Simultaneous detection of SARS-CoV-2, influenza A, respiratory syncytial virus, and measles in wastewater by multiplex RT-qPCR.

A multiplex quantitative reverse transcription polymerase chain reaction (RT-qPCR)-based method was designed for the simultaneous detection of influenza A, SARS-CoV-2, respiratory syncytial virus, and measles virus. The performance of the multiplex assay was compared to four monoplex assays for relative quantification using standard quantification curves. Results showed that the multiplex assay had comparable linearity and analytical sensitivity to the monoplex assays, and the quantification parameters of both assays demonstrated minimal differences. Viral reporting recommendations for the multiplex method were estimated based on the corresponding limit of quantification (LOQ) and the limit of detection at 95 % confidence interval (LOD) values for each viral target. The LOQ was determined by the lowest nominal RNA concentrations where %CV values were ≤35 %. Corresponding LOD values for each viral target were between 15 and 25 gene copies per reaction (GC/rxn), and LOQ values were within 10 to 15 GC/rxn. The detection performance of a new multiplex assay was validated in the field by collecting composite wastewater samples from a local treatment facility and passive samples from three sewer shed locations. Results indicated that the assay could accurately estimate viral loads from various sample types, with samples collected from passive samplers showing a greater range of detectable viral concentrations than composite wastewater samples. This suggests that the sensitivity of the multiplex method may be improved when paired with more sensitive sampling methods. Laboratory and field results demonstrate the robustness and sensitivity of the multiplex assay and its applicability to detect the relative abundance of four viral targets among wastewater samples. Conventional monoplex RT-qPCR assays are suitable for diagnosing viral infections. However, multiplex analysis using wastewater provides a fast and cost-effective way to monitor viral diseases in a population or environment.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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