Dynamics of a stochastic delay differential model for COVID-19 infection with asymptomatic infected and interacting people: Case study in the UAE

Abstract

Public health science is increasingly focusing on understanding how COVID-19 spreads among humans. For the dynamics of COVID-19, we propose a stochastic epidemic model, with time-delays, Susceptible-Infected-Asymptomatic-Quarantined-Recovered (SIAQR). One global positive solution exists with probability one in the model. As a threshold condition of persistence and existence of an ergodic stationary distribution, we deduce a generalized stochastic threshold . To estimate the percentages of people who must be vaccinated to achieve herd immunity, least-squares approaches were used to estimate from real observations in the UAE. Our results suggest that when , a proportion of the population needs to be immunized/vaccinated during the pandemic wave. Numerical simulations show that the proposed stochastic delay differential model is consistent with the physical sensitivity and fluctuation of the real observations.

Global Dynamics of a Stochastic Viral Infection Model with Latently Infected Cells

“…with initial values x(0) > 0, l(0) > 0, y(0) > 0, v(0) > 0, w(0) > 0. l(t) denotes the concentrations of infected cells in latent stage at t. m be the death rate of l(t) and latent infection become productively infected cells at the rate γ. 3,4,5). We define the basic concepts of probability theory and SDEs.…”

“…Mathematical models have been introduced to define the within-host dynamical behaviors of various viral infections, mainly focusing on virus-to-cell spread in the bloodstream, such as human immunodeficiency virus (HIV) [1], COVID-19 [2,3], hepatitis C virus (HCV) [4,5], hepatitis B virus (HBV) [6], human T cell lymphotropic virus I (HTLV-1) [7], etc. Those classical viral infection models are composed of interactions among susceptible cells, infected target cells, and free viruses.…”

A fractional-order multi-vaccination model for COVID-19 with non-singular kernel

“…Recent trends in epidemiological research revealed that applying non-integer order differential equations is vital in obtaining good results for dynamical systems. The classical mathematical models of the integer-order derivatives have been greatly employed in studying infectious diseases [10] , [11] , [12] , [13] , [16] , [17] , [18] , [19] , [47] , [27] , [28] , [23] , [24] , [25] . For instance, Omame et al [9] considered and analyzed an integer-order model for the dynamics of Human papillomavirus and Chlamydia trachomatis using optimal control.…”

Future implications of COVID-19 through Mathematical modeling

“…The studies focussed on different dynamics of the disease. For a new update about modeling in fractional calculus, we refer to [17] , [18] , [19] , [20] , [21] , [22] , [23] , [24] .…”