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Publications

Journal Article Epublish

PubMed: 40743239 DOI: 10.1371/journal.pone.0328488

Reassessment of public awareness and prevention strategies for HIV and COVID-19 co-infections through epidemic modeling.

PLoS One 20(7):e0328488

Authors: Dipo Aldila, Joseph Páez Chávez, Bayu Nugroho, Benjamin Idoko Omede, Olumuyiwa James Peter, Putri Zahra Kamalia

Affiliations

  • Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, Indonesia.
  • Innovative Mathematics and Predictive Analytics for Complex System and Technology Laboratory (IMPACT Lab), Universitas Indonesia, Depok, Indonesia.
  • Center for Applied Dynamical Systems and Computational Methods (CADSCOM), Faculty of Natural Sciences and Mathematics, Escuela Superior Politécnica del Litoral, Guayaquil, Ecuador.
  • Center for Dynamics, Department of Mathematics, TU Dresden, Dresden, Germany.
  • Department of Mathematical Sciences, Prince Abubakar Audu (Formerly Kogi State) University, Anyigba, Nigeria.
  • Department of Mathematics, Saveetha School of Engineering, SIMATS, Saveetha University, Chennai, Tamil Nadu, India.
  • Department of Mathematical and Computer Sciences, University of Medical Sciences, Ondo City, Ondo State, Nigeria.
  • Department of Epidemiology and Biostatistics, School of Public Health, University of Medical Sciences, Ondo City, Ondo State, Nigeria.

Abstract

A co-infection model between HIV and COVID-19 that takes into account COVID-19 vaccination and public awareness is discussed in this article. Rigorous analysis of the model is conducted to establish the existence and local stability conditions of the single-infection models. We discover that when the corresponding reproduction number for COVID-19 and HIV exceeds one, the disease continues to exist in both single-infection models. Furthermore, HIV will always be eradicated if its reproduction number is less than one. Nevertheless, this does not apply to the single-infection COVID-19 model. Even when the fundamental reproduction number is less than one, an endemic equilibrium point may exist due to the potential for a backward bifurcation phenomenon. Consequently, in the single-infection COVID-19 model, bistability between the endemic and disease-free equilibrium may arise when the basic reproduction number is less than one. From the co-infection model, we find that the reproduction number of the co-infection model is the maximum value between the reproduction number of HIV and COVID-19. Our numerical continuation experiments on the co-infection model reveal a threshold indicating that both HIV and COVID-19 may coexist within the population. The disease-free equilibrium for both HIV and COVID-19 is stable only if the reproduction numbers are less than one. Additionally, our two-parameter continuation analysis of the bifurcation diagram shows that the condition where both reproduction numbers equal one serves as an organizing center for the dynamic behavior of the co-infection model. An extended version of our model incorporates four different interventions: face mask usage, vaccination, and public awareness for COVID-19, as well as condom use for HIV, formulated as an optimal control problem. The Pontryagin's Maximum Principle is employed to characterize the optimal control problem, which is solved using a forward-backward iterative method. Numerical investigations of the optimal control model highlight the critical role of a well-designed combination of interventions to achieve optimal reductions in the spread of both HIV and COVID-19.

MeSH

Reproduction, Vaccines, Coinfection, Vaccination, Hiv, Covid-19, Epidemics, Infections