Screening Algorithms to Reduce Burden of Pediatric HIV Testing: A Systematic Review and Meta-analysis

Pediatr Infect Dis J. 2020 Oct;39(10):e303-e309. doi: 10.1097/INF.0000000000002715.


Background: The accuracy of symptom screening to identify children eligible for further HIV testing in generalized epidemics has been examined in several studies. We performed a systematic review and meta-analysis of these studies.

Methods: We screened 5 databases and abstracts from 4 HIV/AIDS conferences. Studies were included if they were performed in clinical settings, included children of 0-15 years old, and used a signs/symptoms screen to determine eligibility for HIV testing. The primary outcomes were sensitivity and specificity of the screening tools. A meta-analysis was performed to evaluate the utility of a screening tool in the outpatient setting.

Results: Our search returned 5529 database results and approximately 6700 conference abstracts, of which 36 articles were reviewed and 7 met criteria for inclusion. All were prospective or cross-sectional studies that developed and/or validated a screening tool to identify children at higher risk for being HIV infected. Sensitivity of the screening tools ranged from 71% to 96%, whereas specificity ranged from 25% to 99%. Meta-analysis of studies evaluating outpatient screening tools revealed a sensitivity of 81.4%, with a specificity of 69.4% for detecting HIV infection.

Conclusions: Few studies have evaluated the use of screening tools for HIV diagnosis in children. Screening tools that exist showed only moderate sensitivity and specificity and missed a substantial number of HIV-infected children in high-prevalence areas. In outpatient settings, the use of a screening tool may help reduce the number of HIV tests needed to identify an HIV-infected child, but at the cost of missed diagnoses. Further studies are needed to determine whether this represents a resource-saving mechanism.

Publication types

  • Meta-Analysis
  • Systematic Review

MeSH terms

  • Adolescent
  • Algorithms*
  • Child
  • Child, Preschool
  • Cross-Sectional Studies
  • HIV Infections / diagnosis*
  • HIV Testing / methods*
  • Humans
  • Infant
  • Infant, Newborn
  • Mass Screening / methods*
  • Prospective Studies