Improving HIV case finding using spatial data infrastructures in Anambra State, Nigeria: a pre-post intervention study.

Abstract

Background: The heightened HIV prevalence in Nigeria is partly associated with challenges in accessing people living with HIV in geographically isolated and unidentified regions. Spatial Data Infrastructure (SDI) is an innovation that has shown promise for HIV case-finding in unidentified settlements. This study reports the use of SDI to improve HIV case identification in Anambra North Senatorial District, Nigeria.

Methods: This study utilised a pre-post intervention study design to analyse data from the implementation of HIV testing services (HTS). Settlements for HTS were identified in the district using SDIs, such as microplans and hotspot maps. Community teams captured areas' names and geolocations using a custom application. Geographical Information Systems technology was overlayed on coordinates to generate microplans and hotspot maps, which were used for targeted tests and new case identification.

Results: Our study showed varying trends across the periods when SDIs were utilised and when they were not. The use of SDI greatly enhanced HIV case identification and provided a strategic framework for HTS implementation. Overall, the period when SDI was used recorded relatively higher new cases than before. Local Government Areas with more rural settlements that leveraged SDI significantly upscaled their case identification.

Conclusions: SDI can facilitate HIV case identification. Our study revealed twice as many cases identified across the periods compared. Our pioneering use of SDI for HIV case finding in Nigeria offers promise for efficient HTS implementation in high-burden and yet-to-be-identified locations.