ArticleEpidemiologia (Basel, Switzerland)2023
Modeling Transmission Dynamics of Tuberculosis-HIV Co-Infection in South Africa.
Article in Epidemiologia (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Mechanistic Models of Virus-Bacteria Co-Infections in Humans: A Systematic Review of Methods and Assumptions.Pathogens (Basel, Switzerland) · 2025Pooled it
- Investigating Gendered Implicit Bias Among Healthcare Workers in South Africa: Development and Piloting of an Implicit Association Test in a High Tuberculosis and HIV Setting.Research square · 2026Article
- Modelling TB-HIV co-infection and evaluating intervention strategies in Thailand.BMC infectious diseases · 2026Article
- Tuberculosis in prisons: an integrated prevention and care cascade for a persistent structural epidemic.Frontiers in public health · 2026Review
- Predicting treatment adherence in patients with drug-resistant tuberculosis: insights from socioeconomic, demographic, and clinical factors of patients in the rural Eastern Cape.Frontiers in tuberculosis · 2025Article
- Article
- A Systematic Literature Review of Mathematical Models for Coinfections: Tuberculosis, Malaria, and HIV/AIDS.Journal of multidisciplinary healthcare · 2024Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
South Africa has the highest number of people living with the human immunodeficiency virus (HIV) in the world, accounting for nearly one in five people living with HIV globally. As of 2021, 8 million people in South Africa were infected with HIV, which is 13% of the country's total population. Approximately 450,000 people in the country develop tuberculosis (TB) disease every year, and 270,000 of those are HIV positive. This suggests that being HIV positive significantly increases one's susceptibility to TB, accelerating the spread of the epidemic. To better understand the disease burden at the population level, a Susceptible-Infected-Recovered-Dead (SIRD) TB-HIV co-infection epidemic model is presented. Parameter values are estimated using the method of moments. The disease-free equilibrium and basic reproduction number of the model are also obtained. Finally, numeric simulations are carried out for a 30-year period to give insights into the transmission dynamics of the co-infection.
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Registered trials
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