Evaluation and Utility of a Family Information Table to Identify and Test Children at Risk for HIV in Kenya

Authors

  • Michelle Meyer, BA School of Medicine, University of California, San Francisco, CA 94143, USA
  • Molly Elmer-DeWitt, BA School of Medicine, University of California, San Francisco, CA 94143USA
  • Cinthia Blat, MPH School of Medicine, University of California, San Francisco, CA 94143 USA and Kenya Medical Research Institute (KEMRI), Family AIDS Care and Education Services (FACES), Kisumu, KENYA
  • Starley B. Shade, PhD Department of Medicine, University of California, San Francisco, CA 94143, USA and Kenya Medical Research Institute (KEMRI), Family AIDS Care and Education Services (FACES), Kisumu, KENYA
  • Ijaa Kapule, MBChB, PhD Kenya Medical Research Institute (KEMRI), Family AIDS Care and Education Services (FACES), Kisumu, KENYA
  • Elizabeth Bukusi, MBChB, PhD Kenya Medical Research Institute (KEMRI), Family AIDS Care and Education Services (FACES), Kisumu, KENYA
  • Craig R. Cohen, MD Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, San Francisco, CA 94143, USA and Kenya Medical Research Institute (KEMRI), Family AIDS Care and Education Services (FACES), Kisumu, KENYA
  • Lisa Abuogi, MD Department of Pediatrics, University of California, San Francisco, CA 94143, USA and Kenya Medical Research Institute (KEMRI), Family AIDS Care and Education Services (FACES), Kisumu, KENYA and Department of Pediatrics, University of Colorado, Denver, CO 80045, USA (current affiliation)

DOI:

https://doi.org/10.21106/ijma.30

Abstract

Background: Effective strategies to identify and screen children at risk for HIV are needed. The objectives of this study were to evaluate the utilization of a family information table (FIT) to identify and test at-risk children in Kenya and identify factors associated with child testing.

Methods: A cross-sectional study was conducted among HIV-infected adults with children at five Kenyan clinics. HIV testing status for children aged ?18 years was gathered from the patients’ FITs and compared to reports from in-person clinic visits as the gold standard. Generalized estimating equations were used to assess predictors for HIV testing of children adjusted for confounders and within parent correlation.

Results: Our sample included 384 HIV-infected adults enrolled in care with 933 reported children. Overall, 323 FITs (84%) correctly listed all children in the family and 340 (89%) documented an HIV testing status (including untested) for all children. Seventy-five percent of parents verbally reported all children tested, compared to only 46% of FITs (OR=13.5, 95% CI 6.5-27.8). Verbal reports identified 739 (79%) children tested, with 55 (7.4%) HIV-positive and 17 (2.3%) HIV-exposed infants (HEI). Of 63 adults with HIV-positive children or HEI, 60 (95%) reported enrolling children into care. Likelihood that children had been tested was higher for younger children (?4y vs. > 4y, aOR=2.0; 95% CI 1.4-2.9) and lower if the partner’s serostatus was unknown vs. seropositive (aOR=0.3; 95% CI: 0.1-0.8).

Conclusions: Although the FIT may be a useful tool to identify children at risk for HIV, this study found underutilization by providers. To maximize impact of this tool, documentation of follow-up for untested and positive
children is essential.

Global Health Implications: Through early documentation of at-risk children and follow up of untested and infected children, the FIT may serve as an effective resource for improving HIV testing and linkage to care.

Key Words: Family Information Table • Pediatrics • HIV/AIDS • Linkage • Kenya • HIV Testing

Copyright © 2014 Meyer et al. Published by Global Health and Education Projects, Inc. This is an open-access article distributed under the terms of the Creative Commons Attribution License CC BY 4.0.

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