HIV: Current Research
Open Access

Department of Epidemiology, Institute of Global Health, University of Geneva, Switzerland

Publications

• Research Article   
  Aggregating Loss to Follow-Up Behavior in People Living With HIV on ART: A Cluster Analysis Using Unsupervised Machine Learning Algorithm in R
  Author(s): Amobi Andrew Onovo*, Abiye Kalaiwo and Christopher Obanubi
  
  Background: This study aimed to aggregate Loss to Follow Up (LTFU) behavior in People Living with HIV (PLHIV) into clusters to examine and describe PLHIV clusters havings similar characteristics and patterns according to their risk profile. Objectives/methods: This was a retrospective, cross-sectional study that randomly reviewed 11,589 records of LTFU adult patients initiated on first-line ART from 313 USAID/PEPFAR-supported HIV clinics spread across 5 of Nigeria’s 6 geographical regions between July 1, 2008, and June 30, 2020. LTFU, was defined for PLHIV on ART as >28 days without an encounter since the last scheduled ART refill appointment. Using the Minkowski method and ward. D2 clustering technique for unsupervised machine learning algorithm "agglomerative hierarchical clustering" in R, we identified 6 clusters associ.. View More»
  DOI: 10.35248/2572-0805.25.10.425

  Abstract HTML PDF