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

F. A. Rihan, H. J. Alsakaji

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

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 R0s<R0. To estimate the percentages of people who must be vaccinated to achieve herd immunity, least-squares approaches were used to estimate R0 from real observations in the UAE. Our results suggest that when R0>1, a proportion max(1−1/R0) 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.

Original languageEnglish
Article number104658
JournalResults in Physics
Volume28
DOIs
Publication statusPublished - Sep 2021

Keywords

  • Coronavirus
  • Mathematical modeling
  • Stationary distribution
  • Stochastic threshold
  • Time-delays

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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