Lessons learnt from assessing and improving accuracy and positive predictive value of the national HIV testing algorithm in Nigeria

Augustine O Mpamugo; Nnaemeka C Iriemenam; Adebobola Bashorun; Olumide O Okunoye; Orji O Bassey; Edewede Onokevbagbe; Tapdiyel Jelpe; Matthias A Alagi; Chidozie Meribe; Rose E Aguolu; Charles E Nzelu; Segun Bello; Babatunde Ezra; Christine A Obioha; Baffa S Ibrahim; Oluwasanmi Adedokun; Akudo Ikpeazu; Chikwe Ihekweazu; Talishiea Croxton; Sylvia B Adebajo; McPaul I J Okoye; Alash'le Abimiku

doi:10.4102/ajlm.v13i1.2339

Lessons learnt from assessing and improving accuracy and positive predictive value of the national HIV testing algorithm in Nigeria

Afr J Lab Med. 2024 Aug 28;13(1):2339. doi: 10.4102/ajlm.v13i1.2339. eCollection 2024.

Authors

Augustine O Mpamugo¹, Nnaemeka C Iriemenam², Adebobola Bashorun³, Olumide O Okunoye², Orji O Bassey², Edewede Onokevbagbe¹, Tapdiyel Jelpe², Matthias A Alagi², Chidozie Meribe², Rose E Aguolu⁴, Charles E Nzelu⁵, Segun Bello^{1

6}, Babatunde Ezra¹, Christine A Obioha¹, Baffa S Ibrahim¹, Oluwasanmi Adedokun¹, Akudo Ikpeazu³, Chikwe Ihekweazu⁷, Talishiea Croxton⁸, Sylvia B Adebajo⁸, McPaul I J Okoye², Alash'le Abimiku⁸

Affiliations

¹ Center for International Health, Education and Biosecurity, Maryland Global Initiatives Corporation, University of Maryland, Baltimore (UMB), Abuja, Nigeria.
² Division of Global HIV and TB, United States Centers for Disease Control and Prevention, Abuja, Nigeria.
³ National AIDS, Viral Hepatitis, and STIs Control Programme, Federal Ministry of Health, Abuja, Nigeria.
⁴ Department of Research Monitoring and Evaluation, National Agency for the Control of AIDS, Abuja, Nigeria.
⁵ Department of Planning, Research and Statistics, Federal Ministry of Health, Abuja, Nigeria.
⁶ Department of Epidemiology and Medical Statistics, Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, Nigeria.
⁷ Nigeria Centers for Disease Control, Abuja, Nigeria.
⁸ Institute of Human Virology, University of Maryland School of Medicine, Baltimore, Maryland, United States.

Abstract

Background: HIV testing remains an entry point into HIV care and treatment services. In 2007, Nigeria adopted and implemented a two-test rapid HIV testing algorithm of three HIV rapid test kits, following the sequence: Alere Determine (first test), Unigold^TM (second test), and STAT-PAK^® as the tie-breaker. Sub-analysis of the 2018 Nigeria HIV/AIDS Indicator and Impact Survey data showed significant discordance between the first and second tests, necessitating an evaluation of the algorithm. This manuscript highlights lessons learnt from that evaluation.

Intervention: A two-phased evaluation method was employed, including abstraction and analysis of retrospective HIV testing data from January 2017 to December 2019 from 24 selected sites supported by the United States President's Emergency Plan for AIDS Relief programme. A prospective evaluation of HIV testing was done among 2895 consecutively enrolled and consented adults, aged 15-64 years, accessing HIV testing services from three selected sites per state across the six geopolitical zones of Nigeria between July 2020 and September 2020. The prospective evaluation was performed both in the field and at the National Reference Laboratory under controlled laboratory conditions. Stakeholder engagements, strategic selection and training of study personnel, and integrated supportive supervision were employed to assure the quality of evaluation procedures and outcomes.

Lessons learnt: The algorithm showed higher sensitivity and specificity in the National Reference Laboratory compared with the field. The approaches to quality assurance were integral to the high-quality study outcomes.

Recommendations: We recommend comparison of testing algorithms under evaluation against a gold standard.

What this study adds: This study provides context-specific considerations in using World Health Organization recommendations to evaluate the Nigerian national HIV rapid testing algorithm.

Keywords: HIV rapid test; HIV/AIDS; Nigeria; lessons learnt; testing algorithm.

Grants and funding

Sources of support This project was supported by the United States President’s Emergency Plan for AIDS Relief through the United States Centers for Disease Control and Prevention under the Grant Number NU2GGHOO2108 NOA 02-03 to the University of Maryland, Baltimore.