F1000Research F1000Research 2046-1402 F1000 Research Limited London, UK 10.12688/f1000research.180372.1 Systematic Review Articles Diagnostic accuracy of rapid lateral flow immunoassay tests in Diagnosing HIV Among Key and General Populations: Six Bayesian Meta-Analyses

[version 1; peer review: awaiting peer review]

 Sari Ayu Nurdiantika Conceptualization Data Curation Funding Acquisition Investigation Methodology Resources Writing – Original Draft Preparation Writing – Review & Editing https://orcid.org/0000-0002-0262-1797 a 1 2 Abinawanto Abinawanto Supervision https://orcid.org/0000-0003-0181-9336 1 Nelwan Erni Juwita Supervision Validation https://orcid.org/0000-0003-4064-5412 2 Fadhillah Fadhillah Supervision 1 Dwiranti Astari Supervision 1 Ariantie Oriza Savitri Supervision https://orcid.org/0000-0001-9499-2474 1 Taufiq Rania Rifdah Data Curation Formal Analysis Investigation Methodology Writing – Original Draft Preparation Writing – Review & Editing https://orcid.org/0009-0004-5138-0469 2 Kalaij Ayers Gilberth Ivano Formal Analysis Software Validation Writing – Review & Editing 2 Assyifa Salsa Billa Software 2 Biology, Universitas Indonesia Fakultas Matematika dan Ilmu Pengetahuan Alam, Depok, West Java, 16424, Indonesia University of Indonesia Faculty of Medicine, Jakarta, Special Capital Region of Jakarta, 10430, Indonesia ayunurdiantika10@gmail.com

No competing interests were disclosed.

 23 6 2026 2026 15 994 20 5 2026 Copyright: © 2026 Sari AN et al. 2026 This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background and Aim

Despite advancements in HIV rapid diagnostic tests (RDTs), diagnosing HIV rapidly remains a significant gap, especially in achieving WHO’s targets for diagnosis, treatment, and viral suppression by 2025. This study aims to analyze the diagnostic accuracy of rapid lateral flow immunoassay tests in diagnosing HIV, by providing pooled estimates of diagnostic accuracy for different RDTs detecting HIV infection, compared with various reference standards across general and key populations.

 Methods

We searched four databases (PubMed, Scopus, Cochrane, DOAJ) for cross-sectional or interventional studies that met the predefined criteria from 2010 to 2025. Risk of bias was assessed using QUADAS-2 and QUADAS-C depending on individual study design. Six Bayesian bivariate random-effects meta-analyses yielded pooled estimates of sensitivity, specificity, diagnostic odds ratio, and summary receiver operating characteristic (ROC) curves were calculated using data from studies involving both general and key populations.

 Results

54 studies were included in this meta-analysis. Across all six reference standards comparisons and subgroups, HIV rapid diagnostic tests demonstrated consistently high diagnostic accuracy. When compared against various reference standard, HSROC curves showed clustering near the upper-left region, indicating strong discriminatory ability, while consistently high DOR values further confirmed the robustness of test performance. The pooled sensitivity and specificity were also relatively high in all analysis, ranging above 99% (when compared to EIA/ELISA alone, EIA plus Western Blot, Western Blot alone, the national HIV testing algorithm, and two EIA/ELISA plus Western Blot and PCR as reference standards.

 Conclusion

Our study demonstrates that HIV rapid diagnostic tests maintain consistently high diagnostic accuracy across diverse reference standards, testing conditions, and population groups. The minimal impact of operator, setting, and specimen type, combined with strong performance even under more stringent reference standards, underscores the reliability of these tests for both clinical and large-scale screening applications. Registration: PROSPERO CRD420251244881 (registered 5 December 2025).

 HIV; rapid diagnostic tests; diagnostic performance; Bayesian meta-analysis; lateral flow immunoassay; enzyme immunoassay; Western Blot; PCR The Indonesia Endowment Fund for Education (LPDP), Ministry of Finance, Republic of Indonesia ScholarshipNo.0001135/IPA/D/PARS-I/2025 This research has been funded by the Indonesia Endowment Fund for Education (LPDP), Ministry of Finance, Republic of Indonesia (Scholarship No. 0001135/IPA/D/PARS-I/2025). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Introduction

In 2024, an estimated 40.8 million people lived with HIV. The WHO targets that by 2025, 95% of people with HIV should have a diagnosis, 95% of those enrolled in antiretroviral treatment, and 95% achieving viral load suppression. However, in 2024, these figures only reached 87%, 89%, and 94%, leaving roughly 5.3 million individuals undiagnosed. 1 Closing this diagnostic gap remains critical to achieving WHO targets. Third-generation HIV testing introduced lateral-flow immunoassay rapid diagnostic tests (RDTs) that detect antibodies, now the backbone of many national HIV diagnosis algorithms worldwide. RDTs deliver results within minutes and require fewer resources than conventional laboratory testing, making them advantageous for point-of-care use. 2 Despite their widespread adoption, diagnosing HIV rapidly remains a significant gap in reaching WHO targets.

Past meta-analyses investigating RDT performance were published before 2020, and new studies have since emerged. 3– 8 HIV diagnostic research continues to evolve, including advancements such as digital self-tests, though current WHO guidelines still recommend HIV self-testing (HIVST) as optional, with low certainty of evidence. 9 This study therefore aims to update and expand prior reviews by establishing reliable sensitivity and specificity estimates across diverse populations, given that test performance variability can meaningfully impact clinical and public health outcomes. It covers adults, children, and UNAIDS-defined key populations, reporting pooled diagnostic accuracy estimates (sensitivity, specificity, diagnostic odds ratio, and summary ROC) against multiple reference standards, with subgroup analyses exploring specimen type, administration method, and testing setting.

 Methods Study eligibility criteria

Studies were eligible if they evaluated the diagnostic accuracy of rapid HIV tests in participants with unknown HIV status, including children (aged 18 months to 18 years) and adults. Eligible populations encompassed the general population, individuals seeking voluntary counseling and testing (VCT), those starting provider-initiated testing and counseling (PITC), pregnant women, and key populations as defined by UNAIDS. The index test included any commercially available blood-based or oral fluid-based RDT from third or fourth-generation testing methods. The target condition was HIV infection, defined by confirmed presence of HIV-1 or HIV-2 antibodies or antigens. Reference standards included national testing algorithms, EIA, ELISA, Western blot, and nucleic acid tests (NAT). Eligible designs were observational studies or RCTs, whether laboratory- or field-based, published in peer-reviewed journals between January 2010 and 31 August 2025, in English. Studies were excluded if they focused on early infant diagnosis, individuals on ART or PrEP, or acute HIV infection prior to seroconversion, or if they failed to report sufficient data to construct 2 × 2 contingency tables.

 Information sources, search, study selection

PubMed, Scopus, Cochrane Library, and DOAJ were searched, supplemented by reference lists, reverse citation searching, conference proceedings, and short communications. Search terms combined keywords related to HIV, RDTs, diagnostic performance, and self-testing, covering publications from 2010 to 31 August 2025. Records were imported into Rayyan for deduplication and screened independently by two reviewers (ANS, RRT). Full texts of potentially relevant studies were assessed for inclusion, with disagreements resolved through a third reviewer (AGK).

 Data collection

Data were extracted using a piloted, standardized form by two independent reviewers (RT and ANS). Extracted variables included study characteristics, index test details, reference standard, 2 × 2 table data, and diagnostic accuracy outcomes. Study authors were contacted when data were unclear. Risk of bias and applicability were assessed using QUADAS-2 across four domains: patient selection, index test, reference standard, and flow and timing. For studies reporting multiple brands, QUADAS-C was applied. Disagreements were resolved by a third reviewer (AGK).

 Data synthesis

The primary measures were sensitivity and specificity. Meta-analysis employed a Bayesian bivariate random-effects model, 10 jointly modeling sensitivity and specificity while accounting for their correlation and between-study heterogeneity. Analyses were performed in R using meta4diag, INLA, and tidyverse packages. Summary estimates included pooled sensitivity, specificity, diagnostic odds ratio, and SROC curves with 95% posterior intervals. Heterogeneity was assessed via τ 2 values and visual inspection of SROC curves and forest plots. Subgroup analyses were conducted for specimen type, test mode, and test setting. Review is registered in Prospero (PROSPERO 2025 CRD420251244881).

 Results Literature search and study selection

We identified 5,012 records through database searches ( Figure 1). After removing 1,124 duplicates, 3,888 unique records were screened by title and abstract, resulting in 3,695 exclusions. Full texts of 193 articles were assessed, of which 27 could not be retrieved and 112 of the remaining 166 were excluded. A total of 54 studies were included in the meta-analyses, 8, 11– 63 with characteristics detailed in the supplementary materials. Studies originated from sub-Saharan Africa, Asia, and Latin America, with some conducted in laboratory environments using stored serum samples. Populations included adults, adolescents, pregnant women, children, and key groups such as men who have sex with men, sex workers, transgender individuals, people who inject drugs, and serodiscordant couples. Sample sizes ranged from fewer than 100 to over 13,000, and reference standards included EIA, ELISA, Western blot, PCR, or combinations thereof.

PRISMA flow diagram.

The overall assessment of bias showed that only about half of the studies had a low risk of bias. Nearly 75% of the studies were identified as having a low risk in patient selection, as well as flow and timing ( Figure 2). There were significant concerns about the handling of the index test and reference standards. These bias issues mainly stemmed from inadequate reporting of blinding and unclear personnel procedures or assignments for each test.

Risk of bias assessment (QUADAS-2 and QUADAS-C). Diagnostic accuracy of HIV RDTs compared to various reference standards

Across all six reference standard comparisons, HIV RDTs demonstrated consistently high diagnostic accuracy ( Table 1). Against EIA or ELISA, pooled sensitivity and specificity were 97.9% (95% CrI: 96.6–98.8%) and 99.8% (95% CrI: 99.7–99.9%), with a DOR of 24,043.91 ( Figure 3). Performance improved further against EIA plus Western Blot (Se = 99.2%; Sp = 99.7%; DOR = 48,787.10; Figure 4) and approached near-perfect accuracy against Western Blot alone (Se = 99.8%; Sp = 99.7%; DOR = 126,407.99; Figure 5). Against the national HIV testing algorithm, pooled estimates remained excellent (Se = 99.1%; Sp = 99.6%; DOR = 29,833.83; Figure 6). Comparisons using two EIA/ELISA plus Western Blot and PCR yielded similarly high sensitivity (99.6% and 99.4%, respectively), though specificity was slightly lower under PCR (96.6%), reflecting its higher molecular precision ( Figures 7– 8). Across all analyses, HSROC curves clustered near the upper-left region and consistently high DOR values confirmed robust test performance. Moderate between-study heterogeneity was observed, particularly in EIA/ELISA comparisons, likely reflecting differences in study design, specimen types, and population characteristics. The weak sensitivity-specificity correlation and overlapping credible intervals indicate this did not translate into clinically meaningful variability.

Bayesian hierarchical meta-analyses of lateral flow immunoassay HIV RDTs compared to various reference standards.
Overall/Subgroup Sensitivity 95% CrI Specificity 95% CrI
Reference Standard: EIA or ELISA
Overall 97.9 96.6–98.8 99.8 99.7–99.9
Specimen
Whole Blood Serum 100 — — —
Venous Blood 88.6 — — —
Operator
HCP-testing 97.9 — 99.8 —
Self-testing 97.9 — 99.9 —
Setting
Lab 98.8 97.1–99.7 99.8 99.5–99.9
Field 96.3 93.9–98.0 99.8 99.6–99.9
Reference Standard: EIA + WB or ELISA + WB
Overall 99.2 — 99.7 —
Specimen
Whole Blood 99.9 — 99.96 —
Stored Serum 99.8 — 97.8 —
Serum 99.7 — 99.1 —
Plasma 99.4 — — —
Finger-prick Blood 86.1 — 99.96 —
Operator
HCP-testing — — — —
Self-testing — — — —
Population
General population 99.8 — 98.7 —
Key population 99 — 99.9 —
Reference Standard: 2 EIA/2 ELISA + WB
Overall 99.6 — 98.7 —
Reference Standard: National HIV Testing Algorithm
Overall 99.1 — 99.6 —
Specimen
Finger-prick Blood 100.0 — 98.5 —
Oral fluid 99.3 — — —
Serum 99.6 — ~100.0 —
Venous Blood 99.1 — 98.7 —
Oral swab 97.9 — — —
Saliva 95.2 — 99.96 —
Operator
HCP-testing 99.4 — 99.7 —
Self-testing 96.8 — 99.6 —
Setting
Lab 99.6 — 100 —
Field 99.1 — 99.6 —
Population
General population 99.1 — 99.5 —
Key population 99.4 — 99.97 —
Reference Standard: PCR
Overall 99.4 — 96.6 —
Reference Standard: Western Blot
Overall 99.8 — 99.7 —
Pooled diagnostic results (Single RDTs vs EIA/ELISA).

A. Overall Summary Receiving Operator Curve (ROC). B, subgroup analysis (Test Mode) ROC. C, subgroup analysis (Specimen). D, subgroup analysis (Setting). E, subgroup analysis (Population). F, pooled sensitivity. G, pooled specificity.

 Pooled diagnostic results (Single RDTs vs EIA + WB or ELISA + WB).

A. Overall Summary Receiving Operator Curve (ROC). B, subgroup analysis (Specimen) ROC. C, subgroup analysis (Setting). D, subgroup analysis (Population). E, pooled sensitivity. F, pooled specificity.

 Pooled diagnostic results (2 EIA or 2 ELISA, + WB).

A. Overall Summary Receiving Operator Curve (ROC). B, pooled sensitivity. C, pooled specificity.

 Pooled diagnostic results (Single RDTs vs national algorithms).

A. Overall Summary Receiving Operator Curve (ROC). B, subgroup analysis (Test Mode) ROC. C, subgroup analysis (Specimen). D, subgroup analysis (Setting). E, subgroup analysis (Population). F, pooled sensitivity. G, pooled specificity.

 Pooled diagnostic results (Single RDTs vs PCR).

A. Overall Summary Receiving Operator Curve (ROC). B, pooled sensitivity. C, pooled specificity.

 Pooled diagnostic results (Single RDTs vs WB).

A. Overall Summary Receiving Operator Curve (ROC). B, pooled sensitivity. C, pooled specificity.

 Subgroup analyses

For EIA/ELISA and national algorithm comparisons, stratification by specimen type, operator, setting, and population consistently demonstrated high accuracy with overlapping credible intervals. Self-testing performed comparably to provider-administered testing, and field-based studies maintained accuracy similar to laboratory settings. Minor reductions in sensitivity were observed in finger-prick samples, but were not clinically significant ( Table 1). Subgroup analyses were not performed for comparisons involving two EIA/ELISA plus Western Blot, PCR, or Western Blot alone, as limited variability in study characteristics, predominantly laboratory-based, provider-administered, general population studies, precluded meaningful stratification.

 Discussion

This study demonstrates that HIV RDTs maintain consistently high diagnostic accuracy across multiple reference standards, testing conditions, and populations. The use of multiple reference standards, including serological assays, composite algorithms, and molecular methods, provides a more comprehensive evaluation than a single meta-analysis approach. Overall, HIV RDTs showed strong discriminatory ability, with performance approaching that of established laboratory-based standards, consistent with previous literature. 3, 6, 64 An important finding is the variation in diagnostic performance depending on the reference standard used. Comparisons against serological standards such as EIA/ELISA and Western Blot demonstrated near-perfect accuracy, reflecting their shared immunological basis. In contrast, slightly lower specificity observed against PCR likely reflects the higher analytical sensitivity of molecular assays, which can detect early or low-level infections not yet identifiable by antibody-based RDTs, rather than true false-positive results, an inherent limitation during the serological window period. 64

Moderate between-study heterogeneity was observed across several analyses. This might be driven by differences in study design, specimen types, testing environments, and population characteristics. However, this did not translate into clinically meaningful variability, as evidenced by strong clustering of HSROC curves and substantial overlap in credible intervals. The weak correlation between sensitivity and specificity further supports the overall stability of test performance across diverse settings. Subgroup analyses confirmed consistently high performance across specimen types, operators, testing settings, and population groups. Minor variations were observed in finger-prick and oral fluid samples, likely due to lower antibody concentrations or variability in sample collection, but these were not clinically significant. 65 Notably, self-testing showed comparable accuracy to healthcare provider-administered testing, supporting its role in expanding access to HIV diagnosis, particularly in resource-limited or high-stigma settings. 66 Similarly, comparable performance between laboratory-based and field-based studies underscores the robustness of HIV RDTs under real-world conditions, supporting their use in decentralized and community-based programs.

This study employed a Bayesian bivariate random-effects model, which offers methodological advantages including more intuitive uncertainty estimates, greater stability in handling sparse or heterogeneous data, and better accommodation of the correlation between sensitivity and specificity. 67, 68 Several limitations should be considered. Variability in study quality, including unclear blinding, differences in reference standard application, and inconsistent reporting, may introduce bias. 69, 70 Some studies used stored laboratory samples, potentially overestimating real-world performance. Variability in test brands, HIV subtypes, and geographic settings may further limit generalizability. 71 At the review level, publication bias toward studies reporting higher accuracy may lead to overestimation of performance, and limited subgroup-specific data restricted more detailed analyses. 72

These findings support the continued and expanded use of HIV RDTs in clinical and community settings. Their high diagnostic accuracy, combined with rapid results, ease of use, and cost-effectiveness, make them well-suited for large-scale screening. 9 The comparable performance of self-testing and field-based testing further highlights their potential in underserved populations. 4 Nevertheless, false-negative results may occur during early infection, and false-positive results, though rare, carry significant psychological and clinical consequences. Confirmatory testing using established algorithms therefore remains essential, particularly in settings with varying HIV prevalence or subtype diversity. 73, 74

Conclusion

To conclude, this study demonstrates that HIV RDTs maintain consistently high diagnostic accuracy across multiple reference standards, populations, and testing conditions. The robustness of these findings supports their role as a reliable tool for HIV diagnosis and screening. While certain limitations and sources of variability remain, the overall evidence strongly supports the integration of HIV RDTs into both clinical practice and public health strategies aimed at improving early detection and linkage to care.

 Ethical approval and informed consent

This study doesn’t require ethical approval or direct informed consent as it uses publicly available data.

 Corresponding author

Ayu Nurdiantika Sari ( ayunurdiantika10@gmail.com)

 Availability of data

The datasets generated and/or analysed during the current study are available in the Zenodo repository titled “PRISMA Flowchart + PRISMA Checklists_Ayu” ( https://doi.org/10.5281/zenodo.19859575). 75

Acknowledgement

We have nothing to declare.

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