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January 17, 20260 citationsOpen Access

Optimising HIV Case Identification in Low-Yield Settings: Evidence from Routine Programme Data in Kebbi, Sokoto, and Zamfara States, Nigeria

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CAChika Ananaba

Key Points

  • The aim is to identify patterns and predictors of HIV positivity using routine testing data to enhance case identification strategies.
  • Conducted a retrospective analysis of HIV testing services data from Kebbi, Sokoto, and Zamfara States.
  • Focused on data collected during FY25 from October 2024 to September 2025.
  • Examined testing yield patterns and predictors of HIV positivity to guide strategies.
  • Identified specific patterns in HIV testing yields across the regions studied.
  • Unveiled predictors that can enhance case identification in low-yield settings.

Abstract

This preprint contains an abstract based on a retrospective analysis of routinely collected HIV testing services (HTS) data from Kebbi, Sokoto, and Zamfara States in Nigeria during FY25 (October 2024 to September 2025). The analysis examines HIV testing yield patterns and predictors of HIV positivity to inform more efficient case identification strategies in low-yield settings.

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Cite This Study

Chika Ananaba (2026) studied this question.

synapsesocial.com/papers/696b25f3d2a12237a93492e5https://doi.org/10.5281/zenodo.18255338
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