Affiliations 

  • 1 Department of Community Health and Social Sciences, CUNY Graduate School of Public Health and Health Policy, New York, NY, USA. vutoanthinhph@gmail.com
  • 2 The Kirby Institute, UNSW Sydney, Sydney, Australia
  • 3 Social Health Clinic, National Center for HIV/AIDS, Dermatology and STDs (NCHADS), Phnom Penh, Cambodia
  • 4 Division of Infectious Diseases and Tropical Medicine, Department of Medicine, Faculty of Medicine and Research Institute for Health Sciences, Chiang Mai University, Chiang Mai, Thailand
  • 5 National Center for Global Health and Medicine, Tokyo, Japan
  • 6 CART CRS, Voluntary Health Services, Chennai, India
  • 7 Chiangrai Prachanukroh Hospital, Chiang Rai, Thailand
  • 8 Faculty of Medicine, Udayana University - Prof. Dr. I.G.N.G. Ngoerah Hospital, Bali, Indonesia
  • 9 Institute of Infectious Diseases, Pune, India
  • 10 Queen Elizabeth Hospital, Hong Kong SAR, China
  • 11 BJ Government Medical College and Sassoon General Hospitals, Pune, India
  • 12 Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
  • 13 Faculty of Medicine Universitas Indonesia - Dr. Cipto Mangunkusumo General Hospital, Jakarta, Indonesia
  • 14 Infectious Diseases Unit, Department of Medicine, University of Malaya, Kuala Lumpur, Malaysia
  • 15 Division of Infectious Diseases, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea
  • 16 Taipei Veterans General Hospital, Taipei, Taiwan
  • 17 Research Institute for Tropical Medicine, Muntinlupa City, Philippines
  • 18 HIV-NAT/ Thai Red Cross AIDS Research Centre, and Tuberculosis Research Unit, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
  • 19 Hospital Sungai Buloh, Sungai Buloh, Malaysia
  • 20 TREAT Asia, amfAR - The Foundation for AIDS Research, Bangkok, Thailand
AIDS Res Ther, 2025 Mar 04;22(1):29.
PMID: 40038791 DOI: 10.1186/s12981-025-00718-8

Abstract

INTRODUCTION: Data on the impact of World Health Organization (WHO)'s guideline changes and COVID-19 on ART initiation in the Asia-Pacific remain scarce. This study described temporal trends from HIV diagnosis to ART initiation from 2013 to 2023 and its associated factors.

METHODS: Adults (≥ 18 years) diagnosed with HIV after 2013 in a regional observational cohort were included. Fine and Gray competing risk regression examined predictors of ART initiation (≥ 3 antiretroviral medications), accounting for those lost to follow-up or deceased before treatment considered as competing risks.

RESULTS: Among 14,968 participants, most were male (70.1%), with a median age of 36 years (interquartile range [IQR]: 28-44). At HIV diagnosis, median CD4 count was 208 cells/µL (IQR: 69-395), and median viral load was 86,296 copies/mL (IQR: 13,186-392,000). Over 85% of participants had initiated ART during the study period. Median time from HIV diagnosis to ART initiation differed across years of HIV diagnosis: 51 days (2013-2015), 28 days (2016-2019), and 26 days (≥ 2020). Factors associated with shorter time to ART initiation were higher country income-level (upper-middle: sub-distribution hazard ratio [SHR] = 1.34, 95% CI: 1.28, 1.40; high: SHR = 1.35, 95% CI: 1.28, 1.43; vs. lower-middle); HIV transmission via male-to-male contact (SHR = 1.06, 95% CI: 1.02, 1.11) or injection drug use (SHR = 1.23, 95% CI: 1.09, 1.38; vs. heterosexual contact); and later years of HIV diagnosis (2016-2019: SHR = 1.33, 95% CI: 1.28, 1.38; ≥ 2020: SHR = 1.40, 95% CI: 1.33, 1.48; vs. 2013-2015). Those with higher CD4 counts had longer time to ART start (350-499 cells/µL: SHR = 0.76, 95% CI: 0.67, 0.86; > 500 cells/µL: SHR = 0.55, 95% CI: 0.49, 0.61; vs. CD4 

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.