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. 2025 Apr 15;18(4):e70144. doi: 10.1111/1751-7915.70144

One‐Step RAA and CRISPR‐Cas13a Method for Detecting Influenza B Virus

Xinling Zhang 1, Shiyu Chen 1, Juezhuo Li 2, Dong‐ang Liu 1, Jianxiu Lai 3, Xiangquan Song 4, Ruiyao Hu 1, Yuting Qiu 1, Keyi Chen 1, Yue Xu 1, Xiaoping Li 1,✉
PMCID: PMC11998173  PMID: 40231967

ABSTRACT

We developed a sensitive and specific method based on recombinase‐aided amplification (RAA) and clustered regularly interspaced short palindromic repeats (CRISPR)‐CRISPR‐associated protein 13a (Cas13a). This method, named CRISPR‐based Rapid and Efficient Test (CRISPRET), is designed for the early diagnosis of Influenza B (FluB) with the aim of shortening its transmission chain. We identified conserved regions in the Influenza B Virus (IBV) NS gene and designed forward and reverse primers along with crRNAs. We then established and optimised the reaction system, and Nucleic Acid Positive Reference Materials of IBV were used to evaluate the detection limit (DL) of CRISPRET. Additionally, we collected 257 clinical samples, comprising 127 samples from patients with IBV infection and 130 samples from healthy individuals, and subjected them to dual detection using CRISPRET and qPCR to evaluate the positive predictive value (PPV), negative predictive value (NPV), sensitivity and specificity of CRISPRET. We designed one forward primer, two reverse primers, and two crRNAs to establish and optimise the CRISPR ET. The method demonstrated the DL of 500 copies·μL−1 when assisted by appropriate equipment. Despite requiring auxiliary equipment and a 30‐min reaction, the CRISPR ET method enables the detection of IBV nucleic acid within approximately the first 5 min, achieving high sensitivity (100%), specificity (97.69%), PPV (97.69%) and NPV (100%), with a concordance rate of 98.83% to qPCR. CRISPRET offers a simple, field‐applicable, one‐step method for the rapid detection of IBV. It has strong potential for field‐testing applications and intelligent integration into existing diagnostic systems.

Keywords: CRISPR‐Cas13, influenza B, one‐step method, RAA, rapid detection

CRISPRET initially designs upstream and downstream primers and crRNAs targeting the NS gene of the Influenza B Virus (FluB) for the identification of the target RNA (NS gene). During testing, RNA from the Influenza B Virus is extracted from clinical throat swab samples using a sample RNA release preservative. The obtained RNA is then combined with the CRISPR‐Cas13a‐targeted RNA system, which includes an RNA fluorescent probe labelled with FAM and BHQ. The samples to be tested were placed into the test wells of the Genchek Fluorometer at a constant temperature of 37°C. The instrument automatically collects fluorescence every 20 s, and the entire reaction curve was obtained after 30 min of reaction. By comparing the results from the Genchek fluorimeter and qPCR, CRISPRET demonstrates high sensitivity (100%), specificity (97.69%), positive predictive value (97.69%), negative predictive value (100%), and an overall concordance rate of 98.83%.

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1. Introduction

Influenza is an acute respiratory infectious disease caused by the influenza virus and is one of the most burdensome infectious diseases in society (Al‐Dorzi et al. 2024). Each year, there are approximately 1 billion cases of seasonal influenza worldwide, with 3–5 million severe cases. Additionally, seasonal influenza results in 290,000 to 650,000 deaths annually (WHO 2023). Influenza viruses are categorised into four types: A, B, C and D, with the Influenza A virus (IAV) and Influenza B virus (IBV) being the most predominant types causing infections. These viruses are primarily transmitted through respiratory droplets expelled when an infected person coughs or sneezes. They exhibit seasonal and regional characteristics in their spread (Dorji et al. 2024; Rousogianni et al. 2024; Çalışkan et al. 2024). In the early stages of infection, it can be difficult for patients to recognise influenza based on symptoms alone, which poses a challenge for preventing and controlling respiratory infections.

Currently, numerous methods are employed to detect influenza, including quantitative polymerase chain reaction (qPCR), viral culture, antigen detection, and serological testing (Peng et al. 2024). qPCR exhibits higher sensitivity compared to other methods. However, it has a lengthy detection cycle and requires expensive equipment and highly trained operators, which contradicts the actual demand for point‐of‐care testing (POCT) (Mautner et al. 2020; Nyaruaba et al. 2022). Moreover, delayed diagnosis can lead to a higher rate of viral transmission, thereby placing significant strain on preventing respiratory infectious diseases. Isothermal amplification techniques have also been applied in detecting influenza viruses; however, their sensitivity often falls short of expectations, and they possess certain limitations (Jee et al. 2023; Tripathy et al. 2023). Nevertheless, the combination of isothermal amplification techniques with the clustered regularly interspaced short palindromic repeats (CRISPR) system can significantly enhance the sensitivity of detection (Razavi et al. 2024). To address these limitations, researchers have explored various combinations of isothermal amplification techniques and CRISPR. Currently, there are detection methods that incorporate loop‐mediated isothermal amplification (LAMP) and recombinase polymerase amplification (RPA) with CRISPR (Gootenberg et al. 2017; Liu et al. 2024). Additionally, CRISPR‐associated proteins (Cas) have the unique advantage of specifically cleaving nucleic acid sequences without temperature cycling (Miao et al. 2023). Recombinase‐aided amplification (RAA) also similarly performs well, which could complete nucleic acid amplification within 30 min at a temperature range of 35°C–40°C (Mao et al. 2023). Therefore, this study aims to establish a simple nucleic acid detection method based on RAA and Cas13a that offers high sensitivity, high specificity, and a detection limit (DL). The sensitivity and specificity of this method will be analysed and compared with qPCR to develop a sensitive, portable and rapid detection method for the early diagnosis and prevention of influenza virus, ultimately reducing the mortality associated with severe influenza.

2. Experimental Procedures

2.1. Materials

2.1.1. Source of Clinical Samples

Clinical samples were collected from individuals aged 1–65 in Hangzhou, China, between January 1, 2024, and March 31, 2024, at the Community Health Service Center of Sandun Town, Xihu District, Hangzhou. The collection included 127 samples from patients with IBV infection and 130 samples from healthy individuals. The experimental protocol was established according to the ethical guidelines of the Helsinki Declaration and has been approved by the medical ethics committee of the Community Health Service Center of Sandun Town, Xihu District, Hangzhou (Number: 20241028001).

2.1.2. Main Reagents and Instruments

The following reagents and equipment were used in this study: single‐stranded binding protein, recombinase protein, Bsμ DNA Polymerase, reverse transcriptase, RNase Inhibitor and rNTPs solution (New England Biolabs, Beijing, China); Polyethylene glycol (PEG); Magnesium acetate (MgOAc) solution; Lbu Cas13a nuclease and T7 RNA polymerase (GenScript Biotech Corporation, Nanjing, China); sample RNA release preservative (Jiangsu Genestone Bio‐technology Co. Ltd., Item No.: FA02001‐01‐100); crRNAs, forward primer, reverse primer and reporter probes (Sangon Biotech Shanghai Co. Ltd.); the 2nd National Reference Panel for Influenza B Viral Nucleic Acids Detection Kit (National Institutes for Food and Drug Control, China, Item No.: 370052–201,801); Influenza A/B Viral nucleic acid detection kit (PCR ‐fluorescence Probing) (Shanghai BioGerm Medical Technology Co. Ltd., Item No.:ZC‐LG‐201‐2); Genchek Fluorimeter (Hangzhou ZC Bio‐Sci & Tech Co. Ltd.); tabletop mini centrifuge (JOANLAB Equipment CO. Ltd.); nucleic acid electrophoresis apparatus (Beijing Liuyi Biotechnology CO. Ltd.); iBright FL1500 imaging system (Thermo Fisher Scientific Inc).

2.2. Methods

2.2.1. Principle of CRISPR‐Cas13a for Rapid Nucleic Acid Detection

The CRISPR‐Cas13a Rapid Detection of Nucleic Acids operates on the principle of forming a highly sensitive complex between CRISPR RNA (crRNA) and Cas13a. When this complex encounters a reaction mixture containing the target RNA, the crRNA binds specifically to the target through base pairing, which activates Cas13a's cleavage activity. This activation leads to the cleavage of a surrounding fluorescent reporter probe, which is labelled with both a fluorophore and a quencher, resulting in fluorescence from the cleaved reporter moiety. This fluorescence can be measured instrumentally to determine if the reaction is positive (Abudayyeh et al. 2016; Wang et al. 2022; Chen et al. 2024). Conversely, if the target RNA is absent from the reaction mixture, cleavage activity cannot be initiated, and no increase in fluorescence signal occurs, indicating a negative result. This principle underlies the efficient detection of nucleic acids.

Building on this principle, we developed a one‐step detection system utilising RAA and CRISPR‐Cas13a by analysing the conserved sequences of the NS gene of the IBV. We designed highly specific primers and crRNAs and optimised the reagent composition. This led to the establishment of a novel rapid detection method for IBV, named the CRISPR‐based Rapid and Efficient Test (CRISPRET), which enables rapid and accurate detection of IBV.

2.2.2. Design of Forward and Reverse Primers and crRNA

Based on the nucleotide sequences of the IBV published in the GenBank database maintained by the National Center for Biotechnology Information (NCBI) in the United States, we selected conserved regions of the NS gene (Ma et al. 2024). Two sets of primers were designed using Primer Premier 6 to amplify specific regions of the NS gene. The specificity of these primer sets for IBV and the absence of genetic homology with human sequences, other respiratory viruses, and common microorganisms were confirmed using Primer‐BLAST (https://www.ncbi.nlm.nih.gov/tools/primer‐blast/index.cgi). Separately, two crRNAs were designed using CHOPCHOP to target the same conserved regions in the NS gene. The potential off‐target effects of the crRNA spacer sequences were minimised through BLAST analysis. Importantly, the sequence divergence between influenza A (IAV) and IBV enabled us to design primers and crRNAs that specifically target IBV. This approach minimised the risk of cross‐reactivity with FluA. All primers and crRNAs were synthesised by Sangon Biotech (Shanghai) Co. Ltd.

2.2.3. Establishment and Optimization of RAA and CRISPR‐Cas13a Reaction System

The preliminary established reaction system (1 T) was detailed in Table 1, with a total volume of 45 μL for the mixed solution. The sample and buffer were then added to this mixed system, and amplification reactions were carried out at a temperature range of 35°C–40°C for 30 min.

TABLE 1.

The components of the reaction system.

Substance Concentration Dosage
Single‐stranded binding protein 90 ng·μL−1 2 μL
Recombinase protein 120 ng·μL−1 1 μL
Bsμ DNA Polymerase 30 ng·μL−1 3.5 μL
Forward primer 10 μmol·mL−1 2 μL
Reverse primer 10 μmol·mL−1 2 μL
Reverse transcriptase 100 U·μL−1 2.5 μL
RNase Inhibitor 50,000 U·mL−1 3 μL
PEG 10 g/100 mL (Distilled water) 7 μL
Lbu Cas13a nuclease 10 μmol·L−1 1 μL
T7 RNA polymerase 60 U·μL−1 5 μL
rNTP 20 mmol·L−1 4 μL
crRNA 5 μmol·L−1 5 μL
DEPC water / 1.5 μL
Reporter probe 1000 μmol·mL−1 (To be optimised) 2 μL
MgOAc 250 mmol·L−1 3.5 μL
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Note: This is a 1 T reaction system with a total of 45 μL. After centrifugation, 5 μL samples were added to the reaction tube and then put into the Genchek fluorometer for the amplification reaction. After 30 min, the magnitude of the value of fluorescence can be used to determine the negative and positive results of an experiment.

Screening for optimal forward and reverse primers: The Nucleic Acid Positive Reference Materials of IBV served as the sample during this screening process. Each combination of forward and reverse primers was tested in the RAA nucleic acid amplification system, followed by detection using agarose gel electrophoresis. A gel imaging system was employed to analyse the DNA separation, allowing us to assess the purity and concentration of DNA by observing the size and brightness of the DNA bands. This process led to selecting the optimal combination of forward and reverse primers.

Screening for optimal crRNA: For screening, the Nucleic Acid Positive Reference Materials of IBV were again used as the sample. Each crRNA was tested independently in the Cas13a reaction under the optimised conditions previously established. The optimal crRNA was identified by comparing the relative value of fluorescence. By integrating the optimised conditions, the best reaction system was obtained.

Screening for optimal Reaction Conditions: The reaction conditions that affect detection results include temperature, concentration of fluorescent probes, and others. Using the value of fluorescence data obtained from the Genchek fluorimeter, optimal reaction conditions were determined by comparing the endpoint value of fluorescence. The screening process followed a one‐variable‐at‐a‐time approach, specifically examining reaction temperatures (ranging from 35°C–40°C) and fluorescent probe concentrations (5, 10, 15 and 20 μmol·mL−1).

2.2.4. Detection Limit Analysis

The Nucleic Acid Positive Reference Materials of IBV (concentration of 5 × 1012 copies·μL−1) were serially diluted in a 1:10 ratio to obtain concentrations of 5 × 106, 5 × 105, 5 × 104, 5 × 103, 5 × 102, 5 × 101, and 5 × 100 copies·μL−1. The detection was performed using the established method, and the DL was evaluated for each reaction within the defined reaction system. The data obtained from five independent repetitions of the detection were statistically analysed.

2.2.5. Sensitivity and Specificity Analysis and Clinical Sample Validation

Parallel detection was conducted using the established CRISPRET methods as well as qPCR on 127 throat swab samples from patients with IBV infection and 130 throat swab samples from healthy individuals. In evaluating the clinical samples, a Ct value of ≤ 35 was considered positive for the qPCR method, which is a critical indicator for assessing the sensitivity and specificity of diagnostic tests. The sensitivity (true positive rate) and specificity (true negative rate) of both methods were then evaluated to determine their concordance rate in detecting these clinical samples. Beyond sensitivity and specificity, it is crucial to consider the positive predictive value (PPV) and negative predictive value (NPV). The PPV indicates the likelihood that a patient with a positive test result genuinely has the disease, while the NPV denotes the likelihood that a patient with a negative test result is genuinely free from the disease (Parikh et al. 2008). This approach not only highlights the reliability of the CRISPRET method but also reinforces the significance of Ct values in clinical diagnostics (Bustin et al. 2009).

2.2.6. Data Analysis

To compare the detection results between qPCR and our method, we conducted a 2 × 2 contingency table analysis. By constructing a 2 × 2 contingency table, we were able to assess the consistency of detection results between the two methods. We calculated sensitivity, specificity, PPV, NPV, and concordance rate (defined as true positives plus true negatives divided by total number of samples) with qPCR using standard formulas (Parikh et al. 2008). These statistical indicators allowed us to comprehensively evaluate the consistency and differences in detection performance between our method and qPCR. The analysis results provide important references for the clinical application of our method.

3. Results

3.1. Results of Forward Primer, Reverse Primer, and crRNA Design

Based on the molecular biology software design, one forward primer (F), two reverse primers (R1 and R2), and two crRNA sequences were obtained (Table 2). We tested each combination of forward and reverse primers using agarose gel electrophoresis to screen for the best forward and reverse primer combinations. It was observed that the band intensity of the forward primer combined with reverse primer R2 (group FR2) was brighter than that of the forward primer combined with reverse primer R1 (group FR1) (Figure 1), indicating a higher amplification efficiency (Raggi et al. 2003). Therefore, we chose group FR2.

TABLE 2.

Influenza B virus primers and crRNA sequences.

Sequence
Forward primer F1 TTGACAGACATAACAGCACAGACTGCCTAT
Reverse primer R1 GCCTCACTACGACTAGACTACGACCAAG
Reverse primer R2 GCCTATCAACGACGATACTACCAGCAAG
crRNA1 GGGAUUUAGACUACCCCAAAAACGAAGGGGACUAAAACACUCCAUGCGAUCACUAGAUCAACUAG
crRNA2 GGGAUUUAGACUACCCCAAAAACGAAGGGGACUAAAACUCAGCAUCCGAUCACUUGAUCGACUAG
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FIGURE 1.

FIGURE 1

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The results of forward and reverse primer screening. The RAA amplification products are between 250 and 500 bp in length.

crRNA is a short RNA molecule that directs Cas13a proteins to specific RNA targets. It consists of two basic regions: a repeat region that binds to the Cas13a protein and a spacer region that contains sequences that are complementary to the target RNA (Yang et al. 2024a, 2021, 2023a). The differences in the spacer region enable crRNAs to target different RNAs, achieving specific recognition of the complex. The performance of crRNA1 and crRNA2 was tested separately under optimised conditions. When each crRNA was tested with the Nucleic Acid Positive Reference Materials of IBV, the value of fluorescence (Figure 2) showed that both crRNA1 and crRNA2 could distinguish between positive and negative samples, with crRNA2 exhibiting a significantly higher endpoint value of fluorescence, indicating more sensitive detection of the target. This increased sensitivity may be because crRNA2 binds to the target RNA at a higher rate than crRNA1, further enhancing the stability of the interaction. Moreover, by engineering crRNA (e.g., extending the 5′ end or adding specific chemical modifications), the collateral cleavage activity of Cas13a can be further enhanced, thereby improving the sensitivity and specificity of nucleic acid detection (Yang et al. 2024b).

FIGURE 2.

FIGURE 2

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Screening results for crRNA1 and crRNA2 (where fluorescence is in a.u. and time is in min).

3.2. Fluorescence Reaction Results and Reaction System Optimisation

The preliminary experimental results indicate that the detection method established in this study can differentiate between positive and negative samples. Based on these findings, the detection reaction system was optimised in a step‐by‐step manner. The results are presented below (Figures 3 and 4).

FIGURE 3.

FIGURE 3

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Value of fluorescence at different reaction temperatures.

FIGURE 4.

FIGURE 4

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Value of fluorescence in response to different fluorescent probe concentrations.

Figure 3 illustrates the endpoint value of fluorescence at various temperatures. The value of fluorescence is the lowest at 35°C. As the temperature rises to 36°C and 37°C, there is a significant increase in the value of fluorescence, which reaches its peak at 37°C. At temperatures between 38°C and 40°C, the value of fluorescence slightly decreases but remains elevated. Therefore, the optimal reaction temperature for the highest value of fluorescence is determined to be 37°C.

Figure 4 demonstrates the effect of different concentrations of fluorescent probes on the endpoint value of fluorescence, with concentrations ranging from 5 to 20 μmol·mL−1. At a concentration of 5 μmol·mL−1, the value of fluorescence is relatively low; however, when the concentration is increased to 10 μmol·mL−1, a significant rise in the value of fluorescence is observed, reaching its maximum. Subsequently, at concentrations of 15 and 20 μmol·mL−1, the value of fluorescence begins to decline. Thus, the best performance is noted at a fluorescent probe concentration of 10 μmol·mL−1.

3.3. Detection Limit

Using the gradient copy number method to analyse the DL, we found that this method can distinguish between positive and negative samples at a minimum of 500 copies·μL−1 when using the Genchek fluorimeter (Table 3).

TABLE 3.

Comparison of the low limit of detection of CRISPR and qPCR.

Concentration of samples (copies·μL−1) The CRISPRET and qPCR methods' positive detection results
CRISPRET qPCR
5 × 106 5/5 5/5
5 × 105 5/5 5/5
5 × 104 5/5 5/5
5 × 103 5/5 5/5
5 × 102 5/5 5/5
5 × 101 0/5 0/5
5 × 100 0/5 0/5
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Note: This is a comparison of the DL of CRISPRET and qPCR using the Nucleic Acid Positive Reference Materials of FluB as the detection object. The DL of CRISPRET is 500 copies·μL−1, and the DL of qPCR is also 500 copies·μL−1.

3.4. The Sensitivity, Specificity, and Concordance Rate of Detection Methods

The dual detection results of qPCR and this method were organised into a 2 × 2 contingency table (Table 4). qPCR identified 127 throat swab samples as positive, with the remaining 130 throat swab samples as negative. The CRISPRET, based on CRISPR‐Cas13a, identified 130 throat swab samples as positive and 127 throat swab samples as negative. The results obtained were a PPV of 97.69%, a sensitivity of 100%; an NPV of 100%, a specificity of 97.69%; and a concordance rate of 98.83%. At the same time, we also used this system for cross‐validation while this system's cross‐reaction was tested with more types of respiratory pathogens, such as IAV, SARS‐CoV‐2, and adenovirus et al. The results indicate that this method performs well in identifying these pathogens.

TABLE 4.

Evaluation of CRISPRET detection performance using qPCR as a gold standard.

CRISPRET qPCR
Positive Negative
Positive 127 3
Negative 0 127
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Note: mNGS verified and confirmed as negative the three samples that were positive for CRISPRET but negative for qPCR. The positive predictive value of CRISPRET was 97.69%, and the sensitivity was 100%. The negative predictive value was 100%, and the specificity was 97.69%. The concordance rate was 98.83% between CRISPRET and qPCR. The sensitivity of qPCR was 98%, and the specificity was 96%.

4. Discussion

Compared to other antiviral technologies, such as RNA interference, the CRISPR‐Cas13 system has a lower off‐target effect and higher efficiency (Yang et al. 2023b; Abudayyeh et al. 2017). In this study, we established a method for detecting IBV based on the CRISPR‐Cas13a system, termed CRISPRET. This method enables rapid single‐tube sample analysis, with detection results obtained through a constant temperature reaction on a low‐cost device within 30 min, and it has a DL for IBV of 500 copies·μL−1, which allows for accurate target RNA detection. It utilises a sensitive fluorescent reporting system, significantly enhancing detection efficiency while maintaining a DL. The process is simple, fast, stable, and cost‐effective. We conducted dual detection of respiratory throat swab samples collected in the early stages using qPCR; this method demonstrated a concordance rate of 98.83%, thereby validating its feasibility and reliability.

CRISPRET is suitable for both professional laboratories and on‐site testing, eliminating the need for nucleic acid extraction. Only a sample RNA release preservative is required for processing. The reaction system can be prepared in advance and transported at low temperatures to the testing site. On‐site detection can be performed by adding 5 μL of sample and buffer to a single reaction tube and incubating. To sum up, the method has good specificity and repeatability, with accuracy comparable to qPCR. The rapid detection method for IBV developed in this study requires a small detection device and cannot be directly observed with the naked eye to obtain test results, which limits its application in scenarios such as home self‐testing. However, the principle used is similar to that of the SHERLOCK test strip (Gootenberg et al. 2017). Both are based on the CRISPR‐Cas system's ability to recognise specific nucleic acid sequences. This innovative approach aims to develop a cost‐effective, fast, and accessible diagnostic tool for the public. It combines RAA technology to enable rapid amplification of target RNA in IBV samples at low temperatures. Additionally, it incorporates the CRISPR‐Cas13a system for specific detection. Cas13a generates a visible signal on paper strips by cleaving reporter molecules. Thus, by integrating these technologies, the study seeks to further develop lateral flow test strip (LFTS) for IBV detection and enhance assay efficiency, allowing users to perform just one incubation step after adding the sample to achieve both amplification and detection simultaneously.

5. Conclusions and Prospects

The RAA & CRISPR‐Cas13a detection method is a highly sensitive and rapid approach for detecting IBV, with the potential for portability and intelligence (Wang et al. 2024). During the COVID‐19 pandemic, Parinaz Fozouni and colleagues developed a CRISPR‐Cas13a technology that integrates with smartphone cameras, enabling quick and accurate detection of SARS‐CoV‐2 from nasal swabs without amplification, facilitating point‐of‐care testing (Fozouni et al. 2021). Additionally, studies have looked into wearable devices using the Extreme Gradient Boosting (XGBoost) algorithm to classify flu patients. While the accuracy is currently low, there is promising potential for future development (Farooq et al. 2024). Therefore, by combining CRISPR with artificial intelligence and machine learning, we can create a data analysis platform for IBV detection, allowing for automatic analysis and interpretation of results. This platform can quickly identify anomalies during flu outbreaks, issue early warnings, and help prevent the spread of FluB. We can also develop similar rapid detection methods for Influenza A, enabling prompt deployment during peak flu seasons.

In summary, CRISPR‐T, based on RAA and CRISPR‐Cas13a, has significant development potential. Integrating artificial intelligence and machine learning will enhance the efficiency and accuracy of our detection platform, enabling real‐time detection, automated analysis, and early warnings, which are crucial for preventing influenza transmission and protecting public health.

Author Contributions

Xinling Zhang: writing – original draft, writing – review and editing, validation, investigation, data curation. Shiyu Chen: writing – original draft, writing – review and editing, validation, data curation. Juezhuo Li: writing – original draft, writing – review and editing, validation. Dong‐ang Liu: writing – review and editing, writing – original draft, formal analysis. Jianxiu Lai: writing – review and editing, writing – original draft, formal analysis. Xiangquan Song: writing – review and editing, writing – original draft, formal analysis. Ruiyao Hu: investigation, validation, writing – review and editing, data curation. Yuting Qiu: investigation, validation. Keyi Chen: investigation, validation. Yue Xu: formal analysis, investigation. Xiaoping Li: conceptualization, methodology, resources, writing – review and editing, writing – original draft, funding acquisition, project administration.

Ethics Statement

This study has been approved by the medical ethics committee of the Community Health Service Center of Sandun Town, Xihu District, Hangzhou (Number: 20241028001).

Conflicts of Interest

The authors declare no conflicts of interest.

Acknowledgements

We would like to express our gratitude to the Community Health Service Center of Sandun Town, Xihu District, Hangzhou, for providing throat swab samples and to the Zhejiang Shuren University Basic Scientific Research Special Funds for their support. This study was financially supported by Zhejiang Shuren University Basic Scientific Research Special Funds (2024XZ011).

Funding: This work was supported by Zhejiang Shuren University Basic Scientific Research Special Funds, 2024XZ011.

Xinling Zhang, Shiyu Chen, Juezhuo Li, Dong‐ang Liu and Jianxiu Lai—co‐first authors.

Data Availability Statement

The data that supports the findings of this study are available in the Supporting Information of this article.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that supports the findings of this study are available in the Supporting Information of this article.

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