Common respiratory virus spectrum and epidemiological trends among children in Northwest China during the post-COVID-19 era

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Methods Retrospective analysis of children with respiratory symptoms who visited our hospital between March 2023 and May 2025 was conducted. Influenza A/B (Flu A/B) antigen testing was performed for 151,809 children; nucleic acid testing for respiratory syncytial virus ༈RSV༉, adenovirus ༈ADV༉, human metapneumovirus (HMPV), and parainfluenza viruses (PIV) I–III was performed for 35,326 children. Demographic and laboratory data were analyzed. Results Across two post-pandemic seasons, most viruses resurged; HMPV and PIV II peaked more prominently in season 2. RSV showed the highest positivity, whereas Flu A had the most positive cases. RSV and PIV III predominated in infants; Flu A, HMPV, and PIV I/II predominated in preschoolers; and Flu B and ADV predominated in school-aged children. Flu A, Flu B, and the RSV shared a winter peak and summer trough, whereas the PIV subtypes displayed distinct seasonality. Clinically, Flu A/B was associated mainly with acute upper respiratory infections; non-severe pneumonia was associated predominantly with RSV, ADV, HMPV, and PIVs. Coinfections were most frequent with ADV and HMPV and least frequent with Flu A and Flu B; the most common dual and triple coinfections were “RSV + ADV” and “RSV + ADV + Flu B”. Conclusion In the post-COVID-19 era, the age distribution, seasonality, and coinfection patterns of pediatric respiratory viruses shifted. Viruses with high detection and coinfection propensities warrant strengthened surveillance and tailored control strategies. respiratory virus epidemiological children post-COVID-19 China Figures Figure 1 Figure 2 Figure 3 Introduction The emergence of the coronavirus disease 2019 (COVID-19) pandemic led to the widespread implementation of public health prevention and control measures globally [ 1 , 2 ]. As a result, the epidemiological patterns of respiratory virus infections in children have changed significantly, becoming a key topic in pediatric infectious disease research. Common respiratory pathogens usually cause acute infections during seasonal outbreaks. However, throughout the COVID-19 pandemic, the epidemiology, clinical features, and public health impact of these viruses showed dynamic changes [ 3 , 4 , 5 ]. These changes are mainly due to the adoption of nonpharmaceutical interventions (NPIs), such as social distancing and mask wearing, which have disrupted traditional seasonal transmission [ 5 ]. This unique situation offers new insights into how respiratory viruses may re-emerge in the future. After the onset of the COVID-19 pandemic, various respiratory viruses experienced significant and diverse changes in their epidemiological patterns, reflecting shifts over time and across regions. Influenza A (Flu A) and B (Flu B) viruses are representative examples [ 6 ]. Early in the pandemic, transmission levels decreased, but regional outbreaks later re-emerged in several areas. Global data show a sharp decline in influenza detection rates and fewer infected individuals, leading to a reduced overall disease burden [ 7 , 8 ]. Similarly, reported cases of adenovirus (ADV) also decreased, although its spread continues to follow a seasonal trend [ 7 ]. In contrast, respiratory syncytial virus (RSV) experienced a strong rebound after the pandemic, with a notable increase in hospitalizations among children and ICU admissions [ 9 ]. Studies have reported a rapid increase in RSV detection, with cases occurring outside the usual season [ 10 ]. Human metapneumovirus (HMPV) and parainfluenza viruses (PIV) show patterns similar to those of influenza and RSV. Although HMPV accounts for a small share of positive cases, it shares clinical features with influenza, and its detection increased after NPIs were relaxed [ 11 ]. PIV show irregular seasonal patterns, with increasing infection rates in some areas [ 11 , 12 ] These virus-specific traits, such as seasonal shifts, are consistent globally. These varied changes result primarily from the complex interaction between virus traits and host immunity, offering further insight into how respiratory virus transmission networks have changed since the pandemic. While the epidemiological changes in individual viruses have been a dominant focus in reported studies, multiple respiratory viruses in children have been systematically examined in few studies. This gap is especially clear in cross-viral comparisons and the long-term tracking of trends after the COVID-19 pandemic. Although research has focused on major pathogens such as influenza and RSV, there is limited analysis of the co-circulation patterns of ADV, HMPV, and PIV are limited. Thus, in the present study, we systematically assessed the epidemiological characteristics of common respiratory viruses among children in the post-pandemic era, aiming to provide robust, evidence-based support for the development of optimized disease control strategies. Materials and methods Study design and participant selection In this single-center retrospective observational study, children under 18 years of age who presented to Xi’an Children’s Hospital (the largest pediatric specialty hospital in Northwest China) with symptoms of acute respiratory tract infection (including fever, cough, nasal congestion, expectoration, sneezing, and dyspnea) between March 1, 2023 and May 31, 2025, were included. All participants underwent antigen testing for influenza A and B viruses or nucleic acid testing for six common respiratory pathogens: RSV, ADV, HMPV, PIV I, PIV II, and PIV III. The choice of a detection method depends on the clinician's clinical judgment. The included children were categorized into four age groups: (1) infant group (< 1 year), (2) toddler group (1 year ≤ age < 3 years), (3) preschooler group (3 years ≤ age < 6 years), and (4) school-age group (6 years ≤ age < 18 years). Based on the epidemiological patterns of infectious diseases, seasonal data were further divided into four periods: spring (March to May), summer (June to August), autumn (September to November), and winter (December to February of the following year). Laboratory testing and data collection For all pediatric participants who included in this study, trained specimen collectors obtained pharyngeal swab samples in accordance with standard operating procedures within a predefined time frame: either at the time of outpatient consultation or within three days following inpatient admission. The collected samples were subsequently submitted to the clinical laboratory for pathogen detection. Flu A and Flu B antigens were detected using the Influenza A/B Virus Antigen Detection Kit (colloidal gold method; Hangzhou Abbott Biomedical Co., Ltd.). The nucleic acids of RSV, ADV, HMPV, PIV I, PIV II, and PIV III were analyzed using the 6-in-1 Respiratory Virus Nucleic Acid Detection Kit (fluorescence PCR method; Shanghai BioGerm Medical Technology Co., Ltd.). To ensure the accuracy and reliability of the results, all assays underwent rigorous internal laboratory quality control, and all outcomes fell within the acceptable quality control range. Demographic characteristics, clinical data, and pathogen detection outcomes of all children included in the study were extracted from the laboratory information system. If any of the target viruses were detected in a sample, the child was considered infected with the corresponding virus. In cases where multiple viruses were detected simultaneously in the same sample, each virus was recorded individually. Repeated test results from the same subject within a one-week interval were excluded. Co-infection was defined as the identification of two or more distinct viruses yielding positive results in the same child within a 7-day period. Statistical analysis Categorical variables, such as year, sex, age group, and season, are expressed as frequencies and percentages. To assess the overall differences among groups, Pearson's chi-square test or Fisher's exact test was employed when applicable. For post hoc pairwise comparisons, the Holm-Bonferroni method was employed for multiple comparison correction. All statistical analyses were performed using SPSS software, version 29.0 (IBM SPSS Statistics for Windows, Armonk, NY, USA). The criterion for statistical significance was a two-tailed P value of less than 0.05. Results Annual and Monthly Epidemiological Trends of Respiratory Viruses From March 2023 to May 2025, a total of 151,809 children underwent Flu A and Flu B antigen testing at our hospital, and 35,326 children were tested for nucleic acids of six respiratory viral pathogens. To examine the annual prevalence trends of targeted respiratory viruses in children, we defined the first two full post-COVID-19 years as “Year 1 AC” and “Year 2 AC”, which corresponded to the periods from March 2023 to February 2024 and from March 2024 to February 2025, respectively. As shown in Table 1 , the number of positive cases for each virus differed between Year 1 AC and Year 2 AC. The detection rates of Flu A, HMPV, and PIV II increased in Year 2 AC ( P < 0.001), whereas those of the other five viruses decreased ( P < 0.001). Specifically, in Year 1 AC, there were 11,689 (12.04%) cases of Flu A, 3,389 (3.49%) of Flu B, 3,634 (20.25%) of RSV, 2,639 (14.71%) of ADV, 622 (3.47%) of HMPV, 297 (1.65%) of PIV I, 91 (0.51%) of PIV II, and 907 (5.05%) of PIV III. In Year 2 AC, these numbers were 7,279 (14.30%) for Flu A, 133 (0.26%) for Flu B, 1,969 (13.57%) for RSV, 859 (5.92%) for ADV, 668 (4.60%) for HMPV, 27 (0.87%) for PIV I, 387 (2.67%) for PIV II, and 683 (4.01%) for PIV III. Table 1 Detection of respiratory viruses in children from Shaanxi, March 2023 to February 2025 Years Flu A χ2 P Flu B χ2 P RSV χ2 P ADV χ2 P Positive (%) Negative Positive (%) Negative Positive (%) Negative Positive (%) Negative Year 1 AC 11689 (12.04) 85391 128109.242 < 0.001 3389 (3.49) 93691 147419.882 < 0.001 3634 (20.25) 14312 27295.063 < 0.001 2639 (14.71) 15307 29839.448 < 0.001 Year 2 AC 7279 (14.30) 43628 133 (0.26) 50774 1969 (13.57) 12546 859 (5.92) 13656 HMPV PIV I PIV II PIV III Positive (%) Negative Positive (%) Negative Positive (%) Negative Positive (%) Negative Year 1 AC 622 (3.47) 17324 31158.085 < 0.001 297 (1.65) 17649 32101.140 < 0.001 91 (0.51) 17855 32162.968 < 0.001 907 (5.05) 17039 30884.950 < 0.001 Year 2 AC 668 (4.60) 13847 127 (0.87) 14388 387 (2.67) 14128 683 (4.01) 13832 Abbreviations: Flu A, influenza A virus; Flu B, influenza B virus; RSV, respiratory syncytial virus; ADV, adenovirus; HMPV, human metapneumovirus; PIV, parainfluenza virus Year 1 AC refers to the period from March 2023 to February 2024; Year 2 AC refers to the period from March 2024 to February 2025 During the post-COVID-19 period, most respiratory viruses showed varying levels of activity during the first epidemic season (Year 1 AC). In contrast, HMPV and PIV II experienced more notable outbreaks during the second epidemic season (Year 2 AC). Flu A had two major waves in March 2023 (6,773 cases, 23.88%) and December 2024 (5,262 cases, 27.68%), whereas Flu B peaked in December 2023 (1,771 cases, 8.10%) and January 2024 (1,141 cases, 8.28%). Compared with Flu A, RSV and ADV had fewer cases but higher average positivity rates. RSV peaked in December 2023 (992 cases, 36.07%) and January 2024 (869 cases, 33.60%), with the highest rate in February 2025 (588 cases, 57.53%). ADV peaked in November 2023 (829 cases, 28.54%) and December 2023 (600 cases, 21.80%). The positive detection rate of HMPV remained stable without major fluctuations. Higher rates were seen in November and December 2024, with 146 (11.32%) and 190 (11.29%) positive cases detected, respectively. Among the three PIV serotypes, PIV III had the highest positivity level in both case count and detection rate. Its peak occurred in June and July 2023, with 271 (19.62%) and 312 (24.92%) cases, respectively. In comparison, PIV I and PIV II had lower detection levels. The highest detection for PIV I was in October 2023 (112 cases, 5.75%), and that for PIV II was in June 2024 (138 cases, 11.00%) (Fig. 1 ). Sex, age and seasonal distribution of various respiratory viruses Tables 2 and 3 illustrate the distribution patterns of eight common viral pathogens associated with pediatric respiratory tract infections. During the period from March 2023 to May 2025, significant differences were observed in the positive detection rates of these respiratory viruses among pediatric patients ( P < 0.001). RSV had the highest detection rate at 17.76%, with 6,273 positive cases reported. In contrast, Flu A had the greatest number of positive detections (n = 19,012), with a detection rate of 12.52%. PIV II had the lowest number of positive cases, with only 488 detected, and the lowest detection rate of all eight viruses was 1.38%. Gender distribution analysis showed significant differences in the detection rates of Flu A, Flu B, RSV, and PIV III ( P < 0.01), with higher rates in male children. No significant sex differences were found for ADV, HMPV, PIV I, or PIV II. Among virus-specific cases, PIV III had the highest proportion in males (60.26%), while PIV II had the lowest percentage (54.71%). Table 2 Results of comparative analysis for pediatric respiratory viruses by total positive cases, gender, age, and season in post-COVID-19 era Variables Flu A Flu B RSV ADV HMPV PIV I PIV II PIV III χ2 P Total number of visits, n 151809 151809 35326 35326 35326 35326 35326 35326 Positive cases, n (%) 19012 a (12.52) 3525 b (2.26) 6273 c (17.76) 3617 d (10.27) 1359 e (3.85) 514 f (1.46) 488 f (1.38) 1789 g (5.06) 22898.768 < 0.001 Gender Male, n (%) 10685 a (56.20) 2029 ab (57.56) 3683 ab (58.71) 2077 ab (57.42) 791 ab (58.20) 304 ab (59.14) 267 a (54.71) 1078 b (60.26) 23.269 0.002 Female, n (%) 8327 a (43.80) 1496 ab (42.44) 2590 ab (41.29) 1540 ab (42.58) 568 ab (41.80) 210 ab (40.86) 221 a (45.29) 711 b (39.74) Age group Infant, n (%) 1335 a (7.02) 293 ad (8.31) 1992 b (31.76) 243 a (6.72) 219 c (16.11) 79 c (15.37) 53 cd (10.86) 550 b (30.74) 2979.006 < 0.001 Toddler, n (%) 3999 a (21.03) 726 a (20.60) 1727 b (27.53) 604 c (16.70) 323 ab (23.77) 138 b (26.85) 95 ac (19.47) 663 d (37.06) 367.911 < 0.001 Preschooler, n (%) 7656 a (40.27) 1182 b (33.53) 1642 c (26.18) 1312 ab (36.27) 640 d (47.09) 208 a (40.47) 221 a (45.29) 422 c (23.59) 633.566 < 0.001 School-age, n (%) 6022 a (31.67) 1324 b (37.56) 912 c (14.54) 1458 b (40.31) 177 c (13.02) 89 cd (17.32) 119 d (24.39) 154 e (8.61) 1781.218 < 0.001 Season Spring, n (%) 7749 a (40.76) 104 b (2.95) 2071 c (33.01) 416 d (11.50) 308 e (22.66) 104 e (20.23) 136 ce (27.87) 481 e (26.89) 2881.886 < 0.001 Summer, n (%) 61 a (0.32) 11 a (0.31) 250 b (3.99) 480 c (13.27) 248 d (18.25) 59 c (11.48) 235 e (48.16) 961 e (53.72) 10331.75 < 0.001 Autumn, n (%) 648 a (3.41) 219 b (6.21) 614 c (9.79) 1370 d (37.88) 374 e (27.52) 290 f (56.42) 41 bc (8.40) 246 g (13.74) 5618.581 < 0.001 Winter, n (%) 10554 a (55.51) 3191 b (90.52) 3338 a (53.21) 1351 c (37.35) 429 d (31.57) 61 e (11.87) 76 e (15.57) 101 f (5.65) 4864.236 < 0.001 Abbreviations: Flu A, influenza A virus; Flu B, influenza B virus; RSV, respiratory syncytial virus; ADV, adenovirus; HMPV, human metapneumovirus; PIV, parainfluenza virus Superscript letters: Matching letters within the same row indicate no significant difference, and the different letters indicate a significant difference. Table 3 Variations in the distribution of individual pediatric respiratory virus across gender, age groups, and seasons in the post-COVID-19 era Variables Flu A χ2 P Flu B χ2 P RSV χ2 P ADV χ2 P Positive (%) Negative Positive (%) Negative Positive (%) Negative Positive (%) Negative Gender Male 10685 (14.58) 62623 544.813 < 0.001 2029 (2.77) 71279 124.209 < 0.001 3683 (18.37) 16367 11.876 < 0.001 2077 (10.36) 17973 0.729 0.393 Female 8327 (10.61) 70174 1496 (1.91) 77005 2590 (16.95) 12686 1540 (10.08) 13736 Age group Infant 1335 a (10.14) 11830 169.151 < 0.001 293 a (2.23) 12872 82.248 < 0.001 1992 a (33.24) 4001 1790.045 < 0.001 243 a (4.05) 5750 464.488 < 0.001 Toddler 3999 b (11.33) 31309 726 a (2.06) 34582 1727 b (22.36) 5997 604 b (7.82) 7120 Preschooler 7656 c (13.48) 49145 1182 a (2.08) 55619 1642 c (15.25) 9127 1312 c (12.18) 9457 School-age 6022 c (12.94) 40513 1324 b (2.85) 45211 912 d (8.41) 9928 1458 d (13.45) 9382 Season Spring 7749 a (13.92) 47932 2607.689 < 0.001 104 a (0.19) 55577 2826.738 < 0.001 2071 a (25.49) 6053 3358.366 < 0.001 416 a (5.12) 7708 568.348 < 0.001 Summer 61 b (0.69) 8826 11 a (0.12) 8876 250 b (3.59) 6718 480 b (6.89) 6488 Autumn 648 c (4.07) 15257 219 b (1.38) 15686 614 c (6.54) 8774 1370 c (14.59) 8018 Winter 10554 d (14.79) 60782 3191 c (4.47) 68145 3338 d (30.78) 7508 1351 d (12.46) 9495 HMPV PIV I PIV II PIV III Positive (%) Negative Positive (%) Negative Positive (%) Negative Positive (%) Negative Gender Male 791 (3.95) 19259 1.207 0.272 304 (1.52) 19746 1.211 0.271 267 (1.33) 19783 0.842 0.359 1078 (5.38) 18972 9.406 0.002 Female 568 (3.72) 14708 210 (1.37) 15066 221 (1.45) 15055 711 (4.65) 14565 Age group Infant 219 a (3.65) 5774 274.508 < 0.001 79 a (1.32) 5914 52.685 < 0.001 53 a (0.88) 5940 54.137 < 0.001 550 a (9.18) 5443 738.593 < 0.001 Toddler 323 a (4.18) 7401 138 b (1.79) 7586 95 a (1.23) 7629 663 a (8.58) 7061 Preschooler 640 b (5.94) 10129 208 b (1.93) 10561 221 b (2.05) 10548 422 b (3.92) 10347 School-age 177 c (1.63) 10663 89 c (0.82) 10751 119 a (1.10) 10721 154 c (1.42) 10686 Season Spring 308 a (3.79) 7816 2.449 0.485 104 a (1.28) 8020 254.801 < 0.001 136 a (1.67) 7988 306.276 < 0.001 481 a (5.92) 7643 1618.273 < 0.001 Summer 248 a (3.56) 6720 59 b (0.85) 6909 235 b (3.37) 6733 961 b (13.79) 6007 Autumn 374 a (3.98) 9014 290 c (3.09) 9098 41 c (0.44) 9347 246 c (2.62) 9142 Winter 429 a (3.96) 10417 61 b (0.56) 10785 76 c (0.70) 10770 101 d (0.93) 10745 Abbreviations: Flu A, influenza A virus; Flu B, influenza B virus; RSV, respiratory syncytial virus; ADV, adenovirus; HMPV, human metapneumovirus; PIV, parainfluenza virus Superscript letters: When classified by age or season, the matching letters within the same column indicate no significant difference, and the different letters indicate a significant difference. All eight viruses exhibited statistically significant differences in positive detection rates across the various age groups. Specifically, RSV and PIV III exhibited the highest positive rates in the infant group (< 1 year old), at 33.24% and 9.18%, respectively. Flu A, HMPV, PIV I, and PIV II had the highest positive detection rates in the preschooler group (3 ∼ 6 years old), with values of 13.48%, 5.94%, 1.93%, and 2.05%, respectively. In contrast, Flu B and ADV demonstrated the highest positive rates in the school-age group (6 ∼ 18 years old), at 2.85% and 13.45%, respectively. Furthermore, Flu A, ADV, and PIV II had the lowest positive detection rates in the infant group, at 10.14%, 4.05%, and 0.88%, respectively. Flu B exhibited the lowest positive rate in the toddler group (1 ∼ 3 years old), at 2.06%. Finally, RSV, HMPV, PIV I, and PIV III had the lowest positive rates in the school-age group, at 8.41%, 1.63%, 0.82%, and 1.42%, respectively. Furthermore, the results of the horizontal comparative analysis revealed statistically significant variations in the number of children among different age groups who tested positive for respiratory viruses ( P < 0.001). With the exception of HMPV, which did not exhibit a significant seasonal distribution pattern, the infections caused by the remaining seven respiratory viruses demonstrated distinct seasonal distribution characteristics ( P < 0.001), although their seasonal trends varied. Flu A, Flu B, and RSV exhibited comparable seasonal distribution patterns, with peak positive rates occurring in winter and the lowest in summer; specifically, the positive rates of these three viruses were 14.49%, 4.47%, and 30.78% in winter, respectively, compared with 0.69%, 0.12%, and 3.59% in summer, respectively. The three subtypes of PIV, by contrast, displayed divergent seasonal profiles. The positive rate of PIV I was relatively high in autumn (3.09%) and lowest in winter (0.56%). PIV II and PIV III were predominantly detected in summer, with positive rates of 3.37% and 13.79%, respectively. Among these, PIV II reached its lowest detection rate in autumn (0.44%), whereas PIV III had the lowest rate in winter (0.93%). In addition, the results of the horizontal comparative analysis revealed statistically significant variations in the number of children who were positive for respiratory viruses among different seasons ( P < 0.001). Distribution Patterns of Clinical Diagnoses Linked to Respiratory Virus Infections The distribution patterns of clinical diagnoses associated with various respiratory viruses demonstrated distinct epidemiological characteristics. Among Flu A- and Flu B-positive patients, the majority were clinically diagnosed with acute upper respiratory tract infections (74.78% and 66.89%, respectively). For the remaining six respiratory viruses, non-severe pneumonia was the most common diagnosis, followed by acute bronchitis. Specifically, among the RSV-positive patients, 41.50% were diagnosed with non-severe pneumonia, and 19.93% were diagnosed with acute bronchitis. For ADV, the corresponding percentages were 31.63% and 22.20%; for HMPV, 50.85% and 25.02%; for PIV I, 34.44% and 27.82%; for PIV II, 39.75% and 29.46%; and for PIV III, 38.96% and 28.95%. Notably, RSV was associated with the highest proportion of patients with severe pneumonia among all investigated viruses, 50 patients (0.80%), followed by ADV with 22 patients (0.61%). In contrast, Flu A accounted for the lowest proportion of severe pneumonia patients, with only 6 (0.03%) (Fig. 2 ). Co-infection characteristics among respiratory viruses As shown in Fig. 3 , among the eight respiratory viruses, ADV had the highest co-infection incidence. Among the 3,617 ADV-positive patients, 886 were co-infected, resulting in a co-infection rate of 24.50%. HMPV followed, with a co-infection incidence of 14.57%. In contrast, Flu A and Flu B were the lowest, at 0.83% and 3.97%, respectively. Among the 26 dual co-infection patterns identified, the “RSV + ADV” combination was the most frequently observed, comprising 521 patients and accounting for nearly half (45.74%) of all dual co-infections. Among the 17 triple co-infection types, “RSV + ADV + Flu B” was the most prevalent combination, with 13 patients reported, representing 29.55% of all triple co-infection patterns. Furthermore, among children with co-infections, significant differences were observed in terms of both sex and age distribution ( P < 0.001). Among the 1183 children with co-infections, co-infections were significantly more prevalent in males than females. Regarding age distribution, preschool children represented the largest group, accounting for 31.95%, whereas infants had the lowest proportion, at 19.0%. No statistically significant difference was found with respect to the source of patients ( P = 0.585). Specifically, 605 children were inpatients, and 578 were outpatients (Table 4 ). Table 4 Comparison of the distribution characteristics of pediatric respiratory virus co-infections by gender, age, and patient source Variable Total number of co-infections Number of co-infections (%) c2 P Gender Male 1183 715 (60.44) 103.143 < 0.001 Female 468 (39.56) Age group Infant 226 a (19.10) 53.292 < 0.001 Toddler 282 b (23.84) Preschooler 378 c (31.95) School-age 297 b (25.11) Patient source Inpatient 605 (51.14) 1.232 0.585 Outpatient 578 (48.86) Superscript letters: Matching letters within the same column indicate no significant difference, and the different letters indicate a significant difference. Discussion This study revealed that epidemiological trends of pediatric respiratory viruses changed significantly between March 2023 and May 2025, which is the post-COVID-19 period. In Year 1 AC, high rates of Flu A, RSV, and ADV were observed, indicating an initial rebound after the pandemic. In Year 2, AC, Flu A, HMPV, and PIV II increased, whereas Flu B, ADV, and others decreased, suggesting a shift in virus circulation as social and economic activities returned to normal. Notably, outbreaks of HMPV and PIV II were delayed until Year 2 AC, indicating that some viruses took longer to return to their normal epidemic patterns post-COVID-19. These changes may be linked to altered virus transmission after the easing of NPIs, such as mask-wearing, social distancing, and school closures. This aligns with previous reports that some viruses rebounded, whereas others declined [ 6 , 13 ]. These observations suggest that in the post-pandemic era, respiratory virus dynamics may be influenced by changes in population immunity, such as immune deficits from reduced viral exposure. Ongoing surveillance of viral trends is therefore essential for improving prevention and management strategies for pediatric respiratory diseases. Results from this study revealed that the positive detection rate of RSV for pediatric respiratory infections was 17.76%, which is consistent with previous findings. RSV is a major respiratory pathogen in children globally (e.g., up to 22.7% detection rate) [ 14 ]. The prevalence of PIV II is low (1.38%), indicating that it is rare in children. Differences in virus detection rates may reflect seasonal patterns or age-related factors [ 15 ]. We also found that compared with female children, male children had higher positive rates for Flu A/B, RSV, and PIV III. This finding is supported by previous studies [ 16 , 17 ]. Chu et al. reported that virus detection in male children was 39.29%, which was higher than that in females (34.67%), and that positivity decreased with age. Abdel et al. also reported that more males were affected by viral acute gastroenteritis (male-to-female ratio of 1:0.8). These findings suggest that male children may be more susceptible to or more often exposed to certain respiratory viruses. Furthermore, we found that respiratory viruses vary significantly in their age-specific and seasonal patterns, indicating that infections depend on both age and season. RSV and PIV III are most common in infants (< 1 year), likely due to underdeveloped immunity. This finding supports earlier studies showing that infants and young children are more susceptible to RSV [ 18 ]. Flu B and ADV peak in school-aged children (6 ~ 18 years), possibly because of increased social contact. Flu A, HMPV, PIV I, and PIV II are most prevalent among preschoolers (3 ~ 6 years), whereas RSV is least common among school-age children. These trends suggest that virus spread is influenced by exposure and immune development [ 19 ]. With the exception of HMPV, most respiratory viruses show clear seasonal patterns, suggesting that traditional seasonal trends have returned after the COVID-19 pandemic. Flu A and B, along with RSV, returned to their usual winter peaks, with much lower activity in summer. This matches the typical winter-dominant pattern seen in temperate regions and supports the idea that viruses regained their pre-pandemic seasonality as NPIs were lifted [ 5 , 20 , 21 ]. PIV I peaked in autumn and was lowest in winter, whereas PIV II/III peaked in summer and declined in winter. These patterns align with previous reports of seasonal transmission [ 22 ]. HMPV showed no clear seasonal trend, which may be due to a slow recovery from pandemic disruptions or a short observation period. These findings indicate that clinical practice should focus on integrated detection and surveillance of multiple pathogens. Ongoing monitoring is also needed for seasonal changes and shifts in the age groups affected. This study demonstrated distinct clinical and diagnostic differences among respiratory viruses. Flu A and Flu B infections mainly present as acute upper respiratory tract infections, indicating that influenza viruses typically cause localized symptoms. In contrast, other respiratory viruses are more commonly linked to lower respiratory tract involvement. Among them, non-severe pneumonia is most frequent, especially for RSV and HMPV, followed by acute bronchitis. These findings align with those of previous studies showing that RSV is the leading cause of pediatric pneumonia and that the majority of lower respiratory tract infections are viral in origin [ 14 ]. RSV has the highest rate of severe pneumonia (0.80%), approximately 26 times higher than that of Flu A (0.03%). These findings support existing evidence that compared with influenza, RSV causes more severe illness in children, likely due to its ability to damage airway mucosa and trigger strong inflammation [ 14 , 23 ]. PIV I–III and ADV also resulted in high severe pneumonia rates (0.61%), significantly above those of influenza, indicating strong lower respiratory tract involvement. In contrast, Flu A and Flu B were associated with very low severe pneumonia rates (0.03–0.06%), which is consistent with their tendency to affect the upper respiratory tract. However, influenza can still cause severe illness in vulnerable groups such as infants, young children, and immunocompromised individuals. Therefore, the observed low rate of severe cases may be due to the predominance of mild, outpatient cases included in the study [ 23 ]. These findings support early identification of high-risk viral pathogens and emphasize the need to improve surveillance and early warning systems for severe respiratory infections. The results of our study also revealed that ADV had the highest co-infection rate (24.50%), followed by hMPV (14.57%). Previous studies reported that up to 57.1% of ADV-infected children had other viral infections, and the hMPV co-infection rate during the pandemic was 30.10% [ 24 , 25 ]. These higher rates may reflect differences in geography and timing. Flu A and B had the lowest co-infection rates (0.83% and 3.97%, respectively), likely due to their seasonal patterns or greater sensitivity to NPIs [ 26 ]. The most common co-infection was “RSV + ADV”, which was detected in 45.74% of the patients. Studies have shown that co-infection with RSV and bacteria can greatly worsen disease severity, and similarly, ADV co-infection with other pathogens significantly increases the risk of severe illness, such as an 81% increase in pneumonia cases [ 27 , 28 ]. The interaction between RSV and ADV may lead to worse clinical outcomes, suggesting the need to further study how these viruses interact. The “RSV + ADV + Flu B” combination accounted for 29.55% (n = 13) of triple infections. Triple-virus infections reflect complex dynamics, possibly shaped by seasonal or immune factors [ 29 ]. The common occurrence of “RSV + ADV + Flu B” likely results from the high prevalence of these viruses in children. More male children had co-infections than females, possibly due to immune differences. However, the exact cause is unknown. Preschoolers were most affected, likely due to underdeveloped immunity and more contact with others [ 30 ]. Infants had the lowest rate, possibly due to maternal antibodies [ 31 ]. No difference was observed between hospitalization and outpatient rates. However, previous studies have demonstrated that viral co-infection can precipitate severe lower respiratory tract symptoms, thereby increasing the risk of hospitalization and prolonging the duration of hospital stay [ 28 ]. Using clinical indicators such as oxygen saturation and respiratory rate may help identify high-risk outpatient patients, improving monitoring and care. This study has several limitations. First, as a single-center retrospective study, it is prone to selection bias and may lack standardized data, which could affect the reliability and generalizability of the findings. Therefore, future multicenter prospective studies are needed to validate these results. Second, the specimen type utilized in this study was a pharyngeal swab. The quality of sampling directly influences the accuracy of the test results, and suboptimal sampling procedures may lead to false-negative outcomes. Third, influenza A and B antigens were detected using the colloidal gold method, which has limited sensitivity and specificity. As a result, false-positive or false-negative results may occur, potentially affecting the accuracy of the findings. Finally, antigen testing for influenza A/B and nucleic acid testing for six respiratory viruses were performed separately, possibly with a time interval between tests. This could introduce bias in identifying co-infections. Conclusion In the post-COVID-19 era, Flu A and B, RSV, ADV, and PIV I–III peaked in Year 1 AC, whereas HMPV and PIV II became prevalent only in Year 2 AC. All eight viruses showed age-related differences in detection rates, and only HMPV lacked a clear seasonal pattern. Flu A and B were mainly linked to upper respiratory infections, whereas the other six were more common in non-severe pneumonia and acute bronchitis. ADV and HMPV were most often involved in co-infections, especially with RSV, and Flu A and B were rarely involved in co-infections. The “RSV + ADV” combination represented the most prevalent dual co-infection pattern, whereas “RSV + ADV + Flu B” was the most common triple co-infection. These findings may provide valuable evidence for the development of targeted prevention and control strategies aimed at addressing the overlapping circulation of pediatric respiratory viruses in the post-COVID-19 era. Declarations Acknowledgements We would like to thank Springer Nature Author Services (www.secure.authorservices.springernature.com) for the linguistic assistance. Ethics statement This study was approved by the Medical Ethics Committee of the Affiliated Children's Hospital of Xi’an Jiaotong University (Ethics [Research] No. 2025-055-03) and followed the ethical principles of the 1964 Declaration of Helsinki and its later amendments. Consent All participants’ personal information was maintained with strict confidentiality. As this study is retrospective and conducted in accordance with relevant Chinese ethical guidelines (Measures for the Ethical Review of Biomedical Research Involving Human Subjects), the requirement for informed consent was formally waived by the the Medical Ethics Committee of the Affiliated Children's Hospital of Xi’an Jiaotong University following review. Author contributions Funding: Z.G.W.; Conceptualization: J.Y.T. and Z.G.W.; Methodology: J.Y.T. and Y.W.; Data collection and curation: W.N.Y., C.C.C. and R.W.; Data analysis: Y.W., W.N.Y., P.W.N., J.F.S. and J.H.L.; Writing: J.Y.T. and Y.W.; Revision: J.Y.T. and Z.G.W. All authors have reviewed the earlier versions of the manuscript, provided critical feedback, and formally approved the final version for submission. Funding This work was supported by General Program of National Natural Science Foundation of China [grant number: 82172312] and Shaanxi Provincial Key Research and Development Program [grant number: 2021SF-003]. Conflicts of interest The authors declare that, during the execution of this study, no commercial relationships or financial interests existed that could be interpreted as potential conflicts of interest. Clinical trial numb er Not applicable. 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1","display":"","copyAsset":false,"role":"figure","size":28509992,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly distribution of the number of positive cases and positivity rates for (a) influenza A virus, (b) influenza B virus, (c) respiratory syncytial virus, (d) adenovirus, (e) human metapneumovirus, and (f-h) parainfluenza virus I–III infections among pediatric patients between March 2023 and May 2025.\u003c/p\u003e\n\u003cp\u003eFlu A, influenza A virus; Flu B, influenza B virus; RSV, respiratory syncytial virus; ADV, adenovirus; HMPV, human metapneumovirus; PIV, parainfluenza virus\u003c/p\u003e","description":"","filename":"Fig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8546358/v1/1ca4b2d3ba9b97a371aa09cf.jpg"},{"id":100672381,"identity":"11499aa0-edce-4f95-baa6-bc601518b94c","added_by":"auto","created_at":"2026-01-20 10:38:20","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":12907191,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of clinical diagnoses among pediatric patients positive for (a) influenza A virus, (b) influenza B virus, (c) respiratory syncytial virus, (d) adenovirus, (e) human metapneumovirus, and (f–h) parainfluenza virus types I–III.\u003c/p\u003e\n\u003cp\u003eFlu A, influenza A virus; Flu B, influenza B virus; RSV, respiratory syncytial virus; ADV, adenovirus; HMPV, human metapneumovirus; PIV, parainfluenza virus\u003c/p\u003e","description":"","filename":"Fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8546358/v1/f34d61dad93700dab0e55bb8.jpg"},{"id":100672370,"identity":"41c87b01-45dd-490e-a9e8-d0b980e34275","added_by":"auto","created_at":"2026-01-20 10:38:17","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":14191905,"visible":true,"origin":"","legend":"\u003cp\u003eCo-infections of respiratory viruses in pediatric patients. (a) Number of mono-infections and co-infections of pediatric respiratory viruses. (b) Network diagram of co-infection relationships among pediatric respiratory viruses. The thickness and intensity of the lines connecting pairs of viruses reflect the frequency of co-infection cases. (c) Number of cases and their proportional distributions across different types of dual co-infection combinations. (d) Number of cases and their proportional distributions across different types of triple co-infection combinations.\u003c/p\u003e\n\u003cp\u003eFlu A, influenza A virus; Flu B, influenza B virus; RSV, respiratory syncytial virus; ADV, adenovirus; HMPV, human metapneumovirus; PIV, parainfluenza virus\u003c/p\u003e","description":"","filename":"Fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8546358/v1/8b3167d1f8ae22f4d32c9674.jpg"},{"id":103251457,"identity":"93871a4d-dd97-4d7f-98e6-79b6076e23d5","added_by":"auto","created_at":"2026-02-23 16:09:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":56765778,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8546358/v1/f293e5a8-7d0f-4bfa-893b-7a249393b400.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Common respiratory virus spectrum and epidemiological trends among children in Northwest China during the post-COVID-19 era","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe emergence of the coronavirus disease 2019 (COVID-19) pandemic led to the widespread implementation of public health prevention and control measures globally [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. As a result, the epidemiological patterns of respiratory virus infections in children have changed significantly, becoming a key topic in pediatric infectious disease research. Common respiratory pathogens usually cause acute infections during seasonal outbreaks. However, throughout the COVID-19 pandemic, the epidemiology, clinical features, and public health impact of these viruses showed dynamic changes [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. These changes are mainly due to the adoption of nonpharmaceutical interventions (NPIs), such as social distancing and mask wearing, which have disrupted traditional seasonal transmission [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This unique situation offers new insights into how respiratory viruses may re-emerge in the future.\u003c/p\u003e \u003cp\u003eAfter the onset of the COVID-19 pandemic, various respiratory viruses experienced significant and diverse changes in their epidemiological patterns, reflecting shifts over time and across regions. Influenza A (Flu A) and B (Flu B) viruses are representative examples [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Early in the pandemic, transmission levels decreased, but regional outbreaks later re-emerged in several areas. Global data show a sharp decline in influenza detection rates and fewer infected individuals, leading to a reduced overall disease burden [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Similarly, reported cases of adenovirus (ADV) also decreased, although its spread continues to follow a seasonal trend [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In contrast, respiratory syncytial virus (RSV) experienced a strong rebound after the pandemic, with a notable increase in hospitalizations among children and ICU admissions [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Studies have reported a rapid increase in RSV detection, with cases occurring outside the usual season [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Human metapneumovirus (HMPV) and parainfluenza viruses (PIV) show patterns similar to those of influenza and RSV. Although HMPV accounts for a small share of positive cases, it shares clinical features with influenza, and its detection increased after NPIs were relaxed [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. PIV show irregular seasonal patterns, with increasing infection rates in some areas [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] These virus-specific traits, such as seasonal shifts, are consistent globally. These varied changes result primarily from the complex interaction between virus traits and host immunity, offering further insight into how respiratory virus transmission networks have changed since the pandemic.\u003c/p\u003e \u003cp\u003eWhile the epidemiological changes in individual viruses have been a dominant focus in reported studies, multiple respiratory viruses in children have been systematically examined in few studies. This gap is especially clear in cross-viral comparisons and the long-term tracking of trends after the COVID-19 pandemic. Although research has focused on major pathogens such as influenza and RSV, there is limited analysis of the co-circulation patterns of ADV, HMPV, and PIV are limited. Thus, in the present study, we systematically assessed the epidemiological characteristics of common respiratory viruses among children in the post-pandemic era, aiming to provide robust, evidence-based support for the development of optimized disease control strategies.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participant selection\u003c/h2\u003e \u003cp\u003eIn this single-center retrospective observational study, children under 18 years of age who presented to Xi\u0026rsquo;an Children\u0026rsquo;s Hospital (the largest pediatric specialty hospital in Northwest China) with symptoms of acute respiratory tract infection (including fever, cough, nasal congestion, expectoration, sneezing, and dyspnea) between March 1, 2023 and May 31, 2025, were included. All participants underwent antigen testing for influenza A and B viruses or nucleic acid testing for six common respiratory pathogens: RSV, ADV, HMPV, PIV I, PIV II, and PIV III. The choice of a detection method depends on the clinician's clinical judgment. The included children were categorized into four age groups: (1) infant group (\u0026lt;\u0026thinsp;1 year), (2) toddler group (1 year\u0026thinsp;\u0026le;\u0026thinsp;age\u0026thinsp;\u0026lt;\u0026thinsp;3 years), (3) preschooler group (3 years\u0026thinsp;\u0026le;\u0026thinsp;age\u0026thinsp;\u0026lt;\u0026thinsp;6 years), and (4) school-age group (6 years\u0026thinsp;\u0026le;\u0026thinsp;age\u0026thinsp;\u0026lt;\u0026thinsp;18 years). Based on the epidemiological patterns of infectious diseases, seasonal data were further divided into four periods: spring (March to May), summer (June to August), autumn (September to November), and winter (December to February of the following year).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eLaboratory testing and data collection\u003c/h3\u003e\n\u003cp\u003eFor all pediatric participants who included in this study, trained specimen collectors obtained pharyngeal swab samples in accordance with standard operating procedures within a predefined time frame: either at the time of outpatient consultation or within three days following inpatient admission. The collected samples were subsequently submitted to the clinical laboratory for pathogen detection. Flu A and Flu B antigens were detected using the Influenza A/B Virus Antigen Detection Kit (colloidal gold method; Hangzhou Abbott Biomedical Co., Ltd.). The nucleic acids of RSV, ADV, HMPV, PIV I, PIV II, and PIV III were analyzed using the 6-in-1 Respiratory Virus Nucleic Acid Detection Kit (fluorescence PCR method; Shanghai BioGerm Medical Technology Co., Ltd.). To ensure the accuracy and reliability of the results, all assays underwent rigorous internal laboratory quality control, and all outcomes fell within the acceptable quality control range. Demographic characteristics, clinical data, and pathogen detection outcomes of all children included in the study were extracted from the laboratory information system. If any of the target viruses were detected in a sample, the child was considered infected with the corresponding virus. In cases where multiple viruses were detected simultaneously in the same sample, each virus was recorded individually. Repeated test results from the same subject within a one-week interval were excluded. Co-infection was defined as the identification of two or more distinct viruses yielding positive results in the same child within a 7-day period.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eCategorical variables, such as year, sex, age group, and season, are expressed as frequencies and percentages. To assess the overall differences among groups, Pearson's chi-square test or Fisher's exact test was employed when applicable. For post hoc pairwise comparisons, the Holm-Bonferroni method was employed for multiple comparison correction. All statistical analyses were performed using SPSS software, version 29.0 (IBM SPSS Statistics for Windows, Armonk, NY, USA). The criterion for statistical significance was a two-tailed \u003cem\u003eP\u003c/em\u003e value of less than 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eAnnual and Monthly Epidemiological Trends of Respiratory Viruses\u003c/h2\u003e \u003cp\u003eFrom March 2023 to May 2025, a total of 151,809 children underwent Flu A and Flu B antigen testing at our hospital, and 35,326 children were tested for nucleic acids of six respiratory viral pathogens. To examine the annual prevalence trends of targeted respiratory viruses in children, we defined the first two full post-COVID-19 years as \u0026ldquo;Year 1 AC\u0026rdquo; and \u0026ldquo;Year 2 AC\u0026rdquo;, which corresponded to the periods from March 2023 to February 2024 and from March 2024 to February 2025, respectively. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the number of positive cases for each virus differed between Year 1 AC and Year 2 AC. The detection rates of Flu A, HMPV, and PIV II increased in Year 2 AC (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), whereas those of the other five viruses decreased (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Specifically, in Year 1 AC, there were 11,689 (12.04%) cases of Flu A, 3,389 (3.49%) of Flu B, 3,634 (20.25%) of RSV, 2,639 (14.71%) of ADV, 622 (3.47%) of HMPV, 297 (1.65%) of PIV I, 91 (0.51%) of PIV II, and 907 (5.05%) of PIV III. In Year 2 AC, these numbers were 7,279 (14.30%) for Flu A, 133 (0.26%) for Flu B, 1,969 (13.57%) for RSV, 859 (5.92%) for ADV, 668 (4.60%) for HMPV, 27 (0.87%) for PIV I, 387 (2.67%) for PIV II, and 683 (4.01%) for PIV III.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDetection of respiratory viruses in children from Shaanxi, March 2023 to February 2025\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"21\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c21\" colnum=\"21\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYears\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eFlu A\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eχ2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eFlu B\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eχ2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c14\" namest=\"c12\"\u003e \u003cp\u003eRSV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eχ2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c19\" namest=\"c17\"\u003e \u003cp\u003eADV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c20\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eχ2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c21\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003ePositive (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003ePositive (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear 1 AC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11689 (12.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e85391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e128109.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3389 (3.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e93691\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e147419.882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3634 (20.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e14312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e27295.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e2639 (14.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e15307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e29839.448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear 2 AC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7279 (14.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e43628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e133 (0.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e50774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1969 (13.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e12546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e859 (5.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e13656\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eHMPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003ePIV I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c14\" namest=\"c12\"\u003e \u003cp\u003ePIV II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c19\" namest=\"c17\"\u003e \u003cp\u003ePIV III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePositive (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003ePositive (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003ePositive (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003ePositive (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear 1 AC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e622 (3.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e17324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e31158.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e297 (1.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e17649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e32101.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e91 (0.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e17855\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e32162.968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e907 (5.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e17039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e30884.950\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear 2 AC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e668 (4.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e13847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e127 (0.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e14388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e387 (2.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e14128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e683 (4.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e13832\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"21\"\u003eAbbreviations: Flu A, influenza A virus; Flu B, influenza B virus; RSV, respiratory syncytial virus; ADV, adenovirus; HMPV, human metapneumovirus; PIV, parainfluenza virus\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"21\"\u003eYear 1 AC refers to the period from March 2023 to February 2024; Year 2 AC refers to the period from March 2024 to February 2025\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDuring the post-COVID-19 period, most respiratory viruses showed varying levels of activity during the first epidemic season (Year 1 AC). In contrast, HMPV and PIV II experienced more notable outbreaks during the second epidemic season (Year 2 AC). Flu A had two major waves in March 2023 (6,773 cases, 23.88%) and December 2024 (5,262 cases, 27.68%), whereas Flu B peaked in December 2023 (1,771 cases, 8.10%) and January 2024 (1,141 cases, 8.28%). Compared with Flu A, RSV and ADV had fewer cases but higher average positivity rates. RSV peaked in December 2023 (992 cases, 36.07%) and January 2024 (869 cases, 33.60%), with the highest rate in February 2025 (588 cases, 57.53%). ADV peaked in November 2023 (829 cases, 28.54%) and December 2023 (600 cases, 21.80%). The positive detection rate of HMPV remained stable without major fluctuations. Higher rates were seen in November and December 2024, with 146 (11.32%) and 190 (11.29%) positive cases detected, respectively. Among the three PIV serotypes, PIV III had the highest positivity level in both case count and detection rate. Its peak occurred in June and July 2023, with 271 (19.62%) and 312 (24.92%) cases, respectively. In comparison, PIV I and PIV II had lower detection levels. The highest detection for PIV I was in October 2023 (112 cases, 5.75%), and that for PIV II was in June 2024 (138 cases, 11.00%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSex, age and seasonal distribution of various respiratory viruses\u003c/h2\u003e \u003cp\u003eTables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrate the distribution patterns of eight common viral pathogens associated with pediatric respiratory tract infections. During the period from March 2023 to May 2025, significant differences were observed in the positive detection rates of these respiratory viruses among pediatric patients (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). RSV had the highest detection rate at 17.76%, with 6,273 positive cases reported. In contrast, Flu A had the greatest number of positive detections (n\u0026thinsp;=\u0026thinsp;19,012), with a detection rate of 12.52%. PIV II had the lowest number of positive cases, with only 488 detected, and the lowest detection rate of all eight viruses was 1.38%. Gender distribution analysis showed significant differences in the detection rates of Flu A, Flu B, RSV, and PIV III (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with higher rates in male children. No significant sex differences were found for ADV, HMPV, PIV I, or PIV II. Among virus-specific cases, PIV III had the highest proportion in males (60.26%), while PIV II had the lowest percentage (54.71%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of comparative analysis for pediatric respiratory viruses by total positive cases, gender, age, and season in post-COVID-19 era\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFlu A\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFlu B\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRSV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eADV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHMPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePIV I\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePIV II\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePIV III\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eχ2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal number of visits, n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e151809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e35326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e35326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive cases, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19012 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(12.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3525 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(2.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6273 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(17.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3617 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(10.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1359 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e514 \u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e488 \u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1789 \u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(5.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e22898.768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale,\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10685 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(56.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2029 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(57.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3683 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(58.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2077 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(57.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e791 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(58.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e304 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(59.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e267 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(54.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1078 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(60.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e23.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale,\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8327 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(43.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1496 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(42.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2590 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(41.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1540 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(42.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e568 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(41.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e210 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(40.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e221 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(45.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e711 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(39.74)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfant,\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1335 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(7.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e293 \u003csup\u003ead\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(8.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1992 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(31.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e243 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(6.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e219 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(16.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e79 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(15.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e53 \u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(10.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e550 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(30.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2979.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToddler,\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3999 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(21.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e726 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(20.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1727 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(27.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e604 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(16.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e323 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(23.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e138 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(26.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e95 \u003csup\u003eac\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(19.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e663 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(37.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e367.911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePreschooler, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7656 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(40.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1182 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(33.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1642 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(26.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1312 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(36.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e640 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(47.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e208 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(40.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e221 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(45.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e422 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(23.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e633.566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSchool-age, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6022 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(31.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1324 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(37.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e912 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(14.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1458 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(40.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e177 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(13.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e89 \u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(17.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e119 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(24.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e154 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(8.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1781.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeason\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpring,\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7749 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(40.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e104 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(2.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2071 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(33.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e416 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(11.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e308 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(22.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e104 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(20.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e136 \u003csup\u003ece\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(27.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e481 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(26.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2881.886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSummer,\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(0.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(0.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e250 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e480 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(13.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e248 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(18.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e59 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(11.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e235 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(48.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e961 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(53.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e10331.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAutumn,\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e648 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e219 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(6.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e614 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(9.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1370 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(37.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e374 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(27.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e290 \u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(56.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e41 \u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(8.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e246 \u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(13.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e5618.581\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWinter,\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10554 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(55.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3191 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(90.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3338 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(53.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1351 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(37.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e429 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(31.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e61 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(11.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e76 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(15.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e101 \u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(5.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4864.236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eAbbreviations: Flu A, influenza A virus; Flu B, influenza B virus; RSV, respiratory syncytial virus; ADV, adenovirus; HMPV, human metapneumovirus; PIV, parainfluenza virus\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eSuperscript letters: Matching letters within the same row indicate no significant difference, and the different letters indicate a significant difference.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVariations in the distribution of individual pediatric respiratory virus across gender, age groups, and seasons in the post-COVID-19 era\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"18\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eFlu A\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eχ2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eFlu B\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eχ2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003eRSV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eχ2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003eADV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eχ2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c18\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePositive (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePositive (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003ePositive (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10685 (14.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e544.813\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2029 (2.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e71279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e124.209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3683 (18.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e16367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e11.876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2077 (10.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e17973\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.729\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.393\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8327 (10.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1496 (1.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e77005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2590 (16.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e12686\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1540 (10.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e13736\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1335 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(10.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e169.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e293 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(2.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12872\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e82.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1992 \u003csup\u003ea\u003c/sup\u003e (33.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e4001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e1790.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e243 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(4.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e5750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e464.488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToddler\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3999 \u003csup\u003eb\u003c/sup\u003e (11.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e726 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(2.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1727 \u003csup\u003eb\u003c/sup\u003e (22.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e604 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(7.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e7120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePreschooler\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7656 \u003csup\u003ec\u003c/sup\u003e (13.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1182 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(2.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e55619\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1642 \u003csup\u003ec\u003c/sup\u003e (15.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e9127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1312 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(12.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e9457\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSchool-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6022 \u003csup\u003ec\u003c/sup\u003e (12.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40513\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1324 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(2.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e45211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e912 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(8.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e9928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1458 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(13.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e9382\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeason\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7749 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(13.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e2607.689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e104 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(0.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e55577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e2826.738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2071 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(25.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e3358.366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e416 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(5.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e7708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e568.348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSummer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(0.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8826\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e250 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e480 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(6.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e6488\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAutumn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e648 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(4.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e219 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15686\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e614 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(6.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e8774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1370 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(14.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e8018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWinter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10554 \u003csup\u003ed\u003c/sup\u003e (14.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3191 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(4.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e68145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3338 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(30.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e7508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1351 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(12.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e9495\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eHMPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003ePIV I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003ePIV II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003ePIV III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePositive (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePositive (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003ePositive (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e791 (3.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e304 (1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e267 (1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e19783\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.842\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1078 (5.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e18972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e9.406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e568 (3.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e210 (1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e221 (1.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e15055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e711 (4.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e14565\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e219 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e274.508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e79 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e52.685\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e53 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5940\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e54.137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e550 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(9.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e5443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e738.593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToddler\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e323 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(4.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e138 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e95 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e7629\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e663 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(8.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e7061\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePreschooler\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e640 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(5.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e208 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e221 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(2.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e10548\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e422 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e10347\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSchool-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e177 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10663\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e89 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e119 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e10721\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e154 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e10686\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeason\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e308 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e2.449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e104 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e254.801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e136 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e7988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e306.276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e481 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(5.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e7643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e1618.273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c18\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSummer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e248 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e59 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(0.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e235 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e961 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(13.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e6007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAutumn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e374 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e290 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e41 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(0.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e9347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e246 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(2.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e9142\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWinter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e429 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e61 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(0.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e76 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e10770\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e101 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e10745\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"18\"\u003eAbbreviations: Flu A, influenza A virus; Flu B, influenza B virus; RSV, respiratory syncytial virus; ADV, adenovirus; HMPV, human metapneumovirus; PIV, parainfluenza virus\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"18\"\u003eSuperscript letters: When classified by age or season, the matching letters within the same column indicate no significant difference, and the different letters indicate a significant difference.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAll eight viruses exhibited statistically significant differences in positive detection rates across the various age groups. Specifically, RSV and PIV III exhibited the highest positive rates in the infant group (\u0026lt;\u0026thinsp;1 year old), at 33.24% and 9.18%, respectively. Flu A, HMPV, PIV I, and PIV II had the highest positive detection rates in the preschooler group (3 \u0026sim; 6 years old), with values of 13.48%, 5.94%, 1.93%, and 2.05%, respectively. In contrast, Flu B and ADV demonstrated the highest positive rates in the school-age group (6 \u0026sim; 18 years old), at 2.85% and 13.45%, respectively. Furthermore, Flu A, ADV, and PIV II had the lowest positive detection rates in the infant group, at 10.14%, 4.05%, and 0.88%, respectively. Flu B exhibited the lowest positive rate in the toddler group (1 \u0026sim; 3 years old), at 2.06%. Finally, RSV, HMPV, PIV I, and PIV III had the lowest positive rates in the school-age group, at 8.41%, 1.63%, 0.82%, and 1.42%, respectively. Furthermore, the results of the horizontal comparative analysis revealed statistically significant variations in the number of children among different age groups who tested positive for respiratory viruses (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eWith the exception of HMPV, which did not exhibit a significant seasonal distribution pattern, the infections caused by the remaining seven respiratory viruses demonstrated distinct seasonal distribution characteristics (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), although their seasonal trends varied. Flu A, Flu B, and RSV exhibited comparable seasonal distribution patterns, with peak positive rates occurring in winter and the lowest in summer; specifically, the positive rates of these three viruses were 14.49%, 4.47%, and 30.78% in winter, respectively, compared with 0.69%, 0.12%, and 3.59% in summer, respectively. The three subtypes of PIV, by contrast, displayed divergent seasonal profiles. The positive rate of PIV I was relatively high in autumn (3.09%) and lowest in winter (0.56%). PIV II and PIV III were predominantly detected in summer, with positive rates of 3.37% and 13.79%, respectively. Among these, PIV II reached its lowest detection rate in autumn (0.44%), whereas PIV III had the lowest rate in winter (0.93%). In addition, the results of the horizontal comparative analysis revealed statistically significant variations in the number of children who were positive for respiratory viruses among different seasons (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDistribution Patterns of Clinical Diagnoses Linked to Respiratory Virus Infections\u003c/h3\u003e\n\u003cp\u003eThe distribution patterns of clinical diagnoses associated with various respiratory viruses demonstrated distinct epidemiological characteristics. Among Flu A- and Flu B-positive patients, the majority were clinically diagnosed with acute upper respiratory tract infections (74.78% and 66.89%, respectively). For the remaining six respiratory viruses, non-severe pneumonia was the most common diagnosis, followed by acute bronchitis. Specifically, among the RSV-positive patients, 41.50% were diagnosed with non-severe pneumonia, and 19.93% were diagnosed with acute bronchitis. For ADV, the corresponding percentages were 31.63% and 22.20%; for HMPV, 50.85% and 25.02%; for PIV I, 34.44% and 27.82%; for PIV II, 39.75% and 29.46%; and for PIV III, 38.96% and 28.95%. Notably, RSV was associated with the highest proportion of patients with severe pneumonia among all investigated viruses, 50 patients (0.80%), followed by ADV with 22 patients (0.61%). In contrast, Flu A accounted for the lowest proportion of severe pneumonia patients, with only 6 (0.03%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eCo-infection characteristics among respiratory viruses\u003c/h3\u003e\n\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, among the eight respiratory viruses, ADV had the highest co-infection incidence. Among the 3,617 ADV-positive patients, 886 were co-infected, resulting in a co-infection rate of 24.50%. HMPV followed, with a co-infection incidence of 14.57%. In contrast, Flu A and Flu B were the lowest, at 0.83% and 3.97%, respectively. Among the 26 dual co-infection patterns identified, the \u0026ldquo;RSV\u0026thinsp;+\u0026thinsp;ADV\u0026rdquo; combination was the most frequently observed, comprising 521 patients and accounting for nearly half (45.74%) of all dual co-infections. Among the 17 triple co-infection types, \u0026ldquo;RSV\u0026thinsp;+\u0026thinsp;ADV\u0026thinsp;+\u0026thinsp;Flu B\u0026rdquo; was the most prevalent combination, with 13 patients reported, representing 29.55% of all triple co-infection patterns. Furthermore, among children with co-infections, significant differences were observed in terms of both sex and age distribution (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Among the 1183 children with co-infections, co-infections were significantly more prevalent in males than females. Regarding age distribution, preschool children represented the largest group, accounting for 31.95%, whereas infants had the lowest proportion, at 19.0%. No statistically significant difference was found with respect to the source of patients (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.585). Specifically, 605 children were inpatients, and 578 were outpatients (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of the distribution characteristics of pediatric respiratory virus co-infections by gender, age, and patient source\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal number of\u003c/p\u003e \u003cp\u003eco-infections\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNumber of\u003c/p\u003e \u003cp\u003eco-infections (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ec2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003e1183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e715 (60.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e103.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e468 (39.56)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e226\u003csup\u003ea\u003c/sup\u003e (19.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e53.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToddler\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e282\u003csup\u003eb\u003c/sup\u003e (23.84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePreschooler\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e378\u003csup\u003ec\u003c/sup\u003e (31.95)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSchool-age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e297\u003csup\u003eb\u003c/sup\u003e (25.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient source\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInpatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e605 (51.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.585\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOutpatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e578 (48.86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eSuperscript letters: Matching letters within the same column indicate no significant difference, and the different letters indicate a significant difference.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study revealed that epidemiological trends of pediatric respiratory viruses changed significantly between March 2023 and May 2025, which is the post-COVID-19 period. In Year 1 AC, high rates of Flu A, RSV, and ADV were observed, indicating an initial rebound after the pandemic. In Year 2, AC, Flu A, HMPV, and PIV II increased, whereas Flu B, ADV, and others decreased, suggesting a shift in virus circulation as social and economic activities returned to normal. Notably, outbreaks of HMPV and PIV II were delayed until Year 2 AC, indicating that some viruses took longer to return to their normal epidemic patterns post-COVID-19. These changes may be linked to altered virus transmission after the easing of NPIs, such as mask-wearing, social distancing, and school closures. This aligns with previous reports that some viruses rebounded, whereas others declined [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. These observations suggest that in the post-pandemic era, respiratory virus dynamics may be influenced by changes in population immunity, such as immune deficits from reduced viral exposure. Ongoing surveillance of viral trends is therefore essential for improving prevention and management strategies for pediatric respiratory diseases.\u003c/p\u003e \u003cp\u003eResults from this study revealed that the positive detection rate of RSV for pediatric respiratory infections was 17.76%, which is consistent with previous findings. RSV is a major respiratory pathogen in children globally (e.g., up to 22.7% detection rate) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The prevalence of PIV II is low (1.38%), indicating that it is rare in children. Differences in virus detection rates may reflect seasonal patterns or age-related factors [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. We also found that compared with female children, male children had higher positive rates for Flu A/B, RSV, and PIV III. This finding is supported by previous studies [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. \u003cem\u003eChu et al.\u003c/em\u003e reported that virus detection in male children was 39.29%, which was higher than that in females (34.67%), and that positivity decreased with age. \u003cem\u003eAbdel et al.\u003c/em\u003e also reported that more males were affected by viral acute gastroenteritis (male-to-female ratio of 1:0.8). These findings suggest that male children may be more susceptible to or more often exposed to certain respiratory viruses. Furthermore, we found that respiratory viruses vary significantly in their age-specific and seasonal patterns, indicating that infections depend on both age and season. RSV and PIV III are most common in infants (\u0026lt;\u0026thinsp;1 year), likely due to underdeveloped immunity. This finding supports earlier studies showing that infants and young children are more susceptible to RSV [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Flu B and ADV peak in school-aged children (6\u0026thinsp;~\u0026thinsp;18 years), possibly because of increased social contact. Flu A, HMPV, PIV I, and PIV II are most prevalent among preschoolers (3\u0026thinsp;~\u0026thinsp;6 years), whereas RSV is least common among school-age children. These trends suggest that virus spread is influenced by exposure and immune development [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. With the exception of HMPV, most respiratory viruses show clear seasonal patterns, suggesting that traditional seasonal trends have returned after the COVID-19 pandemic. Flu A and B, along with RSV, returned to their usual winter peaks, with much lower activity in summer. This matches the typical winter-dominant pattern seen in temperate regions and supports the idea that viruses regained their pre-pandemic seasonality as NPIs were lifted [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. PIV I peaked in autumn and was lowest in winter, whereas PIV II/III peaked in summer and declined in winter. These patterns align with previous reports of seasonal transmission [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. HMPV showed no clear seasonal trend, which may be due to a slow recovery from pandemic disruptions or a short observation period. These findings indicate that clinical practice should focus on integrated detection and surveillance of multiple pathogens. Ongoing monitoring is also needed for seasonal changes and shifts in the age groups affected.\u003c/p\u003e \u003cp\u003eThis study demonstrated distinct clinical and diagnostic differences among respiratory viruses. Flu A and Flu B infections mainly present as acute upper respiratory tract infections, indicating that influenza viruses typically cause localized symptoms. In contrast, other respiratory viruses are more commonly linked to lower respiratory tract involvement. Among them, non-severe pneumonia is most frequent, especially for RSV and HMPV, followed by acute bronchitis. These findings align with those of previous studies showing that RSV is the leading cause of pediatric pneumonia and that the majority of lower respiratory tract infections are viral in origin [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. RSV has the highest rate of severe pneumonia (0.80%), approximately 26 times higher than that of Flu A (0.03%). These findings support existing evidence that compared with influenza, RSV causes more severe illness in children, likely due to its ability to damage airway mucosa and trigger strong inflammation [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. PIV I\u0026ndash;III and ADV also resulted in high severe pneumonia rates (0.61%), significantly above those of influenza, indicating strong lower respiratory tract involvement. In contrast, Flu A and Flu B were associated with very low severe pneumonia rates (0.03\u0026ndash;0.06%), which is consistent with their tendency to affect the upper respiratory tract. However, influenza can still cause severe illness in vulnerable groups such as infants, young children, and immunocompromised individuals. Therefore, the observed low rate of severe cases may be due to the predominance of mild, outpatient cases included in the study [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These findings support early identification of high-risk viral pathogens and emphasize the need to improve surveillance and early warning systems for severe respiratory infections.\u003c/p\u003e \u003cp\u003eThe results of our study also revealed that ADV had the highest co-infection rate (24.50%), followed by hMPV (14.57%). Previous studies reported that up to 57.1% of ADV-infected children had other viral infections, and the hMPV co-infection rate during the pandemic was 30.10% [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. These higher rates may reflect differences in geography and timing. Flu A and B had the lowest co-infection rates (0.83% and 3.97%, respectively), likely due to their seasonal patterns or greater sensitivity to NPIs [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The most common co-infection was \u0026ldquo;RSV\u0026thinsp;+\u0026thinsp;ADV\u0026rdquo;, which was detected in 45.74% of the patients. Studies have shown that co-infection with RSV and bacteria can greatly worsen disease severity, and similarly, ADV co-infection with other pathogens significantly increases the risk of severe illness, such as an 81% increase in pneumonia cases [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The interaction between RSV and ADV may lead to worse clinical outcomes, suggesting the need to further study how these viruses interact. The \u0026ldquo;RSV\u0026thinsp;+\u0026thinsp;ADV\u0026thinsp;+\u0026thinsp;Flu B\u0026rdquo; combination accounted for 29.55% (n\u0026thinsp;=\u0026thinsp;13) of triple infections. Triple-virus infections reflect complex dynamics, possibly shaped by seasonal or immune factors [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The common occurrence of \u0026ldquo;RSV\u0026thinsp;+\u0026thinsp;ADV\u0026thinsp;+\u0026thinsp;Flu B\u0026rdquo; likely results from the high prevalence of these viruses in children. More male children had co-infections than females, possibly due to immune differences. However, the exact cause is unknown. Preschoolers were most affected, likely due to underdeveloped immunity and more contact with others [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Infants had the lowest rate, possibly due to maternal antibodies [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. No difference was observed between hospitalization and outpatient rates. However, previous studies have demonstrated that viral co-infection can precipitate severe lower respiratory tract symptoms, thereby increasing the risk of hospitalization and prolonging the duration of hospital stay [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Using clinical indicators such as oxygen saturation and respiratory rate may help identify high-risk outpatient patients, improving monitoring and care.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, as a single-center retrospective study, it is prone to selection bias and may lack standardized data, which could affect the reliability and generalizability of the findings. Therefore, future multicenter prospective studies are needed to validate these results. Second, the specimen type utilized in this study was a pharyngeal swab. The quality of sampling directly influences the accuracy of the test results, and suboptimal sampling procedures may lead to false-negative outcomes. Third, influenza A and B antigens were detected using the colloidal gold method, which has limited sensitivity and specificity. As a result, false-positive or false-negative results may occur, potentially affecting the accuracy of the findings. Finally, antigen testing for influenza A/B and nucleic acid testing for six respiratory viruses were performed separately, possibly with a time interval between tests. This could introduce bias in identifying co-infections.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn the post-COVID-19 era, Flu A and B, RSV, ADV, and PIV I\u0026ndash;III peaked in Year 1 AC, whereas HMPV and PIV II became prevalent only in Year 2 AC. All eight viruses showed age-related differences in detection rates, and only HMPV lacked a clear seasonal pattern. Flu A and B were mainly linked to upper respiratory infections, whereas the other six were more common in non-severe pneumonia and acute bronchitis. ADV and HMPV were most often involved in co-infections, especially with RSV, and Flu A and B were rarely involved in co-infections. The \u0026ldquo;RSV\u0026thinsp;+\u0026thinsp;ADV\u0026rdquo; combination represented the most prevalent dual co-infection pattern, whereas \u0026ldquo;RSV\u0026thinsp;+\u0026thinsp;ADV\u0026thinsp;+\u0026thinsp;Flu B\u0026rdquo; was the most common triple co-infection. These findings may provide valuable evidence for the development of targeted prevention and control strategies aimed at addressing the overlapping circulation of pediatric respiratory viruses in the post-COVID-19 era.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Springer Nature\u0026nbsp;Author Services (www.secure.authorservices.springernature.com) for the linguistic assistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Medical Ethics Committee of the Affiliated Children\u0026apos;s Hospital of Xi\u0026rsquo;an Jiaotong University (Ethics [Research] No. 2025-055-03) and followed the ethical principles of the 1964 Declaration of Helsinki and its later amendments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants\u0026rsquo; personal information was maintained with strict confidentiality. As this study is retrospective and conducted in accordance with relevant Chinese ethical guidelines (Measures for the Ethical Review of Biomedical Research Involving Human Subjects), the requirement for informed consent was formally waived by the the Medical Ethics Committee of the Affiliated Children\u0026apos;s Hospital of Xi\u0026rsquo;an Jiaotong University following review.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding: Z.G.W.; Conceptualization: J.Y.T. and Z.G.W.; Methodology: J.Y.T. and Y.W.; Data collection and curation: W.N.Y., C.C.C. and R.W.; Data analysis: Y.W., W.N.Y., P.W.N., J.F.S. and J.H.L.; Writing: J.Y.T. and Y.W.; Revision: J.Y.T. and Z.G.W. All authors have reviewed the earlier versions of the manuscript, provided critical feedback, and formally approved the final version for submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by General Program of National Natural Science Foundation of China [grant number: 82172312] and Shaanxi Provincial Key Research and Development\u0026nbsp;Program [grant number: 2021SF-003].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that, during the execution of this study, no commercial relationships or financial interests existed that could be interpreted as potential conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial numb\u003c/strong\u003e\u003cstrong\u003eer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to the patients\u0026apos; privacy rights and the legal protections governing biological sample information under Chinese law but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDoroshenko A, Lee N, MacDonald C, Zelyas N, Asadi L, Kanji JN (eds) (2021) Decline of influenza and respiratory viruses with COVID-19 public health measures: Alberta, Canada. Mayo clinic proceedings; : Elsevier\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen APL, Chu IYH, Yeh ML et al (2021) Differentiating impacts of non-pharmaceutical interventions on non‐coronavirus disease‐2019 respiratory viral infections: Hospital‐based retrospective observational study in Taiwan. Influenza Other Respir Viruses 15(4):478\u0026ndash;487\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbu-Raya B, Paramo MV, Reicherz F, Lavoie PM (2023) Why has the epidemiology of RSV changed during the COVID-19 pandemic? EClinicalMedicine. ;61\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMai W, Ren Y, Tian X et al (2023) Comparison of common human respiratory pathogens among hospitalized children aged\u0026thinsp;\u0026le;\u0026thinsp;6 years in Hainan Island, China, during spring and early summer in 2019\u0026ndash;2021. J Med Virol 95(4):e28692\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao C, Zhang T, Guo L et al (2025) Characterising the asynchronous resurgence of common respiratory viruses following the COVID-19 pandemic. Nat Commun 16(1):1610\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYe Q, Wang D (2022) Epidemiological changes of common respiratory viruses in children during the COVID-19 pandemic. J Med Virol 94(5):1990\u0026ndash;1997\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRodgers L, Sheppard M, Smith A et al (2021) Changes in seasonal respiratory illnesses in the United States during the coronavirus disease 2019 (COVID-19) pandemic. Clin Infect Dis 73(Supplement1):S110\u0026ndash;S7\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShang X, Zhang R, Zheng J et al (2025) Global meta-analysis of short-term associations between ambient temperature and pathogen-specific respiratory infections, 2004 to 2023. Eurosurveillance 30(11):2400375\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWinthrop ZA, Perez JM, Staffa SJ, McManus ML, Duvall MG (2024) Pediatric respiratory syncytial virus hospitalizations and respiratory support after the COVID-19 pandemic. JAMA Netw Open 7(6):e2416852\u0026ndash;e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu P, Xu M, Lu L et al (2022) The changing pattern of common respiratory and enteric viruses among outpatient children in Shanghai, China: two years of the COVID-19 pandemic. J Med Virol 94(10):4696\u0026ndash;4703\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhong-Jie L, Lin-Jie Y, Hai-Yang Z et al (2021) Broad impacts of COVID-19 pandemic on acute respiratory infections in China: an observational study. Clin Infect Dis\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Y, Liang Y, Tang J et al (2023) Clinical impact of human parainfluenza virus infections before and during the COVID-19 pandemic in Southern China. Microbes Infect 25(8):105219\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArmero G, Guitart C, Soler-Garcia A et al (2024) Non-pharmacological interventions during SARS-CoV-2 pandemic: effects on Pediatric viral respiratory infections. Arch Bronconeumol 60(10):612\u0026ndash;618\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoseph NT, Kuller JA, Louis JM, Hughes BL Society for Maternal-Fetal Medicine Statement: Clinical considerations for the prevention of respiratory syncytial virus disease in infants. Am J Obstet Gynecol, 230(2), B41\u0026ndash;B49\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLin S-C, Wang H-C, Lin W-C et al (2023) Viral pneumonia during the COVID-19 pandemic, 2019\u0026ndash;2021 evoking needs for SARS-CoV-2 and additional vaccinations. Vaccines 11(5):905\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChu FL, Li C, Chen L, Dong B, Qiu Y, Liu Y (2022) Respiratory viruses among pediatric inpatients with acute lower respiratory tract infections in Jinan, China, 2016\u0026ndash;2019. J Med Virol 94(9):4319\u0026ndash;4328\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbdel-Rahman ME, Mathew S, Al Thani AA, Ansari KA, Yassine HM (2021) Clinical manifestations associated with acute viral gastroenteritis pathogens among pediatric patients in Qatar. J Med Virol 93(8):4794\u0026ndash;4804\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZarur-Torralvo S, Stand‐Ni\u0026ntilde;o I, Fl\u0026oacute;rez‐Garc\u0026iacute;a V, Mendoza H, Viana‐C\u0026aacute;rdenas E (2023) Viruses responsible for acute respiratory infections before (2016\u0026ndash;2019) and during (2021) circulation of the SARS‐CoV‐2 virus in pediatric patients in a reference center at Barranquilla Colombia: A pattern analysis. J Med Virol 95(1):e28439\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWei M, Li S, Lu X, Hu K, Li Z, Li M (2024) Changing respiratory pathogens infection patterns after COVID-19 pandemic in Shanghai, China. J Med Virol 96(4):e29616\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRobertson M, Eden J-S, Levy A et al (2021) The spatial-temporal dynamics of respiratory syncytial virus infections across the east\u0026ndash;west coasts of Australia during 2016\u0026ndash;17. Virus Evol 7(2):veab068\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCai W, K\u0026ouml;ndgen S, Tolksdorf K et al (2024) Atypical age distribution and high disease severity in children with RSV infections during two irregular epidemic seasons throughout the COVID-19 pandemic, Germany, 2021 to 2023. Eurosurveillance 29(13):2300465\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu B, Wang J, Li Z, Xu C, Yang W (2021) Seasonal association between viral causes of hospitalised acute lower respiratory infections and meteorological factors in China: a retrospective study. Lancet Planet Health 5(3):e154\u0026ndash;e63\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWindsor WJ, Lamb MM, Dominguez SR, Mistry RD, Rao S (2022) Clinical characteristics and illness course based on pathogen among children with respiratory illness presenting to an emergency department. J Med Virol 94(12):6103\u0026ndash;6110\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoracas C, Poeta M, Grieco F et al (2025) Bacterial-like inflammatory response in children with adenovirus leads to inappropriate antibiotic use: a multicenter cohort study. Infection 53(3):935\u0026ndash;946\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDu Y, Li W, Guo Y et al (2022) Epidemiology and genetic characterization of human metapneumovirus in pediatric patients from Hangzhou China. J Med Virol 94(11):5401\u0026ndash;5408\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChiu SS, Cowling BJ, Peiris JM, Chan EL, Wong WH, Lee KP (2022) Effects of nonpharmaceutical COVID-19 interventions on pediatric hospitalizations for other respiratory virus infections, Hong Kong. Emerg Infect Dis 28(1):62\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Y-N, Zhang Y-F, Xu Q et al (2023) Infection and co-infection patterns of community-acquired pneumonia in patients of different ages in China from 2009 to 2020: a national surveillance study. Lancet Microbe 4(5):e330\u0026ndash;e9\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNiu D, Gao Y, Zhang Y et al (2025) Systematic Review and Meta-Analysis of the Association Between Clinical Severity and Co‐Infection of Human Adenovirus With Other Respiratory Pathogens in Children. J Med Virol 97(5):e70370\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRacine T, Piret J, Gilca R, Amini R, Boivin G (2025) Viral Interference and Coinfections: A Perspective From Hospital Surveillance of Respiratory Viruses. J Med Virol. ;97(5)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrumbein H, K\u0026uuml;mmel LS, Fragkou PC et al (2023) Respiratory viral co-infections in patients with COVID‐19 and associated outcomes: A systematic review and meta‐analysis. Rev Med Virol 33(1):e2365\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnderson LJ, Jadhao SJ, Hussaini L et al (2024) Development and comparison of immunologic assays to detect primary RSV infections in infants. Front Immunol 14:1332772\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-clinical-microbiology-and-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejcm","sideBox":"Learn more about [European Journal of Clinical Microbiology \u0026 Infectious Diseases](https://www.springer.com/journal/10096)","snPcode":"10096","submissionUrl":"https://submission.nature.com/new-submission/10096/3","title":"European Journal of Clinical Microbiology \u0026 Infectious Diseases","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"respiratory virus, epidemiological, children, post-COVID-19, China","lastPublishedDoi":"10.21203/rs.3.rs-8546358/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8546358/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo explore the epidemiology of common pediatric respiratory viruses among children in the post\u0026ndash;COVID-19 era.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eRetrospective analysis of children with respiratory symptoms who visited our hospital between March 2023 and May 2025 was conducted. Influenza A/B (Flu A/B) antigen testing was performed for 151,809 children; nucleic acid testing for respiratory syncytial virus ༈RSV༉, adenovirus ༈ADV༉, human metapneumovirus (HMPV), and parainfluenza viruses (PIV) I\u0026ndash;III was performed for 35,326 children. Demographic and laboratory data were analyzed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAcross two post-pandemic seasons, most viruses resurged; HMPV and PIV II peaked more prominently in season 2. RSV showed the highest positivity, whereas Flu A had the most positive cases. RSV and PIV III predominated in infants; Flu A, HMPV, and PIV I/II predominated in preschoolers; and Flu B and ADV predominated in school-aged children. Flu A, Flu B, and the RSV shared a winter peak and summer trough, whereas the PIV subtypes displayed distinct seasonality. Clinically, Flu A/B was associated mainly with acute upper respiratory infections; non-severe pneumonia was associated predominantly with RSV, ADV, HMPV, and PIVs. Coinfections were most frequent with ADV and HMPV and least frequent with Flu A and Flu B; the most common dual and triple coinfections were \u0026ldquo;RSV\u0026thinsp;+\u0026thinsp;ADV\u0026rdquo; and \u0026ldquo;RSV\u0026thinsp;+\u0026thinsp;ADV\u0026thinsp;+\u0026thinsp;Flu B\u0026rdquo;.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn the post-COVID-19 era, the age distribution, seasonality, and coinfection patterns of pediatric respiratory viruses shifted. Viruses with high detection and coinfection propensities warrant strengthened surveillance and tailored control strategies.\u003c/p\u003e","manuscriptTitle":"Common respiratory virus spectrum and epidemiological trends among children in Northwest China during the post-COVID-19 era","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-20 09:21:52","doi":"10.21203/rs.3.rs-8546358/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-01T07:47:14+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-30T09:05:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"255221158935953063453443029486837545341","date":"2026-01-21T02:28:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"23897727868560594665319766179720665678","date":"2026-01-19T06:44:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"70265834990503879405346900423474273854","date":"2026-01-18T06:04:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-15T05:10:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-09T01:04:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-09T01:04:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Clinical Microbiology \u0026 Infectious Diseases","date":"2026-01-08T02:56:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-clinical-microbiology-and-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejcm","sideBox":"Learn more about [European Journal of Clinical Microbiology \u0026 Infectious Diseases](https://www.springer.com/journal/10096)","snPcode":"10096","submissionUrl":"https://submission.nature.com/new-submission/10096/3","title":"European Journal of Clinical Microbiology \u0026 Infectious Diseases","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"dd6311d4-2c59-47c9-a535-8b517ccdd70d","owner":[],"postedDate":"January 20th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-23T16:04:55+00:00","versionOfRecord":{"articleIdentity":"rs-8546358","link":"https://doi.org/10.1007/s10096-026-05437-0","journal":{"identity":"european-journal-of-clinical-microbiology-and-infectious-diseases","isVorOnly":false,"title":"European Journal of Clinical Microbiology \u0026 Infectious Diseases"},"publishedOn":"2026-02-16 15:58:20","publishedOnDateReadable":"February 16th, 2026"},"versionCreatedAt":"2026-01-20 09:21:52","video":"","vorDoi":"10.1007/s10096-026-05437-0","vorDoiUrl":"https://doi.org/10.1007/s10096-026-05437-0","workflowStages":[]},"version":"v1","identity":"rs-8546358","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8546358","identity":"rs-8546358","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}