Evidence map›Paper›PMID 34419087›Full record

ArticleTheoretical biology & medical modelling2021

Markov modelling of viral load adjusting for CD4 orthogonal variable and multivariate conditional autoregressive mapping of the HIV immunological outcomes among ART patients in Zimbabwe.

Zvifadzo Matsena Zingoni, Tobias F Chirwa, Jim Todd, Eustasius Musenge

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Article in Theoretical biology & medical modelling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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3 · Its place in the literature

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3 citing papers in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Zvifadzo Matsena ZingoniDivision of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa. zmatsena28@gmail.com.ORCID 0000-0002-7993-1187
Tobias F ChirwaDivision of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.ORCID 0000-0003-4344-0842
Jim ToddDepartment of Population Health, London School of Hygiene and Tropical Medicine, London, UK.ORCID 0000-0001-5918-4914
Eustasius MusengeDivision of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.ORCID 0000-0002-3382-2372

Funding

Wellcome Trust 107754/Z/15/Z
6 · The paper itself

Abstract

backgroundThis study aimed to jointly model HIV disease progression patterns based on viral load (VL) among adult ART patients adjusting for the time-varying "incremental transients states" variable, and the CD4 cell counts orthogonal variable in a single 5-stage time-homogenous multistate Markov model. We further jointly mapped the relative risks of HIV disease progression outcomes (detectable VL (VL ≥ 50copies/uL) and immune deterioration (CD4 < 350cells/uL) at the last observed visit) conditional not to have died or become loss to follow-up (LTFU).

methodsSecondary data analysis of individual-level patients on ART was performed. Adjusted transition intensities, hazard ratios (HR) and regression coefficients were estimated from the joint multistate model of VL and CD4 cell counts. The mortality and LTFU transition rates defined the extent of patients' retention in care. Joint mapping of HIV disease progression outcomes after ART initiation was done using the Bayesian intrinsic Multivariate Conditional Autoregressive prior model.

resultsThe viral rebound from the undetectable state was 1.78times more likely compared to viral suppression among patients with VL ranging from 50-1000copies/uL. Patients with CD4 cell counts lower than expected had a higher risk of viral increase above 1000copies/uL and death if their VL was above 1000copies/uL (state 2 to 3 (λ

conclusionWith high rates of viral rebound, interventions which encourage ART adherence and continual educational support on the barriers to ART uptake are crucial to achieve and sustain viral suppression to undetectable levels. Area-specific interventions which focus on early ART screening through self-testing, behavioural change campaigns and social support strategies should be strengthened in heavily burdened regions to sustain the undetectable VL. Sustaining undetectable VL lowers HIV transmission in the general population and this is a step towards achieving zero HIV incidences by 2030.

Indexed as

Anti-HIV AgentsHIV InfectionsBayes TheoremCD4 Lymphocyte CountHumansViral LoadZimbabweAnti-HIV AgentsCD4 countsHIV disease progressionJoint multistate modelsJoint spatial mapsMultivariate conditional autoregressive priorViral load

Identifiers

PMID34419087
PMCPMC8379787

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