A mechanistic model for long-term immunological outcomes in South African HIV-infected children and adults receiving ART.

Ujeneza, Eva Liliane; Ndifon, Wilfred; Sawry, Shobna; Fatti, Geoffrey; Riou, Julien Yannis; Davies, Mary-Ann; Nieuwoudt, Martin (2021). A mechanistic model for long-term immunological outcomes in South African HIV-infected children and adults receiving ART. eLife, 10, e42390. eLife Sciences Publications 10.7554/eLife.42390

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Long-term effects of the growing population of HIV-treated people in Southern Africa on individuals and the public health sector at large are not yet understood. This study proposes a novel 'ratio' model that relates CD4+ T-cell counts of HIV-infected individuals to the CD4+ count reference values from healthy populations. We use mixed-effects regression to fit the model to data from 1616 children (median age 4.3 years at ART initiation) and 14,542 adults (median age 36 years at ART initiation). We found that the scaled carrying capacity, maximum CD4+ count relative to an HIV-negative individual of similar age, and baseline scaled CD4+ counts were closer to healthy values in children than in adults. Post-ART initiation, CD4+ growth rate was inversely correlated with baseline CD4+ T-cell counts, and consequently higher in adults than children. Our results highlight the impacts of age on dynamics of the immune system of healthy and HIV-infected individuals.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine (ISPM)

UniBE Contributor:

Riou, Julien Yannis

Subjects:

600 Technology > 610 Medicine & health
300 Social sciences, sociology & anthropology > 360 Social problems & social services

ISSN:

2050-084X

Publisher:

eLife Sciences Publications

Language:

English

Submitter:

Doris Kopp Heim

Date Deposited:

05 Feb 2021 19:26

Last Modified:

05 Dec 2022 15:46

Publisher DOI:

10.7554/eLife.42390

PubMed ID:

33443013

Uncontrolled Keywords:

CD4+ T-cells hiv-1 human immune system infectious disease microbiology mixed model modeling

BORIS DOI:

10.48350/151990

URI:

https://boris.unibe.ch/id/eprint/151990

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