Shifting Patterns of Pediatric Respiratory Viruses During the SARS-CoV-2 Pandemic: A Retrospective Observational Study

Shifting Patterns of Pediatric Respiratory Viruses During the SARS-CoV-2 Pandemic: A Retrospective Observational Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Shifting Patterns of Pediatric Respiratory Viruses During the SARS-CoV-2 Pandemic: A Retrospective Observational Study Mehmet Tekinsoy, Harun Agca This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6464014/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Jan, 2026 Read the published version in BMC Infectious Diseases → Version 1 posted 13 You are reading this latest preprint version Abstract Background: Respiratory tract infections are a leading cause of hospitalization in children and remain a significant contributor to pediatric morbidity. Understanding the epidemiology of viral pathogens—including their seasonal trends and response to global events like pandemics—is essential for public health planning, surveillance strategies, and timely clinical interventions. Methods: This retrospective study evaluated the epidemiology of respiratory viruses in pediatric patients before and during the SARS-CoV-2 pandemic. Nasopharyngeal swab samples from 1,269 children presenting with respiratory symptoms between October 2018 and September 2021 were tested using multiplex PCR targeting RV/EV, RSV A/B, seasonal coronaviruses, influenza, parainfluenza, hMPV, and other viruses. Results: 889 viruses were detected; 579 were single-virus infections, and 143 involved co-infections. RV/EV was the most frequently detected virus in all age groups. RSV was predominant in children under one year, while influenza was more common in older children. The highest testing volume and positivity rates occurred in January. The overall number of tests and positive detections decreased during the pandemic period. RSV, influenza, parainfluenza, and seasonal coronaviruses showed marked declines, whereas RV/EV frequency increased. Conclusions: The circulation of pediatric respiratory viruses shifted significantly during the pandemic. Multiplex PCR-based diagnostics proved valuable for tracking these changes, enabling rapid diagnosis and real-time epidemiological insight. These findings underscore the importance of molecular surveillance in managing pediatric respiratory infections, particularly during global health events. Pediatric respiratory viruses SARS-CoV-2 pandemic multiplex PCR viral epidemiology seasonal variation Figures Figure 1 Introduction Respiratory tract infections are the most common acute infectious diseases worldwide and cause significant mortality and morbidity, particularly in childhood. 1 It is considered normal for a child under the age of five to experience approximately four to five episodes of acute respiratory infections per year. 2 Among children under the age of five, the incidence of respiratory tract infections can reach up to 50%, and these infections are a significant cause of hospitalizations. 3 This higher frequency in this age group is because the respiratory system is still anatomically developing and the immune system has not yet reached its full functionality as seen in adults. 4 The widespread distribution of respiratory infection agents across large geographical areas creates a significant economic burden due to loss of workforce, care needs, and treatment costs. Viruses are the most common causative agents of respiratory tract infections in children. Although their relative frequency changed due to the precautions taken during the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic, the most common viruses are rhinoviruses (RV), respiratory syncytial viruses A and B (RSV A/B), influenza A and B viruses (IAV, IBV), seasonal human coronaviruses 229E, NL63, OC43, HKU1 (hCoV 229E, NL63, OC43, HKU1) and SARS-CoV-2, parainfluenza viruses types 1, 2, 3, and 4 (PIVs 1/2/3/4), adenoviruses (AdV), human metapneumovirus (hMPV) and bocavirus (hBoV). 5 , 6 The SARS-CoV-2 pandemic has provided a unique context for studying viral transmission dynamics. Non-pharmaceutical interventions such as mask-wearing, social distancing, hand hygiene, and lockdowns significantly impacted respiratory virus epidemiology. Notably, these interventions have effectively reduced most respiratory viral infections, yet their effect on RV/EV appears limited, indicating different transmission mechanisms or resistance to preventive measures. 7 In this study, the frequency of respiratory tract infection viruses in the pediatric age group was retrospectively examined before and during the SARS-CoV-2 pandemic, and the epidemiological impact of the precautions taken during the pandemic period was evaluated. Materials and Methods This retrospective study evaluated data from patients aged 18 years and under who presented to the Department of Pediatrics at Bursa Uludag University Medical Research and Training Center between 1 October 2018 and 30 September 2021, with symptoms indicative of respiratory tract infection—such as sore throat, nasal discharge, nasal congestion, and sneezing—and from whom nasopharyngeal swab samples were obtained. The study assessed age, sex, date of sample collection, the clinical department where the sample was taken, and the presence of respiratory viruses identified via multiplex PCR from nasopharyngeal swab samples. The respiratory viruses investigated included adenoviruses, human bocavirus, seasonal human coronaviruses (subtypes hCoV 229E, HKU1, NL63, OC43), influenza viruses (A, subtype A/H1, subtype A/H1N1, B), parainfluenza viruses (types 1, 2, 3, 4), respiratory syncytial virus (RSV A/B), rhino/enteroviruses (RV/EV), human metapneumovirus (hMPV) and human bocavirus (hBoV). For the detection of respiratory viruses, the "Fast-track Diagnostics Respiratory Pathogens 33" multiplex PCR kit (FTD, Malta) was used between October 2018 and December 2019, and the "QIAStat-Dx Respiratory Panel" multiplex PCR kit (Qiagen, Germany) was employed from January 2020 to October 2021. All study data were obtained from the hospital information management system. To enable comparative analysis, the study period was divided into two distinct phases: pre-pandemic (October 2018 to February 2020) and during the pandemic (March 2020 to September 2020), with the latter defined by the first confirmed case of SARS-CoV-2 in Türkiye, reported in March 2020. Statistical Analysis The normality of data distribution was assessed using the Shapiro–Wilk test. Descriptive statistics were presented as mean ± standard deviation, median, and range (minimum-maximum) for continuous variables and as frequency and percentage for categorical variables. Pearson’s Chi-square test, Fisher’s Exact Chi-square test, and the Fisher–Freeman–Halton test were used to analyze categorical data, as appropriate. A p-value of < 0.05 was considered statistically significant. All statistical analyses were performed using IBM SPSS Statistics for Windows, Version 23.0 (IBM Corp., Armonk, NY, USA). Results Demographic Characteristics Our study examined 1269 nasopharyngeal swab samples collected from patients hospitalized in the Department of Pediatrics at Bursa Uludag University Medical Research and Training Center. The distribution of samples evaluated by month is presented in Fig. 1A. Among patients aged 0 to 18 years, 533 (42.0%) were female and 736 (58.0%) were male (Fig. 1B). The mean age was 4.97 ± 4.85 years for females and 4.54 ± 4.81 years for males. The median age was 3.00 years for both genders. Age groups were distributed as follows: 450 patients (35.5%) aged 0–1 year, 335 patients (26.4%) aged 2–4 years, 260 patients (20.5%) aged 5–9 years, and 224 patients (17.7%) aged 10 years or older. Age-frequency distributions are shown in Fig. 1C. Before the pandemic (November 2018 to February 2020), 747 samples (58.9%), and during the pandemic (March 2020 to October 2021), 522 samples (41.1%) were evaluated. Epidemiological Overview of Circulating Viruses A total of 889 distinct viral agents were identified in 1,269 nasopharyngeal swabs. Of these samples, 45.6% tested positive for a single virus, 9.6% tested positive for two, 1.4% tested positive for three, and 0.2% tested positive for four. The most prevalent viruses identified were rhinovirus/enterovirus (RV/EV) in 324 patients (25.5%), followed by RSV A/B in 117 (9.2%), hCoVs NL63, 229E, OC43, HKU1 in 104 (8.2%), IAV in 84 (6.6%), PIVs 1–4 in 83 (6.5%) and AdV in 67 (5.3%). The detection rates and numbers of viral agents are demonstrated in Table 1 . Specifically, the following rates of hCoVs were identified: OC43 in 58 samples (4.6%), 229E in 25 samples (2.0%), HKU1 in 9 samples (0.7%), and NL63 in 12 samples (0.9%) (Fig. 1D). For parainfluenza viruses, the following were detected: PIV-1 in 15 samples (1.2%), PIV-2 in 5 (0.4%), PIV-3 in 46 (3.6%), and PIV-4 in 17 (1.3%) (Fig. 1D). Coinfection was observed in 143 patients, with RV/EV (82), hCoV (51), RSV A/B (45), AdV (39), PIVs (26), hBoV (24), IAV (22), hMPV (13), and IBV (8) as coinfection agents. Table 1 Detection rates and numbers of viral agents AdV hBoV hCoVs IAV IBV PIVs RSV A/B RV/EV hMPV n 67 37 104 84 41 83 117 324 32 % 5,3 2,9 8,2 6,6 3,2 6,5 9,2 25,5 2,5 A subsequent analysis of the distribution of infectious agents according to age groups revealed that the most prevalent viral agent detected in each age group was RV/EV. AdV, hBoV, IBV, PIVs, RSV, and RV/EV detection rates differed significantly between age groups (Table 2 ). Significant differences in the frequency and distribution of pathogens by year were found for each virus (Table 3 ) (p < 0.05). Figure 1E presents the monthly detection rates of the most common viral agents—RV/EV, RSV A/B, IAV, IBV, and hCoVs. The seasonal analysis revealed significant variation in detection rates for all viruses except AdV and hBoV (Table 4 ). Table 2 Viral agents by age group AdV hBoV hCoVs IAV IBV PIVs RSV A/B RV/EV hMPV 0–1 year n 21 6 45 20 5 36 64 115 13 % 4.7 1.3 10.0 4.4 1.1 8.0 14.2 25.6 2.9 2–4 years n 27 20 25 26 7 26 27 108 9 % 8.1 6 7.5 7.8 2.1 7.8 8.1 32.2 2.7 5–9 years n 16 5 20 23 20 14 20 65 6 % 6.2 1.9 7.7 8.8 7.7 5.4 7.7 25 2.3 10–18 years n 3 6 14 15 9 7 6 36 4 % 1.3 2.7 6.3 6.7 4.0 3.1 2.7 16.1 1.8 Total n 67 37 104 84 41 83 117 324 32 % 5.3 2.9 8.2 6.6 3.2 6.5 9.2 25.5 2.5 p 0.005 0.001 0.334 0.101 < 0.001 0.065 < 0.001 < 0.001 0.843 Table 3 Frequency and distribution of viruses by year AdV hBoV hCoVs IAV IBV PIVs RSV A/B RV/EV hMPV 2018 n 11 5 17 1 0 10 24 32 2 % 11.5 5.2 17.7 1.0 0 10.4 25.0 33.3 2.1 2019 n 38 17 52 28 9 32 48 114 19 % 8.8 3.9 12.0 6.5 2.1 7.4 11.1 26.4 4.4 2020 n 6 6 17 55 32 14 35 75 11 % 1.4 1.4 4.0 13.0 7.5 3.3 8.3 17.7 2.6 2021 n 12 9 18 0 0 27 10 103 0 % 3.8 2.8 5.7 0 0 8.5 3.2 32.5 0 p < 0.001 0.08 < 0.001 < 0.001 < 0.001 0.007 < 0.001 < 0.001 0.002 Table 4 Seasonal variation in detected viruses AdV hBoV hCoVs IAV IBV PIV RSV A/B RV/EV hMPV Autumn n 13 12 5 4 0 23 21 98 3 % 4.5 4.1 1.7 1.4 0.0 7.9 7.2 33.8 1.0 Winter n 21 9 47 77 26 16 74 72 17 % 4.8 2.1 10.7 17.6 5.9 3.7 16.9 16.4 3.9 Spring n 22 10 41 3 13 18 22 80 9 % 7.8 3.5 14.5 1.1 4.6 6.4 7.8 28.4 3.2 Summer n 11 6 11 0 2 26 0 74 3 % 4.2 2.3 4.2 0.0 0.8 10.0 0.0 28.6 1.2 p 0.194 0.334 < 0.001 < 0.001 < 0.001 0.007 < 0.001 < 0.001 0.039 To assess the impact of non-pharmaceutical interventions during the SARS-CoV-2 pandemic period, November 2018 to February 2020 was grouped as “before the pandemic”, and March 2020 to October 2021 was grouped as “during the pandemic”. A comparative analysis of the prevalence of various viral agents revealed significant differences in frequencies before and during the pandemic (p < 0.05). The incidence of AdV, hCoVs, IAV, IBV, PIVs, RSV A/B, and hMPV before the pandemic was significantly higher than during the pandemic (p < 0.05). When RV/EV was analyzed, 171 (22.9%) patients were positive before the pandemic, while 153 (29.3%) patients were positive during the pandemic. The observed shift in the incidence of RV/EV was found to be statistically significant (Table 5 ) (p = 0.01). Table 5 Comparison of the frequency and distribution of viruses across periods AdV hBoV hCoVs IAV IBV PIVs RSV A/B RV/EV hMPV Before the pandemic n 53 27 78 82 35 53 101 171 29 % 7.1 3.6 10.4 11.0 4.7 7.1 13.5 22.9 3.9 During the pandemic n 14 10 26 2 6 30 16 153 3 % 2.7 1.9 5.0 0.4 1.1 5.7 3.1 29.3 0.6 p 0.001 0.11 < 0.001 < 0.001 0.001 0.339 < 0.001 0.01 < 0.001 Discussion Acute respiratory tract infections are among the leading causes of morbidity and mortality in childhood. Lower respiratory infections after preterm birth are the second leading cause of death in children under five. 8 Viruses are the primary cause of acute respiratory infections in children. 9 Therefore, the accurate and rapid detection of viral respiratory infections is critical. A comprehensive review conducted during the SARS-CoV-2 pandemic era found that the most commonly detected viral pathogens in childhood respiratory infections were RV/EV and RSV, with detection rates of 29.1% and 11.3%, respectively. 10 Consistent with these findings, our study also identified RV/EV as the most commonly detected virus, present in 324 samples (25.5%), followed by RSV A/B in 117 samples (9.2%). The highest monthly number of samples was recorded in January 2020. This surge may be attributed to several factors: an increase in test requests driven by public concern following the emergence of SARS-CoV-2 in late 2019, the implementation of a new laboratory testing system that enabled faster turnaround times, and the limited availability of SARS-CoV-2 testing at the national level, which led clinicians to adopt exclusion-based diagnostic algorithms for suspected SARS-CoV-2 infection cases. During the early stages of the pandemic (April–May 2020), the number of samples decreased, probably due to concerns about transmission risk during sampling and safety concerns in the laboratory. Our study also included the coronavirus subtypes OC43, 229E, HKU1, and NL63. In a U.S.-based review published in 2024 by Wilson et al., OC43 was the most commonly detected coronavirus, followed by NL63. 11 In our study, OC43 was likewise the most prevalent seasonal coronavirus; however, the second most pervasive was 229E. This discrepancy may be attributed to the male predominance in our study population or minor local variations in the epidemiology of seasonal coronaviruses. 12 RSV is more frequently seen in infancy than in other age groups. Mazur et al. 13 conducted a review demonstrating that RSV predominantly affects infants and is associated with high morbidity and mortality rates, particularly in low- and middle-income countries. According to a study by Cacho et al. 14 , 53.4% of children are infected with RSV in their first year of life. In our research, RSV was likewise most frequently observed in the 0–1 year age group. Since 2023, several vaccines have been approved by the Food and Drug Administration and the European Medical Agency to prevent RSV infections in older adults and infants. To protect infants from RSV, appropriate maternal vaccination during late pregnancy is recommended. 15 The seasonal relationship of influenza types shows that these viruses are more common in winter. According to a review by Tamerius et al. 16 , possible explanations include cold and dry air impairing mucociliary function, reduced sunlight exposure, lowering vitamin D levels and weakening the immune system, and people spending more time indoors in close contact. In our study, influenza viruses were generally detected in winter as well. RSV, similar to influenza, peaks during the winter months. According to Hamid et al. 17 , in the years preceding the pandemic (2017–2019), the RSV season typically began in October, peaked in December, and ended by April. Consistent with these findings, our study also found that RSV was most frequently detected during the winter months and primarily in children aged 0–1 year. Coronaviruses also peak in winter, similar to influenza and RSV. Varghese et al. 18 observed that the incidence of coronaviruses such as OC43, 229E, HKU1, and NL63 began increasing in late autumn and peaked in January–February. Our findings align with this pattern. Rhinoviruses can be detected year-round but peak in the autumn. Gao et al. 19 reported the highest detection rates of RV/EV in autumn. Neugebauer et al. 20 also found peaks in September/October and April. Consistent with these studies, our findings show that RV/EV was present throughout the year but significantly more frequent in autumn. Significant shifts in the prevalence and seasonal peaks of respiratory infections were observed during the pandemic, likely attributable to widespread mask use, enhanced hygiene practices, and the implementation of lockdown measures. Several studies 21 – 24 reported significantly higher detection rates for AdV, hCoV, IAV, IBV, PIVs, RSV A/B, and MPV before the pandemic. Del Ricco et al. 25 observed a sharp decline in almost all respiratory viruses during the pandemic, while RV/EV detection remained stable or even increased. Takashita et al. 26 found significantly lower influenza, MPV, RSV, and parainfluenza detection during the pandemic. They noted no enveloped viruses were detected after May 2020, while non-enveloped viruses like RV/EV and AdV continued to be found. They attributed this to the more significant environmental stability of non-enveloped viruses. They also reported an increased detection rate of RV/EV among children under 10. Leung et al. 27 found that surgical masks effectively reduced transmission of influenza and coronaviruses, but not RV/EV. In our study, consistent with these findings, detection rates of AdV, hCoV, IAV, IBV, PIVs, RSVA/B, and hMPV declined during the pandemic, while RV/EV detection rate increased. Possible explanations include poor mask efficacy against RV/EV, high incidence in children, low mask compliance in children, resistance to environmental conditions as a non-enveloped virus, and frequent reinfections due to numerous serotypes. Conclusion The frequency and distribution of respiratory viral pathogens in pediatric populations exhibit considerable variability depending on seasonal fluctuations, interannual trends, and the occurrence of pandemics. Non-pharmaceutical interventions implemented during the SARS-CoV-2 pandemic—including the use of face masks, enhanced hygiene practices, and physical distancing—led to a marked reduction not only in SARS-CoV-2 transmission but also in the circulation of numerous other respiratory viruses. Nevertheless, these measures did not uniformly suppress all viral agents, as demonstrated by the persistent detection of rhinovirus/enterovirus (RV/EV) throughout the pandemic. Following the relaxation of pandemic-related restrictions, several previously attenuated respiratory viruses have reemerged, frequently exhibiting shifts in their typical seasonal epidemiology. Given that viral respiratory tract infections continue to represent a leading cause of pediatric morbidity and hospitalization, particularly during the winter months, timely and accurate etiological diagnosis is of critical importance. Rapid molecular diagnostic techniques—such as multiplex polymerase chain reaction (PCR) assays-play a pivotal role in informing targeted clinical management and public health interventions. Early viral identification enables the prompt implementation of appropriate infection control measures, thereby limiting nosocomial transmission. Moreover, it contributes to rationalizing antimicrobial use by reducing prescription unnecessary antibiotics. In addition to vaccination, the availability of antiviral agents and monoclonal antibodies provides effective therapeutic and prophylactic options for specific viral pathogens, including influenza viruses and RSV A/B. Limitations Limitations of our study include the absence of clinical data such as presenting symptoms, underlying comorbidities, and final diagnoses; the single-center design, despite the institution being a large tertiary referral center; and the exclusion of SARS-CoV-2 data during the pandemic period. Additionally, the lack of data from the post-pandemic period limits the ability to assess long-term changes in the epidemiological patterns of respiratory viruses following the relaxation of public health measures. Abbreviations 229E : Human coronavirus 229E AdV : Adenoviruses H1N1 : Hemagglutinin type 1 and neuraminidase type 1 (influenza subtype) hCoV : Human coronavirus hBoV : Human bocavirus HKU1 : Human coronavirus HKU1 hMPV : Human metapneumovirus IAV : Influenza A virus IBV : Influenza B virus NL63 : Human coronavirus NL63 NP : Nasopharyngeal OC43 : Human coronavirus OC43 PIVs 1/2/3/4 : Parainfluenza virus types 1, 2, 3, and 4 PCR : Polymerase chain reaction RSV A/B : Respiratory syncytial virus types A and B RV/EV : Rhinovirus/Enterovirus SARS-CoV-2 : Severe acute respiratory syndrome coronavirus 2 Declarations Conflicts of Interest and Source of Funding: The authors declare no conflicts of interest. No external funding or support was received for this study. Ethics Approval and Consent to Participate This study was approved by the Clinical Research Ethics Committee of Bursa Uludag University Faculty of Medicine (Decision No: 2021-17/12, dated 2 November 2021). The research was conducted in accordance with the principles of the Declaration of Helsinki. The requirement for informed consent was waived by the Clinical Research Ethics Committee of Bursa Uludag University Faculty of Medicine due to the retrospective and anonymized nature of the data. Clinical Trial Clinical trial number: Not applicable. Consent for Publication Not applicable. This study does not contain any individual person’s data in any form (including individual details, images, or videos). Availability of Data and Material The datasets generated and analyzed during the study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research received no external funding. Author Contributions M.T. designed the study, reviewed the literature, and drafted the manuscript. H.A. supervised the study and provided critical revisions. All authors approved the final version. Acknowledgments The authors thank Dr. Rabia Rusen for her contribution to the statistical analysis and Dr. Osman Merdan for his constructive feedback during manuscript preparation. This study was conducted initially as part of the first author’s medical specialty thesis in medical microbiology at Bursa Uludag University, completed in 2022. Data collection and analysis were performed while affiliated with Bursa Uludag University. References Sirota SB, Doxey MC, Dominguez RMV, et al. Global, regional, and national burden of upper respiratory infections and otitis media, 1990–2021: a systematic analysis from the Global Burden of Disease Study 2021. Lancet Infect Dis . Published online January 2024. doi:10.1016/s1473-3099(24)00430-4 Hassen S, Getachew M, Eneyew B, et al. Determinants of acute respiratory infection (ARI) among under-five children in rural areas of Legambo District, South Wollo Zone, Ethiopia: A matched case–control study. International Journal of Infectious Diseases . 2020;96:688-695. doi:10.1016/j.ijid.2020.05.012 Amit Patel, Shobha Chaturvedi, Mehar Bano, Aditya Pandey. Prevalence of acute respiratory infections among under-five children and its association with sociodemographic factors and housing conditions in a rural area of the Bundelkhand region: A cross-sectional study. Asian J Med Sci . 2023;14(11):142-148. doi:10.3126/ajms.v14i11.55735 South F, Usf T, Graduate D, Usf G, Theses D, Luque JS. Breathing Easier: Ethnographic Study of Acute Respiratory Infection Breathing Easier: Ethnographic Study of Acute Respiratory Infection in Children in Rural Ecuador in Children in Rural Ecuador .; 2006. https://digitalcommons.usf.edu/etd Xie J, Florin TA, Funk AL, Tancredi DJ, Kuppermann N, Freedman SB. Respiratory Viral Co-infection in SARS-CoV-2-Infected Children During the Early and Late Pandemic Periods. Pediatric Infectious Disease Journal . Published online 2024. doi:10.1097/INF.0000000000004623 Khales P, Razizadeh MH, Ghorbani S, Moattari A, Saadati H, Tavakoli A. Prevalence of respiratory viruses in children with respiratory tract infections during the COVID-19 pandemic era: a systematic review and meta-analysis. BMC Pulm Med . 2025;25(1). doi:10.1186/s12890-025-03587-z Käding N, Waldeck F, Meier B, et al. Influence of non-pharmaceutical interventions during the COVID-19 pandemic on respiratory viral infections – a prospective population-based cohort study. Front Public Health . 2024;12. doi:10.3389/fpubh.2024.1415778 Perin J, Mulick A, Yeung D, et al. Global, regional, and national causes of under-5 mortality in 2000–19: an updated systematic analysis with implications for the Sustainable Development Goals. Lancet Child Adolesc Health . 2022;6(2):106-115. doi:10.1016/S2352-4642(21)00311-4 Zhu G, Xu D, Zhang Y, et al. Epidemiological characteristics of four common respiratory viral infections in children. Virol J . 2021;18(1). doi:10.1186/s12985-020-01475-y Khales P, Razizadeh MH, Ghorbani S, Moattari A, Saadati H, Tavakoli A. Prevalence of respiratory viruses in children with respiratory tract infections during the COVID-19 pandemic era: a systematic review and meta-analysis. BMC Pulm Med . 2025;25(1). doi:10.1186/s12890-025-03587-z Wilson R, Kovacs D, Crosby M, Ho A. Global Epidemiology and Seasonality of Human Seasonal Coronaviruses: A Systematic Review. Open Forum Infect Dis . 2024;11(8). doi:10.1093/ofid/ofae418 Nickbakhsh S, Nickbakhsh S, Ho A, et al. Epidemiology of Seasonal Coronaviruses: Establishing the Context for the Emergence of Coronavirus Disease 2019. Journal of Infectious Diseases . 2020;222(1):17-25. doi:10.1093/infdis/jiaa185 Mazur NI, Caballero MT, Nunes MC. Severe respiratory syncytial virus infection in children: burden, management, and emerging therapies. The Lancet . Published online September 2024. doi:10.1016/s0140-6736(24)01716-1 Cacho F, Gebretsadik T, Anderson LJ, et al. Respiratory Syncytial Virus Prevalence and Risk Factors among Healthy Term Infants, United States. Emerg Infect Dis . 2024;30(10):2199-2202. doi:10.3201/eid3010.240609 CDC Recommendation RSV Vaccine for Pregnant Women. https://www.cdc.gov/rsv/hcp/vaccine-clinical-guidance/pregnant-people.html. Tamerius J, Nelson MI, Zhou SZ, Viboud C, Miller MA, Alonso WJ. Global influenza seasonality: Reconciling patterns across temperate and tropical regions. Environ Health Perspect . 2011;119(4):439-445. doi:10.1289/ehp.1002383 Hamid S, Winn A, Parikh R, et al. Seasonality of Respiratory Syncytial Virus-United States, 2017-2023 .; 2022. https://www.cdc.gov/mmwr/mmwr_continuingEducation.html Varghese L, Zachariah P, Vargas C, et al. Epidemiology and clinical features of human coronaviruses in the pediatric population. J Pediatric Infect Dis Soc . 2018;7(2):151-158. doi:10.1093/jpids/pix027 Landes MB, Neil RB, Mccool SS, et al. The frequency and seasonality of influenza and other respiratory viruses in Tennessee: Two influenza seasons of surveillance data, 2010-2012. Influenza Other Respir Viruses . 2013;7(6):1122-1127. doi:10.1111/irv.12145 Neugebauer F, Bergs S, Liebert UG, Hönemann M. Human Rhinoviruses in Pediatric Patients in a Tertiary Care Hospital in Germany: Molecular Epidemiology and Clinical Significance. Viruses . 2022;14(8). doi:10.3390/v14081829 Abushahin A, Toma H, Alnaimi A, et al. Impact of COVID‑19 pandemic restrictions and subsequent relaxation on the prevalence of respiratory virus hospitalizations in children. BMC Pediatr . 2024;24(1). doi:10.1186/s12887-024-04566-9 Wan L, Li L, Zhang H, et al. The changing pattern of common respiratory viruses among children from 2018 to 2021 in Wuhan, China. Arch Virol . 2023;168(12). doi:10.1007/s00705-023-05891-7 Liu P, Xu M, Cao L, et al. Impact of COVID-19 pandemic on the prevalence of respiratory viruses in children with lower respiratory tract infections in China. Virol J . 2021;18(1). doi:10.1186/s12985-021-01627-8 Baker RE, Park SW, Yang W, et al. The impact of COVID-19 nonpharmaceutical interventions on the future dynamics of endemic infections. Published online 2020. doi:10.1073/pnas.2013182117/-/DCSupplemental.y Del Riccio M, Caini S, Bonaccorsi G, et al. Global analysis of respiratory viral circulation and timing of epidemics in the pre–COVID-19 and COVID-19 pandemic eras, based on data from the Global Influenza Surveillance and Response System (GISRS). International Journal of Infectious Diseases . 2024;144. doi:10.1016/j.ijid.2024.107052 Takashita E, Kawakami C, Momoki T, et al. Increased risk of rhinovirus infection in children during the coronavirus disease-19 pandemic. Influenza Other Respir Viruses . 2021;15(4):488-494. doi:10.1111/irv.12854 Leung NHL, Chu DKW, Shiu EYC, et al. Respiratory virus shedding in exhaled breath and efficacy of face masks. Nat Med . 2020;26(5):676-680. doi:10.1038/s41591-020-0843-2 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 10 Jan, 2026 Read the published version in BMC Infectious Diseases → Version 1 posted Editorial decision: Revision requested 15 May, 2025 Reviews received at journal 15 May, 2025 Reviews received at journal 11 May, 2025 Reviews received at journal 06 May, 2025 Reviewers agreed at journal 27 Apr, 2025 Reviewers agreed at journal 25 Apr, 2025 Reviewers agreed at journal 24 Apr, 2025 Reviewers agreed at journal 24 Apr, 2025 Reviewers invited by journal 24 Apr, 2025 Editor assigned by journal 24 Apr, 2025 Editor invited by journal 23 Apr, 2025 Submission checks completed at journal 22 Apr, 2025 First submitted to journal 22 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6464014","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":448448347,"identity":"e82b49db-dc72-4e3b-aad2-d740ca567d8a","order_by":0,"name":"Mehmet Tekinsoy","email":"","orcid":"","institution":"Technical University of Munich","correspondingAuthor":false,"prefix":"","firstName":"Mehmet","middleName":"","lastName":"Tekinsoy","suffix":""},{"id":448448348,"identity":"8b55b403-0c45-4669-843e-214c25dd05a9","order_by":1,"name":"Harun Agca","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYBACAziLvYHxAAMbmiB+LTwHGJC0JBCjRSKBSC3m7GefSRfU1Mrzz3xjcJinzM6ugb15mwTjj3s4tVj2pJtJzzh23HDG7RyglnPJyQ08x8okGBKKcTvsQBqbNA/bsQQGkBbeNuZkBokcM6AW3C4zOP8MqOXfsQT5m2dAWuqTGeTfENByA2gLb1tNgsENHpCWw3YMEjyEtDxjtubtO2C48UxawcE5544nsPGkFVskpOFzWBrjbZ5vdfJyxw9vfPCmrNqen/3wxhsfbHBrgYLDcFZiG4gkqIGBoQ7OsieseBSMglEwCkYaAADlBVEJVh2gbwAAAABJRU5ErkJggg==","orcid":"","institution":"Bursa Uludag University","correspondingAuthor":true,"prefix":"","firstName":"Harun","middleName":"","lastName":"Agca","suffix":""}],"badges":[],"createdAt":"2025-04-16 13:38:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6464014/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6464014/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12879-025-12513-x","type":"published","date":"2026-01-10T15:57:32+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82136750,"identity":"58264f10-4223-4707-8dbd-f003e1da2b92","added_by":"auto","created_at":"2025-05-07 06:14:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":98785,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA. \u003c/strong\u003eNumber of samples per month\u003cstrong\u003eB. \u003c/strong\u003eGender distribution \u003cstrong\u003eC. \u003c/strong\u003eAge profile of the study\u003c/p\u003e\n\u003cp\u003epopulation \u003cstrong\u003eD.\u003c/strong\u003eDistribution of hCoVs and PIVs \u003cstrong\u003eE.\u003c/strong\u003eTemporal variation in the monthly detection\u003c/p\u003e\n\u003cp\u003erates of the most prevalent viral agents\u003c/p\u003e","description":"","filename":"Figure11.png","url":"https://assets-eu.researchsquare.com/files/rs-6464014/v1/b27b896ec07193f20c079341.png"},{"id":100069444,"identity":"e77da5f5-7640-421f-a9d4-2f55c8ca73fb","added_by":"auto","created_at":"2026-01-12 16:14:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":982687,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6464014/v1/6fd0e483-0851-4161-882e-86c3e3b441cb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Shifting Patterns of Pediatric Respiratory Viruses During the SARS-CoV-2 Pandemic: A Retrospective Observational Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRespiratory tract infections are the most common acute infectious diseases worldwide and cause significant mortality and morbidity, particularly in childhood.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e It is considered normal for a child under the age of five to experience approximately four to five episodes of acute respiratory infections per year.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Among children under the age of five, the incidence of respiratory tract infections can reach up to 50%, and these infections are a significant cause of hospitalizations. \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003eThis higher frequency in this age group is because the respiratory system is still anatomically developing and the immune system has not yet reached its full functionality as seen in adults.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e The widespread distribution of respiratory infection agents across large geographical areas creates a significant economic burden due to loss of workforce, care needs, and treatment costs.\u003c/p\u003e \u003cp\u003eViruses are the most common causative agents of respiratory tract infections in children. Although their relative frequency changed due to the precautions taken during the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic, the most common viruses are rhinoviruses (RV), respiratory syncytial viruses A and B (RSV A/B), influenza A and B viruses (IAV, IBV), seasonal human coronaviruses 229E, NL63, OC43, HKU1 (hCoV 229E, NL63, OC43, HKU1) and SARS-CoV-2, parainfluenza viruses types 1, 2, 3, and 4 (PIVs 1/2/3/4), adenoviruses (AdV), human metapneumovirus (hMPV) and bocavirus (hBoV).\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe SARS-CoV-2 pandemic has provided a unique context for studying viral transmission dynamics. Non-pharmaceutical interventions such as mask-wearing, social distancing, hand hygiene, and lockdowns significantly impacted respiratory virus epidemiology. Notably, these interventions have effectively reduced most respiratory viral infections, yet their effect on RV/EV appears limited, indicating different transmission mechanisms or resistance to preventive measures.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn this study, the frequency of respiratory tract infection viruses in the pediatric age group was retrospectively examined before and during the SARS-CoV-2 pandemic, and the epidemiological impact of the precautions taken during the pandemic period was evaluated.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThis retrospective study evaluated data from patients aged 18 years and under who presented to the Department of Pediatrics at Bursa Uludag University Medical Research and Training Center between 1 October 2018 and 30 September 2021, with symptoms indicative of respiratory tract infection\u0026mdash;such as sore throat, nasal discharge, nasal congestion, and sneezing\u0026mdash;and from whom nasopharyngeal swab samples were obtained.\u003c/p\u003e \u003cp\u003eThe study assessed age, sex, date of sample collection, the clinical department where the sample was taken, and the presence of respiratory viruses identified via multiplex PCR from nasopharyngeal swab samples. The respiratory viruses investigated included adenoviruses, human bocavirus, seasonal human coronaviruses (subtypes hCoV 229E, HKU1, NL63, OC43), influenza viruses (A, subtype A/H1, subtype A/H1N1, B), parainfluenza viruses (types 1, 2, 3, 4), respiratory syncytial virus (RSV A/B), rhino/enteroviruses (RV/EV), human metapneumovirus (hMPV) and human bocavirus (hBoV).\u003c/p\u003e \u003cp\u003eFor the detection of respiratory viruses, the \"Fast-track Diagnostics Respiratory Pathogens 33\" multiplex PCR kit (FTD, Malta) was used between October 2018 and December 2019, and the \"QIAStat-Dx Respiratory Panel\" multiplex PCR kit (Qiagen, Germany) was employed from January 2020 to October 2021. All study data were obtained from the hospital information management system.\u003c/p\u003e \u003cp\u003eTo enable comparative analysis, the study period was divided into two distinct phases: pre-pandemic (October 2018 to February 2020) and during the pandemic (March 2020 to September 2020), with the latter defined by the first confirmed case of SARS-CoV-2 in T\u0026uuml;rkiye, reported in March 2020.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eThe normality of data distribution was assessed using the Shapiro\u0026ndash;Wilk test. Descriptive statistics were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, median, and range (minimum-maximum) for continuous variables and as frequency and percentage for categorical variables. Pearson\u0026rsquo;s Chi-square test, Fisher\u0026rsquo;s Exact Chi-square test, and the Fisher\u0026ndash;Freeman\u0026ndash;Halton test were used to analyze categorical data, as appropriate. A p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant. All statistical analyses were performed using IBM SPSS Statistics for Windows, Version 23.0 (IBM Corp., Armonk, NY, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDemographic Characteristics\u003c/h2\u003e \u003cp\u003eOur study examined 1269 nasopharyngeal swab samples collected from patients hospitalized in the Department of Pediatrics at Bursa Uludag University Medical Research and Training Center. The distribution of samples evaluated by month is presented in Fig.\u0026nbsp;1A. Among patients aged 0 to 18 years, 533 (42.0%) were female and 736 (58.0%) were male (Fig.\u0026nbsp;1B). The mean age was 4.97\u0026thinsp;\u0026plusmn;\u0026thinsp;4.85 years for females and 4.54\u0026thinsp;\u0026plusmn;\u0026thinsp;4.81 years for males. The median age was 3.00 years for both genders. Age groups were distributed as follows: 450 patients (35.5%) aged 0\u0026ndash;1 year, 335 patients (26.4%) aged 2\u0026ndash;4 years, 260 patients (20.5%) aged 5\u0026ndash;9 years, and 224 patients (17.7%) aged 10 years or older. Age-frequency distributions are shown in Fig.\u0026nbsp;1C. Before the pandemic (November 2018 to February 2020), 747 samples (58.9%), and during the pandemic (March 2020 to October 2021), 522 samples (41.1%) were evaluated.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEpidemiological Overview of Circulating Viruses\u003c/h3\u003e\n\u003cp\u003eA total of 889 distinct viral agents were identified in 1,269 nasopharyngeal swabs. Of these samples, 45.6% tested positive for a single virus, 9.6% tested positive for two, 1.4% tested positive for three, and 0.2% tested positive for four. The most prevalent viruses identified were rhinovirus/enterovirus (RV/EV) in 324 patients (25.5%), followed by RSV A/B in 117 (9.2%), hCoVs NL63, 229E, OC43, HKU1 in 104 (8.2%), IAV in 84 (6.6%), PIVs 1\u0026ndash;4 in 83 (6.5%) and AdV in 67 (5.3%). The detection rates and numbers of viral agents are demonstrated in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Specifically, the following rates of hCoVs were identified: OC43 in 58 samples (4.6%), 229E in 25 samples (2.0%), HKU1 in 9 samples (0.7%), and NL63 in 12 samples (0.9%) (Fig.\u0026nbsp;1D). For parainfluenza viruses, the following were detected: PIV-1 in 15 samples (1.2%), PIV-2 in 5 (0.4%), PIV-3 in 46 (3.6%), and PIV-4 in 17 (1.3%) (Fig.\u0026nbsp;1D). Coinfection was observed in 143 patients, with RV/EV (82), hCoV (51), RSV A/B (45), AdV (39), PIVs (26), hBoV (24), IAV (22), hMPV (13), and IBV (8) as coinfection agents.\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 rates and numbers of viral agents\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ehBoV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ehCoVs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIAV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIBV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePIVs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRSV A/B\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eRV/EV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ehMPV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e324\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2,9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8,2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6,6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3,2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e9,2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e25,5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2,5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA subsequent analysis of the distribution of infectious agents according to age groups revealed that the most prevalent viral agent detected in each age group was RV/EV. AdV, hBoV, IBV, PIVs, RSV, and RV/EV detection rates differed significantly between age groups (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Significant differences in the frequency and distribution of pathogens by year were found for each virus (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Figure\u0026nbsp;1E presents the monthly detection rates of the most common viral agents\u0026mdash;RV/EV, RSV A/B, IAV, IBV, and hCoVs. The seasonal analysis revealed significant variation in detection rates for all viruses except AdV and hBoV (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\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\u003eViral agents by age group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ehBoV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ehCoVs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIAV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIBV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePIVs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRSV A/B\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eRV/EV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ehMPV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0\u0026ndash;1 year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e25.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2\u0026ndash;4 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e32.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e5\u0026ndash;9 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e10\u0026ndash;18 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e16.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e25.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.5\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\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.843\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\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\u003eFrequency and distribution of viruses by year\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ehBoV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ehCoVs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIAV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIBV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePIVs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRSV A/B\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eRV/EV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ehMPV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e33.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e26.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e32.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\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\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\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\u003eSeasonal variation in detected viruses\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ehBoV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ehCoVs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIAV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIBV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePIV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRSV A/B\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eRV/EV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ehMPV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAutumn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e33.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWinter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e16.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e16.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSpring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e28.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSummer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e28.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.2\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\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.039\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo assess the impact of non-pharmaceutical interventions during the SARS-CoV-2 pandemic period, November 2018 to February 2020 was grouped as \u0026ldquo;before the pandemic\u0026rdquo;, and March 2020 to October 2021 was grouped as \u0026ldquo;during the pandemic\u0026rdquo;. A comparative analysis of the prevalence of various viral agents revealed significant differences in frequencies before and during the pandemic (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The incidence of AdV, hCoVs, IAV, IBV, PIVs, RSV A/B, and hMPV before the pandemic was significantly higher than during the pandemic (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). When RV/EV was analyzed, 171 (22.9%) patients were positive before the pandemic, while 153 (29.3%) patients were positive during the pandemic. The observed shift in the incidence of RV/EV was found to be statistically significant (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) (p\u0026thinsp;=\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of the frequency and distribution of viruses across periods\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ehBoV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ehCoVs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIAV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIBV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePIVs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRSV A/B\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eRV/EV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ehMPV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBefore the pandemic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e22.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDuring the pandemic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e29.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.6\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\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.339\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAcute respiratory tract infections are among the leading causes of morbidity and mortality in childhood. Lower respiratory infections after preterm birth are the second leading cause of death in children under five.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Viruses are the primary cause of acute respiratory infections in children.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Therefore, the accurate and rapid detection of viral respiratory infections is critical.\u003c/p\u003e \u003cp\u003eA comprehensive review conducted during the SARS-CoV-2 pandemic era found that the most commonly detected viral pathogens in childhood respiratory infections were RV/EV and RSV, with detection rates of 29.1% and 11.3%, respectively.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e Consistent with these findings, our study also identified RV/EV as the most commonly detected virus, present in 324 samples (25.5%), followed by RSV A/B in 117 samples (9.2%).\u003c/p\u003e \u003cp\u003eThe highest monthly number of samples was recorded in January 2020. This surge may be attributed to several factors: an increase in test requests driven by public concern following the emergence of SARS-CoV-2 in late 2019, the implementation of a new laboratory testing system that enabled faster turnaround times, and the limited availability of SARS-CoV-2 testing at the national level, which led clinicians to adopt exclusion-based diagnostic algorithms for suspected SARS-CoV-2 infection cases. During the early stages of the pandemic (April\u0026ndash;May 2020), the number of samples decreased, probably due to concerns about transmission risk during sampling and safety concerns in the laboratory.\u003c/p\u003e \u003cp\u003eOur study also included the coronavirus subtypes OC43, 229E, HKU1, and NL63. In a U.S.-based review published in 2024 by Wilson et al., OC43 was the most commonly detected coronavirus, followed by NL63.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e In our study, OC43 was likewise the most prevalent seasonal coronavirus; however, the second most pervasive was 229E. This discrepancy may be attributed to the male predominance in our study population or minor local variations in the epidemiology of seasonal coronaviruses. \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eRSV is more frequently seen in infancy than in other age groups. Mazur et al.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e conducted a review demonstrating that RSV predominantly affects infants and is associated with high morbidity and mortality rates, particularly in low- and middle-income countries. According to a study by Cacho et al.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, 53.4% of children are infected with RSV in their first year of life. In our research, RSV was likewise most frequently observed in the 0\u0026ndash;1 year age group. Since 2023, several vaccines have been approved by the Food and Drug Administration and the European Medical Agency to prevent RSV infections in older adults and infants. To protect infants from RSV, appropriate maternal vaccination during late pregnancy is recommended.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe seasonal relationship of influenza types shows that these viruses are more common in winter. According to a review by Tamerius et al.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, possible explanations include cold and dry air impairing mucociliary function, reduced sunlight exposure, lowering vitamin D levels and weakening the immune system, and people spending more time indoors in close contact. In our study, influenza viruses were generally detected in winter as well. RSV, similar to influenza, peaks during the winter months. According to Hamid et al.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, in the years preceding the pandemic (2017\u0026ndash;2019), the RSV season typically began in October, peaked in December, and ended by April. Consistent with these findings, our study also found that RSV was most frequently detected during the winter months and primarily in children aged 0\u0026ndash;1 year. Coronaviruses also peak in winter, similar to influenza and RSV. Varghese et al. \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e observed that the incidence of coronaviruses such as OC43, 229E, HKU1, and NL63 began increasing in late autumn and peaked in January\u0026ndash;February. Our findings align with this pattern. Rhinoviruses can be detected year-round but peak in the autumn. Gao et al. \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e reported the highest detection rates of RV/EV in autumn. Neugebauer et al. \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e also found peaks in September/October and April. Consistent with these studies, our findings show that RV/EV was present throughout the year but significantly more frequent in autumn.\u003c/p\u003e \u003cp\u003eSignificant shifts in the prevalence and seasonal peaks of respiratory infections were observed during the pandemic, likely attributable to widespread mask use, enhanced hygiene practices, and the implementation of lockdown measures. Several studies\u003csup\u003e\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e reported significantly higher detection rates for AdV, hCoV, IAV, IBV, PIVs, RSV A/B, and MPV before the pandemic. Del Ricco et al.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e observed a sharp decline in almost all respiratory viruses during the pandemic, while RV/EV detection remained stable or even increased. Takashita et al.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e found significantly lower influenza, MPV, RSV, and parainfluenza detection during the pandemic. They noted no enveloped viruses were detected after May 2020, while non-enveloped viruses like RV/EV and AdV continued to be found. They attributed this to the more significant environmental stability of non-enveloped viruses. They also reported an increased detection rate of RV/EV among children under 10. Leung et al.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e found that surgical masks effectively reduced transmission of influenza and coronaviruses, but not RV/EV. In our study, consistent with these findings, detection rates of AdV, hCoV, IAV, IBV, PIVs, RSVA/B, and hMPV declined during the pandemic, while RV/EV detection rate increased. Possible explanations include poor mask efficacy against RV/EV, high incidence in children, low mask compliance in children, resistance to environmental conditions as a non-enveloped virus, and frequent reinfections due to numerous serotypes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe frequency and distribution of respiratory viral pathogens in pediatric populations exhibit considerable variability depending on seasonal fluctuations, interannual trends, and the occurrence of pandemics. Non-pharmaceutical interventions implemented during the SARS-CoV-2 pandemic\u0026mdash;including the use of face masks, enhanced hygiene practices, and physical distancing\u0026mdash;led to a marked reduction not only in SARS-CoV-2 transmission but also in the circulation of numerous other respiratory viruses. Nevertheless, these measures did not uniformly suppress all viral agents, as demonstrated by the persistent detection of rhinovirus/enterovirus (RV/EV) throughout the pandemic. Following the relaxation of pandemic-related restrictions, several previously attenuated respiratory viruses have reemerged, frequently exhibiting shifts in their typical seasonal epidemiology.\u003c/p\u003e \u003cp\u003eGiven that viral respiratory tract infections continue to represent a leading cause of pediatric morbidity and hospitalization, particularly during the winter months, timely and accurate etiological diagnosis is of critical importance. Rapid molecular diagnostic techniques\u0026mdash;such as multiplex polymerase chain reaction (PCR) assays-play a pivotal role in informing targeted clinical management and public health interventions. Early viral identification enables the prompt implementation of appropriate infection control measures, thereby limiting nosocomial transmission. Moreover, it contributes to rationalizing antimicrobial use by reducing prescription unnecessary antibiotics.\u003c/p\u003e \u003cp\u003eIn addition to vaccination, the availability of antiviral agents and monoclonal antibodies provides effective therapeutic and prophylactic options for specific viral pathogens, including influenza viruses and RSV A/B.\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eLimitations of our study include the absence of clinical data such as presenting symptoms, underlying comorbidities, and final diagnoses; the single-center design, despite the institution being a large tertiary referral center; and the exclusion of SARS-CoV-2 data during the pandemic period. Additionally, the lack of data from the post-pandemic period limits the ability to assess long-term changes in the epidemiological patterns of respiratory viruses following the relaxation of public health measures.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003e229E\u003c/strong\u003e: Human coronavirus 229E\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAdV\u003c/strong\u003e: Adenoviruses\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eH1N1\u003c/strong\u003e: Hemagglutinin type 1 and neuraminidase type 1 (influenza subtype)\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ehCoV\u003c/strong\u003e: Human coronavirus\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ehBoV\u003c/strong\u003e: Human bocavirus\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eHKU1\u003c/strong\u003e: Human coronavirus HKU1\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ehMPV\u003c/strong\u003e: Human metapneumovirus\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eIAV\u003c/strong\u003e: Influenza A virus\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eIBV\u003c/strong\u003e: Influenza B virus\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eNL63\u003c/strong\u003e: Human coronavirus NL63\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eNP\u003c/strong\u003e: Nasopharyngeal\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eOC43\u003c/strong\u003e: Human coronavirus OC43\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ePIVs 1/2/3/4\u003c/strong\u003e: Parainfluenza virus types 1, 2, 3, and 4\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ePCR\u003c/strong\u003e: Polymerase chain reaction\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eRSV A/B\u003c/strong\u003e: Respiratory syncytial virus types A and B\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eRV/EV\u003c/strong\u003e: Rhinovirus/Enterovirus\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eSARS-CoV-2\u003c/strong\u003e: Severe acute respiratory syndrome coronavirus 2\u003c/li\u003e\n\u003c/ul\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflicts of Interest and Source of Funding:\u003c/strong\u003e The authors declare no conflicts of interest. No external funding or support was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Clinical Research Ethics Committee of Bursa Uludag University Faculty of Medicine (Decision No: 2021-17/12, dated 2 November 2021). The research was conducted in accordance with the principles of the Declaration of Helsinki.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe requirement for informed consent was waived by the Clinical Research Ethics Committee of Bursa Uludag University Faculty of Medicine due to the retrospective and anonymized nature of the data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical trial number: Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This study does not contain any individual person\u0026rsquo;s data in any form (including individual details, images, or videos).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM.T. designed the study, reviewed the literature, and drafted the manuscript. H.A. supervised the study and provided critical revisions. All authors approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank Dr. Rabia Rusen for her contribution to the statistical analysis and Dr. Osman Merdan for his constructive feedback during manuscript preparation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study was conducted initially as part of the first author\u0026rsquo;s medical specialty thesis in medical microbiology at Bursa Uludag University, completed in 2022. Data collection and analysis were performed while affiliated with Bursa Uludag University.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSirota SB, Doxey MC, Dominguez RMV, et al. Global, regional, and national burden of upper respiratory infections and otitis media, 1990\u0026ndash;2021: a systematic analysis from the Global Burden of Disease Study 2021. \u003cem\u003eLancet Infect Dis\u003c/em\u003e. Published online January 2024. doi:10.1016/s1473-3099(24)00430-4\u003c/li\u003e\n\u003cli\u003eHassen S, Getachew M, Eneyew B, et al. Determinants of acute respiratory infection (ARI) among under-five children in rural areas of Legambo District, South Wollo Zone, Ethiopia: A matched case\u0026ndash;control study. \u003cem\u003eInternational Journal of Infectious Diseases\u003c/em\u003e. 2020;96:688-695. doi:10.1016/j.ijid.2020.05.012\u003c/li\u003e\n\u003cli\u003eAmit Patel, Shobha Chaturvedi, Mehar Bano, Aditya Pandey. Prevalence of acute respiratory infections among under-five children and its association with sociodemographic factors and housing conditions in a rural area of the Bundelkhand region: A cross-sectional study. \u003cem\u003eAsian J Med Sci\u003c/em\u003e. 2023;14(11):142-148. doi:10.3126/ajms.v14i11.55735\u003c/li\u003e\n\u003cli\u003eSouth F, Usf T, Graduate D, Usf G, Theses D, Luque JS. \u003cem\u003eBreathing Easier: Ethnographic Study of Acute Respiratory Infection Breathing Easier: Ethnographic Study of Acute Respiratory Infection in Children in Rural Ecuador in Children in Rural Ecuador\u003c/em\u003e.; 2006. https://digitalcommons.usf.edu/etd\u003c/li\u003e\n\u003cli\u003eXie J, Florin TA, Funk AL, Tancredi DJ, Kuppermann N, Freedman SB. Respiratory Viral Co-infection in SARS-CoV-2-Infected Children During the Early and Late Pandemic Periods. \u003cem\u003ePediatric Infectious Disease Journal\u003c/em\u003e. Published online 2024. doi:10.1097/INF.0000000000004623\u003c/li\u003e\n\u003cli\u003eKhales P, Razizadeh MH, Ghorbani S, Moattari A, Saadati H, Tavakoli A. Prevalence of respiratory viruses in children with respiratory tract infections during the COVID-19 pandemic era: a systematic review and meta-analysis. \u003cem\u003eBMC Pulm Med\u003c/em\u003e. 2025;25(1). doi:10.1186/s12890-025-03587-z\u003c/li\u003e\n\u003cli\u003eK\u0026auml;ding N, Waldeck F, Meier B, et al. Influence of non-pharmaceutical interventions during the COVID-19 pandemic on respiratory viral infections \u0026ndash; a prospective population-based cohort study. \u003cem\u003eFront Public Health\u003c/em\u003e. 2024;12. doi:10.3389/fpubh.2024.1415778\u003c/li\u003e\n\u003cli\u003ePerin J, Mulick A, Yeung D, et al. Global, regional, and national causes of under-5 mortality in 2000\u0026ndash;19: an updated systematic analysis with implications for the Sustainable Development Goals. \u003cem\u003eLancet Child Adolesc Health\u003c/em\u003e. 2022;6(2):106-115. doi:10.1016/S2352-4642(21)00311-4\u003c/li\u003e\n\u003cli\u003eZhu G, Xu D, Zhang Y, et al. Epidemiological characteristics of four common respiratory viral infections in children. \u003cem\u003eVirol J\u003c/em\u003e. 2021;18(1). doi:10.1186/s12985-020-01475-y\u003c/li\u003e\n\u003cli\u003eKhales P, Razizadeh MH, Ghorbani S, Moattari A, Saadati H, Tavakoli A. Prevalence of respiratory viruses in children with respiratory tract infections during the COVID-19 pandemic era: a systematic review and meta-analysis. \u003cem\u003eBMC Pulm Med\u003c/em\u003e. 2025;25(1). doi:10.1186/s12890-025-03587-z\u003c/li\u003e\n\u003cli\u003eWilson R, Kovacs D, Crosby M, Ho A. Global Epidemiology and Seasonality of Human Seasonal Coronaviruses: A Systematic Review. \u003cem\u003eOpen Forum Infect Dis\u003c/em\u003e. 2024;11(8). doi:10.1093/ofid/ofae418\u003c/li\u003e\n\u003cli\u003eNickbakhsh S, Nickbakhsh S, Ho A, et al. Epidemiology of Seasonal Coronaviruses: Establishing the Context for the Emergence of Coronavirus Disease 2019. \u003cem\u003eJournal of Infectious Diseases\u003c/em\u003e. 2020;222(1):17-25. doi:10.1093/infdis/jiaa185\u003c/li\u003e\n\u003cli\u003eMazur NI, Caballero MT, Nunes MC. Severe respiratory syncytial virus infection in children: burden, management, and emerging therapies. \u003cem\u003eThe Lancet\u003c/em\u003e. Published online September 2024. doi:10.1016/s0140-6736(24)01716-1\u003c/li\u003e\n\u003cli\u003eCacho F, Gebretsadik T, Anderson LJ, et al. Respiratory Syncytial Virus Prevalence and Risk Factors among Healthy Term Infants, United States. \u003cem\u003eEmerg Infect Dis\u003c/em\u003e. 2024;30(10):2199-2202. doi:10.3201/eid3010.240609\u003c/li\u003e\n\u003cli\u003eCDC Recommendation RSV Vaccine for Pregnant Women. https://www.cdc.gov/rsv/hcp/vaccine-clinical-guidance/pregnant-people.html.\u003c/li\u003e\n\u003cli\u003eTamerius J, Nelson MI, Zhou SZ, Viboud C, Miller MA, Alonso WJ. Global influenza seasonality: Reconciling patterns across temperate and tropical regions. \u003cem\u003eEnviron Health Perspect\u003c/em\u003e. 2011;119(4):439-445. doi:10.1289/ehp.1002383\u003c/li\u003e\n\u003cli\u003eHamid S, Winn A, Parikh R, et al. \u003cem\u003eSeasonality of Respiratory Syncytial Virus-United States, 2017-2023\u003c/em\u003e.; 2022. https://www.cdc.gov/mmwr/mmwr_continuingEducation.html\u003c/li\u003e\n\u003cli\u003eVarghese L, Zachariah P, Vargas C, et al. Epidemiology and clinical features of human coronaviruses in the pediatric population. \u003cem\u003eJ Pediatric Infect Dis Soc\u003c/em\u003e. 2018;7(2):151-158. doi:10.1093/jpids/pix027\u003c/li\u003e\n\u003cli\u003eLandes MB, Neil RB, Mccool SS, et al. The frequency and seasonality of influenza and other respiratory viruses in Tennessee: Two influenza seasons of surveillance data, 2010-2012. \u003cem\u003eInfluenza Other Respir Viruses\u003c/em\u003e. 2013;7(6):1122-1127. doi:10.1111/irv.12145\u003c/li\u003e\n\u003cli\u003eNeugebauer F, Bergs S, Liebert UG, H\u0026ouml;nemann M. Human Rhinoviruses in Pediatric Patients in a Tertiary Care Hospital in Germany: Molecular Epidemiology and Clinical Significance. \u003cem\u003eViruses\u003c/em\u003e. 2022;14(8). doi:10.3390/v14081829\u003c/li\u003e\n\u003cli\u003eAbushahin A, Toma H, Alnaimi A, et al. Impact of COVID‑19 pandemic restrictions and subsequent relaxation on the prevalence of respiratory virus hospitalizations in children. \u003cem\u003eBMC Pediatr\u003c/em\u003e. 2024;24(1). doi:10.1186/s12887-024-04566-9\u003c/li\u003e\n\u003cli\u003eWan L, Li L, Zhang H, et al. The changing pattern of common respiratory viruses among children from 2018 to 2021 in Wuhan, China. \u003cem\u003eArch Virol\u003c/em\u003e. 2023;168(12). doi:10.1007/s00705-023-05891-7\u003c/li\u003e\n\u003cli\u003eLiu P, Xu M, Cao L, et al. Impact of COVID-19 pandemic on the prevalence of respiratory viruses in children with lower respiratory tract infections in China. \u003cem\u003eVirol J\u003c/em\u003e. 2021;18(1). doi:10.1186/s12985-021-01627-8\u003c/li\u003e\n\u003cli\u003eBaker RE, Park SW, Yang W, et al. The impact of COVID-19 nonpharmaceutical interventions on the future dynamics of endemic infections. Published online 2020. doi:10.1073/pnas.2013182117/-/DCSupplemental.y\u003c/li\u003e\n\u003cli\u003eDel Riccio M, Caini S, Bonaccorsi G, et al. Global analysis of respiratory viral circulation and timing of epidemics in the pre\u0026ndash;COVID-19 and COVID-19 pandemic eras, based on data from the Global Influenza Surveillance and Response System (GISRS). \u003cem\u003eInternational Journal of Infectious Diseases\u003c/em\u003e. 2024;144. doi:10.1016/j.ijid.2024.107052\u003c/li\u003e\n\u003cli\u003eTakashita E, Kawakami C, Momoki T, et al. Increased risk of rhinovirus infection in children during the coronavirus disease-19 pandemic. \u003cem\u003eInfluenza Other Respir Viruses\u003c/em\u003e. 2021;15(4):488-494. doi:10.1111/irv.12854\u003c/li\u003e\n\u003cli\u003eLeung NHL, Chu DKW, Shiu EYC, et al. Respiratory virus shedding in exhaled breath and efficacy of face masks. \u003cem\u003eNat Med\u003c/em\u003e. 2020;26(5):676-680. doi:10.1038/s41591-020-0843-2\u003c/li\u003e\n\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":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Pediatric respiratory viruses, SARS-CoV-2 pandemic, multiplex PCR, viral epidemiology, seasonal variation","lastPublishedDoi":"10.21203/rs.3.rs-6464014/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6464014/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003eRespiratory tract infections are a leading cause of hospitalization in children and remain a significant contributor to pediatric morbidity. Understanding the epidemiology of viral pathogens\u0026mdash;including their seasonal trends and response to global events like pandemics\u0026mdash;is essential for public health planning, surveillance strategies, and timely clinical interventions.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eThis retrospective study evaluated the epidemiology of respiratory viruses in pediatric patients before and during the SARS-CoV-2 pandemic. Nasopharyngeal swab samples from 1,269 children presenting with respiratory symptoms between October 2018 and September 2021 were tested using multiplex PCR targeting RV/EV, RSV A/B, seasonal coronaviruses, influenza, parainfluenza, hMPV, and other viruses.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003e889 viruses were detected; 579 were single-virus infections, and 143 involved co-infections. RV/EV was the most frequently detected virus in all age groups. RSV was predominant in children under one year, while influenza was more common in older children. The highest testing volume and positivity rates occurred in January. The overall number of tests and positive detections decreased during the pandemic period. RSV, influenza, parainfluenza, and seasonal coronaviruses showed marked declines, whereas RV/EV frequency increased.\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e \u003cp\u003eThe circulation of pediatric respiratory viruses shifted significantly during the pandemic. Multiplex PCR-based diagnostics proved valuable for tracking these changes, enabling rapid diagnosis and real-time epidemiological insight. These findings underscore the importance of molecular surveillance in managing pediatric respiratory infections, particularly during global health events.\u003c/p\u003e","manuscriptTitle":"Shifting Patterns of Pediatric Respiratory Viruses During the SARS-CoV-2 Pandemic: A Retrospective Observational Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-07 06:14:31","doi":"10.21203/rs.3.rs-6464014/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-15T06:39:47+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-15T04:55:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-12T01:20:21+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-06T14:13:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"164142655403929825074321703456254048606","date":"2025-04-27T23:51:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"96420240889604289282300383194663474464","date":"2025-04-25T18:55:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"119405570237745491437726467594574084058","date":"2025-04-25T03:16:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"171569978616654224448026607643072938904","date":"2025-04-24T23:10:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-24T09:48:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-24T09:46:24+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-04-23T10:20:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-22T14:47:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2025-04-22T14:46:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f8fa685f-01c8-431b-8d47-efe26e3e0fd4","owner":[],"postedDate":"May 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:06:33+00:00","versionOfRecord":{"articleIdentity":"rs-6464014","link":"https://doi.org/10.1186/s12879-025-12513-x","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2026-01-10 15:57:32","publishedOnDateReadable":"January 10th, 2026"},"versionCreatedAt":"2025-05-07 06:14:31","video":"","vorDoi":"10.1186/s12879-025-12513-x","vorDoiUrl":"https://doi.org/10.1186/s12879-025-12513-x","workflowStages":[]},"version":"v1","identity":"rs-6464014","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6464014","identity":"rs-6464014","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}