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

African Journal of Laboratory Medicine

 
 
Field Value
 
Title Lessons learnt from assessing and improving accuracy and positive predictive value of the national HIV testing algorithm in Nigeria
 
Creator Mpamugo, Augustine O. Iriemenam, Nnaemeka C. Bashorun, Adebobola Okunoye, Olumide O. Bassey, Orji O. Onokevbagbe, Edewede Jelpe, Tapdiyel Alagi, Matthias A. Meribe, Chidozie Aguolu, Rose E. Nzelu, Charles E. Bello, Segun Ezra, Babatunde Obioha, Christine A. Ibrahim, Baffa S. Adedokun, Oluwasanmi Ikpeazu, Akudo Ihekweazu, Chikwe Croxton, Talishiea Adebajo, Sylvia B. Okoye, McPaul I.J. Abimiku, Alash’le
 
Subject Health; Medicine; Laboratory; Infectious disease; HIV lessons learnt; HIV/AIDS; HIV rapid test; testing algorithm; Nigeria
Description 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), UnigoldTM (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.
 
Publisher AOSIS
 
Contributor US Centers for Disease Control and Prevention Maryland Global Initiatives Corporation University of Maryland Baltimore National AIDS and STIs Control Program Nigeria National AIDS Control Agency, Nigeria Nigeria Centers for Disease Control
Date 2024-08-28
 
Type info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion — Cross sectional
Format text/html application/epub+zip text/xml application/pdf application/pdf
Identifier 10.4102/ajlm.v13i1.2339
 
Source African Journal of Laboratory Medicine; Vol 13, No 1 (2024); 7 pages 2225-2010 2225-2002
 
Language eng
 
Relation
The following web links (URLs) may trigger a file download or direct you to an alternative webpage to gain access to a publication file format of the published article:

https://ajlmonline.org/index.php/ajlm/article/view/2339/2953 https://ajlmonline.org/index.php/ajlm/article/view/2339/2954 https://ajlmonline.org/index.php/ajlm/article/view/2339/2955 https://ajlmonline.org/index.php/ajlm/article/view/2339/2958 https://ajlmonline.org/index.php/ajlm/article/view/2339/2956
 
Coverage Nigeria January 2017 to December 2019 15-64 year;, male; female
Rights Copyright (c) 2024 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. Obioh https://creativecommons.org/licenses/by/4.0
ADVERTISEMENT