TB Research

COVID-19 epidemiology and performance of the WHO clinical algorithm to diagnose COVID-19 in people with HIV from Ukraine

Vasylyev M, Buhiichyk V, Buhiichyck N, Groenendijk A, Ben I, Ostapiuk L, Sluzhynska M, Bierman WFW, et al. (14 authors)

International journal of STD & AIDS · 2024-02

Abstract

Background The two main objectives were to evaluate the COVID-19 point prevalence and the test performance of the WHO case definition to diagnose COVID-19 clinically in people with HIV in West Ukraine. Methods Multicenter cross-sectional study in Lviv, Ukraine, from October 2020-November 2021. COVID-19 unvaccinated people with HIV were included regardless of COVID-19 symptoms at routine clinical visits and had standardized medical, quality of life (EQ(5D)) and SARS-CoV-2 serology assessments. Reported symptoms indicating potential COVID-19 events at inclusion or between March 2020 and inclusion were classified by the WHO case definition as suspected, probable or confirmed. A clinical COVID-19 case was defined as being SARS-CoV-2 seropositive with at least a suspected COVID-19 according to the WHO case definition. The primary endpoints were the clinical COVID-19 prevalence and the test characteristics of the WHO case definition with SARS-CoV-2 serology as reference. (Clinicaltrials.gov:NCT04711954). Results The 971 included people with HIV were median 40 years, 38.8% women, 44.8% had prior AIDS, and 55.6% had comorbidities. SARS-CoV-2 seroprevalence was 40.1% (95%CI:37.0-43.1) and 20.5% (95%CI:18.0-23.1) had clinical COVID-19 median 4 months (IQR:2-7) before inclusion. Clinical COVID-19 occurred less frequently in people with HIV with tuberculosis history, injecting drug use, CD4+ T-cells Conclusions COVID-19 unvaccinated people with HIV from Ukraine had a significant COVID-19 rate and using the WHO case definition had insufficient diagnostic accuracy to diagnose these cases. The lower burden in vulnerable people with HIV was unexpected but might reflect a shielding effect.

MeSH terms

  • Humans
  • HIV Infections
  • Prevalence
  • Cross-Sectional Studies
  • Algorithms
  • Quality of Life
  • Adult
  • Middle Aged
  • World Health Organization
  • Ukraine
  • Female
  • Male
  • COVID-19
  • SARS-CoV-2