Loss to Follow-Up Risk among HIV Patients on ART in Zimbabwe, 2009-2016: Hierarchical Bayesian Spatio-Temporal Modeling

Int J Environ Res Public Health. 2022 Sep 2;19(17):11013. doi: 10.3390/ijerph191711013.

Abstract

Loss to follow-up (LTFU) is a risk factor for poor outcomes in HIV patients. The spatio-temporal risk of LTFU is useful to identify hotspots and guide policy. Secondary data on adult HIV patients attending a clinic in provinces of Zimbabwe between 2009 and 2016 were used to estimate the LTFU risk in each of the 10 provinces. A hierarchical Bayesian spatio-temporal Poisson regression model was fitted using the Integrated Nested Laplace Approximation (INLA) package with LTFU as counts adjusting for age, gender, WHO clinical stage, tuberculosis coinfection and duration on ART. The structured random effects were modelled using the conditional autoregression technique and the temporal random effects were modelled using first-order random walk Gaussian priors. The overall rate of LTFU was 22.7% (95%CI: 22.6/22.8) with Harare (50.28%) and Bulawayo (31.11%) having the highest rates. A one-year increase in the average number of years on ART reduced the risk of LTFU by 35% (relative risk (RR) = 0.651; 95%CI: 0.592-0.712). In general, the provinces with the highest exceedance LTFU risk were Matabeleland South and Matabeleland North. LTFU is one of the drawbacks of HIV prevention. Interventions targeting high-risk regions in the southern and northern regions of Zimbabwe are a priority. Community-based interventions and programmes which mitigate LTFU risk remain essential in the global HIV prevention campaign.

Keywords: ART; HIV prevention; LTFU risk; conditional autoregressive models; poisson regression; spatio-temporal.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Anti-HIV Agents* / therapeutic use
  • Bayes Theorem
  • Follow-Up Studies
  • HIV Infections* / drug therapy
  • HIV Infections* / epidemiology
  • Humans
  • Lost to Follow-Up
  • Proportional Hazards Models
  • Zimbabwe / epidemiology

Substances

  • Anti-HIV Agents

Grants and funding

This work was supported by the Developing Excellence in Leadership, Training and Science (DELTAS) Africa Initiative Sub-Saharan Africa Consortium for Advanced Biostatistics (SSACAB) [Grant No. DEL-15-005]. The DELTAS Africa Initiative is an independent funding scheme of the African Academy of Sciences (AAS) Alliance for Accelerating Excellence in Science in Africa (AESA) and is supported by the New Partnership for Africa’s Development Planning and Coordinating Agency (NEPAD Agency) with funding from the Wellcome Trust [Grant No. 107754/Z/15/Z] and the United Kingdom government. The views expressed in this publication are those of the authors and not necessarily those of the AAS, NEPAD Agency, Wellcome Trust, the UK government or the Ministry of Health and Child Care, Zimbabwe. This work was also supported by the Wits University Research Committee (URC) [Grant number: URC-2021].