model under the Hyers-Ulam condition. For an approximate solution, the iterative fractional order Predictor-Corrector scheme is utilized. The simulation of this scheme is conducted using Matlab as the numeric computing environment, with various fractional order values ranging from 0.75 to 1. Over time, all compartments demonstrate convergence and stability. The numerical simulations highlight the necessity for the government to implement the most effective food safety control interventions. These measures could involve food safety awareness and training campaigns targeting restaurant managers, staff members involved in online food delivery, as well as food delivery personnel., Comment: This preprint is published in 'Modeling Earth Systems and Environment' [https://doi.org/10.1007/s40808-024-02046-8]

We investigate the dynamics of the hepatitis B virus by integrating variable-order calculus and discrete analysis. Specifically, we utilize the Caputo variable-order difference operator in this study. To establish the existence and uniqueness results of the model, we employ a fixed-point technique. Furthermore, we prove that the model exhibits bounded and positive solutions. Additionally, we explore the local stability of the proposed model by determining the basic reproduction number. Finally, we present several numerical simulations to illustrate the richness of our results., Comment: This is a preprint whose final form is published in 'Chaos, Solitons and Fractals' (see https://doi.org/10.1016/j.chaos.2024.114987)

We formulate an integrated pest management model to control natural pests of the crop through the periodic application of biopesticide and chemical pesticides. In a theoretical analysis of the system pest eradication, a periodic solution is found and established. All the system variables are proved to be bounded. Our main goal is then to ensure that pesticides are optimized, in terms of pesticide concentration and pesticide application frequency, and that the optimum combination of pesticides is found to provide the most benefit to the crop. By using Floquet theory and the small amplitude perturbation method, we prove that the pest eradication periodic solution is locally and globally stable. The acquired results establish a threshold time limit for the impulsive release of various controls as well as some valid theoretical conclusions for effective pest management. Furthermore, after a numerical comparison, we conclude that integrated pest management is more effective than single biological or chemical controls. Finally, we illustrate the analytical results through numerical simulations., Comment: This is a preprint of a paper whose final and definite form is published Open Access in 'Axioms' at [https://doi.org/10.3390/axioms12040391]

In this article, we develop a simple mathematical GNU Octave/MATLAB code that is easy to modify for the simulation of mathematical models governed by fractional-order differential equations, and for the resolution of fractional-order optimal control problems through Pontryagin's maximum principle (indirect approach to optimal control). For this purpose, a fractional-order model for the respiratory syncytial virus (RSV) infection is considered. The model is an improvement of one first proposed by the authors in [Chaos Solitons Fractals 117 (2018), 142--149]. The initial value problem associated with the RSV infection fractional model is numerically solved using Garrapa's fde12 solver and two simple methods coded here in Octave/MATLAB: the fractional forward {Euler's} method and the predict-evaluate-correct-evaluate (PECE) method of Adams--Bashforth--Moulton. A fractional optimal control problem is then formulated having treatment as the control. The fractional Pontryagin maximum principle is used to characterize the fractional optimal control and the extremals of the problem are determined numerically through the implementation of the forward-backward PECE method. The implemented algorithms are available on GitHub and, at the end of the paper, in appendixes, both for the uncontrolled initial value problem as well as for the fractional optimal control problem, using the free GNU Octave computing software and assuring compatibility with~MATLAB., Comment: This is a preprint of a paper whose final and definite form is published Open Access in 'Mathematics' at [https://doi.org/10.3390/math11061511]. The developed Octave/Matlab code is available at [https://github.com/SilverioRosa/numres-focp]

We analyze mathematical models for COVID-19 with discrete time delays and vaccination. Sufficient conditions for the local stability of the endemic and disease-free equilibrium points are proved for any positive time delay. The stability results are illustrated through numerical simulations performed in MATLAB., Comment: This is a preprint of a paper whose final and definite form is published Open Access in 'Axioms' at [https://doi.org/10.3390/axioms11080400]

We improve a recent mathematical model for cholera by adding a time delay that represents the time between the instant at which an individual becomes infected and the instant at which he begins to have symptoms of cholera disease. We prove that the delayed cholera model is biologically meaningful and analyze the local asymptotic stability of the equilibrium points for positive time delays. An optimal control problem is proposed and analyzed, where the goal is to obtain optimal treatment strategies, through quarantine, that minimize the number of infective individuals and the bacterial concentration, as well as treatment costs. Necessary optimality conditions are applied to the delayed optimal control problem, with a $L^1$ type cost functional. We show that the delayed cholera model fits better the cholera outbreak that occurred in the Department of Artibonite -- Haiti, from 1 November 2010 to 1 May 2011, than the non-delayed model. Considering the data of the cholera outbreak in Haiti, we solve numerically the delayed optimal control problem and propose solutions for the outbreak control and eradication., Comment: This is a preprint of a paper whose final and definite form is published Open Access in 'Math. Model. Nat. Phenom.' at [https://www.mmnp-journal.org]. Submitted to MMNP: Sept 23, 2021; Revised: March 15, 2022; Accepted: June 25, 2022

A fractional-order compartmental model was recently used to describe real data of the first wave of the COVID-19 pandemic in Portugal [Chaos Solitons Fractals 144 (2021), Art. 110652]. Here, we modify that model in order to correct time dimensions and use it to investigate the third wave of COVID-19 that occurred in Portugal from December 2020 to February 2021, and that has surpassed all previous waves, both in number and consequences. A new fractional optimal control problem is then formulated and solved, with vaccination and preventive measures as controls. A cost-effectiveness analysis is carried out, and the obtained results are discussed., Comment: This is a preprint of a paper whose final and definite form is published Open Access in 'Axioms' at [https://doi.org/10.3390/axioms11040170]

We study a prey-predator model based on the classical Lotka-Volterra system with Leslie-Gower and Holling IV schemes and a constant-effort harvesting. Our goal is twofold: to present the model proposed by Cheng and Zhang in 2021, pointing out some inconsistencies; to analyse the number and type of equilibrium points of the model. We end by proving the stability of the meaningful equilibrium point, according to the distribution of the eigenvalues., Comment: This is a preprint whose final form is published by Springer Nature Switzerland AG in the book 'Dynamic Control and Optimization'. Submitted 30/Nov/2021; Accepted 10/Feb/2022

We study the global dynamics of a reaction-diffusion SEIR infection model with distributed delay and nonlinear incidence rate. The well-posedness of the proposed model is proved. By means of Lyapunov functionals, we show that the disease free equilibrium state is globally asymptotically stable when the basic reproduction number is less or equal than one, and that the disease endemic equilibrium is globally asymptotically stable when the basic reproduction number is greater than one. Numerical simulations are provided to illustrate the obtained theoretical results., Comment: This is a preprint whose final form is published by Elsevier in the book 'Mathematical Analysis of Infectious Diseases', 1st Edition - June 1, 2022. ISBN: 9780323905046

This study presents new estimates for fractional derivatives without singular kernels defined by some specific functions. Based on obtained inequalities, we give a useful method to establish the global stability of steady states for fractional-order systems and generalize some works existing in the literature. Finally, we apply our results to prove the global stability of a fractional-order SEIR model with a general incidence rate., Comment: This is a preprint whose final form is published by Elsevier in the book 'Mathematical Analysis of Infectious Diseases', 1st Edition - June 1, 2022. ISBN: 9780323905046

We propose and study a shifted SICA epidemic model, extending the one of Silva and Torres (2017) to the stochastic setting driven by both Brownian motion processes and jump L\'evy noise. L\'evy noise perturbations are usually ignored by existing works of mathematical modelling in epidemiology, but its incorporation into the SICA epidemic model is worth to consider because of the presence of strong fluctuations in HIV/AIDS dynamics, often leading to the emergence of a number of discontinuities in the processes under investigation. Our work is organised as follows: (i) we begin by presenting our model, by clearly justifying its used form, namely the component related to the L\'evy noise; (ii) we prove existence and uniqueness of a global positive solution by constructing a suitable stopping time; (iii) under some assumptions, we show extinction of HIV/AIDS; (iv) we obtain sufficient conditions assuring persistence of HIV/AIDS; (v) we illustrate our mathematical results through numerical simulations., Comment: This is a preprint whose final form is published by Elsevier in the book 'Mathematical Analysis of Infectious Diseases', 1st Edition - June 1, 2022. ISBN: 9780323905046

We develop a mathematical model for transferring the vaccine BNT162b2 based on the heat diffusion equation. Then, we apply optimal control theory to the proposed generalized SEIR model. We introduce vaccination for the susceptible population to control the spread of the COVID-19 epidemic. For this, we use the Pontryagin minimum principle to find the necessary optimality conditions for the optimal control. The optimal control problem and the heat diffusion equation are solved numerically. Finally, several simulations are done to study and predict the spread of the COVID-19 epidemic in Italy. In particular, we compare the model in the presence and absence of vaccination., Comment: This is a preprint whose final form is published by Elsevier at [https://doi.org/10.1016/B978-0-32-390504-6.00007-3]

A Caputo-type fractional-order mathematical model for "metapopulation cholera transmission" was recently proposed in [Chaos Solitons Fractals 117 (2018), 37--49]. A sensitivity analysis of that model is done here to show the accuracy relevance of parameter estimation. Then, a fractional optimal control (FOC) problem is formulated and numerically solved. A cost-effectiveness analysis is performed to assess the relevance of studied control measures. Moreover, such analysis allows us to assess the cost and effectiveness of the control measures during intervention. We conclude that the FOC system is more effective only in part of the time interval. For this reason, we propose a system where the derivative order varies along the time interval, being fractional or classical when more advantageous. Such variable-order fractional model, that we call a 'FractInt' system, shows to be the most effective in the control of the disease., Comment: This is a preprint of a paper whose final and definite form is published Open Access in Fractal Fract. at [https://doi.org/10.3390/fractalfract5040261]. Please cite this paper as follows: Rosa, S.; Torres, D.F.M. Fractional-Order Modelling and Optimal Control of Cholera Transmission. Fractal Fract. 2021, 5, 261. https://doi.org/10.3390/fractalfract5040261

In [Ecological Complexity 44 (2020) Art. 100885, DOI: 10.1016/j.ecocom.2020.100885] a continuous-time compartmental mathematical model for the spread of the Coronavirus disease 2019 (COVID-19) is presented with Portugal as case study, from 2 March to 4 May 2020, and the local stability of the Disease Free Equilibrium (DFE) is analysed. Here, we propose an analogous discrete-time model and, using a suitable Lyapunov function, we prove the global stability of the DFE point. Using COVID-19 real data, we show, through numerical simulations, the consistence of the obtained theoretical results., Comment: This is a preprint of a paper whose final and definite form is published Open Access in 'Axioms', available in [https://doi.org/10.3390/axioms10040314]. Please cite this article as: S. Vaz and D. F. M. Torres, A discrete-time compartmental epidemiological model for COVID-19 with a case study for Portugal, Axioms 10 (2021), no. 4, Art. 314, 14 pp

Controlling an epidemiological model is often performed using optimal control theory techniques for which the solution depends on the equations of the control system, objective functional and possible state and/or control constraints. In this paper, we propose a model-free control approach based on an algorithm that operates in 'real-time' and drives the state solution according to a direct feedback on the state solution that is aimed to be minimized, and without knowing explicitly the equations of the control system. We consider a concrete epidemic problem of minimizing the number of HIV infected individuals, through the preventive measure pre-exposure prophylaxis (PrEP) given to susceptible individuals. The solutions must satisfy control and mixed state-control constraints that represent the limitations on PrEP implementation. Our model-free based control algorithm allows to close the loop between the number of infected individuals with HIV and the supply of PrEP medication 'in real time', in such manner that the number of infected individuals is asymptotically reduced and the number of individuals under PrEP medication is below a fixed constant value. We prove the efficiency of our approach and compare the model-free control solutions with the ones obtained using a classical optimal control approach via Pontryagin maximum principle. The performed numerical simulations allow us to conclude that the model-free based control strategy highlights new and interesting performances compared with the classical optimal control approach., Comment: This is a preprint of a paper whose final and definite form is published open access by 'Mathematical Biosciences and Engineering' (ISSN: 1551-0018) at [https://www.aimspress.com/mbe/article/5926/special-articles]

In this research, we provide a mathematical analysis for the novel coronavirus responsible for COVID-19, which continues to be a big source of threat for humanity. Our fractional-order analysis is carried out using a non-singular kernel type operator known as the Atangana--Baleanu--Caputo (ABC) derivative. We parametrize the model adopting available information of the disease from Pakistan in the period 9th April to 2nd June 2020. We obtain the required solution with the help of a hybrid method, which is a combination of the decomposition method and the Laplace transform. Furthermore, a sensitivity analysis is carried out to evaluate the parameters that are more sensitive to the basic reproduction number of the model. Our results are compared with the real data of Pakistan and numerical plots are presented at various fractional orders., Comment: Final form is published Open Access in 'Axioms' [https://doi.org/10.3390/axioms10040290]. Submitted 1-Aug-2021; Revised 27-Aug and 22-Sept-2021; Accepted 28-Oct-2021; Published 1-Nov-2021. Citation: A. Din, A. Khan, A. Zeb, M.R. Sidi Ammi, M. Tilioua and D.F.M. Torres, Hybrid method for simulation of a fractional COVID-19 model with real case application, Axioms 10 (2021), no. 4, Art. 290, 17pp

We apply optimal control theory to a generalized SEIR-type model. The proposed system has three controls, representing social distancing, preventive means, and treatment measures to combat the spread of the COVID-19 pandemic. We analyze such optimal control problem with respect to real data transmission in Italy. Our results show the appropriateness of the model, in particular with respect to the number of quarantined/hospitalized (confirmed and infected) and recovered individuals. Considering the Pontryagin controls, we show how in a perfect world one could have drastically diminish the number of susceptible, exposed, infected, quarantined/hospitalized, and death individuals, by increasing the population of insusceptible/protected., Comment: This is a preprint of a paper whose final and definite form is published by 'Kuwait Journal of Science' (KJS), ISSN 2307-4108 (print), ISSN 2307-4116 (online), available at [https://journalskuwait.org/kjs]

We propose a qualitative analysis of a recent fractional-order COVID-19 model. We start by showing that the model is mathematically and biologically well posed. Then, we give a proof on the global stability of the disease free equilibrium point. Finally, some numerical simulations are performed to ensure stability and convergence of the disease free equilibrium point., Comment: This is a preprint of a paper whose final and definite form is published Open Access in 'Axioms', available in [https://doi.org/10.3390/axioms10030135]. Please cite this article as: F. Nda\"irou and D. F. M. Torres, Mathematical Analysis of a Fractional COVID-19 Model Applied to Wuhan, Spain and Portugal, Axioms 10 (2021), no. 3, Art. 135, 13 pp

In this work, we derive a nonstandard finite difference scheme for the SICA (Susceptible-Infected-Chronic-AIDS) model and analyze the dynamical properties of the discretized system. We prove that the discretized model is dynamically consistent with the continuous, maintaining the essential properties of the standard SICA model, namely, the positivity and boundedness of the solutions, equilibrium points, and their local and global stability., Comment: This is a preprint of a paper whose final and definite form is published Open Access in 'Mathematical Biosciences and Engineering' (ISSN 1551-0018), available at [https://doi.org/10.3934/mbe.2021231]. Submitted 23/March/2021; Revised 05/May/2021; Accepted 20/May/2021; Published 26/May/2021

We propose and study a new mathematical model of the human immunodeficiency virus (HIV). The main novelty is to consider that the antibody growth depends not only on the virus and on the antibodies concentration but also on the uninfected cells concentration. The model consists of five nonlinear differential equations describing the evolution of the uninfected cells, the infected ones, the free viruses, and the adaptive immunity. The adaptive immune response is represented by the cytotoxic T-lymphocytes (CTL) cells and the antibodies with the growth function supposed to be trilinear. The model includes two kinds of treatments. The objective of the first one is to reduce the number of infected cells, while the aim of the second is to block free viruses. Firstly, the positivity and the boundedness of solutions are established. After that, the local stability of the disease free steady state and the infection steady states are characterized. Next, an optimal control problem is posed and investigated. Finally, numerical simulations are performed in order to show the behavior of solutions and the effectiveness of the two incorporated treatments via an efficient optimal control strategy., Comment: This is a preprint of a paper whose final and definite form is with 'Discrete and Continuous Dynamical Systems - Series S' (DCDS-S), ISSN 1937-1632 (print), ISSN 1937-1179 (online), available at [http://aimsciences.org/journal/1937-1632]. Paper Submitted 01-June-2019; Revised 10-May-2021; Accepted 21-May-2021. arXiv admin note: text overlap with arXiv:1801.10048

We investigate, through a fractional mathematical model, the effects of physical distance on the SARS-CoV-2 virus transmission. Two controls are considered in our model for eradication of the spread of COVID-19: media education, through campaigns explaining the importance of social distancing, use of face masks, etc., towards all population, while the second one is quarantine social isolation of the exposed individuals. A general fractional order optimal control problem, and associated optimality conditions of Pontryagin type, are discussed, with the goal to minimize the number of susceptible and infected while maximizing the number of recovered. The extremals are then numerically obtained., Comment: This is a preprint of a paper whose final and definite form is published by 'Alexandria Engineering Journal' (ISSN: 1110-0168). Submitted 6/Jan/2021; Revised 28/Jan/2021; Accepted 12/Feb/2021

The novel coronavirus disease (COVID-19) pneumonia has posed a great threat to the world recent months by causing many deaths and enormous economic damage worldwide. The first case of COVID-19 in Morocco was reported on 2 March 2020, and the number of reported cases has increased day by day. In this work, we extend the well-known SIR compartmental model to deterministic and stochastic time-delayed models in order to predict the epidemiological trend of COVID-19 in Morocco and to assess the potential role of multiple preventive measures and strategies imposed by Moroccan authorities. The main features of the work include the well-posedness of the models and conditions under which the COVID-19 may become extinct or persist in the population. Parameter values have been estimated from real data and numerical simulations are presented for forecasting the COVID-19 spreading as well as verification of theoretical results., Comment: This is a preprint of a paper whose final and definite form is published, open access, by 'Axioms' (ISSN: 2075-1680). Submitted Axioms: 2 Dec 2020; Revised: 20 and 31 Jan 2021; correction to proofs: 4 Feb 2021

A fractional compartmental mathematical model for the spread of the COVID-19 disease is proposed. Special focus has been done on the transmissibility of super-spreaders individuals. Numerical simulations are shown for data of Galicia, Spain, and Portugal. For each region, the order of the Caputo derivative takes a different value, that is not close to one, showing the relevance of considering fractional models., Comment: This is a preprint of a paper whose final and definite form is published by 'Chaos Solitons Fractals' (ISSN: 0960-0779). Paper Submitted 04/June/2020; Revised 22/July/2020 and 02/Aug/2020; Accepted 04/Jan/2021

We investigate the celebrated mathematical SICA model but using fractional differential equations in order to better describe the dynamics of HIV-AIDS infection. The infection process is modelled by a general functional response and the memory effect is described by the Caputo fractional derivative. Stability and instability of equilibrium points are determined in terms of the basic reproduction number. Furthermore, a fractional optimal control system is formulated and the best strategy for minimizing the spread of the disease into the population is determined through numerical simulations based on the derived necessary optimality conditions., Comment: This is a preprint of a paper whose final and definite form is with 'The European Physical Journal Plus', E-ISSN 2190-5444. Submitted: 02-Feb-2020 / Revised: 20-Oct-2020 and 24-Nov-2020 / Accepted: 08-Dec-2020

We propose a compartmental mathematical model for the spread of the COVID-19 disease, showing its usefulness with respect to the pandemic in Portugal, from the first recorded case in the country till the end of the three states of emergency. New results include the compartmental model, described by a system of seven ordinary differential equations; proof of positivity and boundedness of solutions; investigation of equilibrium points and their stability analysis; computation of the basic reproduction number; and numerical simulations with official real data from the Portuguese health authorities. Besides completely new, the proposed model allows to describe quite well the spread of COVID-19 in Portugal, fitting simultaneously not only the number of active infected individuals but also the number of hospitalized individuals, respectively with a $L^2$ error of $9.2152e-04$ and $1.6136e-04$ with respect to the initial population. Such results are very important, from a practical point of view, and far from trivial from a mathematical perspective. Moreover, the obtained value for the basic reproduction number is in agreement with the one given by the Portuguese authorities at the end of the emergency states., Comment: This is a preprint of a paper whose final and definite form is published by 'Ecological Complexity' (ISSN: 1476-945X). Paper Submitted 05/June/2020; Revised 24/July/2020, 08/Sept/2020 and 02/Nov/2020; Accepted 17/Nov/2020

Coronavirus disease 2019 (COVID-19) poses a great threat to public health and the economy worldwide. Currently, COVID-19 evolves in many countries to a second stage, characterized by the need for the liberation of the economy and relaxation of the human psychological effects. To this end, numerous countries decided to implement adequate deconfinement strategies. After the first prolongation of the established confinement, Morocco moves to the deconfinement stage on May 20, 2020. The relevant question concerns the impact on the COVID-19 propagation by considering an additional degree of realism related to stochastic noises due to the effectiveness level of the adapted measures. In this paper, we propose a delayed stochastic mathematical model to predict the epidemiological trend of COVID-19 in Morocco after the deconfinement. To ensure the well-posedness of the model, we prove the existence and uniqueness of a positive solution. Based on the large number theorem for martingales, we discuss the extinction of the disease under an appropriate threshold parameter. Moreover, numerical simulations are performed in order to test the efficiency of the deconfinement strategies chosen by the Moroccan authorities to help the policy makers and public health administration to make suitable decisions in the near future., Comment: This is a preprint of a paper whose final and definite form is published by 'Mathematical Modelling of Natural Phenomena' at [http://doi.org/10.1051/mmnp/2020040]. Paper Submitted 16-May-2020; Revised 20-Aug-2020; Accepted 28-Oct-2020

We propose a mathematical model for the spread of Japanese encephalitis, with emphasis on environmental effects on the aquatic phase of mosquitoes. The model is shown to be biologically well-posed and to have a biologically and ecologically meaningful disease free equilibrium point. Local stability is analyzed in terms of the basic reproduction number and numerical simulations presented and discussed., Comment: This is a preprint of a paper whose final and definite form is published Open Access in 'Mathematics' (ISSN 2227-7390), available at [https://www.mdpi.com/journal/mathematics]. Submitted: 10-Sept-2020; Revised: 8-Oct-2020; Accepted to Mathematics (ISSN 2227-7390): 19-Oct-2020

The SEIR model is a compartmental model used to simulate the dynamics of an epidemic. In this chapter, we introduce two control functions in the compartmental SEIR model representing vaccination and plasma transfusion. Optimal control problems are proposed to study the effects of these two control measures, on the reduction of infected individuals and increase of recovered ones, with minimal costs. Up to our knowledge, the plasma transfusion treatment has never been considered as a control strategy for epidemics mitigation. The proposed vaccination and treatment strategies may have a real application in the challenging and hard problem of controlling the COVID-19 pandemic., Comment: This is a preprint of a paper whose final and definite form is published in 'Analysis of Infectious Disease Problems (Covid-19) and Their Global Impact', Springer Nature Singapore Pte Ltd. Submitted 15/July/2020; revised 02/Oct/2020; accepted 08/Oct/2020

Nowadays, coronavirus disease 2019 (COVID-19) poses a great threat to public health and economy worldwide. Unfortunately, there is yet no effective drug for this disease. For this, several countries have adopted multiple preventive interventions to avoid the spread of COVID-19. Here, we propose a delayed mathematical model to predict the epidemiological trend of COVID-19 in Morocco. Parameter estimation and sensitivity analysis of the proposed model are rigorously studied. Moreover, numerical simulations are presented in order to test the effectiveness of the preventive measures and strategies that were imposed by the Moroccan authorities and also help policy makers and public health administration to develop such strategies., Comment: This is a preprint of a paper whose final and definite form is published in 'Analysis of Infectious Disease Problems (Covid-19) and Their Global Impact', Springer Nature Singapore Pte Ltd. First submitted 18/April/2020; revised 22/Sept/2020; accepted 08/Oct/2020

We propose a mathematical model for the transmission dynamics of SARS-CoV-2 in a homogeneously mixing non constant population, and generalize it to a model where the parameters are given by piecewise constant functions. This allows us to model the human behavior and the impact of public health policies on the dynamics of the curve of active infected individuals during a COVID-19 epidemic outbreak. After proving the existence and global asymptotic stability of the disease-free and endemic equilibrium points of the model with constant parameters, we consider a family of Cauchy problems, with piecewise constant parameters, and prove the existence of pseudo-oscillations between a neighborhood of the disease-free equilibrium and a neighborhood of the endemic equilibrium, in a biologically feasible region. In the context of the COVID-19 pandemic, this pseudo-periodic solutions are related to the emergence of epidemic waves. Then, to capture the impact of mobility in the dynamics of COVID-19 epidemics, we propose a complex network with six distinct regions based on COVID-19 real data from Portugal. We perform numerical simulations for the complex network model, where the objective is to determine a topology that minimizes the level of active infected individuals and the existence of topologies that are likely to worsen the level of infection. We claim that this methodology is a tool with enormous potential in the current pandemic context, and can be applied in the management of outbreaks (in regional terms) but also to manage the opening/closing of borders., Comment: 23 pages, 10 figures, submitted 5-Oct-2020

The COVID-19 pandemic has forced policy makers to decree urgent confinements to stop a rapid and massive contagion. However, after that stage, societies are being forced to find an equilibrium between the need to reduce contagion rates and the need to reopen their economies. The experience hitherto lived has provided data on the evolution of the pandemic, in particular the population dynamics as a result of the public health measures enacted. This allows the formulation of forecasting mathematical models to anticipate the consequences of political decisions. Here we propose a model to do so and apply it to the case of Portugal. With a mathematical deterministic model, described by a system of ordinary differential equations, we fit the real evolution of COVID-19 in this country. After identification of the population readiness to follow social restrictions, by analyzing the social media, we incorporate this effect in a version of the model that allow us to check different scenarios. This is realized by considering a Monte Carlo discrete version of the previous model coupled via a complex network. Then, we apply optimal control theory to maximize the number of people returning to "normal life" and minimizing the number of active infected individuals with minimal economical costs while warranting a low level of hospitalizations. This work allows testing various scenarios of pandemic management (closure of sectors of the economy, partial/total compliance with protection measures by citizens, number of beds in intensive care units, etc.), ensuring the responsiveness of the health system, thus being a public health decision support tool., Comment: Paper whose final and definite form is published Open Access by 'Scientific Reports', ISSN 2045-2322, Springer Nature. Submitted 01/Sept/2020; Revised 16/Dec/2020; Accepted 27/Jan/2021; Published by [www.nature.com/scientificreports], see [https://doi.org/10.1038/s41598-021-83075-6]

We revisit the SICA (Susceptible-Infectious-Chronic-AIDS) mathematical model for transmission dynamics of the human immunodeficiency virus (HIV) with varying population size in a homogeneously mixing population. We consider SICA models given by systems of ordinary differential equations and some generalizations given by systems with fractional and stochastic differential operators. Local and global stability results are proved for deterministic, fractional, and stochastic-type SICA models. Two case studies, in Cape Verde and Morocco, are investigated., Comment: This is a preprint of the following paper: C. J. Silva and D. F. M. Torres, On SICA models for HIV transmission, published in 'Mathematical Modelling and Analysis of Infectious Diseases', edited by K. Hattaf and H. Dutta, Springer Nature Switzerland AG. Submitted 28/Dec/2019; revised 21/Apr/2020; accepted 24/Apr/2020. arXiv admin note: text overlap with arXiv:1703.06446, arXiv:1612.00732, arXiv:1812.06965

We propose a compartmental mathematical model for the spread of the COVID-19 disease with special focus on the transmissibility of super-spreaders individuals. We compute the basic reproduction number threshold, we study the local stability of the disease free equilibrium in terms of the basic reproduction number, and we investigate the sensitivity of the model with respect to the variation of each one of its parameters. Numerical simulations show the suitability of the proposed COVID-19 model for the outbreak that occurred in Wuhan, China., Comment: Submitted 27-March-2020; Revised 10-April-2020; Accepted 22-April-2020 to 'Chaos, Solitons & Fractals', ISSN: 0960-0779

We propose a mathematical model for the transmission dynamics of some strains of the bacterium Vibrio cholerae, responsible for the cholera disease in humans. We prove that, when the basic reproduction number is equal to one, a transcritical bifurcation occurs for which the endemic equilibrium emanates from the disease-free point. A control function is introduced into the model, representing the distribution of chlorine water tablets for water purification. An optimal control problem is then proposed and analyzed, where the goal is to determine the fraction of susceptible individuals who should have access to chlorine water tablets in order to minimize the total number of new infections plus the total cost associated with the distribution of chlorine water tablets, over the considered period of time. Finally, we consider real data of the cholera outbreak in Yemen, from 27 April 2017 to 15 April 2018, choosing the values of the parameters of the uncontrolled model that fit the real data. Using our optimal control results, we show, numerically, that the distribution of chlorine water tablets could have stopped, in a fast way, the worst cholera outbreak that ever occurred in human history. Due to the critical situation of Yemen, we also simulate the case where only a small percentage of susceptible individuals has access to chlorine water tablets and obtain an optimal control solution that decreases, substantially, the maximum number of infective individuals attained at the outbreak., Comment: This is a preprint of a paper whose final and definite form is with 'J. Optim. Theory Appl.' (JOTA). Submitted 6-Apr-2019; Revised 12-Oct-2019 and 21-Jan-2020; Accepted 15-Apr-2020

We provide easy and readable GNU Octave/MATLAB code for the simulation of mathematical models described by ordinary differential equations and for the solution of optimal control problems through Pontryagin's maximum principle. For that, we consider a normalized HIV/AIDS transmission dynamics model based on the one proposed in our recent contribution (Silva, C.J.; Torres, D.F.M. A SICA compartmental model in epidemiology with application to HIV/AIDS in Cape Verde. Ecol. Complex. 2017, 30, 70--75), given by a system of four ordinary differential equations. An HIV initial value problem is solved numerically using the ode45 GNU Octave function and three standard methods implemented by us in Octave/MATLAB: Euler method and second-order and fourth-order Runge-Kutta methods. Afterwards, a control function is introduced into the normalized HIV model and an optimal control problem is formulated, where the goal is to find the optimal HIV prevention strategy that maximizes the fraction of uninfected HIV individuals with the least HIV new infections and cost associated with the control measures. The optimal control problem is characterized analytically using the Pontryagin Maximum Principle, and the extremals are computed numerically by implementing a forward-backward fourth-order Runge-Kutta method. Complete algorithms, for both uncontrolled initial value and optimal control problems, developed under the free GNU Octave software and compatible with MATLAB are provided along the article., Comment: Submitted 1-Oct-2019; Revised 7-Dec-2019; Accepted 17-Dec-2019; Published 19-Dec-2019 in Math. Comput. Appl., EISSN 2297-8747 [https://doi.org/10.3390/mca25010001]

We propose a fractional order model for HIV/AIDS transmission. Local and uniform stability of the fractional order model is studied. The theoretical results are illustrated through numerical simulations., Comment: This is a preprint of a paper whose final and definite form is with 'Mathematics and Computers in Simulation', ISSN: 0378-4754. Submitted 21/Jan/2018; Revised 1/Feb/2019; Accepted for publication 1/March/2019. arXiv admin note: text overlap with arXiv:1703.06446, arXiv:1801.07059

We investigate the global behaviour of a SIRI epidemic model with distributed delay and relapse. From the theory of functional differential equations with delay, we prove that the solution of the system is unique, bounded, and positive, for all time. The basic reproduction number $R_{0}$ for the model is computed. By means of the direct Lyapunov method and LaSalle invariance principle, we prove that the disease free equilibrium is globally asymptotically stable when $R_{0} < 1$. Moreover, we show that there is a unique endemic equilibrium, which is globally asymptotically stable, when $R_{0} > 1$., Comment: This is a preprint of a paper whose final and definite form is with 'Statistics Opt. Inform. Comput.', Vol. 7, No 2 (2019). See [http://www.iapress.org]. Submitted 26/July/2018; Revised and Accepted 22/Dec/2018

We study the global dynamics of a SICA infection model with general incidence rate. The proposed model is calibrated with cumulative cases of infection by HIV-AIDS in Morocco from 1986 to 2015. We first prove that our model is biologically and mathematically well-posed. Stability analysis of different steady states is performed and threshold parameters are identified where the model exhibits clearance of infection or maintenance of a chronic infection. Furthermore, we examine the robustness of the model to some parameter values by examining the sensitivity of the basic reproduction number. Finally, using numerical simulations with real data from Morocco, we show that the model predicts well such reality., Comment: This is a preprint of a paper whose final and definite form is with 'Statistics Opt. Inform. Comput.', Vol. 7, No 2 (2019). See [http://www.IAPress.org]. Submitted 16/Sept/2018; Revised 10 & 15/Dec/2018; Accepted 15/Dec/2018

A human respiratory syncytial virus surveillance system was implemented in Florida in 1999, to support clinical decision-making for prophylaxis of premature newborns. Recently, a local periodic SEIRS mathematical model was proposed in [Stat. Optim. Inf. Comput. 6 (2018), no.1, 139--149] to describe real data collected by Florida's system. In contrast, here we propose a non-local fractional (non-integer) order model. A fractional optimal control problem is then formulated and solved, having treatment as the control. Finally, a cost-effectiveness analysis is carried out to evaluate the cost and the effectiveness of proposed control measures during the intervention period, showing the superiority of obtained results with respect to previous ones., Comment: This is a preprint of a paper whose final and definite form is with 'Chaos, Solitons & Fractals', available from [http://www.elsevier.com/locate/issn/09600779]. Submitted 23-July-2018; Revised 14-Oct-2018; Accepted 15-Oct-2018. arXiv admin note: substantial text overlap with arXiv:1801.09634

We propose and analyse a mathematical model for cholera considering vaccination. We show that the model is epidemiologically and mathematically well posed and prove the existence and uniqueness of disease-free and endemic equilibrium points. The basic reproduction number is determined and the local asymptotic stability of equilibria is studied. The biggest cholera outbreak of world's history began on 27th April 2017, in Yemen. Between 27th April 2017 and 15th April 2018 there were 2275 deaths due to this epidemic. A vaccination campaign began on 6th May 2018 and ended on 15th May 2018. We show that our model is able to describe well this outbreak. Moreover, we prove that the number of infected individuals would have been much lower provided the vaccination campaign had begun earlier., Comment: This is a preprint of a paper whose final and definite form is with 'AIMS Mathematics', available in open access from [http://www.aimspress.com/journal/Math]. Submitted 7-July-2018; Revised 14-Sept-2018; Accepted 12-Oct-2018. arXiv admin note: substantial text overlap with arXiv:1611.02195

We propose a stochastic SICA epidemic model for HIV transmission, described by stochastic ordinary differential equations, and discuss its perturbation by environmental white noise. Existence and uniqueness of the global positive solution to the stochastic HIV system is proven, and conditions under which extinction and persistence in mean hold, are given. The theoretical results are illustrated via numerical simulations., Comment: This is a preprint of a paper whose final and definite form is with 'Applied Mathematics Letters', ISSN 0893-9659. Submitted 22/Jan/2018; Revised 03/May/2018; Accepted for publication 03/May/2018

A state wide Human Respiratory Syncytial Virus (HRSV) surveillance system was implemented in Florida in 1999 to support clinical decision-making for prophylaxis of premature infants. The research presented in this paper addresses the problem of fitting real data collected by the Florida HRSV surveillance system by using a periodic SEIRS mathematical model. A sensitivity and cost-effectiveness analysis of the model is done and an optimal control problem is formulated and solved with treatment as the control variable., Comment: This is a preprint of a paper whose final and definite form is published in Stat. Optim. Inf. Comput. [http://www.iapress.org/]

We propose a Caputo type fractional-order mathematical model for the transmission dynamics of tuberculosis (TB). Uniform asymptotic stability of the unique endemic equilibrium of the fractional-order TB model is proved, for any $\alpha \in (0, 1)$. Numerical simulations for the stability of the endemic equilibrium are provided., Comment: This is a preprint of a paper whose final and definite form is with Math. Model. Nat. Phenom., ISSN: 0973-5348, available at http://dx.doi.org/10.1051/mmnp/2018015 . Paper Submitted 12-08-2017; Revised 19-01-2018; Accepted 22-01-2018

We propose a new mathematical model for the spread of Zika virus. Special attention is paid to the transmission of microcephaly. Numerical simulations show the accuracy of the model with respect to the Zika outbreak occurred in Brazil., Comment: This is a preprint of a paper whose final and definite form is with 'Mathematical Methods in the Applied Sciences', ISSN 0170-4214. Submitted Aug 10, 2017; Revised Nov 13, 2017; accepted for publication Nov 14, 2017

We propose a model for the human immunodeficiency virus type 1 (HIV-1) infection with intracellular delay and prove the local asymptotical stability of the equilibrium points. Then we introduce a control function representing the efficiency of reverse transcriptase inhibitors and consider the pharmacological delay associated to the control. Finally, we propose and analyze an optimal control problem with state and control delays. Through numerical simulations, extremal solutions are proposed for minimization of the virus concentration and treatment costs., Comment: This is a preprint of a paper whose final and definite form is with 'Discrete and Continuous Dynamical Systems - Series B' (DCDS-B), ISSN 1531-3492 (print), ISSN 1553-524X (online), available at [http://aimsciences.org/journals/home.jsp?journalID=2]. Paper Submitted 12-July-2016; Revised 26-Nov-2016 and 01-March-2017; Accepted 21-Aug-2017

We study an optimal control problem for a non-autonomous SEIRS model with incidence given by a general function of the infective, the susceptible and the total population, and with vaccination and treatment as control variables. We prove existence and uniqueness results for our problem and, for the case of mass-action incidence, we present some simulation results designed to compare an autonomous and corresponding periodic model, as well as the controlled versus uncontrolled models., Comment: Preprint of a paper whose final and definite form is with 'Discrete and Continuous Dynamical Systems -- Series S' (DCDS-S), ISSN 1937-1632 (print), ISSN 1937-1179 (online), available at [http://dx.doi.org/10.3934/dcdss.2018067]. Paper Submitted 03-April-2017; Revised 20-June-2017; Accepted 21-June-2017. In this version minor corrections detected during reading of the galley proof were done

Ebola virus is one of the most virulent pathogens for humans. We present a mathematical description of different Susceptible-Exposed-Infectious-Recovered (SEIR) models. By using mathematical modeling and analysis, the latest major outbreak of Ebola virus in West Africa is described. Our aim is to study and discuss the properties of SEIR models with respect to Ebola virus, the information they provide, and when the models make sense. We added to the basic SEIR model demographic effects in order to analyze the equilibria with vital dynamics. Numerical simulations confirm the theoretical analysis. The control of the propagation of the virus through vaccination is investigated and the case study of Liberia is discussed in detail., Comment: This is a preprint of a paper whose final and definite form is with 'Commun. Fac. Sci. Univ. Ank. Ser. A1 Math. Stat.', ISSN: 1303-5991. Submitted 27 Sept 2016; Article revised 05 Apr 2017; Article accepted for publication 01 May 2017. arXiv admin note: text overlap with arXiv:1603.05794