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An In Vitro Model for Measuring Immune Responses to Malaria in the Context of HIV Co-infection
Published on: October 6, 2015
Co-infection dynamics of COVID-19 and HIV/AIDS
Tesfaneh Debele Batu1, Legesse Lemecha Obsu2, Chernet Tuge Deressa3
1Department of Applied Mathematics, Adama Science and Technology University, Adama, Ethiopia.
Insights
COVID-19 and Human Immunodeficiency Virus (HIV) co-infection poses significant risks, particularly for individuals with advanced HIV. Mathematical modeling and Ethiopian data analysis reveal that increased vaccination and treatment rates can reduce co-infection fatalities.
Area of Science:
- Epidemiology and Mathematical Modeling
- Infectious Disease Dynamics
Background:
- Coronavirus Disease 2019 (COVID-19) and Human Immunodeficiency Virus (HIV) remain significant public health challenges, with co-infection posing a particular threat to immunocompromised individuals.
- People with advanced HIV are a vulnerable population at high risk for severe outcomes when co-infected with COVID-19.
- The lack of a cure for HIV and the potential for recurrent COVID-19 infections necessitate understanding co-infection dynamics.
Purpose of the Study:
- To investigate the impact of intervention strategies on COVID-19 and HIV co-infection outcomes.
- To identify key parameters influencing mortality risk in people living with HIV who contract COVID-19.
- To analyze the transmission dynamics of COVID-19 and HIV co-infection using a mathematical model.
Main Methods:
- Development and rigorous analysis of a mathematical model for COVID-19 and HIV co-infection.
- Establishment of the model's invariant region, positivity, and boundedness.
- Calculation of reproduction numbers, examination of equilibria, and analysis of backward bifurcation for the COVID-19 sub-model.
- Parametric estimation using Ethiopian data, followed by numerical simulations to assess parameter effects and intervention impacts.
Main Results:
- Parameters related to increased exposure and infectiousness in HIV patients positively correlate with higher co-infection rates.
- Increased COVID-19 vaccination rates ([Formula: see text]) demonstrate a suppressive effect on co-infection cases.
- Enhanced treatment rates for COVID-19 ([Formula: see text] and [Formula: see text]) in co-infected individuals significantly reduce the risk of death.
- Backward bifurcation in the COVID-19 sub-model indicates that an R0 less than 1 is insufficient for disease elimination.
Conclusions:
- Improving COVID-19 vaccine delivery programs and medical interventions are crucial for reducing COVID-19-related mortality in people living with HIV.
- Targeted interventions addressing increased infectiousness and exposure in HIV patients are vital for controlling co-infection.
- Mathematical modeling provides valuable insights into the complex dynamics of infectious disease co-infections and the efficacy of control strategies.
Abstract:
Although there are many results that can be used to treat and prevent Coronavirus Disease 2019 (COVID-19) and Human Immunodeficiency Virus (HIV), these diseases continue to be public health concerns and cause socioeconomic consequences. Following compromised immunity, COVID-19 is considered to be a challenge for people with HIV. People with advanced HIV are considered a vulnerable population at high risk in several case studies that discuss COVID-19 and HIV co-infection. As there is no cure for HIV and there is a chance of contracting COVID-19 again, co-infection continues to pose a problem. The purpose of this study is to investigate the impact of intervention strategies and identify the role of different parameters in risking people living with HIV to death when they get infected with COVID-19. This is achieved through the development and rigorous analysis of a mathematical model that considers a population at risk of death due to COVID-19 and HIV. The model formulation provides a detailed explanation of the transmission dynamics of COVID-19 and HIV co-infection. The solution's invariant region, positivity, and boundedness were established. The reproduction numbers of the sub-models and the co-infection model were determined. The existence and stability of equilibria, including backward bifurcation for the COVID-19 sub-model, were examined. The epidemiological significance of backward bifurcation is that the condition [Formula: see text] less than 1 for eliminating COVID-19, though necessary, is no longer sufficient. Parametric estimation and curve fitting were performed based on data from Ethiopia. Numerical simulations were employed to support and clarify the analytical findings and to show some parameter effects on COVID-19 and HIV co-infection. Accordingly, the simulations indicated that parameters [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text], related to HIV patients' exposure to other diseases and the increase in infectiousness, have a positive role in increasing the number of co-infections. On the other hand, an increase in COVID-19 vaccination ([Formula: see text]) shows the suppression of co-infection cases. In addition, treating co-infected individuals for COVID-19, increasing treatment rates [Formula: see text] and [Formula: see text], reduces the death risk of HIV-infected individuals due to the co-infection burden. It was implied that improving vaccine delivery programs and other medical interventions have important contributions to lowering the risk of COVID-19 infection-related fatalities in HIV patients.
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