A fractional-order mathematical model for malaria and COVID-19 co-infection dynamics

This study proposes a fractional-order mathematical model for malaria and COVID-19 co-infection using the Atangana-Baleanu Derivative. We explain the various stages of the diseases together in humans and mosquitoes, and we also establish the existence and uniqueness of the fractional order co-infection model solution using the fixed point theorem. We conduct the qualitative analysis along with an epidemic indicator, the basic reproduction number R0 of this model. We investigate the global stability at the disease and endemic free equilibrium of the malaria-only, COVID-19-only, and co-infection models. We run different simulations of the fractional-order co-infection model using a two-step Lagrange interpolation polynomial approximate method with the aid of the Maple software package. The results reveal that reducing the risk of malaria and COVID-19 by taking preventive measures will reduce the risk factor for getting COVID-19 after contracting malaria and will also reduce the risk factor for getting malaria after contracting COVID-19 even to the point of extinction.

Mathematical model of COVID-19 in Nigeria with optimal control

The novel Coronavirus Disease 2019 (COVID-19) is a highly infectious disease caused by a new strain of severe acute respiratory syndrome of coronavirus 2 (SARS-CoV-2). In this work, we proposed a mathematical model of COVID-19. We carried out the qualitative analysis along with an epidemic indicator which is the basic reproduction number ( R 0 ) of this model, stability analysis of COVID-19 free equilibrium (CFE) and Endemic equilibrium (EE) using Lyaponuv function are considered. We extended the basic model into optimal control system by incorporating three control strategies. These are; use of face-mask and hand sanitizer along with social distancing; treatment of COVID-19 patients and active screening with testing and the third control is prevention against recurrence and reinfection of humans who have recovered from COVID-19. Daily data given by Nigeria Center for Disease Control (NCDC) in Nigeria is used for simulation of the proposed COVID-19 model to see the effects of the control measures. The biological interpretation of this findings is that, COVID-19 can be effectively managed or eliminated in Nigeria if the control measures implemented are capable of taking or sustaining the basic reproductive number R 0 to a value below unity. If the three control strategies are well managed by the government namely; NCDC, Presidential Task Force (PTF) and Federal Ministry of Health (FMOH) or policymakers, then COVID-19 in Nigeria will be eradicated.

A mathematical model for entropy generation in a Powell-Eyring nanofluid flow in a porous channel

The continuous generation of entropy leads to exergy destruction which reduces the performance of a physical system. Hence, entropy minimization becomes necessary. New applications of nanofluids due to their enhanced thermo-physical properties has spurred new studies into the heat transfer and entropy generation rate in nanofluids in the last decade. In this study, we investigate the heat transfer performance and entropy generation rate in a mixed convective flow of a hydromagnetic Aluminum oxide-water Powell-Eyring nanofluid flow through a vertical channel. The nanofluid dynamic viscosity adopted is based on experimental data. The combined effects of the magnetic field, nonlinear thermal radiation, viscous dissipation, suction/injection and convective cooling on the heat transfer and entropy generation were considered. The dimensionless equations describing the flow and energy balance were solved using an efficient iterative spectral local linearization method. The computational analysis of the rate of entropy generation in the channel for various flow parameters is presented. The result shows that increasing the nanoparticle volume fraction and thermal radiation parameter enhanced the temperature profiles, entropy generation and the Bejan number. The results from this study may help engineers in the optimization of thermal systems.