Skip to main content
NCBI home page
Virology Journal logoLink to Virology Journal
. 2025 Jul 8;22:227. doi: 10.1186/s12985-025-02862-z

Molecular epidemiology, coinfection, and diversity of enteroviruses detected in respiratory samples collected from patients with influenza-like illness in Hangzhou, China, in 2023

Xiaofeng Qiu 1,2, Feifei Cao 1,2, Shi Cheng 1,2, Jun Li 1,2,✉
PMCID: PMC12239461  PMID: 40629413

Abstract

The coronavirus pandemic in China ended in 2022, and stringent control measures were lifted in 2023. This study investigated the pathogen and endemic characteristics of enteroviruses (EVs) in patients with influenza-like illness (ILI) in Hangzhou, China, in 2023, providing a foundation for the prevention and control of EV infections. Throughout 2023, 3,480 throat swab samples were collected from hospitals across Hangzhou. Among these, 130 were positive for EVs, with a positivity rate of 3.74%. Successful sequencing and typing were achieved for 91 cases (70.00%, 91/130), which included four enterovirus A (EV-A), three enterovirus B (EV-B), and one enterovirus D (EV-D) species. EV-A was predominant in 94.51% (86/91) of the samples, followed by EV-B (4.40%, 4/91) and EV-D (1.10%, 1/91). Notably, coxsackievirus A6 was the dominant genotype detected, accounting for 60.44% (55/91) of the samples. Coinfection with 12 distinct non-EV respiratory pathogens was also observed in a significant proportion (75.82%, 69/91) of the samples. Summer and autumn represented peak periods for EV circulation, and children < 8 years of age constituted the primary demographic group affected. There were no sex-based differences in the positivity rate of EV detection (χ²=0.258, P = 0.655). Phylogenetic analyses based on partial VP1 sequences revealed that each representative strain clustered with its corresponding reference strain. Isolated CV-A4 strains were classified within subgenotype C2, CV-A6 strains within subgenotype D3, and CV-A10 strains within subgenotype C1. In conclusion, EV infections among ILI cases in Hangzhou during 2023 peaked in summer and autumn (July and October), with CV-A6 emerging as the predominant type. Children aged 0–7 years constituted the primary risk group for EV infection, with no significant sex-based differences observed. Incorporating EV screening into influenza sentinel surveillance would enhance understanding of endemic trends and pathogen characteristics in ILI patients, thereby informing evidence-based prevention policies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12985-025-02862-z.

Keywords: Enterovirus, Influenza-like illness, Genotype, Coinfection, Endemic characteristics

Highlights

1. Overall, 130 EV strains were detected in patients with influenza-like illness, and 91 strains were identified as having determined genotypes.

2. CV-A6 was the most prevalent type in 2023, followed by CV-A4.

3. EV endemics occurred mainly in the summer and autumn of 2023.

4. Children aged 0–7 years constitute the key population for the prevention and control of EV infection.

5. This study revealed 12 distinct respiratory pathogen types that exhibited coinfection with EVs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12985-025-02862-z.

Introduction

The current enterovirus (EV) classification includes 15 species, EVs A‒L and human rhinoviruses (A‒C), seven of which (EVs A‒D and rhinoviruses A‒C) can cause human infections (https://ictv.global/msl). EVs are widespread in humans and the natural environment and can cause hand, foot, and mouth disease [1–3]; respiratory tract infection [4]; viral encephalitis [5–7]; acute flaccid paralysis [8]; viral myocarditis [9]; fulminant hepatitis [10]; and other diseases [10]– [11].

The predominant genotypes associated with EV-induced influenza-like illness (ILI) have been reported in recent years. The major genotypes of EVs that cause ILI are coxsackievirus A6 (CV-A6), CV-A2, CV-A4, CV-A5, CV-A10, EV-D68, and CV-B5 [12–16]. The predominant genotypes of EVs vary across different areas, years and populations. EV endemicity in China typically peaks during summer and autumn, with highest activity observed in June and July [1, 17–20]. Sun et al. (2024) reported a 3.4% EV positivity rate (1,162/34,152) in children in Hangzhou between January 2019 and May 2023 [1], with the highest rates occurring among 3–7-year-olds [1]. During peak COVID-19 restrictions in 2021, we detected EVs in 10.35% (286/2,762) of ILI cases in Hangzhou, primarily affecting children under 8 years [20].

The coronavirus disease 2019 (COVID-19) pandemic in China ended on December 5, 2022, and 2023 was the first year in which strict control of the outbreak was lifted. This study focused on the pathogenic spectrum and endemic characteristics of EVs in ILI patients after the COVID-19 pandemic in Hangzhou, China, providing a scientific basis for the prevention and treatment of EV infections. To ensure the scientific rigor and representativeness of the sample collection, two sentinel hospitals were selected: a tertiary-grade A class general hospital and a tertiary-grade A class children’s hospital in Hangzhou, China.

This study aimed to: (i) investigate the EV prevalence and genotype distribution in Hangzhou’s sentinel ILI surveillance samples from 2023; (ii) assess EV co-infections with other respiratory pathogens; and (iii) analyze the phylogenetic characteristics of EVs.

Methods

Study population

In accordance with the national influenza surveillance program (2017), samples were taken from patients with a body temperature greater than 38 °C and cough or sore throat who had not received antiviral treatment within 3 days of onset. Samples were obtained from two influenza sentinel surveillance hospitals in Hangzhou: 1,457 (41.87%) from outpatient departments of a tertiary Grade-A general hospital and 2,023 from a children’s hospital (1,317 [37.84%] outpatients and 706 [20.29%] severe acute respiratory infection [SARI] inpatients). Using random sampling, samples from ≥ 20 ILI outpatients were collected weekly from each hospital, and samples from ≥ 10 SARI inpatients were collected weekly from the children’s hospital. The samples were stored at 2–8 °C within 48 h, transported to the laboratory for immediate analysis, and stored at − 70 °C for long-term storage. Throat swab samples were collected from 3,480 influenza-like patients from sentinel hospitals between January 1st and December 31st, 2023.

Viral RNA extraction and detection of EVs and other respiratory viruses

Total viral RNA was extracted from the clinical samples using a Tianlong™ DNA/RNA Extraction Kit and a GeneRotex 96 nucleic acid extractor (Xi’an Tianlong Science and Technology Co., Ltd., Xi’an, China) according to the manufacturer’s protocol, and the viral DNA/RNA extracts were eluted in 80 µL of elution buffer. The samples were immediately tested for EVs and other respiratory viruses via a multiplex real-time PCR kit for the detection of 10 respiratory pathogens (Beijing Applied Biological Technologies Co., Ltd., Beijing, China), which included influenza A virus, influenza B virus, human adenovirus (HAdV), respiratory syncytial virus (RSV), parainfluenza virus (PIV), human metapneumovirus (HMPV), human rhinovirus (HRV), coronavirus (COVs, excluding COVID-19), human bocavirus (HBoV), and EV [21–26]. Streptococcus pneumoniae (SP), Mycoplasma pneumoniae (MP), and Chlamydophila pneumoniae (CP) triplet real-time fluorescent PCR detection reagents (Beijing Applied Biological Technologies Co., Ltd., Beijing, China) were used to detect the nucleic acids of these three pneumonia-causing pathogens. Moreover, a COVID-19 nucleic acid detection kit (triple fluorescent PCR) (Jiangsu Bioperfectus Technologies Co., Ltd., Jiangsu, China) was used immediately to detect the presence of COVID-19 in the samples. The Influenza A H1N1 (2009)/Seasonal H3 Subtype/B Type BV Line/BY Line Flu Virus Nucleic Acid Detection Kit (fluorescent PCR method) (Jiangsu Bioperfectus Technologies Co., Ltd., Jiangsu, China) was used immediately to detect the influenza virus. The coxsackievirus A16 (CV-A16) & enterovirus 71 (EV71) Real-Time PCR Kit and the CV-A6 and CV-A10 Real-Time PCR Kit (Jiangsu Bioperfectus Technologies Co., Ltd., Jiangsu, China) were designed for the in vitro qualitative detection of RNA from CV-A16, EV71, CV-A6, and CV-A10 obtained from human throat swabs. The DNA/RNA from all the samples was amplified via real-time PCR and examined on an ABI Quant Studio 5 real-time PCR machine (Applied Biosystems, Life Technologies, Carlsbad, CA). The residual nucleic acid extracts were stored at − 80 °C until typing.

Genotyping of EVs

The primers used for VP1 genotyping of EVs were synthesized by Sangon Biotech Co., Ltd. (Shanghai, China), as described previously [27–28]. EV-positive RNA samples were used to synthesize cDNA via a reverse transcription kit (DRR6210A, Takara Bio, Shiga, Japan). A Takara ExTaq HS PCR kit (DRR006A, Takara Bio, Shiga, Japan) was used to amplify the EV VP1 gene, and the reaction conditions were set according to the kit instructions and references [27–28]. The PCR products were sequenced by Sangon Biotech (Shanghai). The sequence identity of the EV strains was determined via the BLAST search tool (http://www.ncbi.nlm.nih.gov/blast). Phylogenetic analysis was carried out via neighbor joining with 1000 bootstrapping replicates available in Molecular Evolutionary Genetics Analysis Version 11.0 (MEGA 11). The reference sequences of the EV genotypes were downloaded from the NCBI GenBank website. Sequences from GenBank were identified on the basis of accession number, country, and year of collection. The online visualization tool iTOL was used to visualize the phylogenetic tree of VP1 (https://itol.embl.de/).

Statistical analyses

The data were analyzed via Excel 2019. Statistical analyses were performed using SPSS software, version 21 (IBM, Armonk, New York, USA), and a chi-square test was used to assess differences between categorical variables, with P < 0.05 considered indicative of statistical significance. Violin plots and alluvial diagrams were plotted by using https://www.bioinformatics.com.cn (last accessed on 10 Oct 2024), an online platform for data analysis and visualization [29].

Results

EV detection

Among the 3,480 ILI cases, 130 samples were EV-positive upon initial screening, indicating a prevalence of 3.74% (130/3,480). 70% (91/130) of the EV-positive strains could be genotyped, including 4 types of EV-A strains (CV-A4, A6, A10, A16), 3 types of EV-B strains (CV-B5, E9, E18), and 1 type of EV-D strain (EV-D68) (Table 1; Fig. 1). 30% (39/130) of the EV-positive samples could not be genotyped. EV-A was the major species detected in 94.51% (86/91) of the samples, followed by EV-B in 4.40% (4/91) and EV-D in 1.10% (1/91) of the samples. We found that CV-A6 (n = 55) was the predominant EV genotype in ILI patients, followed by CV-A4 (n = 26). The other EV genotypes were CV-A10 (n = 4), E9 (n = 2), CV-A16 (n = 1), CV-B5 (n = 1), E18 (n = 1), and EV-D68 (n = 1).

Table 1.

Distribution of enterovirus genotypes

Group Genotypes Number of cases Percentage(%)
EV-A
CV-A4 26 20.00
CV-A6 55 42.31
CV-A10 4 3.08
CV-A16 1 0.77
EV-B
CV-B5 1 0.77
E9 2 1.54
E18 1 0.77
EV-D
EV-D68 1 0.77
Untyped 39 30.00
Total 130 100.00
Open in a new tab

Fig. 1.

Fig. 1

Open in a new tab

Flowchart illustrating the enrolled ILI cases during the study period in 2023. Notes: COVID-19: Coronavirus 2019, HAdVs: human adenoviruses, HBoV: human bocavirus, COVs: Coronavirus, H3N2: Influenza A (H3N2) viruses, HMPV: Human metapneumovirus, HRV: Human rhinovirus, MP: Mycoplasma pneumonia, CP: Chlamydia pneumonia, SP: Streptococcus pneumonia, PIV: Parainfluenza virus, RSV: Respiratory syncytial virus

Patient characteristics

From 1 January to 31 December 2023, 3,480 ILI patients were enrolled. Using random sampling, samples from ≥ 20 ILI outpatients were collected weekly from each sentinel hospital, and samples from ≥ 10 inpatients were collected weekly from the children’s hospital. The outpatient group comprised 2,774 cases (79.71%), while inpatients accounted for 706 (20.29%). The median age at diagnosis was 10 years (range: 1 month–93 years), with 70.0% of suspected cases occurring in children aged 0–7 years. Males represented 47.8% of ILI patients (male-to-female ratio: 0.92). No sex-based difference in EV positivity rates was observed (χ²=0.258, P = 0.655; Figs. 2B and 3A). Due to the random sampling methodology, the age distribution may not reflect population epidemiology.

Fig. 2.

Fig. 2

Open in a new tab

Temporal and Age distribution of enterovirus in Hangzhou, China, 2023. (A) Temporal distribution. (B) Age distribution

Fig. 3.

Fig. 3

Open in a new tab

(A) Violin plot showing the age distribution of enterovirus positive patients. (B) Alluvial diagram showing correlations between enterovirus serotype sidentified and sampling months and age groups in Hangzhou, China, 2023

Temporal distribution

A total of 266, 287, 303, 276, 313, 278, 306, 325, 260, 299, 315 and 252 samples were collected each month from January to December, respectively. The monthly positivity rates for EVs from January to December were as follows: 0.75%, 0.00%, 0.00%, 0.72%, 0.96%, 6.12%, 10.13%, 5.85%, 4.62%, 7.36%, 6.35%, and 0.79%, respectively. The temporal distribution of EVs among patients with ILI indicated distinct prevalence patterns across different months (Fig. 2A). EVs were detected throughout the year except in February and March. The endemic status of EVs exhibited seasonal variation, with peaks occurring during the summer and autumn months; the highest infection rate was observed in July at 10.13% (31/306), followed by October, with the second-highest rate of 7.36% (22/299).

The numbers of cases reported in spring, summer, autumn, and winter were 892, 909, 874, and 805, respectively; among these cases, the numbers of EV-positive instances were 5, 67, 54, and 4, respectively, resulting in positivity rates of 0.56%, 7.37%, 6.18%, and 0.50%, respectively. The chi-square test revealed that the overall differences among the four seasons were statistically significant (χ²=96.393, P < 0.001); however, the difference in positivity rates between summer and autumn was not statistically significant (χ²=1.001, P = 0.347). Spring and winter presented the lowest incidence rates for EVs, with positivity rates falling below 1%.

Age distribution

The six age categories (0–3, 4–7, 8–17, 18–40, 41–65, and ≥ 66 years) were defined based on distinct biological, immunological, and social-behavioral transitions that influence EV infection risk and disease severity. The groups are consistent with global EV surveillance frameworks (e.g., WHO HFMD guidelines). The age distribution of the enrolled patients was as follows: 0–3 years (15.55%, n = 541), 4–7 years (24.66%, n = 858), 8–17 years (22.18%, n = 772), 18–40 years (23.05%, n = 802), 41–65 years (10.89%, n = 379), and ≥ 66 years (3.68%, n = 128); the corresponding EV positivity rates were 7.21%, 6.06%, 2.85%, 2.00%, 0.26%, and 0.00%, respectively (Figs. 2B and 3). Significant overall differences in EV positivity were observed among age groups (χ²=57.158, P < 0.001). Pairwise comparisons revealed (1) significantly higher rates in the 0–3 year vs. 8–17 year (χ²=13.644, P < 0.001), 18–40 year (χ²=22.361, P < 0.001), 41–65 year (χ²=25.848, P < 0.001), and ≥ 66 year (χ²=9.799, P < 0.001) age groups; (2) significantly higher rates in the 4–7 year vs. 8–17 year (χ²=9.667, P = 0.002), 18–40 year (χ²=17.441, P < 0.001), 41–65 year (χ²=21.540, P < 0.001), and ≥ 66 year (χ²=8.189, P = 0.001) age groups; and (3) significantly higher rates in the 8–17 year vs. 41–65 year (χ²=12.230, P = 0.002) and ≥ 66 year (χ²=8.680, P = 0.003) age groups. Conversely, no significant differences were observed between the 0–3 vs. 4–7 year (χ²=0.719, P = 0.436) or between the 8–17 vs. 18–40 year (χ²=1.220, P = 0.325) age groups. Children aged 0–7 years exhibited significantly higher EV positivity rates than older cohorts.

Coinfection

We performed detailed coinfection analysis on EV-positive samples (n = 130). that the results demonstrated that EV coinfections exclusively involved non-EV respiratory pathogens. Analysis of the infection complexity distribution revealed single (24.6%, 32/130), dual (36.2%, 47/130), triple (30.0%, 39/130), quadruple (8.5%, 11/130), and quintuple (0.8%, 1/130) EV infections (Fig. 4A-B).

Fig. 4.

Fig. 4

Open in a new tab

The Multi-positive samples by respiratory pathogens among the enterovirus positive samples in Hangzhou, Zhejiang Province, China, 2023. (A) EVs (B) Overall of EVs. (C) The other respiratory pathogens. (D) Overall of the other respiratory pathogens. (E) The distribution of co-infected with other respiratory pathogens among the enterovirus positive samples. Notes: COVID-19: Coronavirus 2019, HAdVs: human adenoviruses, HBoV: human bocavirus, COVs: Coronavirus, H3N2: Influenza A (H3N2) viruses, HMPV: Human metapneumovirus, HRV: Human rhinovirus, MP: Mycoplasma pneumonia, CP: Chlamydia pneumonia, SP: Streptococcus pneumonia, PIV: Parainfluenza virus, RSV: Respiratory syncytial virus

The 162 co-detected respiratory pathogens included HRV (n = 40), SP (n = 33), MP (n = 18), HMPV (n = 16), H3N2 (n = 11), PIV (n = 10), HBoV (n = 9), SARS-CoV-2 (n = 7), RSV (n = 6), CoVs (n = 6), HAdVs (n = 4), and CP (n = 2) (Figs. 1 and 4C-D). The coinfection levels among these pathogens were as follows: dual (28.4%, 46/162), triple (48.8%, 79/162), quadruple (20.4%, 35/162), and quintuple (2.5%, 4/162).

Among the genotyped EV samples (n = 91), 24.2% (22/91) showed single EV infections (CV-A6:19, CV-A4:2, E18:1). The majority (75.8%, 69/91) exhibited coinfections with other respiratory pathogens (Fig. 4E). Collectively, EV infections predominantly presented as dual coinfections, whereas other pathogens most frequently occurred in triple coinfections.

Among the total cohort, 36.26% (33/91) of patients experienced simultaneous coinfection with two pathogens, 30.77% (28/91) had three concurrent infections, and 8.79% (8/91) were simultaneously infected by four different pathogens. The respiratory pathogens associated with coinfections alongside EVs included COVID-19 at a rate of 2.90% (2/69), HAdVs at 4.35% (3/69), HBoV at 7.25% (5/69), COVs at 5.80% (4/69), influenza A virus subtype H3N2 at 1.45% (1/69), HMPV at 20.29% (14/69), HRV at 42.03% (29/69), accounting for the highest proportion, MP at 18.84% (13/69), CP at 2.90% (2/69), SP at 39.13% (27/69), PIV at 10.14% (7/69), and RSV at 5.80% (4/69). HRV (42.0%) and SP (39.1%) were the predominant coinfecting pathogens, followed by HMPV (20.3%) and MP (18.8%).

Phylogenetic analysis

Among the EV-positive samples, representative samples were processed for typing via the VP1 reverse transcription-seminested PCR (RT‒snPCR) assay to identify EVs in a diverse array of clinical specimens [27]– [28]. The sequence identity of the EV strains was determined via the BLAST search tool. A VP1 nucleotide sequence similarity > 75% or amino acid sequence similarity > 85% is defined as the same virus serotype [30]. The VP1 nucleotide sequence similarity between representative strains of CV-A4 (B585, B617, B709, B938, B949, B1076, B1089, B1107, B117, B1304, S301/Hangzhou/CHN/2023) and the prototype strain (accession number AY421762) ranged from 83.8 to 85.0%. Among the CV-A4 strains analyzed in this study, the sequence similarity varied from 96.3 to 100%. For CV-A6, the nucleotide sequence similarity between representative strains (B986, B998, B1147, and B1160/Hangzhou/CHN/2023) and the prototype strain (accession number AY421764) was between 83.8% and 86.1%, whereas the sequence similarity among these representative strains was 93.4–100%. The nucleotide sequence similarity between representative strains of CV-A10 (A813, B1193/Hangzhou/CHN/2023) and the prototype strain (accession number AY421767) was 76.5–76.8%, with an intragroup similarity of 98.7%. The nucleotide sequence similarity between the representative CV-A16 strain (A892/Hangzhou/CHN/2023) and the prototype strain (accession number U05876) was 76.6%. For CV-B5, the similarity between the representative strain (S328/Hangzhou/CHN/2023) and the prototype strain (accession number AF114383) was 80.2%. The nucleotide sequence similarity between representative E9 strains (B741 and B804/Hangzhou/CHN/2023) and the prototype strain (accession number X84981) was 77.5% and 77.9%, respectively. The nucleotide sequence similarity between the E18 strain (A1024/Hangzhou/CHN/2023) and the prototype strain (accession number AF317694) was 84.5%. Finally, the nucleotide sequence similarity between the EV-D68 representative strain (B968/Hangzhou/CHN/2023) and the prototype strain (accession number AY355268) was 77.0%. Phylogenetic analysis was carried out via neighbor joining with 1000 bootstrapping replicates in MEGA 11. Figure 5A shows the phylogenetic relationship between EV VP1 nucleotide sequences from 23 representative strains of EV genotypes and reference prototype strains downloaded from GenBank. The sequences of the 23 representative strains are publicly available in GenBank under the accession numbers PP738598–PP738608 and PQ124013–PQ124024 ( Supplementary Table S1).

Fig. 5.

Fig. 5

Open in a new tab

The Neighbor-Joining Phylogenetic tree based on VP1 of enterovirus representative strains causing Influenza-like Illness (ILI) in Hangzhou city, China. (A) All the enterovirus VP1 sequences in this study used was 313 bp. (B) CV-A4 representative strains. (C) CV-A6 representative strains. (D) CV-A10 representative strains. Note: Outpatient Samples of adults number start with A, outpatient samples of Minors number start with B; The sample of inpatient start with S. ▲: Prototype strains form GenBank. *: Enterovirus strains isolated in this study

Given the relatively high positive detection rates of CV-A4, CV-A6, and CV-A10, we conducted separate gene phylogenetic tree analyses for each (Fig. 5B-D). The prototype strain of CV-A2 (accession number AY421760) was selected as the outgroup. The phylogenetic analysis of the VP1 region clearly indicated that all the CV-A4 strains are grouped into four distinct genotypes, designated A, B, C, and D. Notably, the C genotype can be further subdivided into five subgenotypes: C1 to C5 [27]. In this study, eleven isolated CV-A4 strains were classified within subgenotype C2 (Fig. 5B), demonstrating a close relationship with circulating CV-A4 strains in China. Subgenotype C2 was first identified in 2006 and has shown an increasing prevalence each subsequent year [17].

Genotyping revealed that CV-A6 is the primary pathogen involved. We constructed a phylogenetic tree using our laboratory’s isolates of CV-A6 alongside globally representative strains available in public databases. The circulating strains of CV-A6 in China can be categorized into four genotypes labeled A through D; furthermore, genotype D can be subdivided into three subgenotypes: D1 to D3 [17]. Our findings indicate that these four isolated strains of CV-A6 belong to subgenotype D3 (Fig. 5C).

On the basis of analyses conducted on the VP1 region, we identified seven genotypes for CV-A10, specifically designated genotypes A through G. Notably, genotype C was further subdivided into two subgenotypes: C1 and C2 [32]. In this study, the isolated strains of CV-A10 were determined to belong to subgenotype C1 (Fig. 5D).

Discussion

EVs replicate mainly in the oropharynx and gastrointestinal tract and are transmitted through the fecal-hand-mouth route and/or respiratory tract [33]. EV infection can spread to various organs and can lead to substantial complications, including death. EVs are among the main causative agents of aseptic meningitis/encephalitis and can cause poliomyelitis in humans. Many countries regard EVs as important pathogens that cause influenza [18, 34]. Pellegrinelli L et al. studied the epidemiology of IVs, human parainfluenza virus, and EVs in ILI patients under 5 years of age during seven consecutive winters (2010–2017) in northern Italy. In total, 16 samples were sequenced, and 9 genotypes of EV-A (6) and EV-B (10) were identified: CV-A2, CV-A4, CV-A5, CV-A6, CV-A9, and CV-B2 and CV-B5, E11 and E13 [20]. Ming-Zhu Xie et al. studied the molecular epidemiology of children with herpangina from 2019 to 2020 in Tongzhou district, Beijing, China [18]. Four genotypes, including CV-A6, CV-A4, CV-A10 and CV-A16, were identified in 2019, and only three genotypes, including CV-A6, CV-A10 and CV-A16, were identified in 2020 [18].

Sun et al. (2024) reported a 3.4% EV positivity rate (1,162/34,152) in children from Hangzhou between January 2019 and May 2023 [1], noting the decline in certain serotypes (particularly EV71 and CA16) alongside an increase in unidentified serotypes [1]. Pre-pandemic surveillance in 2019 detected EV positivity in 7.08% (75/1,060) of pediatric ILI cases from Hangzhou [19]with genotypes belonging to 9 types: CV-A2, A4, A5, A6, A9, A10, E7, E11, E18, and EV-D68 (CV-A2 and A4 predominant). During the 2021 pandemic period in Hangzhou, EV positivity rose to 10.35% (286/2,762) [20], peaking in summer/autumn with highest rates in June-July and a secondary September peak [20]. Males showed significantly higher positivity than females (χ²=18.913, P < 0.001) [20], and genotyping succeeded in 156 cases (54.55%), revealing 5 EV-A (CV-A2,A4,A5,A6,A10) and 6 EV-B (CV-B1,B3,E9,E18,E21,E30; CV-A4 predominant) types [20].

In our 2023 sentinel surveillance of 3,480 ILI cases, EV prevalence was 3.74% (130/3,480). No significant difference existed in comparison with Sun et al.‘s 2019–2023 rate (3.4%, χ²=0.985, P = 0.330), though the rates were significantly lower than those in both 2019 (7.08%, χ²=18.886, P < 0.001) and 2021 (10.35%, χ²=94.323, P < 0.001).

Ninety-one of EV-positive cases were successfully typed, covering 7 genotypes. CV-A6 was the dominant genotype, with a positivity rate of 1.58% (55/3,480); CV-A4 had a positivity rate of 0.75% (26/3,480); and the other EV genotypes were CV-A10, E9, CV-A16, CV-B5, E18, and EV-D68. Among the 130 EV nucleic acid-positive cases, 39 were not successfully typed, possibly because the sensitivity of real-time fluorescence PCR is greater than that of the VP1 RT-snPCR assay, making it difficult to identify samples with low nucleic acid concentrations via the VP1 RT-snPCR assay.

EVs, as a cause of ILI, showed widespread occurrence in 2023, with some suggested outbreaks (e.g., CV-A6 in June, July, August and October) (Fig. 2B). CV-A4 and CV-A6 had the longest durations of endemic status, from May to December. Infections in 0–3-year-old children included the most diverse EV genotypes, with six different genotypes detected: CV-A4, CV-A6, CV-A10, CV-B5, E9, and EV-D68 (Fig. 2B). The genotypes of EVs detected in 4–7-year-old children were CV-A4, CV-A6 and CV-A10. The genotypes of EVs detected in children aged 8–17 years include CV-A4, CV-A6, CV-A10 and E18. EVs, including CV-A6 and CV-A10, are detected in the population aged 18–40 years.

The clinical diagnosis of CV-A4 infection in Hangzhou residents, in addition to the common symptoms of acute upper respiratory tract infection, acute tonsilitis, and herpangina, includes lower respiratory tract infection symptoms such as bronchitis [35–37]. CV-A6, CV-A10, and CV-A16 often cause hand, foot, and mouth disease in children, and infected individuals can also present with flu-like symptoms, further confirming the diversity of clinical manifestations of EV [18, 37]. CV-B5, E9, and E18 can all cause severe diseases such as viral encephalitis [38]– [39]. EV-D68 often causes acute respiratory diseases in infants and young children, often leading to severe pneumonia [40]. Although the incidence of these EVs is low, vigilance must be maintained. Genetic evolutionary analysis of the EV VP1 sequence revealed that the 23 EV strains in Hangzhou presented different degrees of variation compared with the reference strains, and different evolutionary branches also appeared within the same genotype.

We observed significantly higher EV prevalence among children under 8 years of age (Fig. 2B), with the highest infection rate observed in 0-3-year olds (7.21%) and the second highest in 4-7-year olds (6.06%). Conversely, individuals ≥ 66 years old showed no EV detection (0.00%), demonstrating a significant inverse correlation between infection risk and age (χ²=57.158, P < 0.001).

While random sampling may limit the generalizability of age distribution patterns, our surveillance design mitigated temporal bias through systematic weekly collection of samples from ≥ 40 ILI outpatients from each sentinel hospital and ≥ 10 pediatric inpatients weekly. This consistent sampling framework supports the validity of age-stratified analyses despite methodological constraints.

After the adjustment of endemic prevention and control policies in 2023, Chi J et al. reported that more children developed community-acquired pneumonia with severe clinical symptoms and that more antibiotics and antiviral drugs were used [41]. The number of children infected with more than two pathogens was greater in 2023, especially the number of children coinfected with the virus and MP [40]. In this study, we also identified 12 respiratory pathogens involved in coinfection with EVs, including COVID-19, HAdVs, HBoV, COVs, influenza A (H3N2) viruses, HMPV, HRV, MP, CP, SP, PIV, and RSV. The most prevalent pathogens involved in coinfections with EVs were HRV (42.03%), followed closely by SP (39.13%), HMPV (20.29%), and MP (18.84%). The presence of pathogens other than EVs was not confirmed by gene sequencing and was based only on fluorescence PCR. The results of this study provide evidence for coinfection by multiple pathogens in patients with ILI. The role of EVs in coinfections with multiple pathogens in patients with ILI needs further study. However, CV-A4, CV-A6, and E18 can cause respiratory tract infections independently.

The observed coinfections between EVs and diverse respiratory pathogens (including viruses such as HRV, HMPV, H3N2, and bacteria like Sp, Mp) underscore significant clinical and epidemiological implications. Clinically, these coinfections may exacerbate disease severity, prolong symptom duration, and complicate diagnosis and therapeutic decision-making—particularly when involving bacterial pathogens or synergistic viral pairs. Epidemiologically, their age-specific and seasonal patterns reflect dynamic pathogen interactions within populations, while the inclusion of CoVs highlights the evolving landscape of respiratory pathogen ecology amid the COVID-19 pandemic. Comprehensive surveillance of such coinfections is thus critical for optimizing individual patient management, forecasting severe disease burden, and guiding public health interventions.

Phylogenetic analysis of the VP1 gene was performed using 23 representative strains from eight EV genotypes identified in this study, alongside 16 reference strains from GenBank. All representative strains clustered with their genotype-matched reference sequences (Fig. 4A). Eleven CV-A4 isolates clustered within subgenotype C2 (Fig. 4B), a lineage first identified in 2006 that has exhibited increasing global prevalence [17].

Four CV-A6 strains belonged to subgenotype D3 (Fig. 4C), which has emerged as the dominant circulating genotype worldwide and shows particularly high prevalence throughout Southeast Asia and Europe [42]. Notably, the CV-A6 D3 subgenotype exhibits heightened infectivity and virulence potential, characteristics that may contribute to its association with large-scale outbreaks [43].

Conclusion

This study provides timely insights into the EV epidemiological landscape in the post-COVID-19 era in China. Key findings revealed multiple EV genotypes causing ILI in Hangzhou during 2023, with an overall EV positivity rate of 3.74% (130/3,480). CV-A6 emerged as the dominant genotype (1.58%, 55/3,480), belonging to subgenotype D3. EV infections peaked in summer and autumn (July and October), with children aged 0–7 years constituting the key at-risk population, showing no sex-based differences. Notably, CV-A4, CV-A6, and E18 were detected as sole pathogens in respiratory infections, alongside 12 other respiratory pathogens identified in EV coinfections. Incorporating EV screening into influenza sentinel surveillance would enhance understanding of endemic trends and pathogen characteristics in ILI patients, thereby informing evidence-based prevention policies.

Electronic Supplementary Material

Below is the link to the electronic supplementary material.

Supplementary Material 1 (17.7KB, docx)
12985_2025_2862_MOESM2_ESM.png (1MB, png)

Fig.5 The Neighbor-Joining Phylogenetic tree

Acknowledgements

We thank Mingjie Chen (Shanghai NewCore Biotechnology Co., Ltd.) for providing data analysis and visualization support.

Author contributions

Xiaofeng Qiu: Sample collection & dectection, Formal analysis, Data curation, Writing-original draft, Writing -review & editing. feifei Cao: Sample collection & dectection. Shi Cheng: Sample collection & dectection. Jun Li: Writing - review & editing, Financial support. All authors reviewed the manuscript.

Funding

This work was supported by Zhejiang Province Science and Technology Plan Program for Disease Prevention and Control (2025JK240), the Zhejiang Provincial Key Laboratory Construction Project (2024ZY01026), and the Construction Fund of Key Medical Disciplines of Hangzhou (2025HZGF13).

Data availability

The sequencing data that support the findings of this study are openly available in GenBank, accession number PP738598– PP738608, PQ124013– PQ124024. No other data are publicly available.

Declarations

Ethics approval and consent to participate

This study did not involve human experimentation or human participants. The only human materials used were throat swab samples collected from influenza-like illness (ILI) patients, which for public health purposes according to the national ILI guidelines. Written informed consent for the use of their clinical sample was obtained from the parents of the children. This study was approved by the Ethics Review Committee of the Hangzhou center for Disease Control and Prevention (Approval number 2024-10).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  • 1.Sun J, Guo Y, Li L, Li Y, Zhou H, Li W. Epidemiology of childhood enterovirus infections in hangzhou, china, 2019–2023. Virol J. 2024;21(1):198. 10.1186/s12985-024-02469-w. Published 2024 Aug 26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Naomiya K, Ito T, Saito A, et al. Clinical features and characteristics of hand, foot, and mouth disease caused by recent coxsackievirus A6: five cases in Japan from 2019 to 2022. Infect Dis Rep. 2024;16(4):587–92. 10.3390/idr16040044. Published 2024 Jun 29. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Fan H, Li MY, Shi P, Cao ZX, Xu Q, Ji H. Zhonghua Liu Xing Bing Xue Za Zhi. 2024;45(7):977–82. 10.3760/cma.j.cn112338-20231225-00374 [DOI] [PubMed] [Google Scholar]
  • 4.Puenpa J, Mauleekoonphairoj J, Linsuwanon P, et al. Prevalence and characterization of enterovirus infections among pediatric patients with hand foot mouth disease, herpangina and influenza like illness in thailand, 2012. PLoS ONE. 2014;9(6):e98888. 10.1371/journal.pone.0098888 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Gundamraj V, Hasbun R. Viral meningitis and encephalitis: an update. Curr Opin Infect Dis. 2023;36(3):177–85. 10.1097/QCO.0000000000000922 [DOI] [PubMed] [Google Scholar]
  • 6.Leon KE, Schubert RD, Casas-Alba D, et al. Genomic and serologic characterization of enterovirus A71 brainstem encephalitis. Neurol Neuroimmunol Neuroinflamm. 2020;7(3):e703. 10.1212/NXI.0000000000000703. Published 2020 Mar 5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Posnakoglou L, Tatsi EB, Chatzichristou P, et al. Molecular epidemiology of enterovirus in children with central nervous system infections. Viruses. 2021;13:100. 10.3390/v13010100 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Uprety P, Graf EH. Enterovirus infection and acute flaccid myelitis. Curr Opin Virol. 2020;40:55–60. 10.1016/j.coviro.2020.06.006 [DOI] [PubMed] [Google Scholar]
  • 9.Zhang Y, Zhou X, Chen S, Sun X, Zhou C. Immune mechanisms of group B coxsackievirus induced viral myocarditis. Virulence. 2023;14(1):2180951. 10.1080/21505594.2023.2180951 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Pedrosa C, Lage MJ, Virella D. Congenital echovirus 21 infection causing fulminant hepatitis in a neonate. BMJ Case Rep. 2013. 10.1136/bcr-2012-008394. Published 2013 Apr 9. 2013:bcr2012008394. [DOI] [PMC free article] [PubMed]
  • 11.Garmaroudi FS, Marchant D, Hendry R, et al. Coxsackievirus B3 replication and pathogenesis. Future Microbiol. 2015;10(4):629–53. 10.2217/fmb.15.5 [DOI] [PubMed] [Google Scholar]
  • 12.Hellferscee O, Tempia S, Walaza S, et al. Enterovirus genotypes among patients with severe acute respiratory illness, influenza-like illness, and asymptomatic individuals in South africa, 2012–2014. J Med Virol. 2017;89(10):1759–67. 10.1002/jmv.24869 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Li J, Ni N, Cui Y, et al. An outbreak of a novel Recombinant coxsackievirus A4 in a kindergarten, Shandong province, china, 2021. Emerg Microbes Infect. 2022;11(1):2207–10. 10.1080/22221751.2022.2114855 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Huaman JL, Carrion G, Ampuero JS et al. Non-rhinovirus enteroviruses associated with respiratory infections in Peru (2005–2010). Virol J. 2014;11:169. Published 2014. 10.1186/1743-422X-11-169 [DOI] [PMC free article] [PubMed]
  • 15.Chen L, Shi L, Yang H et al. Identification and Whole-Genome Sequencing of Four Enterovirus D68 Strains in Southern China in Late 2015. Genome Announc. 2016;4(5):e01014-16. Published 2016. 10.1128/genomeA.01014-16 [DOI] [PMC free article] [PubMed]
  • 16.Berginc N, Lunar MM, Šramel N, Poljak M. Molecular epidemiology and characterization ofenteroviruses detected in cerebrospinal fluid and respiratorysamples in slovenia, 2014–2023. J Med Virol. 2024;96:e29827. 10.1002/jmv.29827 [DOI] [PubMed] [Google Scholar]
  • 17.Chen Y, Chen S, Shen Y, et al. Molecular evolutionary dynamics of coxsackievirus A6 causing hand, foot, and mouth disease from 2021 to 2023 in china: genomic epidemiology study. JMIR Public Health Surveill. 2024;10:e59604. 10.2196/59604. Published 2024 Jul 31. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Xie MZ, Chen LY, Yang YN, et al. Molecular epidemiology of herpangina children in Tongzhou district, beijing, china, during 2019–2020. Front Med (Lausanne). 2022;9:822796. 10.3389/fmed.2022.822796. Published 2022 Apr 25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Qiu X, Li J, Yang X, Cheng S, Pan J. Serotype distribution of enteroviruses in child cases with influenza-like illness in Hangzhou City. Chin J Microbiol Immunol. 2021;41(06):427–32. (Chinese). [Google Scholar]
  • 20.Qiu X, Cao F, Cheng S, Pan J, Li J. Epidemiological characteristics of influenza virus and enteroviruses among influenza-like cases in Hangzhou city, china, in 2021. Chin J Virol. 2024;40(3):536–45. (Chinese). [Google Scholar]
  • 21.Auburn H, Zuckerman M, Broughton S, Greenough A, Smith M. Detection of nine respiratory RNA viruses using three multiplex RT-PCR assays incorporating a novel RNA internal control transcript. J Virol Methods. 2011;176:9–13. 10.1016/j.jviromet.2011.05.017 [DOI] [PubMed] [Google Scholar]
  • 22.Bezerra PGM, Britto MCA, Correia JB, et al. Viral and atypical bacterial detection in acute respiratory infection in children under five years. PLoS ONE. 2011;6:e18928. 10.1371/journal.pone.0018928 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Chen Y, Cui D, Zheng S, N1. Simultaneous detection of influenza A, influenza B, and respiratory syncytial viruses and subtyping of influenza A H3N2 virus and H1 (2009) virus by multiplex real-time PCR. J Clin Microbiol. 2011;49:1653–1656. 10.1128/JCM.02184-10 [DOI] [PMC free article] [PubMed]
  • 24.Vos N, Vankeerberghen A, Vaeyens F, Vaerenbergh K, Boel A, Beenhouwer H. Simultaneous detection of human bocavirus and adenovirus by multiplex real-time PCR in a Belgian paediatric population. Eur J Clin Microbiol Infect Dis. 2009;28:1305–10. 10.1007/s10096-009-0780-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Dierssen U, Rehren F, Henke-Gendo C, Harste G, Heim A. Rapid routine detection of enterovirus RNA in cerebrospinal fluid by a one‐step real‐time RT‐PCR assay. J Clin Virol. 2008;42:58–64. 10.1016/j.jcv.2007.11.016 [DOI] [PubMed] [Google Scholar]
  • 26.Klemenc J, Asad Ali S, Johnson M, et al. Real-time reverse transcriptase PCR assay for improved detection of human metap-neumovirus. J Clin Virol. 2012;54:371–5. 10.1016/j.jcv.2012.05.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Nix WA, Oberste MS, Pallansch MA. Sensitive, seminested PCR amplification of VP1 sequences for direct identification of all enterovirus serotypes from original clinical specimens. J Clin Microbiol. 2006;44(8):2698–704. 10.1128/JCM.00542-06 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Oberste MS, Maher K, Kilpatrick DR, Pallansch MA. Molecular evolution of the human enteroviruses: correlation of serotype with VP1 sequence and application to picornavirus classification. J Virol. 1999;73(3):1941–8. 10.1128/JVI.73.3.1941-1948.1999 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Tang D, Chen M, Huang X, Zhang G, Zeng L, Zhang G, Wu S, Wang Y. SRplot: A free online platform for data visualization and graphing. PLoS One. 2023;18(11):e0294236. 10.1371/journal.pone.0294236. PMID: 37943830. [DOI] [PMC free article] [PubMed]
  • 30.Suresh S, Forgie S, Robinson J. Non-polio enterovirus detection with acute flaccid paralysis: A systematic review. J Med Virol. 2018;90(1):3–7. 10.1002/jmv.24933 [DOI] [PubMed] [Google Scholar]
  • 31.Ji T, Guo Y, Lv L, et al. Emerging recombination of the C2 sub-genotype of HFMD-associated CV-A4 is persistently and extensively circulating in China. Sci Rep. 2019;9(1):13668. Published 2019 Sep 20. 10.1038/s41598-019-49859-7 [DOI] [PMC free article] [PubMed]
  • 32.He F, Zhu C, Wu X et al. Genomic surveillance reveals low-level circulation of two subtypes of genogroup C coxsackievirus A10 in Nanchang, Jiangxi Province, China, 2015–2023. Front Microbiol. 2024;15:1459917. Published 2024 Sep 17. 10.3389/fmicb.2024.1459917 [DOI] [PMC free article] [PubMed]
  • 33.van Janse M, Mans J, Mafuyeka RT, Strydom KA, Myburgh M, van Zyl WB. Diversity of enteroviruses in cerebrospinal fluid specimens collected from hospitalised patients in the private and public sector in South Africa. J Med Virol. 2024;96(3):e29514. 10.1002/jmv.29514 [DOI] [PubMed] [Google Scholar]
  • 34.Pellegrinelli L, Bubba L, Galli C, et al. Epidemiology and molecular characterization of influenza viruses, human parechoviruses and enteroviruses in children up to 5 years with influenza-like illness in Northern Italy during seven consecutive winter seasons (2010–2017). J Gen Virol. 2017;98(11):2699–711. 10.1099/jgv.0.000937 [DOI] [PubMed] [Google Scholar]
  • 35.Wang M, Li J, Yao MX, et al. Genome analysis of coxsackievirus A4 isolates from hand, foot, and mouth disease cases in shandong, China. Front Microbiol. 2019;10:1001. 10.3389/fmicb.2019.01001. Published 2019 May 7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Li JS, Dong XG, Qin M, et al. Outbreak of febrile illness caused by coxsackievirus A4 in a nursery school in beijing, China. Virol J. 2015;12:92. 10.1186/s12985-015-0325-1. Published 2015 Jun 18. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Li W, Gao HH, Zhang Q et al. Large outbreak of herpangina in children caused by enterovirus in summer of 2015 in Hangzhou, China. Sci Rep. 2016;6:35388. Published 2016 10.1038/srep35388 [DOI] [PMC free article] [PubMed]
  • 38.Pan D, Mohamed B, Gupta A, et al. Clinical and molecular epidemiology of enterovirus infections in cerebrospinal fluid samples, 2019–2023. J Med Virol. 2024;96(9):e29924. 10.1002/jmv.29924 [DOI] [PubMed] [Google Scholar]
  • 39.Nkosi N, Preiser W, van Zyl G, et al. Molecular characterisation and epidemiology of enterovirus-associated aseptic meningitis in the Western and Eastern cape provinces, South Africa 2018–2019. J Clin Virol. 2021;139:104845. 10.1016/j.jcv.2021.104845 [DOI] [PubMed] [Google Scholar]
  • 40.Larsson SB, Vracar D, Karlsson M, Ringlander J, Norder H. Epidemiology and clinical manifestations of different enterovirus and rhinovirus types show that EV-D68 May still have an impact on severity of respiratory infections. J Med Virol. 2022;94(8):3829–39. 10.1002/jmv.27767 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Chi J, Tang H, Wang F, Wang Y, Chen Z. Surge in Mycoplasma pneumoniae infection and respiratory viruses Co-infection in children with Community-Acquired pneumonia in the Post-Pandemic. Pediatr Health Med Ther. 2024;15:279–88. 10.2147/PHMT.S473669. Published 2024 Sep 7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Song Y, Zhang Y, Ji T, et al. Persistent circulation of coxsackievirus A6 of genotype D3 in Mainland of China between 2008 and 2015. Sci Rep. 2017;7(1):5491. 10.1038/s41598-017-05618-0. Published 2017 Jul 14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Chen Y, Ji W, Duan G, et al. Childhood hand, foot and mouth disease sequelae cohort study in henan, china: cohort profile. BMJ Open. 2025;15(1):e083958. 10.1136/bmjopen-2024-083958. Published 2025 Jan 9. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

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

Data Citations

  1. Pedrosa C, Lage MJ, Virella D. Congenital echovirus 21 infection causing fulminant hepatitis in a neonate. BMJ Case Rep. 2013. 10.1136/bcr-2012-008394. Published 2013 Apr 9. 2013:bcr2012008394. [DOI] [PMC free article] [PubMed]

Supplementary Materials

Supplementary Material 1 (17.7KB, docx)
12985_2025_2862_MOESM2_ESM.png (1MB, png)

Fig.5 The Neighbor-Joining Phylogenetic tree

Data Availability Statement

The sequencing data that support the findings of this study are openly available in GenBank, accession number PP738598– PP738608, PQ124013– PQ124024. No other data are publicly available.

Articles from Virology Journal are provided here courtesy of BMC

RESOURCES