Post-COVID-19 Seasonality of Influenza, Respiratory Syncytial Virus, and SARS-CoV-2 Among Hospitalized Children in Western Iran: A Molecular Surveillance Study (2023–2024)

Post-COVID-19 Seasonality of Influenza, Respiratory Syncytial Virus, and SARS-CoV-2 Among Hospitalized Children in Western Iran: A Molecular Surveillance Study (2023–2024) | 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 Post-COVID-19 Seasonality of Influenza, Respiratory Syncytial Virus, and SARS-CoV-2 Among Hospitalized Children in Western Iran: A Molecular Surveillance Study (2023–2024) Ensieh Masoorian, Ali Teimoori, Somaye Bakhtiari, Farid Azizi Jalilian, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7175880/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background This study aimed to characterize the prevalence, seasonality, and co-infection patterns of respiratory syncytial virus (RSV), influenza A and B, and SARS-CoV-2 among hospitalized children aged 0–5 years in Hamedan Province, a semi-arid region in western Iran, from April 2023 to March 2024. Key research questions included assessing post-pandemic shifts in viral seasonality, evaluating the extent of RSV circulation, and determining the frequency of co-infections in a resource-limited pediatric setting where regional data remain scarce. Methods A total of 586 nasopharyngeal/oropharyngeal samples were collected from children aged 0–5 years hospitalized with acute respiratory symptoms (≥2 of: fever ≥38°C, cough, dyspnea, oxygen saturation <95%). Multiplex real-time PCR (sensitivity 95%, specificity 98%) was used to detect RSV, SARS-CoV-2, and influenza A (H1N1, H3N2) and B. Statistical analysis included chi-square and Fisher’s exact tests, and generalized linear models (binomial distribution, logit link). Results Among 586 inpatients (mean age: 2.8 years; 62.5% male), 27.0% tested positive for influenza (60% influenza A [35% H1N1, 25% H3N2], 40% influenza B), 6.0% for RSV, and 6.3% for SARS-CoV-2. Influenza peaked in autumn (41.3%, p < 0.001), RSV in winter (18.2%, p < 0.001), and SARS-CoV-2 in spring (15.3%, p = 0.005). Co-infections were rare (0.9%). Conclusions Findings reveal altered post-pandemic seasonality, reduced RSV activity, and low co-infection rates, suggesting potential ecological and immunological shifts. These trends highlight the need for sustained virus-specific surveillance and recalibrated vaccination strategies—particularly influenza vaccination in autumn and RSV prophylaxis in winter—in resource-limited pediatric settings. Respiratory syncytial virus (RSV) Influenza A and B SARS-CoV-2 Pediatric hospitalization Post-COVID-19 surveillance Epidemiology Seasonality Iran Figures Figure 1 Figure 2 Background Acute respiratory infections (ARIs), predominantly driven by viruses such as respiratory syncytial virus (RSV), influenza, and rhinoviruses, remain a leading cause of hospitalization and mortality among children under five years of age. This burden is especially severe in low- and middle-income countries (LMICs), where healthcare systems often face substantial resource constraints [ 1 , 2 ]. Prior to the COVID-19 pandemic, ARIs accounted for approximately 15% of global pediatric deaths [ 3 ]. RSV alone was responsible for over 75,000 deaths and 24.8 million infections annually, placing a considerable burden on public health systems worldwide [ 4 ]. The emergence of SARS-CoV-2 and the global implementation of non-pharmaceutical interventions (NPIs)—including school closures, mask mandates, and travel restrictions—led to unprecedented disruptions in the transmission dynamics of common pediatric respiratory viruses [ 5 , 6 ]. These measures resulted in the temporary suppression of RSV, influenza, and other respiratory pathogens during the early pandemic period, significantly altering previously well-characterized seasonal circulation patterns [ 7 , 8 ]. Following the relaxation of NPIs, however, atypical and off-season resurgences of respiratory viruses were documented across multiple regions [ 9 , 10 ], raising concerns about population-level immunity gaps due to reduced exposure and the long-term effects of altered viral ecology [ 11 , 12 ]. For example, in southwestern Iran, RSV reappeared in spring 2022 after a near-total absence during the height of the pandemic [ 11 ]. Similarly, countries such as Mexico, Saudi Arabia, Canada, China, and Argentina reported increased pediatric hospitalizations related to RSV, influenza, and parainfluenza—often occurring outside their historical seasonal peaks[ 12 – 16 ]. These trends suggest a global reset of viral transmission patterns; however, robust, longitudinal surveillance data from Middle Eastern countries [ 17 ]—including Iran—remain limited. This is particularly concerning given that regional variations in demographic structure, climatic conditions, and healthcare access may uniquely influence viral transmission and resurgence. Understanding the current seasonality and prevalence of respiratory viruses is critical for outbreak prediction, targeted vaccination strategies (e.g., administering influenza vaccines in autumn and RSV prophylaxis in winter), and optimal allocation of healthcare resources—particularly in LMICs where pediatric populations play a central role in virus transmission within households and communities. In Iran, pandemic-related disruptions in virological monitoring and a research focus on COVID-19–specific outcomes, such as multisystem inflammatory syndrome in children (MIS-C), have limited the availability of comprehensive post-pandemic epidemiological data on other major respiratory pathogens [ 18 , 19 ]. This study aims to systematically characterize the prevalence, seasonal distribution, and co-circulation of RSV, influenza, and SARS-CoV-2 among hospitalized children aged 0–5 years in Hamedan Province, western Iran, during the 2023–2024 post-COVID-19 surveillance period. Using multiplex PCR diagnostics conducted across all counties in the province, this investigation constitutes the first post-pandemic, province-wide molecular surveillance effort of its kind in western Iran. To our knowledge, it is also the first large-scale study in Iran to concurrently assess these three respiratory viruses in hospitalized young children in the post-COVID-19 era. Given Hamedan’s cold, semi-arid climate and its representativeness of much of the western Iranian plateau, the findings from this study offer actionable insights for optimizing public health strategies, including vaccination and surveillance policies, in Iran and comparable resource-limited settings. Materials and methods: Study Design and Population This cross-sectional, province-wide surveillance study was conducted from April 2023 to March 2024 in Hamedan Province, western Iran. Respiratory specimens were collected from 586 inpatient children aged 0–5 years presenting with acute respiratory symptoms (≥ 2 of: fever ≥ 38°C, cough, dyspnea, oxygen saturation < 95%) at various hospitals across Hamedan Province. The sample size of 586 was determined based on regional studies estimating respiratory virus prevalence in pediatric populations, ensuring sufficient power to detect significant differences in positivity rates [ 25 ]. All samples were sent to the Reference Health Laboratory of Hamedan Province for analysis. Inclusion criteria required hospitalization for acute respiratory symptoms, with no hospitalization in the prior 14 days to minimize nosocomial transmission bias. Children with chronic respiratory conditions or recent antibiotic use were excluded. The study was approved by the Ethics Committee of Hamedan University of Medical Sciences (approval code: IR.UMSHA.REC.1403.807), with written informed consent obtained from parents or guardians. Sample Collection and Transport Nasopharyngeal and oropharyngeal swabs were collected using sterile Dacron swabs (Good Care, China) and placed in 4 mL of viral transport medium (VTM). Samples were transported to the virology laboratory under refrigerated conditions (2–8°C) using cold chain packaging to ensure RNA integrity. Sample quality was verified by assessing RNA concentration and purity via spectrophotometry (A260/A280 ratio ≥ 1.8). Molecular Detection of Respiratory Viruses Viral RNA was extracted using the Beh Gen extraction kit (BPVD050, Iran) according to the manufacturer’s protocol. Real-time multiplex PCR was performed using the Geneova diagnostic kit (GA-SARSFluASV.100, Iran; sensitivity 95%, specificity 98%) to detect respiratory syncytial virus (RSV), SARS-CoV-2, and influenza A and B. Influenza A-positive samples were subtyped into H1N1 and H3N2 using gene-specific probes. Primers and probes are detailed in Tables 1 and 2 , including sequences and annealing temperatures. Amplification was conducted on a Rotor-Gene Q thermocycler (QIAGEN), with a cycle threshold (Ct) of < 35 defining positivity for virus-specific amplification curves, as validated by the kit manufacturer’s guidelines. Internal controls, including amplification of the human RNase P gene, were used to verify sample integrity and assay reliability. Table 1 Primers and Probes for Detection of Influenza A and B Primer/probes Sequences 5 , to 3 , InfA Forward GAC CRA TCC TGT CAC CTC TGA C InfA Reverse AGG GCA TTY TGG ACA AAK CGT CTA InfA probe TGC AGT CCT CGC TCA CTG GGC ACG InfB Forward GAG ACA CAA TTG CCT ACC TGC TT InfB Reverse TTC TTT CCC ACC GAA CCA AC InfB probe AGA AGA TGG AGA AGG CAA AGC AGA ACT AGC † Abbreviations: InfA, influenza A; InfB, influenza B. Primer and probe sequences were provided by the World Health Organization (WHO) protocols for influenza typing and are subject to periodic updates by WHO. Samples were tested using a Rotor-Gene Q thermocycler with a cycle threshold (Ct) < 40 for positivity. Table 2 Primers and probes to distinguish between different subtypes of influenza A Primer/probes Sequences 5 , to 3 , InfA Forward SW GCA CGG TCA GCA CTT ATY CTR AG InfA Reverse SW GTG RGC TGG GTT TTC ATT TGG TC SW InfA probe 6-FAM-CYA CTG CAA GCC CAT ACA CAC AAG CAG GCA-BHQ-1 AH 3 Forward AAG CAT TCC YAA TGA CAA ACC AH 3 Reverse ATT GCR CCR AAT ATG CCT CTA GT AH 3 probe 6-FAM-CAG GAT CAC ATA TGG GSC CTG TCC CAG- BHQ-1 H 1 Forward AAA CTA TGC AAA CTA AGA GGG CT H 1 Reverse TGT TTC CAC AAT GTA GGA CCA H 1 probe 6-FAM- CCA GAG TGT GAA TCA CTC TCC ACA-BHQ-1 † Abbreviations: SW, Swine influenza A (H1N1)-related genes; H1, influenza A subtype H1N1; AH3, influenza A subtype H3N2. Primer and probe sequences targeting hemagglutinin (HA) and neuraminidase (NA) genes were provided by the World Health Organization (WHO) protocols for influenza A subtyping and are subject to periodic updates by WHO. Subtyping was performed using a Rotor-Gene Q thermocycler with a cycle threshold (Ct) < 40 for positivity. Data Management and Statistical Analysis Demographic, clinical, and molecular data were recorded in a centralized electronic database and analyzed using SPSS v24 (IBM Corp., Armonk, NY) and GraphPad Prism v9. Visualizations were created using Seaborn v0.11 and Matplotlib v3.5 in Python, with Fisher’s exact tests performed using SciPy v1.8. Descriptive statistics summarized demographics, seasonal trends, and virus-specific positivity rates, with categorical variables reported as frequencies (%) and continuous variables as means (SD). Chi-square tests assessed differences in virus positivity by sex and season. Fisher’s exact tests were used when expected cell counts were < 5. Logistic regression models evaluated associations between virus positivity and demographic factors (age, sex, geographic region). Seasonal trends were analyzed using generalized linear models (GLMs) with a binomial distribution and logit link to model virus positivity. A significance level of p < 0.05 was applied, with 95% confidence intervals (CIs) reported for prevalence estimates. Results From April 2023 to March 2024, 586 respiratory specimens were collected from inpatient children aged 0–5 years (mean age: 2.8 years, SD: 1.4) presenting with acute respiratory symptoms in Hamedan Province, Iran. The study population comprised 366 males (n = 366; 62.5%) and 220 females (n = 220; 37.5%). Geographically, 255 participants (n = 255; 43.5%) resided in Hamedan City, and 331 (n = 331; 56.5%) were from other provincial regions. Sample collection was highest in autumn (n = 264; 45.0%), followed by winter (n = 187; 31.9%), spring (n = 111; 18.9%), and summer (n = 24; 4.1%), as shown in Table 3 . Table 3 Demographic description of the patients Variable Category Number of cases Percentage (%) Sex Female 220 37.5 Male 366 62.5 Case classification Inpatient 586 100 Outpatient 0 0 Region Hamedan 255 44.0 Other regions 331 56.0 Season Winter 187 31.9 Spring 111 18.9 Summer 24 4.1 Autumn 264 45.0 † Data represent 586 children aged 0–5 years hospitalized with acute respiratory symptoms. Percentages are calculated based on the total sample size (n = 586) unless otherwise specified. Multiplex real-time PCR identified 158 children (n = 158; 27.0%, 95% CI: 23.4–30.8) who tested positive for influenza, 37 (n = 37; 6.3%, 95% CI: 4.5–8.6) for SARS-CoV-2, and 35 (n = 35; 6.0%, 95% CI: 4.2–8.2) for RSV. Among influenza cases, 60% were influenza A (H1N1: 35%, H3N2: 25%) and 40% were influenza B (Fig. 1 ). Co-infections were rare (n = 5; 0.9%), with two cases of RSV/SARS-CoV-2, two of RSV/influenza, and one of SARS-CoV-2/influenza, as presented in Table 4 . Fisher’s exact test showed no significant association between co-infection and demographic factors (p = 0.62). Table 4 Co-Infection Patterns Co-Infection Type Number of Cases Percentage (%) RSV/SARS-CoV-2 2 0.34 RSV/Influenza 2 0.34 SARS-CoV-2/Influenza 1 0.17 Total 5 0.9 † Abbreviations: RSV, respiratory syncytial virus; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2. Co-infections were detected using multiplex real-time PCR. No significant association was found between co-infection and demographic factors (Fisher’s exact test, p = 0.62). Virus positivity by sex showed no significant differences, as presented in Table 5 . Influenza was detected in 25.1% of males (n = 92; 95% CI: 20.8–29.8) and 30.0% of females (n = 66; 95% CI: 24.0–36.5) (χ² = 1.91, p = 0.17). RSV was detected in 7.1% of males (n = 26; 95% CI: 4.7–10.2) and 4.1% of females (n = 9; 95% CI: 1.9–7.7) (χ² = 1.72, p = 0.19). SARS-CoV-2 was identified in 6.8% of males (n = 25; 95% CI: 4.4–10.0) and 5.5% of females (n = 12; 95% CI: 2.8–9.5) (χ² = 0.70, p = 0.40). Logistic regression, adjusting for age and region, confirmed no significant sex-based associations for influenza (adjusted OR: 1.28, 95% CI: 0.87–1.89, p = 0.21), RSV (adjusted OR: 1.77, 95% CI: 0.85–3.67, p = 0.13), or SARS-CoV-2 (adjusted OR: 1.24, 95% CI: 0.59–2.61, p = 0.57). Table 5 Virus Positivity by Sex Virus Sex Number Positive Percentage (95% CI) χ² p-value Influenza Male 92 25.1% (20.8–29.8) 1.91 0.17 Female 66 30.0% (24.0–36.5) RSV Male 26 7.1% (4.7–10.2) 1.72 0.19 Female 9 4.1% (1.9–7.7) SARS-CoV-2 Male 25 6.8% (4.4–10.0) 0.70 0.40 Female 12 5.5% (2.8–9.5) † Abbreviations: RSV, respiratory syncytial virus; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; CI, confidence interval. Positivity rates were determined using multiplex real-time PCR. Statistical significance was assessed using chi-square tests (p < 0.05). Seasonal analysis revealed distinct temporal distributions across viruses, as illustrated in Fig. 2 . RSV was detected exclusively in winter (n = 35; 18.2%), with no cases in other seasons (χ² = 13.8, df = 3, p < 0.001). Influenza peaked in autumn (n = 110; 41.3%), followed by winter (n = 43; 23.0%) (χ² = 35.6, df = 3, p < 0.001). SARS-CoV-2 exhibited a spring peak (n = 17; 15.3%), with lower rates in other seasons (χ² = 12.8, df = 3, p = 0.005). Generalized linear models with binomial distribution and logit link confirmed significant seasonal variation for all viruses (p < 0.01). Discussion The COVID-19 pandemic, through widespread non-pharmaceutical interventions (NPIs), profoundly altered the epidemiology of pediatric respiratory viruses, disrupting their seasonality and co-circulation patterns [ 21 , 22 ]. This province-wide surveillance study in Hamedan, a semi-arid region representative of western Iran, conducted from April 2023 to March 2024, provides critical insights into the post-pandemic dynamics of respiratory syncytial virus (RSV), influenza A and B, and SARS-CoV-2 among hospitalized children aged 0–5 years. As the first molecular surveillance effort of its kind in western Iran, this study addresses a significant data gap in the Middle East, where regional factors such as climate and healthcare access uniquely shape viral transmission [ 17 ]. Three key findings emerged: influenza re-established dominance as the primary viral pathogen, RSV exhibited suppressed circulation limited to winter, and SARS-CoV-2 displayed an atypical spring peak, reflecting ecological and immunological shifts in a vulnerable pediatric population. Influenza was detected in 27.0% of hospitalized cases (n = 158, 95% CI: 23.4–30.8), with a pronounced peak in autumn (41.3%, n = 110/264, p < 0.001) and sustained circulation into winter (23.0%, n = 43/187), as shown in Fig. 1 . This resurgence aligns with global trends observed after the relaxation of NPIs, as reported in Australia (winter 2022 surge) and Canada (autumn 2023 peak) [ 23 , 24 ]. The concurrent circulation of influenza A subtypes (H1N1: 35%, H3N2: 25%) and influenza B (40%) underscores a high viral diversity, likely driven by reduced population immunity following limited exposure during the pandemic [ 25 ]. Notably, influenza positivity was higher among females (30.0% vs. 25.1%, p = 0.17), which may reflect sex-based immunological differences or differential exposure patterns, as seen in prior pediatric contact studies in Thailand and elsewhere [ 25 ]. Hamedan’s semi-arid climate, characterized by cold winters and dry conditions, may have amplified autumn transmission, as low humidity facilitates aerosolized viral spread [ 17 ]. The substantial clinical burden in this inpatient cohort emphasizes the urgent need for high influenza vaccination coverage, with campaigns prioritized for early autumn to preempt seasonal peaks in resource-limited settings. RSV circulation was markedly reduced, detected in only 6.0% of cases (n = 35, 95% CI: 4.2–8.2) and confined exclusively to winter (18.2%, n = 35/187, p < 0.001). This contrasts sharply with pre-pandemic RSV prevalence in Iran, which ranged from 16–22% with broader seasonality (autumn to spring) [ 20 , 26 ]. The suppression may stem from multiple factors: residual immunity gaps from decreased exposure during NPIs, sustained behavioral changes (e.g., delayed daycare attendance, improved hygiene), and ecological competition from influenza’s rapid resurgence. In contrast, other regions have reported intense RSV rebounds post-COVID. For example, southern Brazil recorded nearly 3,000 RSV cases in a sharp 2021 resurgence, driven by delayed seasonality [ 27 ], while Sydney’s 2022 winter surge saw elevated hospitalization rates among RSV-infected infants, despite no variant-driven changes [ 28 ]. Hamedan’s cold, semi-arid climate may modulate RSV’s winter confinement, as low temperatures favor its stability [ 17 ]. Given RSV’s historical role as a leading cause of pediatric hospitalization globally, ongoing surveillance is critical to anticipate potential future surges, particularly in regions with limited RSV prophylaxis access. SARS-CoV-2 was identified in 6.3% of cases (n = 37, 95% CI: 4.5–8.6), with an unexpected spring peak (15.3%, n = 17/111, p = 0.005). This deviates from its traditional winter dominance, reflecting a decoupling likely driven by variant evolution and hybrid immune landscapes [ 29 , 30 ]. Multi-region studies, including those in China and New Zealand, have similarly reported spring or summer SARS-CoV-2 surges, attributed to variant-specific transmissibility and waning immunity rather than climatic factors alone [ 31 ]. In Hamedan, the spring signal may indicate waning maternal antibodies, low pediatric vaccine uptake, or regional re-exposure patterns among young children. The absence of genomic sequencing limits our ability to confirm variant-specific drivers, such as Omicron sublineages, which have been linked to altered seasonality globally [ 30 ]. These findings underscore the need for continuous SARS-CoV-2 monitoring, particularly in spring, to guide pediatric vaccination strategies in resource-constrained settings. Co-infections were rare (0.9%, n = 5), significantly lower than global inpatient reports of up to 18% [ 32 ], as detailed in Table 5 . This low rate may reflect temporal separation of viral peaks, with influenza dominating autumn, RSV in winter, and SARS-CoV-2 in spring, potentially coupled with innate immune interference [ 33 ]. For instance, the absence of concurrent RSV and influenza or SARS-CoV-2 infections supports antagonistic interactions, as noted in Lithuanian pediatric studies during 2021–2022 [ 34 ]. However, co-detection does not necessarily imply functional interference, and biological validation is needed. The inpatient focus of this study likely underestimates co-infections, which are more prevalent in milder outpatient settings, as reported in recent Chinese and Australian studies (e.g., up to 25% co-detection in community-acquired infections) [ 35 , 36 ]. These differences highlight the importance of integrating outpatient data to capture broader transmission dynamics. The observed patterns likely result from a complex interplay of immunological, ecological, and behavioral factors. RSV’s suppressed reappearance may reflect an “immunity debt” from reduced exposure during NPIs, compounded by influenza’s ecological dominance [ 37 , 38 ]. Similarly, SARS-CoV-2’s spring surge suggests adaptation to shifting host immunity, potentially exacerbated by low vaccination coverage in Iranian children. Hamedan’s semi-arid climate, with low humidity enhancing influenza transmission and cold winters favoring RSV stability, further modulates these dynamics [ 17 ]. These findings can inform Iran’s national vaccination programs, emphasizing early autumn influenza vaccination and winter RSV prophylaxis to mitigate household transmission in resource-limited settings. This study provides valuable insights but is subject to certain limitations. The focus on an inpatient population with severe cases offers a critical perspective on pediatric disease burden but may limit generalizability to community settings, potentially overestimating severe case prevalence and underestimating community-level co-infections. The absence of genomic sequencing restricts insights into variant-specific seasonality, and the lack of clinical severity scoring precludes detailed outcome comparisons. Future studies could enhance understanding of these evolving patterns by incorporating whole-genome sequencing, longitudinal tracking, and combined outpatient-inpatient surveillance. Despite these limitations, this study provides robust evidence for informing regional health policies. From a policy perspective, these findings necessitate urgent recalibration of public health strategies. Sentinel hospital systems in Iran should prioritize real-time monitoring to detect seasonality shifts and emerging variants. Vaccination campaigns must align with observed trends: influenza vaccines should be administered in early autumn, RSV prophylaxis targeted for high-risk infants in winter, and SARS-CoV-2 monitoring extended into spring. Consideration of viral interference could guide intervention timing, prioritizing dominant pathogens seasonally. In resource-limited settings like Hamedan, where pediatric populations drive household transmission, a data-driven surveillance framework integrating clinical, molecular, and ecological data is essential for effective respiratory virus preparedness in the post-pandemic era. Conclusion This study presents the first province-wide molecular surveillance of RSV, influenza, and SARS-CoV-2 in young children in post-pandemic Iran. The results highlight a shift in seasonal virus dynamics, with influenza regaining dominance, RSV activity restricted to winter, and an atypical spring peak in SARS-CoV-2. The low co-infection rate suggests competitive interactions between viruses in the pediatric population. These observations have critical implications for regional health policy, including the timing of vaccinations and the design of surveillance systems. Ongoing, adaptive monitoring of respiratory pathogens will be essential to mitigate future outbreaks and protect vulnerable pediatric populations in the evolving post-COVID landscape. Abbreviations ARI: Acute Respiratory Infection LMIC: Low- and Middle-Income Country NPI: Non-Pharmaceutical Intervention RSV: Respiratory Syncytial Virus SARS-CoV-2: Severe Acute Respiratory Syndrome Coronavirus 2 PCR: Polymerase Chain Reaction GLM: Generalized Linear Model Ct: Cycle Threshold VTM: Viral Transport Medium MIS-C: Multisystem Inflammatory Syndrome in Children CI: Confidence Interval OR: Odds Ratio SD: Standard Deviation WHO: World Health Organization InfA: Influenza A InfB: Influenza B SW: Swine Influenza A (H1N1)-related genes H1: Influenza A subtype H1N1 AH3: Influenza A subtype H3N2 HA: Hemagglutinin NA: Neuraminidase Declarations Ethics Approval and Consent to Participate This study was approved by the Ethics Committee of Hamadan University of Medical Sciences, Hamadan, Iran (approval code: IR.UMSHA.REC.1403.807). The research was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was obtained from the parents or legal guardians of all participating children prior to their enrollment in the study. Consent for Publication Not applicable Availability of Data and Materials The datasets generated and analyzed during this study are available from the corresponding author upon reasonable request, subject to ethical and privacy restrictions due to the involvement of pediatric patient data. Competing Interests The authors declare no financial or non-financial competing interests related to this study. Funding This study was supported by a grant from Hamadan University of Medical Sciences (project code: 140311029794). The funding body had no role in the study design, data collection, analysis, interpretation, manuscript preparation, or decision to submit for publication. Author Contributions Nastaran Ansari conceptualized and designed the study, supervised its execution, critically reviewed the manuscript, and served as the guarantor for the integrity of the work. Ensieh Masourian conducted the experimental work and drafted the initial manuscript. Somaye Bakhtiari contributed to data acquisition. Ali Teimoori and Farid Azizi Jalilian provided critical revisions for intellectual content. Roya Najafi Vosough performed statistical analysis and data interpretation. All authors contributed to the study design or data analysis, reviewed and approved the final manuscript, and are accountable for all aspects of the work. Acknowledgements This research was part of a Master’s thesis at Hamadan University of Medical Sciences. The authors gratefully acknowledge the staff at the Reference Laboratory of Public Health, Hamadan, for their support in data collection, as well as all study participants. 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Determination of genetic characterization and circulation pattern of Respiratory Syncytial Virus (RSV) in children with a respiratory infection, Tehran, Iran, during 2018-2019. Virus Research. 2021 Nov 1;305:198564. Ferrero F. Impact of the COVID-19 pandemic on the circulation of common respiratory viruses. Arch Argent Pediatr. 2022;120(4):218–9. Gaasbeek CM, Visser M, de Vries RD, Koopmans M, van Binnendijk R, den Hartog G. Impact of COVID-19 Nonpharmaceutical Interventions on Bordetella pertussis, Human Respiratory Syncytial Virus, Influenza Virus, and Seasonal Coronavirus Antibody Levels: A Systematic Review. Open Forum Infect Dis. 2024;11. Chen B, Zhu Z, Li Q, He D. Resurgence of different influenza types in China and the US in 2021. Mathematical biosciences and engineering. 2023;20(4):6327-33. Cheung IM, Paynter J, Broderick D, Trenholme A, Byrnes CA, Grant CC, Huang SQ, Turner N, McIntyre P. Severe Acute Respiratory Infection (SARI) due to Influenza in Post‐COVID Resurgence: Disproportionate Impact on Older Māori and Pacific Peoples. Influenza and other respiratory viruses. 2024 Nov;18(11):e70029. Sawani A, Suwanpakdee D, Watanaveeradej V, Weg A, Ellison DW, Klungthong C, et al. Predictors of Influenza-Associated Hospitalization and Pneumonia in a Pediatric Population in Bangkok, Thailand. Open Forum Infect Dis . 2018;5(Suppl 1):S256–S257. Ramzali M, Salimi V, Cheraghali F, Hosseini SD, Yasaghi M, Samadizadeh S, Rastegar M, Nakstad B, Tahamtan A. Epidemiology and clinical features of respiratory syncytial virus (RSV) infection in hospitalized children during the COVID‐19 pandemic in Gorgan, Iran. Health Science Reports. 2024 Jan;7(1):e1787. Vianna LA, Siqueira M, Volpini LPB, Louro I, Resende P. Seasonality, molecular epidemiology, and virulence of Respiratory Syncytial Virus (RSV): A perspective into the Brazilian Influenza Surveillance Program. PLoS ONE . 2021;16. Walker GJ, Foster CS, Sevendal A, Domazetovska A, Kamalakkannan A, Williams PC, Kim KW, Condylios A, Stelzer-Braid S, Bartlett AW, Rawlinson W. Clinical, genomic, and immunological characterization of RSV surge in Sydney, Australia, 2022. Pediatrics. 2024 Jan 1;153(2):e2023063667. Vattiatio G, Lustig A, Maclaren OJ, Plank M. Modelling the dynamics of infection, waning of immunity and re-infection with the Omicron variant of SARS-CoV-2 in Aotearoa New Zealand. Epidemics. 2022;41:100657. Bobrovitz N, Ware H, Ma X, Li Z, Hosseini R, Cao C, et al. Protective effectiveness of previous SARS-CoV-2 infection and hybrid immunity against the omicron variant and severe disease: a systematic review and meta-regression. Lancet Infect Dis. 2023;23:556–67. Smith TP, Mishra S, Dorigatti I, Dixit MK, Tristem M, Pearse WD. Differential responses of SARS-CoV-2 variants to environmental drivers during their selective sweeps. Sci Rep . 2024;14. Takashita E, Ichikawa M, Fujisaki S, Morita H, Nagata S, Miura H, et al. Antiviral susceptibility of SARS-CoV-2 and influenza viruses from 3 co-infected pediatric patients. Int J Infect Dis . 2024;107134. Mai K, Pan W, Lin Z, Wang Y, Yang Z. Pathogenesis of influenza and SARS-CoV-2 co-infection at the extremes of age: decipher the ominous tales of immune vulnerability. Adv Biotechnol . 2025;3(1):5. Steponavičienė A, Burokienė S, Ivaškevičienė I, Stacevičienė I, Vaičiūnienė D, Jankauskienė A. Influenza and respiratory syncytial virus infections in pediatric patients during the COVID‑19 pandemic: a single-center experience in Vilnius, Lithuania (October 2021–April 2022). Children (Basel) . 2023;10(1):126. Zhang Y, Huang X, Zhang J, Tao Z. Risk factors for hospitalization and pneumonia development of pediatric patients with seasonal influenza during February–April 2023. Frontiers in Public Health. 2024 Jan 5;11:1300228. Grech AK, Foo CT, Paul E, Aung AK, Yu C. Epidemiological trends of respiratory tract pathogens detected via mPCR in Australian adult patients before COVID-19. BMC Infectious Diseases. 2024 Jan 2;24(1):38. Munro AP, House T. Cycles of susceptibility: Immunity debt explains altered infectious disease dynamics post-pandemic. Clinical Infectious Diseases. 2024 Oct 11:ciae493. Czerkies M, Kochańczyk M, Korwek Z, Prus W, Lipniacki T. Respiratory Syncytial Virus protects bystander cells against Influenza A virus infection by triggering secretion of type I and type III interferons. J Virol . 2022;96(3). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 12 Sep, 2025 Reviews received at journal 12 Sep, 2025 Reviewers agreed at journal 02 Sep, 2025 Reviews received at journal 29 Aug, 2025 Reviewers agreed at journal 29 Aug, 2025 Reviewers agreed at journal 29 Aug, 2025 Reviewers agreed at journal 28 Aug, 2025 Reviewers invited by journal 28 Aug, 2025 Editor assigned by journal 21 Aug, 2025 Submission checks completed at journal 19 Aug, 2025 First submitted to journal 21 Jul, 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. 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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-7175880","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":509419086,"identity":"6079c715-4800-4b5b-8f84-4afdc2bbf40c","order_by":0,"name":"Ensieh Masoorian","email":"","orcid":"","institution":"Hamadan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ensieh","middleName":"","lastName":"Masoorian","suffix":""},{"id":509419088,"identity":"8729fc76-5e1a-4bff-99fc-cc4aa7719a9d","order_by":1,"name":"Ali Teimoori","email":"","orcid":"","institution":"Hamadan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Teimoori","suffix":""},{"id":509419089,"identity":"d7181d0e-8cc1-4a5f-86be-f21fdcd24710","order_by":2,"name":"Somaye Bakhtiari","email":"","orcid":"","institution":"Hamadan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Somaye","middleName":"","lastName":"Bakhtiari","suffix":""},{"id":509419092,"identity":"1637cf15-9c61-45fd-a6c2-544ee55b036e","order_by":3,"name":"Farid Azizi Jalilian","email":"","orcid":"","institution":"Hamadan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Farid","middleName":"Azizi","lastName":"Jalilian","suffix":""},{"id":509419093,"identity":"eb63a9bf-7cdb-4155-89ff-e79de6a3af1a","order_by":4,"name":"Roya Najafi Vosough","email":"","orcid":"","institution":"Hamadan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Roya","middleName":"Najafi","lastName":"Vosough","suffix":""},{"id":509419094,"identity":"2d3fcfe5-7148-4b33-ab26-3cd1f7ba6f4c","order_by":5,"name":"Nastaran Ansari","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYDADNvYGBgbGBgjnAHFaeA6QqoVBIgGhBS8wZz/A+Lngj10+n+Qb040/d9gx8LcfYDxcgUeLZU8Cs/TMtmTLNukcs9u8Z5IZJM4kMBw8g0eLwYEEBmneBmYDNpAWxjZmBoYbDAwH8TnQ4PwD5t88f+oN2CTPmN382VbPIE9Qy40ENmketsMGbBI8Zjd42w4DRQhqedhmzdt23ICNJ63sNpDBY3gmsYGAw5IP3+b5U20g3354G9Bh1XJyxw8f/ohPC0Zc8BAZO6NgFIyCUTAK8AEAc8RKTaXvTPMAAAAASUVORK5CYII=","orcid":"","institution":"Hamadan University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Nastaran","middleName":"","lastName":"Ansari","suffix":""}],"badges":[],"createdAt":"2025-07-21 09:53:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7175880/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7175880/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90803734,"identity":"9f924ec3-4c7d-4837-b5d8-6f8c5372d858","added_by":"auto","created_at":"2025-09-08 10:36:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":91736,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePositivity Rates of Respiratory Viruses in Hamedan Province, Iran (2023–2024).\u003c/strong\u003e Stacked bar chart showing the percentage of inpatient children aged 0–5 years (n=586) testing positive for influenza (27.0%, n=158; H1N1: 35%, n=55; H3N2: 25%, n=40; influenza B: 40%, n=63), RSV (6.0%, n=35), and SARS-CoV-2 (6.3%, n=37) via multiplex real-time PCR. Error bars represent 95% confidence intervals for overall positivity rates. Sample sizes (n) are annotated above each bar or segment.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7175880/v1/6b8b9ed89e83f4f2498dfd8e.png"},{"id":90803743,"identity":"65b8b859-4519-4ef8-85ef-fb8bbcb879d0","added_by":"auto","created_at":"2025-09-08 10:36:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":80988,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSeasonal Distribution of Respiratory Virus Positivity in Children Aged 0–5 Years, Hamedan Province, Iran (2023–2024). \u003c/strong\u003eLine plots depict the percentage of RSV, influenza, and SARS-CoV-2 cases detected in each season, analyzed using generalized linear models (GLMs) with a binomial distribution and logit link (p \u0026lt; 0.01 for all viruses). Influenza peaked in autumn (41.3%), RSV in winter (18.2%), and SARS-CoV-2 in spring (15.3%), indicating distinct seasonal circulation patterns.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7175880/v1/cb8949a8ef689662e2a16b9f.png"},{"id":90805443,"identity":"063da64b-737b-4386-a1fe-0281ac21991e","added_by":"auto","created_at":"2025-09-08 10:53:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":869059,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7175880/v1/b577dbc0-8fdb-4b23-a6f5-764ead9aeee7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Post-COVID-19 Seasonality of Influenza, Respiratory Syncytial Virus, and SARS-CoV-2 Among Hospitalized Children in Western Iran: A Molecular Surveillance Study (2023–2024)","fulltext":[{"header":"Background","content":"\u003cp\u003eAcute respiratory infections (ARIs), predominantly driven by viruses such as respiratory syncytial virus (RSV), influenza, and rhinoviruses, remain a leading cause of hospitalization and mortality among children under five years of age. This burden is especially severe in low- and middle-income countries (LMICs), where healthcare systems often face substantial resource constraints [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Prior to the COVID-19 pandemic, ARIs accounted for approximately 15% of global pediatric deaths [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. RSV alone was responsible for over 75,000 deaths and 24.8\u0026nbsp;million infections annually, placing a considerable burden on public health systems worldwide [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe emergence of SARS-CoV-2 and the global implementation of non-pharmaceutical interventions (NPIs)\u0026mdash;including school closures, mask mandates, and travel restrictions\u0026mdash;led to unprecedented disruptions in the transmission dynamics of common pediatric respiratory viruses [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These measures resulted in the temporary suppression of RSV, influenza, and other respiratory pathogens during the early pandemic period, significantly altering previously well-characterized seasonal circulation patterns [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Following the relaxation of NPIs, however, atypical and off-season resurgences of respiratory viruses were documented across multiple regions [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], raising concerns about population-level immunity gaps due to reduced exposure and the long-term effects of altered viral ecology [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFor example, in southwestern Iran, RSV reappeared in spring 2022 after a near-total absence during the height of the pandemic [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Similarly, countries such as Mexico, Saudi Arabia, Canada, China, and Argentina reported increased pediatric hospitalizations related to RSV, influenza, and parainfluenza\u0026mdash;often occurring outside their historical seasonal peaks[\u003cspan additionalcitationids=\"CR13 CR14 CR15\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. These trends suggest a global reset of viral transmission patterns; however, robust, longitudinal surveillance data from Middle Eastern countries [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u0026mdash;including Iran\u0026mdash;remain limited. This is particularly concerning given that regional variations in demographic structure, climatic conditions, and healthcare access may uniquely influence viral transmission and resurgence.\u003c/p\u003e\u003cp\u003eUnderstanding the current seasonality and prevalence of respiratory viruses is critical for outbreak prediction, targeted vaccination strategies (e.g., administering influenza vaccines in autumn and RSV prophylaxis in winter), and optimal allocation of healthcare resources\u0026mdash;particularly in LMICs where pediatric populations play a central role in virus transmission within households and communities. In Iran, pandemic-related disruptions in virological monitoring and a research focus on COVID-19\u0026ndash;specific outcomes, such as multisystem inflammatory syndrome in children (MIS-C), have limited the availability of comprehensive post-pandemic epidemiological data on other major respiratory pathogens [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study aims to systematically characterize the prevalence, seasonal distribution, and co-circulation of RSV, influenza, and SARS-CoV-2 among hospitalized children aged 0\u0026ndash;5 years in Hamedan Province, western Iran, during the 2023\u0026ndash;2024 post-COVID-19 surveillance period. Using multiplex PCR diagnostics conducted across all counties in the province, this investigation constitutes the first post-pandemic, province-wide molecular surveillance effort of its kind in western Iran. To our knowledge, it is also the first large-scale study in Iran to concurrently assess these three respiratory viruses in hospitalized young children in the post-COVID-19 era. Given Hamedan\u0026rsquo;s cold, semi-arid climate and its representativeness of much of the western Iranian plateau, the findings from this study offer actionable insights for optimizing public health strategies, including vaccination and surveillance policies, in Iran and comparable resource-limited settings.\u003c/p\u003e"},{"header":"Materials and methods:","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Population\u003c/h2\u003e\u003cp\u003eThis cross-sectional, province-wide surveillance study was conducted from April 2023 to March 2024 in Hamedan Province, western Iran. Respiratory specimens were collected from 586 inpatient children aged 0\u0026ndash;5 years presenting with acute respiratory symptoms (\u0026ge;\u0026thinsp;2 of: fever\u0026thinsp;\u0026ge;\u0026thinsp;38\u0026deg;C, cough, dyspnea, oxygen saturation\u0026thinsp;\u0026lt;\u0026thinsp;95%) at various hospitals across Hamedan Province. The sample size of 586 was determined based on regional studies estimating respiratory virus prevalence in pediatric populations, ensuring sufficient power to detect significant differences in positivity rates [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. All samples were sent to the Reference Health Laboratory of Hamedan Province for analysis. Inclusion criteria required hospitalization for acute respiratory symptoms, with no hospitalization in the prior 14 days to minimize nosocomial transmission bias. Children with chronic respiratory conditions or recent antibiotic use were excluded. The study was approved by the Ethics Committee of Hamedan University of Medical Sciences (approval code: IR.UMSHA.REC.1403.807), with written informed consent obtained from parents or guardians.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSample Collection and Transport\u003c/h3\u003e\n\u003cp\u003eNasopharyngeal and oropharyngeal swabs were collected using sterile Dacron swabs (Good Care, China) and placed in 4 mL of viral transport medium (VTM). Samples were transported to the virology laboratory under refrigerated conditions (2\u0026ndash;8\u0026deg;C) using cold chain packaging to ensure RNA integrity. Sample quality was verified by assessing RNA concentration and purity via spectrophotometry (A260/A280 ratio\u0026thinsp;\u0026ge;\u0026thinsp;1.8).\u003c/p\u003e\n\u003ch3\u003eMolecular Detection of Respiratory Viruses\u003c/h3\u003e\n\u003cp\u003eViral RNA was extracted using the Beh Gen extraction kit (BPVD050, Iran) according to the manufacturer\u0026rsquo;s protocol. Real-time multiplex PCR was performed using the Geneova diagnostic kit (GA-SARSFluASV.100, Iran; sensitivity 95%, specificity 98%) to detect respiratory syncytial virus (RSV), SARS-CoV-2, and influenza A and B. Influenza A-positive samples were subtyped into H1N1 and H3N2 using gene-specific probes. Primers and probes are detailed in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, including sequences and annealing temperatures. Amplification was conducted on a Rotor-Gene Q thermocycler (QIAGEN), with a cycle threshold (Ct) of \u0026lt;\u0026thinsp;35 defining positivity for virus-specific amplification curves, as validated by the kit manufacturer\u0026rsquo;s guidelines. Internal controls, including amplification of the human RNase P gene, were used to verify sample integrity and assay reliability.\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\u003ePrimers and Probes for Detection of Influenza A and B\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimer/probes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSequences 5\u003csup\u003e,\u003c/sup\u003e to 3\u003csup\u003e,\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInfA Forward\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGAC CRA TCC TGT CAC CTC TGA C\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInfA Reverse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAGG GCA TTY TGG ACA AAK CGT CTA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInfA probe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTGC AGT CCT CGC TCA CTG GGC ACG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInfB Forward\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGAG ACA CAA TTG CCT ACC TGC TT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInfB Reverse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTC TTT CCC ACC GAA CCA AC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInfB probe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAGA AGA TGG AGA AGG CAA AGC AGA ACT AGC\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\u0026dagger; Abbreviations: InfA, influenza A; InfB, influenza B. Primer and probe sequences were provided by the World Health Organization (WHO) protocols for influenza typing and are subject to periodic updates by WHO. Samples were tested using a Rotor-Gene Q thermocycler with a cycle threshold (Ct)\u0026thinsp;\u0026lt;\u0026thinsp;40 for positivity.\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\u003ePrimers and probes to distinguish between different subtypes of influenza A\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimer/probes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSequences 5\u003csup\u003e,\u003c/sup\u003e to 3\u003csup\u003e,\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInfA Forward SW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCA CGG TCA GCA CTT ATY CTR AG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInfA Reverse SW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGTG RGC TGG GTT TTC ATT TGG TC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSW InfA probe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6-FAM-CYA CTG CAA GCC CAT ACA CAC AAG CAG GCA-BHQ-1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAH\u003csub\u003e3\u003c/sub\u003e Forward\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAAG CAT TCC YAA TGA CAA ACC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAH\u003csub\u003e3\u003c/sub\u003e Reverse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATT GCR CCR AAT ATG CCT CTA GT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAH\u003csub\u003e3\u003c/sub\u003e probe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6-FAM-CAG GAT CAC ATA TGG GSC CTG TCC CAG- BHQ-1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH\u003csub\u003e1\u003c/sub\u003e Forward\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAAA CTA TGC AAA CTA AGA GGG CT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH\u003csub\u003e1\u003c/sub\u003e Reverse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTGT TTC CAC AAT GTA GGA CCA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH\u003csub\u003e1\u003c/sub\u003e probe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6-FAM- CCA GAG TGT GAA TCA CTC TCC ACA-BHQ-1\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\u0026dagger; Abbreviations: SW, Swine influenza A (H1N1)-related genes; H1, influenza A subtype H1N1; AH3, influenza A subtype H3N2. Primer and probe sequences targeting hemagglutinin (HA) and neuraminidase (NA) genes were provided by the World Health Organization (WHO) protocols for influenza A subtyping and are subject to periodic updates by WHO. Subtyping was performed using a Rotor-Gene Q thermocycler with a cycle threshold (Ct)\u0026thinsp;\u0026lt;\u0026thinsp;40 for positivity.\u003c/p\u003e\n\u003ch3\u003eData Management and Statistical Analysis\u003c/h3\u003e\n\u003cp\u003eDemographic, clinical, and molecular data were recorded in a centralized electronic database and analyzed using SPSS v24 (IBM Corp., Armonk, NY) and GraphPad Prism v9. Visualizations were created using Seaborn v0.11 and Matplotlib v3.5 in Python, with Fisher\u0026rsquo;s exact tests performed using SciPy v1.8. Descriptive statistics summarized demographics, seasonal trends, and virus-specific positivity rates, with categorical variables reported as frequencies (%) and continuous variables as means (SD). Chi-square tests assessed differences in virus positivity by sex and season. Fisher\u0026rsquo;s exact tests were used when expected cell counts were \u0026lt;\u0026thinsp;5. Logistic regression models evaluated associations between virus positivity and demographic factors (age, sex, geographic region). Seasonal trends were analyzed using generalized linear models (GLMs) with a binomial distribution and logit link to model virus positivity. A significance level of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was applied, with 95% confidence intervals (CIs) reported for prevalence estimates.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFrom April 2023 to March 2024, 586 respiratory specimens were collected from inpatient children aged 0\u0026ndash;5 years (mean age: 2.8 years, SD: 1.4) presenting with acute respiratory symptoms in Hamedan Province, Iran. The study population comprised 366 males (n\u0026thinsp;=\u0026thinsp;366; 62.5%) and 220 females (n\u0026thinsp;=\u0026thinsp;220; 37.5%). Geographically, 255 participants (n\u0026thinsp;=\u0026thinsp;255; 43.5%) resided in Hamedan City, and 331 (n\u0026thinsp;=\u0026thinsp;331; 56.5%) were from other provincial regions. Sample collection was highest in autumn (n\u0026thinsp;=\u0026thinsp;264; 45.0%), followed by winter (n\u0026thinsp;=\u0026thinsp;187; 31.9%), spring (n\u0026thinsp;=\u0026thinsp;111; 18.9%), and summer (n\u0026thinsp;=\u0026thinsp;24; 4.1%), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\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\u003eDemographic description of the patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber of cases\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercentage (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e220\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37.5\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\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e366\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCase classification\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInpatient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e586\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOutpatient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHamedan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e255\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44.0\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\u003eOther regions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e331\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSeason\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWinter\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e187\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.9\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\u003eSpring\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSummer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAutumn\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e264\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45.0\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\u0026dagger; Data represent 586 children aged 0\u0026ndash;5 years hospitalized with acute respiratory symptoms. Percentages are calculated based on the total sample size (n\u0026thinsp;=\u0026thinsp;586) unless otherwise specified.\u003c/p\u003e\u003cp\u003eMultiplex real-time PCR identified 158 children (n\u0026thinsp;=\u0026thinsp;158; 27.0%, 95% CI: 23.4\u0026ndash;30.8) who tested positive for influenza, 37 (n\u0026thinsp;=\u0026thinsp;37; 6.3%, 95% CI: 4.5\u0026ndash;8.6) for SARS-CoV-2, and 35 (n\u0026thinsp;=\u0026thinsp;35; 6.0%, 95% CI: 4.2\u0026ndash;8.2) for RSV. Among influenza cases, 60% were influenza A (H1N1: 35%, H3N2: 25%) and 40% were influenza B (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Co-infections were rare (n\u0026thinsp;=\u0026thinsp;5; 0.9%), with two cases of RSV/SARS-CoV-2, two of RSV/influenza, and one of SARS-CoV-2/influenza, as presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Fisher\u0026rsquo;s exact test showed no significant association between co-infection and demographic factors (p\u0026thinsp;=\u0026thinsp;0.62).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCo-Infection Patterns\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCo-Infection Type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of Cases\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercentage (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRSV/SARS-CoV-2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRSV/Influenza\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSARS-CoV-2/Influenza\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.9\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\u0026dagger; Abbreviations: RSV, respiratory syncytial virus; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2. Co-infections were detected using multiplex real-time PCR. No significant association was found between co-infection and demographic factors (Fisher\u0026rsquo;s exact test, p\u0026thinsp;=\u0026thinsp;0.62).\u003c/p\u003e\u003cp\u003eVirus positivity by sex showed no significant differences, as presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Influenza was detected in 25.1% of males (n\u0026thinsp;=\u0026thinsp;92; 95% CI: 20.8\u0026ndash;29.8) and 30.0% of females (n\u0026thinsp;=\u0026thinsp;66; 95% CI: 24.0\u0026ndash;36.5) (χ\u0026sup2; = 1.91, p\u0026thinsp;=\u0026thinsp;0.17). RSV was detected in 7.1% of males (n\u0026thinsp;=\u0026thinsp;26; 95% CI: 4.7\u0026ndash;10.2) and 4.1% of females (n\u0026thinsp;=\u0026thinsp;9; 95% CI: 1.9\u0026ndash;7.7) (χ\u0026sup2; = 1.72, p\u0026thinsp;=\u0026thinsp;0.19). SARS-CoV-2 was identified in 6.8% of males (n\u0026thinsp;=\u0026thinsp;25; 95% CI: 4.4\u0026ndash;10.0) and 5.5% of females (n\u0026thinsp;=\u0026thinsp;12; 95% CI: 2.8\u0026ndash;9.5) (χ\u0026sup2; = 0.70, p\u0026thinsp;=\u0026thinsp;0.40). Logistic regression, adjusting for age and region, confirmed no significant sex-based associations for influenza (adjusted OR: 1.28, 95% CI: 0.87\u0026ndash;1.89, p\u0026thinsp;=\u0026thinsp;0.21), RSV (adjusted OR: 1.77, 95% CI: 0.85\u0026ndash;3.67, p\u0026thinsp;=\u0026thinsp;0.13), or SARS-CoV-2 (adjusted OR: 1.24, 95% CI: 0.59\u0026ndash;2.61, p\u0026thinsp;=\u0026thinsp;0.57).\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\u003eVirus Positivity by Sex\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVirus\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber Positive\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercentage (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eχ\u0026sup2;\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInfluenza\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25.1% (20.8\u0026ndash;29.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30.0% (24.0\u0026ndash;36.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRSV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.1% (4.7\u0026ndash;10.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.1% (1.9\u0026ndash;7.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSARS-CoV-2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.8% (4.4\u0026ndash;10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.5% (2.8\u0026ndash;9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u0026dagger; Abbreviations: RSV, respiratory syncytial virus; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; CI, confidence interval. Positivity rates were determined using multiplex real-time PCR. Statistical significance was assessed using chi-square tests (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003eSeasonal analysis revealed distinct temporal distributions across viruses, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. RSV was detected exclusively in winter (n\u0026thinsp;=\u0026thinsp;35; 18.2%), with no cases in other seasons (χ\u0026sup2; = 13.8, df\u0026thinsp;=\u0026thinsp;3, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Influenza peaked in autumn (n\u0026thinsp;=\u0026thinsp;110; 41.3%), followed by winter (n\u0026thinsp;=\u0026thinsp;43; 23.0%) (χ\u0026sup2; = 35.6, df\u0026thinsp;=\u0026thinsp;3, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). SARS-CoV-2 exhibited a spring peak (n\u0026thinsp;=\u0026thinsp;17; 15.3%), with lower rates in other seasons (χ\u0026sup2; = 12.8, df\u0026thinsp;=\u0026thinsp;3, p\u0026thinsp;=\u0026thinsp;0.005). Generalized linear models with binomial distribution and logit link confirmed significant seasonal variation for all viruses (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe COVID-19 pandemic, through widespread non-pharmaceutical interventions (NPIs), profoundly altered the epidemiology of pediatric respiratory viruses, disrupting their seasonality and co-circulation patterns [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This province-wide surveillance study in Hamedan, a semi-arid region representative of western Iran, conducted from April 2023 to March 2024, provides critical insights into the post-pandemic dynamics of respiratory syncytial virus (RSV), influenza A and B, and SARS-CoV-2 among hospitalized children aged 0\u0026ndash;5 years. As the first molecular surveillance effort of its kind in western Iran, this study addresses a significant data gap in the Middle East, where regional factors such as climate and healthcare access uniquely shape viral transmission [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Three key findings emerged: influenza re-established dominance as the primary viral pathogen, RSV exhibited suppressed circulation limited to winter, and SARS-CoV-2 displayed an atypical spring peak, reflecting ecological and immunological shifts in a vulnerable pediatric population.\u003c/p\u003e\u003cp\u003eInfluenza was detected in 27.0% of hospitalized cases (n\u0026thinsp;=\u0026thinsp;158, 95% CI: 23.4\u0026ndash;30.8), with a pronounced peak in autumn (41.3%, n\u0026thinsp;=\u0026thinsp;110/264, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and sustained circulation into winter (23.0%, n\u0026thinsp;=\u0026thinsp;43/187), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. This resurgence aligns with global trends observed after the relaxation of NPIs, as reported in Australia (winter 2022 surge) and Canada (autumn 2023 peak) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The concurrent circulation of influenza A subtypes (H1N1: 35%, H3N2: 25%) and influenza B (40%) underscores a high viral diversity, likely driven by reduced population immunity following limited exposure during the pandemic [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Notably, influenza positivity was higher among females (30.0% vs. 25.1%, p\u0026thinsp;=\u0026thinsp;0.17), which may reflect sex-based immunological differences or differential exposure patterns, as seen in prior pediatric contact studies in Thailand and elsewhere [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Hamedan\u0026rsquo;s semi-arid climate, characterized by cold winters and dry conditions, may have amplified autumn transmission, as low humidity facilitates aerosolized viral spread [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The substantial clinical burden in this inpatient cohort emphasizes the urgent need for high influenza vaccination coverage, with campaigns prioritized for early autumn to preempt seasonal peaks in resource-limited settings.\u003c/p\u003e\u003cp\u003eRSV circulation was markedly reduced, detected in only 6.0% of cases (n\u0026thinsp;=\u0026thinsp;35, 95% CI: 4.2\u0026ndash;8.2) and confined exclusively to winter (18.2%, n\u0026thinsp;=\u0026thinsp;35/187, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This contrasts sharply with pre-pandemic RSV prevalence in Iran, which ranged from 16\u0026ndash;22% with broader seasonality (autumn to spring) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The suppression may stem from multiple factors: residual immunity gaps from decreased exposure during NPIs, sustained behavioral changes (e.g., delayed daycare attendance, improved hygiene), and ecological competition from influenza\u0026rsquo;s rapid resurgence. In contrast, other regions have reported intense RSV rebounds post-COVID. For example, southern Brazil recorded nearly 3,000 RSV cases in a sharp 2021 resurgence, driven by delayed seasonality [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], while Sydney\u0026rsquo;s 2022 winter surge saw elevated hospitalization rates among RSV-infected infants, despite no variant-driven changes [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Hamedan\u0026rsquo;s cold, semi-arid climate may modulate RSV\u0026rsquo;s winter confinement, as low temperatures favor its stability [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Given RSV\u0026rsquo;s historical role as a leading cause of pediatric hospitalization globally, ongoing surveillance is critical to anticipate potential future surges, particularly in regions with limited RSV prophylaxis access.\u003c/p\u003e\u003cp\u003eSARS-CoV-2 was identified in 6.3% of cases (n\u0026thinsp;=\u0026thinsp;37, 95% CI: 4.5\u0026ndash;8.6), with an unexpected spring peak (15.3%, n\u0026thinsp;=\u0026thinsp;17/111, p\u0026thinsp;=\u0026thinsp;0.005). This deviates from its traditional winter dominance, reflecting a decoupling likely driven by variant evolution and hybrid immune landscapes [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Multi-region studies, including those in China and New Zealand, have similarly reported spring or summer SARS-CoV-2 surges, attributed to variant-specific transmissibility and waning immunity rather than climatic factors alone [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In Hamedan, the spring signal may indicate waning maternal antibodies, low pediatric vaccine uptake, or regional re-exposure patterns among young children. The absence of genomic sequencing limits our ability to confirm variant-specific drivers, such as Omicron sublineages, which have been linked to altered seasonality globally [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. These findings underscore the need for continuous SARS-CoV-2 monitoring, particularly in spring, to guide pediatric vaccination strategies in resource-constrained settings.\u003c/p\u003e\u003cp\u003eCo-infections were rare (0.9%, n\u0026thinsp;=\u0026thinsp;5), significantly lower than global inpatient reports of up to 18% [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. This low rate may reflect temporal separation of viral peaks, with influenza dominating autumn, RSV in winter, and SARS-CoV-2 in spring, potentially coupled with innate immune interference [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. For instance, the absence of concurrent RSV and influenza or SARS-CoV-2 infections supports antagonistic interactions, as noted in Lithuanian pediatric studies during 2021\u0026ndash;2022 [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. However, co-detection does not necessarily imply functional interference, and biological validation is needed. The inpatient focus of this study likely underestimates co-infections, which are more prevalent in milder outpatient settings, as reported in recent Chinese and Australian studies (e.g., up to 25% co-detection in community-acquired infections) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. These differences highlight the importance of integrating outpatient data to capture broader transmission dynamics.\u003c/p\u003e\u003cp\u003eThe observed patterns likely result from a complex interplay of immunological, ecological, and behavioral factors. RSV\u0026rsquo;s suppressed reappearance may reflect an \u0026ldquo;immunity debt\u0026rdquo; from reduced exposure during NPIs, compounded by influenza\u0026rsquo;s ecological dominance [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Similarly, SARS-CoV-2\u0026rsquo;s spring surge suggests adaptation to shifting host immunity, potentially exacerbated by low vaccination coverage in Iranian children. Hamedan\u0026rsquo;s semi-arid climate, with low humidity enhancing influenza transmission and cold winters favoring RSV stability, further modulates these dynamics [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These findings can inform Iran\u0026rsquo;s national vaccination programs, emphasizing early autumn influenza vaccination and winter RSV prophylaxis to mitigate household transmission in resource-limited settings.\u003c/p\u003e\u003cp\u003eThis study provides valuable insights but is subject to certain limitations. The focus on an inpatient population with severe cases offers a critical perspective on pediatric disease burden but may limit generalizability to community settings, potentially overestimating severe case prevalence and underestimating community-level co-infections. The absence of genomic sequencing restricts insights into variant-specific seasonality, and the lack of clinical severity scoring precludes detailed outcome comparisons. Future studies could enhance understanding of these evolving patterns by incorporating whole-genome sequencing, longitudinal tracking, and combined outpatient-inpatient surveillance. Despite these limitations, this study provides robust evidence for informing regional health policies.\u003c/p\u003e\u003cp\u003eFrom a policy perspective, these findings necessitate urgent recalibration of public health strategies. Sentinel hospital systems in Iran should prioritize real-time monitoring to detect seasonality shifts and emerging variants. Vaccination campaigns must align with observed trends: influenza vaccines should be administered in early autumn, RSV prophylaxis targeted for high-risk infants in winter, and SARS-CoV-2 monitoring extended into spring. Consideration of viral interference could guide intervention timing, prioritizing dominant pathogens seasonally. In resource-limited settings like Hamedan, where pediatric populations drive household transmission, a data-driven surveillance framework integrating clinical, molecular, and ecological data is essential for effective respiratory virus preparedness in the post-pandemic era.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study presents the first province-wide molecular surveillance of RSV, influenza, and SARS-CoV-2 in young children in post-pandemic Iran. The results highlight a shift in seasonal virus dynamics, with influenza regaining dominance, RSV activity restricted to winter, and an atypical spring peak in SARS-CoV-2. The low co-infection rate suggests competitive interactions between viruses in the pediatric population. These observations have critical implications for regional health policy, including the timing of vaccinations and the design of surveillance systems. Ongoing, adaptive monitoring of respiratory pathogens will be essential to mitigate future outbreaks and protect vulnerable pediatric populations in the evolving post-COVID landscape.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eARI: Acute Respiratory Infection\u003c/p\u003e\n\u003cp\u003eLMIC: Low- and Middle-Income Country\u003c/p\u003e\n\u003cp\u003eNPI: Non-Pharmaceutical Intervention\u003c/p\u003e\n\u003cp\u003eRSV: Respiratory Syncytial Virus\u003c/p\u003e\n\u003cp\u003eSARS-CoV-2: Severe Acute Respiratory Syndrome Coronavirus 2\u003c/p\u003e\n\u003cp\u003ePCR: Polymerase Chain Reaction\u003c/p\u003e\n\u003cp\u003eGLM: Generalized Linear Model\u003c/p\u003e\n\u003cp\u003eCt: Cycle Threshold\u003c/p\u003e\n\u003cp\u003eVTM: Viral Transport Medium\u003c/p\u003e\n\u003cp\u003eMIS-C: Multisystem Inflammatory Syndrome in Children\u003c/p\u003e\n\u003cp\u003eCI: Confidence Interval\u003c/p\u003e\n\u003cp\u003eOR: Odds Ratio\u003c/p\u003e\n\u003cp\u003eSD: Standard Deviation\u003c/p\u003e\n\u003cp\u003eWHO: World Health Organization\u003c/p\u003e\n\u003cp\u003eInfA: Influenza A\u003c/p\u003e\n\u003cp\u003eInfB: Influenza B\u003c/p\u003e\n\u003cp\u003eSW: Swine Influenza A (H1N1)-related genes\u003c/p\u003e\n\u003cp\u003eH1: Influenza A subtype H1N1\u003c/p\u003e\n\u003cp\u003eAH3: Influenza A subtype H3N2\u003c/p\u003e\n\u003cp\u003eHA: Hemagglutinin\u003c/p\u003e\n\u003cp\u003eNA: Neuraminidase\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics Approval and Consent to Participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Hamadan University of Medical Sciences, Hamadan, Iran (approval code: IR.UMSHA.REC.1403.807). The research was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was obtained from the parents or legal guardians of all participating children prior to their enrollment in the study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for Publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of Data and Materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during this study are available from the corresponding author upon reasonable request, subject to ethical and privacy restrictions due to the involvement of pediatric patient data.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting Interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no financial or non-financial competing interests related to this study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by a grant from Hamadan University of Medical Sciences (project code: 140311029794). The funding body had no role in the study design, data collection, analysis, interpretation, manuscript preparation, or decision to submit for publication.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthor Contributions\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNastaran Ansari conceptualized and designed the study, supervised its execution, critically reviewed the manuscript, and served as the guarantor for the integrity of the work. Ensieh Masourian conducted the experimental work and drafted the initial manuscript. Somaye Bakhtiari contributed to data acquisition. Ali Teimoori and Farid Azizi Jalilian provided critical revisions for intellectual content. Roya Najafi Vosough performed statistical analysis and data interpretation. All authors contributed to the study design or data analysis, reviewed and approved the final manuscript, and are accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcknowledgements\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis research was part of a Master\u0026rsquo;s thesis at Hamadan University of Medical Sciences. The authors gratefully acknowledge the staff at the Reference Laboratory of Public Health, Hamadan, for their support in data collection, as well as all study participants. Special thanks are extended to Hamadan University of Medical Sciences for their academic and logistical support.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eNair H, Sim\u0026otilde;es EAF, Rudan I, Gessner BD, Azziz-Baumgartner E, Zhang JSF, et al. The burden of respiratory infections in low- and middle-income countries in the era of new diagnostics and vaccines. 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RSV epidemiology in Argentina: From COVID19 to maternal immunization.\u0026nbsp;\u003cem\u003ePediatr Infect Dis J\u003c/em\u003e. 2025;44(2S):S23-S26.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eHemida MG, Alnaeem A. Some one health based control strategies for the Middle East respiratory syndrome coronavirus. One Health. 2020;9:100102.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eReicherz F, Xu RY, Abu-Raya B, Majdoubi A, Michalski C, Golding L, et al. Waning immunity against respiratory syncytial virus during the coronavirus disease 2019 pandemic. J Infect Dis. 2022;226(12):2064-8.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eEden JS, Sikazwe C, Xie R, Deng YM, Sullivan SG, Michie A, et al. Off-season RSV epidemics in Australia after easing of COVID-19 restrictions. Nat Commun. 2022;13(1):2884. doi: 10.1038/s41467-022-30485-3.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eTavakoli F, Izadi A, Yavarian J, Sharifi‐Zarchi A, Salimi V, Mokhtari-Azad T. 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Antiviral susceptibility of SARS-CoV-2 and influenza viruses from 3 co-infected pediatric patients.\u0026nbsp;\u003cem\u003eInt J Infect Dis\u003c/em\u003e. 2024;107134.\u003c/li\u003e\n \u003cli\u003eMai K, Pan W, Lin Z, Wang Y, Yang Z. Pathogenesis of influenza and SARS-CoV-2 co-infection at the extremes of age: decipher the ominous tales of immune vulnerability.\u0026nbsp;\u003cem\u003eAdv Biotechnol\u003c/em\u003e. 2025;3(1):5.\u003c/li\u003e\n \u003cli\u003eSteponavičienė A, Burokienė S, Iva\u0026scaron;kevičienė I, Stacevičienė I, Vaičiūnienė D, Jankauskienė A. Influenza and respiratory syncytial virus infections in pediatric patients during the COVID‑19 pandemic: a single-center experience in Vilnius, Lithuania (October 2021\u0026ndash;April 2022).\u0026nbsp;\u003cem\u003eChildren (Basel)\u003c/em\u003e. 2023;10(1):126.\u003c/li\u003e\n \u003cli\u003eZhang Y, Huang X, Zhang J, Tao Z. Risk factors for hospitalization and pneumonia development of pediatric patients with seasonal influenza during February\u0026ndash;April 2023. Frontiers in Public Health. 2024 Jan 5;11:1300228.\u003c/li\u003e\n \u003cli\u003eGrech AK, Foo CT, Paul E, Aung AK, Yu C. Epidemiological trends of respiratory tract pathogens detected via mPCR in Australian adult patients before COVID-19. BMC Infectious Diseases. 2024 Jan 2;24(1):38.\u003c/li\u003e\n \u003cli\u003eMunro AP, House T. Cycles of susceptibility: Immunity debt explains altered infectious disease dynamics post-pandemic. Clinical Infectious Diseases. 2024 Oct 11:ciae493.\u003c/li\u003e\n \u003cli\u003eCzerkies M, Kochańczyk M, Korwek Z, Prus W, Lipniacki T. Respiratory Syncytial Virus protects bystander cells against Influenza A virus infection by triggering secretion of type I and type III interferons.\u0026nbsp;\u003cem\u003eJ Virol\u003c/em\u003e. 2022;96(3).\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":"journal-of-epidemiology-and-global-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Journal of Epidemiology and Global Health](https://www.springer.com/journal/44197)","snPcode":"44197","submissionUrl":"https://submission.nature.com/new-submission/44197/3","title":"Journal of Epidemiology and Global Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Respiratory syncytial virus (RSV), Influenza A and B, SARS-CoV-2, Pediatric hospitalization, Post-COVID-19 surveillance, Epidemiology, Seasonality, Iran","lastPublishedDoi":"10.21203/rs.3.rs-7175880/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7175880/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to characterize the prevalence, seasonality, and co-infection patterns of respiratory syncytial virus (RSV), influenza A and B, and SARS-CoV-2 among hospitalized children aged 0–5 years in Hamedan Province, a semi-arid region in western Iran, from April 2023 to March 2024. Key research questions included assessing post-pandemic shifts in viral seasonality, evaluating the extent of RSV circulation, and determining the frequency of co-infections in a resource-limited pediatric setting where regional data remain scarce.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003cbr\u003e\nA total of 586 nasopharyngeal/oropharyngeal samples were collected from children aged 0–5 years hospitalized with acute respiratory symptoms (≥2 of: fever ≥38°C, cough, dyspnea, oxygen saturation \u0026lt;95%). Multiplex real-time PCR (sensitivity 95%, specificity 98%) was used to detect RSV, SARS-CoV-2, and influenza A (H1N1, H3N2) and B. Statistical analysis included chi-square and Fisher’s exact tests, and generalized linear models (binomial distribution, logit link).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003cbr\u003e\nAmong 586 inpatients (mean age: 2.8 years; 62.5% male), 27.0% tested positive for influenza (60% influenza A [35% H1N1, 25% H3N2], 40% influenza B), 6.0% for RSV, and 6.3% for SARS-CoV-2. Influenza peaked in autumn (41.3%, p \u0026lt; 0.001), RSV in winter (18.2%, p \u0026lt; 0.001), and SARS-CoV-2 in spring (15.3%, p = 0.005). Co-infections were rare (0.9%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003cbr\u003e\nFindings reveal altered post-pandemic seasonality, reduced RSV activity, and low co-infection rates, suggesting potential ecological and immunological shifts. These trends highlight the need for sustained virus-specific surveillance and recalibrated vaccination strategies—particularly influenza vaccination in autumn and RSV prophylaxis in winter—in resource-limited pediatric settings.\u003c/p\u003e","manuscriptTitle":"Post-COVID-19 Seasonality of Influenza, Respiratory Syncytial Virus, and SARS-CoV-2 Among Hospitalized Children in Western Iran: A Molecular Surveillance Study (2023–2024)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-08 10:36:52","doi":"10.21203/rs.3.rs-7175880/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-13T03:59:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-12T21:59:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"95288269320082614076460820081422526744","date":"2025-09-02T16:59:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-29T18:23:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"215074606613537946621870417339671124350","date":"2025-08-29T13:42:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"129130076711239801695359745976196838819","date":"2025-08-29T09:01:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"78844456793947964256697907644224158568","date":"2025-08-28T21:56:24+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-28T15:09:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-21T09:50:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-19T22:44:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Epidemiology and Global Health","date":"2025-07-21T09:44:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-epidemiology-and-global-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Journal of Epidemiology and Global Health](https://www.springer.com/journal/44197)","snPcode":"44197","submissionUrl":"https://submission.nature.com/new-submission/44197/3","title":"Journal of Epidemiology and Global Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9ea97f25-c90a-4418-957e-788887dfe098","owner":[],"postedDate":"September 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-11-29T11:08:50+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-08 10:36:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7175880","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7175880","identity":"rs-7175880","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}