A mathematical model for the dynamics of COVID-19 pandemic involving the infective immigrants
Since the first outbreak in Wuhan, China, in December 31, 2019, COVID-19 pandemic has been spreading to many countries in the world. The ongoing COVID-19 pandemic has caused a major global crisis, with 554,767 total confirmed cases, 484,570 total recovered cases, and 12,306 deaths in Iraq as of February 2, 2020. In the absence of any effective therapeutics or drugs and with an unknown epidemiological life cycle, predictive mathematical models can aid in the understanding of both control and management of coronavirus disease. Among the important factors that helped the rapid spread of the epidemic are immigration, travelers, foreign workers, and foreign students. In this work, we develop a mathematical model to study the dynamical behavior of COVID-19 pandemic, involving immigrants' effects with the possibility of re-infection. Firstly, we studied the positivity and roundedness of the solution of the proposed model. The stability results of the model at the disease-free equilibrium point were presented when . Further, it was proven that the pandemic equilibrium point will persist uniformly when . Moreover, we confirmed the occurrence of the local bifurcation (saddle-node, pitchfork, and transcritical). Finally, theoretical analysis and numerical results were shown to be consistent.