Transmission dynamics of novel coronavirus SARS-CoV-2 among healthcare workers,a case study in Iran

One of the main concerns during the COVID-19 pandemic was the protection of healthcare workers against the novel coronavirus. The critical role and vulnerability of healthcare workers during the COVID-19 pandemic leads us to derive a mathematical model to express the spread of coronavirus between the healthcare workers. In the first step, the SECIRH model is introduced, and then the mathematical equations are written. The proposed model includes eight state variables, i.e., Susceptible, Exposed, Carrier, Infected, Hospitalized, ICU admitted, Dead, and finally Recovered. In this model, the vaccination, protective equipment, and recruitment policy are considered as preventive actions. The formal confirmed data provided by the Iranian ministry of health is used to simulate the proposed model. The simulation results revealed that the proposed model has a high degree of consistency with the actual COVID-19 daily statistics. In addition, the roles of vaccination, protective equipment, and recruitment policy for the elimination of coronavirus among the healthcare workers are investigated. The results of this research help the policymakers to adopt the best decisions against the spread of coronavirus among healthcare workers.

     

Investigation of the effects of two parallel wires' non-uniform magnetic field on heat and biomagnetic fluid flow in an aneurysm

ABSTRACT

In this paper, effects of two wires magnetic field on heat transfer and biomagnetic fluid flow in an aneurysm have been investigated using the ferrohydrodynamics model. Using the finite volume method and the SIMPLE algorithm, the governing equations have been discretised. Simulations have been carried out for both conditions of wires in the same and opposite directions and different magnetic numbers of 41 and 82. Results show that the magnetic field causes a decrease in heat transfer of blood flow towards the walls. Moreover, major energy loss or pressure drop, arising from mean wall shear stress, decreases but local or minor energy loss, arising from aneurysm vortexes, increases. Furthermore, risk factors of aneurysm rupture is decreased under the effect of the magnetic field. The effective contact surface between drug-coated magnetic nanoparticles and the aneurysm tissue may increase and residence time of drug on the cells of the region would decrease.     

Design a robust sliding mode controller based on the state and parameter estimation for the nonlinear epidemiological model of Covid-19

In this research, the challenging problem of Covid-19 mitigation is looked at from an engineering point of view. At first, the behavior of coronavirus in the Iranian and Russian societies is expressed by a set of ordinary differential equations. In the proposed model, the control input signals are vaccination, social distance and facial masks, and medical treatment. The unknown parameters of the system are estimated by long short-term memory (LSTM) algorithm. In the LSTM algorithm, the problem of long-term dependency is prevented. The uncertainty and measurement noises are inherent characteristics of epidemiological models. For this reason, an extended Kalman filter (EKF) is developed to estimate the state variables of the proposed model. In continuation, a robust sliding mode controller is designed to control the spread of coronavirus under vaccination, social distance and facial masks, and medical treatment. The stability of the closed-loop system is guaranteed by the Lyapunov theorems. The official confirmed data provided by the Iranian and Russian ministries of health are employed to simulate the proposed algorithms. It is understood from simulation results that global vaccination has the potential to create herd immunity in long term. Under the proposed controller, daily Covid-19 infections and deaths become less than 500 and 10 people, respectively.