ArticleInfectious Disease Modelling2019
A mathematical modelling study of HIV infection in two heterosexual age groups in Kenya.
Article in Infectious Disease Modelling, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 33 citations in OpenAlex.
- HIV Social-network intervention more effective in older populations in Kenya.BMC public health · 2024Trial
- Gender-responsive infectious disease models: Guidelines and systematic scoping review.Dialogues in health · 2026Review
- A potential transition from a concentrated to a generalized HIV epidemic: the case of Madagascar.Infectious diseases of poverty · 2023Article
- Mathematical Model of HIV/AIDS Considering Sexual Preferences Under Antiretroviral Therapy, a Case Study in San Juan de Pasto, Colombia.Journal of computational biology : a journal of computational molecular cell biology · 2022Article
- A fractional order HIV-TB co-infection model in the presence of exogenous reinfection and recurrent TB.Nonlinear dynamics · 2021Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
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Abstract
The control of HIV demands different interventions for different age groups. In the present manuscript, we formulate and analyze a mathematical compartmental models of HIV transmission within and between two age groups in Kenya. We fitted the model to data using MCMC technique and inferred the parameters. We also estimate the reproduction numbers, namely within age group transmission and between age groups transmission basic reproduction numbers. The analysis of the data revealed that there is significant difference in mean number of new HIV infections between males and females within the two age groups. More, particularly, females are highly infected with HIV as compared to their male counterparts. Calculation of the reproduction numbers within and between age groups provides insights into control that cannot be deduced simply from observations on the prevalence of infection. More specifically, the analysis showed that the per capita rate of HIV transmission was highest when there is interaction between young adults to adults and most HIV infections occurred in adult population. Furthermore, the sensitivity analysis demonstrated that the reproduction numbers depend mainly on the probabilities of infection. This results can be used to guide HIV interventions, condom distribution and antiretroviral therapy. Precisely, the results can be used to educate the young adults on practicing safe sex with their partners in order to contain the occurrence of new infections.
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