Diagnostic accuracy of recombinase polymerase amplification-based assays for mosquito-borne virus detection in clinical samples: a systematic review and meta-analysis
Unknown authors
Sep 2026· Frontiers in Cellular and Infection Microbiology· 0 citations· 61 references
TL;DR
RPA-based assays showed good diagnostic accuracy for mosquito-borne virus detection, with high pooled sensitivity, specificity and AUC, suggesting that RPA-based methods may provide a useful technical choice for rapid case identification and public health response.
Abstract
Mosquito-borne viral diseases pose an important public health threat due to their frequent outbreaks, similar early clinical manifestations, and potential for rapid transmission. Conventional diagnostic methods, such as virus isolation, serological assays and RT-qPCR, are reliable but may be limited by long turnaround time, cross-reactivity, laboratory equipment requirements and trained operators. Recombinase polymerase amplification (RPA)-based methods have emerged as promising tools for rapid detection of mosquito-borne viruses, but their overall diagnostic accuracy still requires comprehensive evaluation. This meta-analysis aimed to systematically evaluate the diagnostic performance of RPA-based assays for mosquito-borne virus detection.
A systematic search of PubMed, Embase, Web of Science, Scopus and MEDLINE was conducted using search terms related to mosquito-borne viruses, RPA technology and diagnostic accuracy. Studies reporting sensitivity and specificity or providing sufficient data to construct 2 × 2 contingency tables were included. The methodological quality of included studies was assessed using QUADAS-2. R software was used for statistical analysis. A Bayesian bivariate random-effects model was applied to calculate pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR) and summary receiver operating characteristic (SROC) curve.
Ten studies involving 13 data sets in total were included in this meta-analysis. The pooled sensitivity and specificity of RPA-based assays were 0.96 (95% CrI: 0.92–0.98) and 0.99 (95% CrI: 0.98–1.00), respectively. The pooled PLR was 146.25 (95% CrI: 35.79–597.57), and the pooled NLR was 0.05 (95% CrI: 0.02–0.10). The area under the SROC curve was 0.987 (95% CrI: 0.972–0.995), suggesting excellent overall diagnostic performance. Subgroup analyses showed that RPA-based assays maintained good diagnostic accuracy in both CRISPR-based and non-CRISPR groups, as well as in DENV and non-DENV subgroups. No significant publication bias was detected by Deeks’ funnel plot asymmetry test.
RPA-based assays showed good diagnostic accuracy for mosquito-borne virus detection, with high pooled sensitivity, specificity and AUC. These findings suggest that RPA-based methods may provide a useful technical choice for rapid case identification and public health response. Nevertheless, the limited number of included studies, methodological limitations and insufficient real-world evidence warrant cautious interpretation. More high-quality prospective studies are still needed to confirm their practical feasibility and application value in clinical and public health settings.
https://www.crd.york.ac.uk/prospero/
, identifier CRD420261380107.
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