Dynamics of respiratory virus transmission in children during and after COVID-19 outbreak control in Baiyin, China

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Methods Severe acute respiratory infection (SARI) specimens in hospitalized children were collected from 2021-2023 in Baiyin, China. We conducted real-time fluorescence quantitative PCR (RT-qPCR) to detect various respiratory viruses, including influenza virus (IFV), human respiratory syncytial virus (HRSV), human rhinovirus (HRV), human parainfluenza virus (HPIV), human metapneumovirus (HMPV), human adenovirus (HADV), enterovirus (EV), and human coronavirus (HCoV). The results were statistically analyzed by SPSS 26.0 software. Results A total of 1353 nasopharyngeal swab specimens were collected from children with acute respiratory tract infections (ARTIs) between 2021 and 2023. The male-to-female ratio was 1.49:1 and the overall viral detection rate was 33.85% (458/1353). Data were analyzed by comparing two distinct periods: before the lifting of the COVID-19 control measures (January 1, 2021 –December 6, 2022) and after the lifting of the control measures (December 7, 2022 – December 31, 2023). No statistically significant difference was observed in pathogen-positive detection rates between periods with and without control measures for the age groups ≤1 year (OR: 0.986, 95% CI:0.960-1.013) and 1-3 years (OR: 1.018, 95% CI:0.997-1.060). However, significant differences were found in the 3-6 years (OR:1.097, 95% CI:1.049-1.146) and >6 years (OR:1.099, 95%CI: 1.063-1.138) age groups, as well as in males (OR:1.293, 95%CI:1.156-1.445) and females (OR: 1.354, 95%CI:1.157-1.583). The overall positive detection rate of respiratory viruses increased significantly from 27.84% to 44.84% (OR:1.313, 95% CI:1.198-1.438) after the lifting of COVID-19 control measures. Before the lifting of control measures, the order of respiratory virus-positive detection rates in children was human parainfluenza virus (HPIV) > human respiratory syncytial virus (HRSV) > human adenovirus (HAdV) > human rhinovirus (HRV) > human metapneumovirus (HMPV) > enterovirus (EV) > human coronavirus (HCoV) > influenza virus (IFV). After lifting the control measures, the order was EV > IFV > HAdV > HCoV > HPIV > HRV > HMPV > HRSV. Compared with the period before lifting the control measures, a rightward shift in the peak detection time period was observed for HRV, HMPV, HAdV, and EV. After lifting the control measures, the positive detection rates of IFV (OR:1.090, 95%CI:1.059-1.122), EV (OR:1.102, 95%CI:1.064-1.141), and HCoV (OR:1.043, 95%CI:1.017-1.070) increased significantly. A significant decrease was seen in the positive detection rate for HRSV (OR:0.965, 95%CI:0.946-0.985); and a non-significant decrease in the positive detection rate for HPIV (OR:0.971, 95%CI:0.943-1.001).and no significant difference was seen in the positive detection rate for HMPV (OR:1.019, 95%CI:0.989-1.032).and HADV (OR:1.028, 95%CI:0.999-1.059).Notably, influenza virus rebounded significantly between January and February 2023. Conclusions These findings help elucidate that social interventions can influence the prevalence of childhood respiratory viruses during a unique historical period. The implementation of the COVID-19 outbreak control measures may have curbed the spread of childhood respiratory viruses. Surveillance of respiratory pathogens must be strengthened after control measures are lifted to reduce the risk of respiratory viruses affecting children's health. Children Respiratory viruses Coronavirus disease 2019 Preventive and control measures Figures Figure 1 Figure 2 Figure 3 Introduction Acute respiratory infections (ARIs) are the leading cause of morbidity and mortality among children and infants worldwide, with viruses responsible for approximately 80% of these cases [ 1 ]. Since December 2019, the rapid global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), has triggered a pandemic with unprecedented and far-reaching impacts on society [ 2 ][ 3 ][ 4 ][ 5 ]. In response to the outbreak, countries around the world have implemented non-pharmacological interventions, including wearing face masks, maintaining social distancing, practicing hand hygiene, quarantining, closing schools and malls, and restricting travel to control the spread of the virus. Since the end of January 2020, the Chinese government has enacted a series of effective public health measures [ 6 ], followed by similar initiatives in many other countries [ 7 ]. Research has shown that these interventions not only effectively curtailed the spread of COVID-19 [ 8 ] but also influenced the transmission of various other respiratory pathogens [ 9 ][ 10 ], leading to the early cessation of influenza virus (IFV) transmission in many Northern Hemisphere countries [ 11 ]. Additionally, the epidemic season for human respiratory syncytial virus (HRSV) has undergone significant changes, marked by a notable decline in its global detection rate. However, Sullivan et al. reported an increase in the detection rate of human rhinovirus (HRV) in Australia in May 2020, contrasting with the declining trends observed for most respiratory viruses [ 12 ]. This discrepancy highlights the evolving epidemiological trends of respiratory viruses that warrant further investigation. On December 7, 2022, China comprehensively adjusted and optimized its epidemic prevention and control strategy. Subsequently, the Omicron variant spread rapidly, leading to a peak in cases. Control measures were fully lifted, mask usage declined significantly, public activities resumed, and schools and public spaces reopened. To understand the changes in the spectrum of common respiratory viruses before and after the implementation of these control measures, this study investigates the detection rates of respiratory viruses in children in Baiyin, Gansu Province, China. Baiyin, located in northwest China, has a resident population of over 1.5 million people and is characterized by unique climatic and demographic features. However, its healthcare infrastructure is relatively underdeveloped, contributing to an increased disease burden in the region. To our knowledge, no prior studies have been conducted in this area. Therefore, this retrospective study analyzes respiratory viruses in clinical samples from children with severe acute respiratory infections (SARI) collected from January 2021 to December 2023 in Baiyin. We further examine the changes in respiratory virus profiles before and after the control measures for COVID-19, aiming to enhance preventive strategies for viral infections in children. Materials and methods Source of specimen In this study, children hospitalized with acute respiratory tract infections in one hospital in Baiyin City, Gansu Province, from January 2020 to December 2023, were selected as study subjects. Inclusion criteria: ①age ≤ 16 years old; ②symptoms consistent with acute infection (at least one of the following): fever, chills, abnormal white blood cell distribution count (decreased or increased); ③clinical symptoms (at least one of the following): runny nose, coughing and sputum, wheezing, pharyngeal and laryngeal edema or soreness, chest tightness and chest pain, fatigue, abdominal pain and diarrhea. Nasopharyngeal swab specimens were collected by qualified medical staff of the sentinel hospitals in strict accordance with the monitoring program, and case information was collected. Specimens were stored at 4 ℃ for 24 h after collection and transported to the laboratory, and specimens sent for examination for more than 24 h were stored at -70℃. Reagents In this study, the total viral nucleic acid extraction reagent was the Rapid Nucleic Acid Extraction Kit by Magnetic Bead Method (Xi'an Tianlong Science and Technology Co., Ltd., China), the respiratory virus detection was the 22 respiratory pathogen nucleic acid detection kit (Beijing Jocheng Huisheng Biotechnology Co., Ltd., China), and the nucleic acid extraction instrument was the fully automated nucleic acid extractor (Xi'an Tianlong Science and Technology Co., Ltd., China), The instrument for respiratory virus detection was Q5 real-time fluorescence quantitative PCR instrument (ABI, USA).. Nucleic acid testing of specimens In this study, Total viral nucleic acids were extracted from specimens using the Xi'an Tianlong Nucleic Acid Rapid Extraction Kit (Xi'an Tianlong Science and Technology Co., Ltd., China) according to the manufacturer's instructions. Common respiratory viruses, including influenza virus (IFV), human respiratory syncytial virus (HRSV), human rhinovirus (HRV), human parainfluenza virus (HPIV), human metapneumovirus (HMPV), human adenovirus (HADV), enterovirus (EV), and human coronavirus (HCoV), were detected by quantitative real-time PCR (qPCR) using a 22-target respiratory pathogen nucleic acid detection kit Statistical analysis The cases were grouped by age based on the collected demographic information: ≤1 year, 1–3 years, 3–6 years, and > 6 years. IBM SPSS software (version 26.0) was used for the processing and statistical analysis. Data are presented as numbers and percentages (%). Continuous variables with normal distribution were compared using t-tests, whereas non-normally distributed variables were analyzed using the Mann-Whitney U test. Categorical data were analyzed using the chi-squared test or Fisher's exact test. Chi-square tests and cross-tabulations were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs). Statistical significance was set at P < 0.05. Graphs were created using GraphPad Prism 8.0. Results Detection of respiratory viruses in children A total of 1,353 acute respiratory cases in children were collected from January 1, 2021, to December 31, 2023. There were 809 male (809/1353, 59.79%) and 544 female (544/1353, 40.21%) cases. The male to female ratio was 1.49:1. 363 cases were ≤ 1 year, 387 cases were 1–3 years, 387 cases were 3–6 years, and 216 cases were > 6 years. Except for the age groups ≤ 1year and 1-3years,the difference in the detection rate of pathogens in the other age groups was statistically significant (P < 0.005).In 2021, there were 85 (85/315, 26.98%) positive specimens for either virus, with the top 3 viruses being HPIV, EV, and HRSV. 81 (81/315, 25.71%) of the 85 positive specimens were found to be infected with one virus, and 4 (4/315, 1.27%) were found to be infected with multiple viruses; In 2022, there were 160 (160/565, 28.32%) positive specimens for either virus, with the top 3 viruses being HADV, HRSV, and HPIV. 146 (146/565, 25.84%) of the 160 positive specimens that tested positive for one viral infection, and 14 (14/565, 2.48%) tested positive for one viral infection; and 2023, there were 213 positive specimens tested positive for multiple viral infections. There were 213 (213/473, 45.03%) virus-positive specimens, and the top three viruses were EV, IFV, and HADV. Of the 213 positive samples, one viral infection was detected in 186 (186/473, 39.32%), and multiple viral infections were detected in 27 (27/473, 5.71%), and the differences in detection rates between the years 2021–2023 among the The difference in the detection rate of respiratory viruses was statistically significant (P < 0.05) The results are detailed in Table 1 Table 1 Overall frequency of 8 respiratory pathogens in different years Characteristics 2021 (n = 315) 2022 (565) 2023 (473) P -value (χ²) Age positive,n(%) ≤ 1year 11 (3.49) 45 (7.96) 24 (5.07) 0.017(8.1982) 1-3years 34 (10.79) 60 (10.62) 58 (12.26) 0.678(0.777) 3-6years 29 (9.21) 43 (7.61) 77 (16.28) 6years 11 (3.49) 12 (2.12) 54 (11.42) < 0.001(45.122) Gender Male (cases) 199 320 290 positive, n(%) 57 (28.64) 78 (24.38) 124 (42.76) < 0.001(25.000) Female (cases) 116 245 183 positive, n(%) 28 (24.14) 82 (33.47) 89 (48.63) < 0.001(20.224) Pathogens positive, n(%) Total 85 (26.98) 160 (28.32) 213 (45.03) < 0.001(40.763) Mixed 4 (1.27) 14 (2.48) 27 (5.71) 0.001(13.754) Influenza virus 0(0) 6 (1.06) 42 (8.88) < 0.001(61.085) Human respiratory syncytial virus 16 (5.08) 31 (5.49) 9 (1.90) 0.010(9.250) Human rhinovirus 3 (0.95) 28 (4.96) 25 (5.29) 0.005(10.579) Human parainfluenza virus 45 (14.29) 29 (5.13) 27 (5.71) < 0.001(27.777) Human metapneumovirus 2 (0.63) 23 (4.07) 18 (3.81) 0.013(8.689) Human adenovirus 5 (1.59) 35 (6.19) 34 (7.19) 0.002(12.459) Enterovirus 17 (5.40) 8 (1.42) 56 (11.84) < 0.001(49.954) Human coronavirus 3 (0.95) 17 (3.01) 30 (6.34) < 0.001(16.721) Age distribution of respiratory viruses in children IFV was not detected in two age groups,≤1 year and 3–6 years, and had low positive detection rates in all other age groups in 2021 and 2022, but its positive detection rate increased with age in 2023 (Fig. 1 a). HRSV had positive detection rates in children in all age groups in 2023, except for children > 6 years of age, which were lower than in 2021 and 2022 (Fig. 1 b). The positive detection rates of HRV and HADV in 2022 and 2023 showed an opposite trend in the age groups of ≤ 1 year and 3–6 years (Fig. 1 c,f). Respiratory viral infections were more common in children aged 1–3 years, with a clear umbrella distribution of HPIV, HMPV, EV, and HCOV (Fig .1d, e, g, h). Detection of respiratory viruses before and after the lifting of control measures Before and after the lifting of control measures, the difference in the positive detection rate of pathogens was statistically significant (p < 0.005) in all age groups except the ≤ 1 year and 1–3 years age groups. Before the lifting of control measures, the total positive detection rate of respiratory viruses was 27.84%, and the mixed positive detection rate was 2.05%, and after the lifting of control measures, the total positive detection rate increased to 44.84% (OR:1.313, 95% CI:1.198–1.438), and the mixed positive detection rate increased to 5.71% (OR:1.014–1.064, 95% CI:1.014–1.064). The positive detection rates for IFV, HRV, HMPV, HADV, EV, and HCOV were 0.68%, 3.52%, 2.84%, 4.55%, 2.84%, and 2.27%, respectively, before the control measures were lifted. After the control measures were lifted, the positive detection rates for IFV, HRV, HMPV, HADV, EV, and HCOV increased to 8.88% (OR:1.090, 95% CI:1.059–1.122), 5.29% (OR:1.019, 95%CI:0.994–1.044), 3.81% (OR:1.010,95% CI:0.989–1.032),7.19% (OR:1.028, 95% CI: 0.999–1.059),11.84% (OR:1.102, 95%CI:1.064–1.141),and6.34% (OR:1.043, 95%CI: 1.017–1.070), and the six viruses with positive detection rates were significantly higher than those before the lifting of controls, with a significant increase in the positive detection rate of three pathogens, IFV, EV and HCOV, and a non-significant increase in the positive detection rate of. However, after the control measures were lifted, the positive detection rates of HRSV and HPIV decreased from 5.34% and 8.41% before the control was lifted to 1.09% (OR: 0.965, 95% CI: 0.946–0.985) and 5.71% (OR:0.971, 95% CI:0.943–1.001), a nonsignificant decrease in the positive detection rate of HRSV and a nonsignificant increase in the positive detection rate of HPIV. HRSV was significantly reduced, and the positive detection rate of HPIV was not significantly reduced. The order of respiratory virus positivity in children before the lifting of control measures was HPIV > HRSV > HADV > HRV > HMPV > EV > HCOV > IFV; after the lifting of control measures, the order was EV > IFV > HADV > HCOV > HPIV > HRV > HMPV > HRSV. The results are shown in Table 2 . Table 2 Overall frequency of 8 respiratory pathogens in different years before and after the lifting of control measures Characteristics 2021–2022 (n = 880) 2023 (473) P -value (χ²) OR 95% CI Age positive,n(%) ≤ 1year 56 (6.36) 24 (5.07) 0.338(0.920) 0.986 0.960 to 1.013 1-3years 94 (10.68) 58 (12.26) 0.380(0.770) 1.018 0.997 to 1.060 3-6years 72 (8.18) 77 (16.28) 6years 23 (2.61) 54 (11.42) < 0.001(44.417) 1.099 1.063 to 1.138 Gender Male (cases) 519 290 positive, n(%) 135 (26.01) 124 (42.76) < 0.001(23.973) 1.293 1.156 to 1.445 Female (cases) 361 183 positive, n(%) 110 (30.47) 89 (48.63) < 0.001(17.269) 1.354 1.157 to 1.583 Pathogens positive, n(%) Total 245 (27.84) 213 (45.03) < 0.001(40.602) 1.313 1.198 to 1.438 Single 227 (25.80) 186 (39.32) < 0.001(26.548) 1.223 1.126 to 1.328 Mixed 18 (2.05) 27 (5.71) < 0.001(12.836) 1.039 1.014 to 1.064 Influenza virus 6 (0.68) 42 (8.88) < 0.001(60.419) 1.090 1.059 to 1.122 Human respiratory syncytial virus 47 (5.34) 9 (1.90) 0.002(9.166) 0.965 0.946 to 0.985 Human rhinovirus 31 (3.52) 25 (5.29) 0.121(2.409) 1.019 0.994 to 1.044 Human parainfluenza virus 74 (8.41) 27 (5.71) 0.071(3.249) 0.971 0.943 to 1.001 Human metapneumovirus 25 (2.84) 18 (3.81) 0.335(0.930) 1.010 0.989 to 1.032 Human adenovirus 40 (4.55) 34 (7.19) 0.041(4.156) 1.028 0.999 to 1.059 Enterovirus 25 (2.84) 56 (11.84) < 0.001(44.259) 1.102 1.064 to 1.141 Human coronavirus 20 (2.27) 30 (6.34) < 0.001(14.317) 1.043 1.017 to 1.070 Monthly distribution of respiratory viruses before and after lifting of control measures Both before and after the lifting of controls, the positive detection rate of IFV was highest in February. However, the positive detection rate of IFV was significantly higher after the lifting of control measures (P < 0.001). It is noteworthy that IFV was not detected in 2021 (Fig. 2 a).The positive detection rate of HRSV showed a decreasing trend from January to August in 2021–2022, and then increased from September onwards, however, after the lifting of the control measures, surprisingly, there were only two small peaks of epidemiology in June and October and they were lower than the average level before the lifting of the control measures (Fig. 2 b). HRV was predominantly prevalent from June to September, and it is noteworthy that the peak of HRV prevalence shifted rightward from June before the lifting of the control measures to August after the lifting of the control measures (Fig. 2 c). 2023 had no detectable HPIV in January and March-May, and the prevalence trend was in the form of the letter “W + V” before the lifting of the control measures, However, after the lifting of control measures, the epidemiological trend was “M+Ʌ” (Fig. 2 d). HMPV epidemics appeared in February before the lifting of control measures and peaked in June, but after the lifting of control measures, the epidemiological trend began in May and peaked in July, which was a backward shift of the epidemiological peak (Fig. 2 e). From 2021 to 2022, the positive detection rate of HADV declined rapidly from January, was lowest in February, and then began to rise again reaching a small peak in March and then began to decline, with no detections in May, followed by a yearly peak in June, and then the subsequent prevalence levels tumbled but were below the June level, whereas after the lifting of the control measures, the prevalence trend of HADV in the period from January to May and in October to December was the opposite of that before the lifting of the control measures, the opposite before the lifting of control measures, but the same epidemiologic trend from May to October. It is worth noting that although the epidemiological trends from May to October are the same, the peak of the epidemiological peak is shifted to the right (Fig. 2 f). Before the lifting of control measures, the epidemic of EV started in March and reached the peak in July, with an interruption in August, and then rose to October and then declined, with a detection in January 2023, no detection from February to April, and the level of prevalence in May gradually rose to the peak in August, and then declined. There was a gradual increase in prevalence levels in May to a peak in August, followed by a gradual decline. It is worth noting that although the overall epidemiological trend of EV was similar before and after the lifting of control measures, the peak of the epidemic was shifted to the right at the same time (Fig. 2 g), and the epidemiological trend of HCOV was similar throughout the year before and after the lifting of control measures, but the positive detection rate of HCOV after the lifting of control measures was much higher than that before the lifting of control measures (Fig. 2 h). Neighbors were surprised by the low detection rate of all viruses except IFV from January to May 2023 (Fig. 2 ). Changes in respiratory viral profiles in different age groups before and after control measures were lifted Information on child cases was categorized into four groups based on age: ≤1 year age group, 1–3 years age group, 3–6 years age group, and > 6 years. Before the control measures were lifted, in each age group, the top three pathogens were HRSV, HRV, and HADV in the ≤ 1 year group (Fig. 3 a); HPIV, HRSV, HADV, and EV in the 1–3 years group (Fig. 3 b); HPIV, HRSV, and HADV in the 3–6 years group (Fig. 3 c); and HPIV, HRV, and EV in the > 6 years group (Fig. 3 d). After the control measures were lifted, in each age group positive detection rates, the top three pathogens were, respectively, HPIV, IFV, and HCOV in the ≤ 1 year group (Fig. 3 a); HCOV, HRV, HPIV, and EV in the 1–3 years group (Fig. 3 b); and EV, IFV, and HADV in the 3–6 years group and in the > 6 years group. For HPIV positive detection rates, positive detection rates in both the 1–3 years and 3–6 years groups decreased, while the HRSV positive detection rate decreased in the ≤ 1 year, 1–3 years, and 3–6 years groups, and the detection rates of HRV, HMPV, HADV, and HCOV decreased in the 1 year group but increased at all other ages, including IFV. The HPIV was high in children under 3 years of age, both before and after the lifting of controls (Fig. 3 ). Discussion Viruses are the main pathogens that cause respiratory infections in children[ 13 ]. As the COVID-19 pandemic developed, outbreaks in countries around the world gradually subsided. The resumption of global travel, relaxation of protective measures, and reopening of public places and schools have led to the resurgence of childhood respiratory viruses. Numerous studies have shown that the implementation of global NPIs has significantly reduced the incidence of most respiratory pathogens and altered the epidemiological characteristics[ 14 ][ 15 ]. This study analyzed the detection of respiratory viruses in clinical samples of children with severe acute respiratory infections (SARI) from January 2021 to December 2023 in Baiyin City, Gansu Province, China. The results showed that the overall positive detection rate of common respiratory viruses among children in this study was 33.85% (458/1353), which was lower than that of Kunming in China (52.45%) [ 16 ] and Xuzhou in China (36%) [ 17 ] but higher than that of Australia (32.10%) [ 18 ], suggesting that there may be geographic variations in the prevalence of respiratory viruses in children. Before lifting the control measures, the positive detection rate of common respiratory viruses in the children was 27.84% (245/880), and there was no statistically significant difference in respiratory virus infection rate between the sexes of children ; after the lifting of control measures, the positive detection rate of common respiratory viruses in children was 45.03% (213/473), and there was no statistically significant difference in respiratory virus infection rate between the sexes of children. This may be due to the fact that respiratory virus transmission was restricted during the pandemic to control the spread of SARS-CoV-2 by increasing social distances, decreasing people's mobility, and other related PHSMs. Since December 2022, control measures were lifted, and normal production and life order resumed. The increase in people's mobility, the number of gatherings, and the decrease in the proportion of people wearing masks and the "immunization debt" during the control period created favorable conditions for the spread of respiratory viruses. The data showed that there was no significant change in the rate of respiratory virus positivity in children under 3 years of age before and after the lifting of controls, whereas the difference in the rate of positivity in children over 3 years of age was significant. This is because children over three years of age are school-age children in a broader sense than children under three years of age, and the increase in congregation after the lifting of controls has led to an increase in contact with children and other objects and a greater ability to move on their own, which may lead to an increased risk of infection from touching the mouth and nose. Before lifting the control measures, the order of respiratory virus positivity in children was as follows: HPIV > HRSV > HADV > HRV > HMPV > EV > HCOV > IFV, and after lifting the control measures: EV > IFV > HADV > HCOV > HPIV > HRV > HMPV > HRSV. The order of positive respiratory virus detection in this study changed significantly before and after lifting the controls, reflecting the susceptibility of controls to different viruses and their respective transmission dynamics after lifting. This may involve a number of factors, such as virus characteristics, immunization gaps, cross-immunization, climatic influences, and changes in host susceptibility. After the lifting of control measures, EV: increased contact between children and relaxation of hygiene practices may lead to rapid transmission of enteroviruses via the fecal-oral and respiratory routes, which can result in a rapid rise in the EV rank; IFV: coincides with the epidemic season for IFV. In addition, the fact that many people were not infected with influenza during the control period resulted in a large immune gap in the population, making them more susceptible to infection after the de-escalation. HADV: The rise in may indicate that its ability to spread through contact sequencing of HADV was unleashed after. The opening of schools and childcare centers and the de-escalation accelerated the spread of HADV. HCOV: The detection of coronavirus viruses other than SARS-CoV-2 may have increased, or the infection rate may have risen due to the decline in the immunity of the population; HPIV: Its decrease in sorting may be due to competing transmission of other viruses (EV and IFV) or to the effect of previously accumulated immunity on the suppression of HPIV transmission; HRV: The decline in HRV sorting may be due to a more prominent prevalence of other viruses, resulting in a relative decline in HRV sorting. HMPV: HMPV's sorting is still relatively backward, which may indicate that it has a relatively weak ability to transmit; HRSV: It is worth noting that RSV sorting declined significantly after the lifting of controls, which is consistent with the study conducted in Ningbo City, Zhejiang Province [ 19 ]. This may be attributed to the co-prevalence of other viruses interfering with RSV transmission, suppression of RSV prevalence by accumulated immunity during NPIs, etc., leading to a lower ranking. Before the lifting of control measures, the top three viruses were HPIV (8.41%), HRSV (5.34%), and HADV (4.55%); after the lifting of control measures, the top three viruses were EV (11.84%), IFV (8.88%), and HADV (7.19%), and the intensity of prevalence of EV and IFV exceeded that of HPIV and HRSV. EV has become the dominant viral pathogen. This may be due to factors such as the lifting of NPI measures, immune debt, interactions between viruses, and changes in behavioral patterns. The respiratory viruses with the highest detection rates differed from those reported in studies in other geographic regions of China [ 21 ], which may be attributed to the differences in the study population and sample size. In addition, control measures implemented during the outbreak may have altered the prevalence of certain viruses, and epidemiological interference between respiratory viruses can affect virus frequencies at both the host and population levels and interfere with the subsequent frequency and duration of a particular virus or virus type [ 20 ][ 21 ]. After lifting the control measures, the epidemiologic activity of five respiratory viruses (IFV, HRV, HMPV, HADV, EV, and HCOV) other than HRSV and HPIV increased. From the study results, it appears that after the lifting of control measures, HRV and HMPV epidemics peaked approximately 1–3 months later than before the lifting of control measures, but this result needs to be verified by reviewing the pre-COVID-19 viruses for comparison. In addition, the single infection rate before the lifting of the control measures (25.80%) was significantly lower than that after the lifting of the control measures (39.32%). The lower total positive detection rate of the virus during the NPIs (27.84%) led to a significantly lower rate of mixed infections before the lifting of the control measures (2.08%) than after the lifting of the measures (5.71%), which may also be related to the social environment, the changes in the immunity of the population, the timing of the pathogen itself, changes in its activity patterns, population mobility, and natural environments, as well as the changes in its behavior. The change may also be related to the combination of multiple influencing factors such as social environment, changes in immunity of the population, the time of the pathogen's own activity, regularity, population mobility, and changes in the natural environment [ 22 ][ 23 ][ 24 ]. The positivity rates of HRSV and HPIV decreased after the lifting of control measures, whereas the IFV increased significantly, consistent with the results of the study by Zhang et al.[ 25 ]. From January to May, after the lifting of controls, there was an interruption in the detection rate of most viruses and a rightward shift in the peak prevalence. It is possible that the rapid spread of SARS-CoV-2 after the lifting of controls suppressed the spread of other respiratory viruses during the same period, leading to a delay in the peak epidemiological activity of other pathogens. This suggests that the increased detection of SARS-CoV-2 may have produced some degree of interference at the host level, which led to a temporary reduction in host susceptibility to viral infections and induced a period of inappropriate immunity to other pathogens. The specific mechanism of interference may be related to the sustained upregulation of COVID-19 interferon-stimulated genes, chemokines, and cytokines [ 26 ]. The elevated IFV detection rate in this study was highly significant (P < 0.001) and similar to the results of multinational studies in the northern hemisphere [ 27 ][ 28 ]. This may be related to the higher virulence and pathogenicity of the original SARS-CoV-2 strain, which attacked the host more intensely and for a longer period of time [ 29 ], which in turn reduced the chances of influenza viruses infecting the host, and hence the absolute limitation of influenza activity in the first year of the COVID-19 pandemic. Reduced virulence and severity of the Delta and Omicron strains increased the probability of influenza infection in the host. This may explain why influenza activity increased after the delta pandemic, or it may be that the lifting of controls, increased congregational activity, decreased rates of mask wearing, and untimely vaccination during the control period created favorable conditions for influenza virus transmission and infection. Most of the viruses had the highest detection rate in the 1–3 years group, consistent with the findings of Jartti et al. [ 30 ], showing a clear umbrella distribution feature, which is consistent with the findings of Kunming, Yunnan Province, China [ 16 ]. Before the lifting of control measures, children were in a low prevalence state in the whole age group, which may be related to strict control measures. After lifting the control measures, the IFV infection rate showed a positive correlation with age, which may be because IFV antibody duration is short and socialization activities increase the risk of transmission. In contrast to IFV, HRSV showed a roughly negative correlation with age, and related studies showed that the activities of IFV and HRSV in the host body had interference [ 31 ]. The susceptible age group for EV changed from 1–3 years before control lifting to 3–6 years after control lifting. The reason may be that children in the 1–3 years group before the lifting of control measures had relatively low immune function and were too small to ensure wearing of masks. After the lifting of control measures, children in the 3–6 years group were more likely to come into contact with a variety of respiratory pathogens because their immune system had not yet matured fully and also because of their intensive living and daily routine environment and wide range of activities, which naturally resulted in a higher risk of infection. Specifically, the children were susceptible to respiratory pathogens both before and after lifting the control measures. This result is consistent with those of previous studies [ 32 ][ 33 ]. Changes in the epidemiological patterns of respiratory multipathogens may pose a great challenge to clinical diagnosis and treatment. In general, the similarity of symptoms and signs of respiratory multipathogen infections makes it difficult to rapidly detect and identify specific respiratory pathogens, and the lack of specific therapeutic drugs and their empirical use may lead to increased drug resistance. In addition to non-pharmacological interventions to change the epidemiology of viruses, mutual interference between viruses is one of the hypotheses to change the epidemiology of viruses. Studies have demonstrated potential interference between different respiratory viruses [ 34 ]. For example, surveillance of respiratory viral infections in Norway has shown that RSV is rarely detected during influenza epidemics, suggesting activity interference between the two [ 31 ]. Mutual interference between IFV and HRSV has also been reported in other countries during different winters [ 35 ][ 36 ]. HRSV spread in Victoria, Australia, from 2002 to 2017, on average, 6 weeks earlier than IFV-A. During the 2009 influenza pandemic, shifts in influenza activity were associated with changes in seasonal HRSV activity, further supporting a negative interference effect between viruses [ 37 ][ 38 ][ 39 ]. These findings suggest a positive or negative epidemiological pattern of correlation between respiratory viruses [ 40 ]. Although we achieved better results, this study has some limitations. First, the study only included hospitalized children in a single region, which may not be fully representative of the wider population of children with ARTIs. Second, the role of respiratory multipathogen influences may change with an increase in the number of regions covered, the population of children, and the duration of future studies. Second, the study did not include data from other cities, which limits our ability to generalize the epidemiological model of respiratory multi-pathogens to a wider region. Finally, this study included only eight common respiratory viruses, which may have overlooked the infection burden of other pathogens. To overcome these limitations, future studies need to further explore more regions and track for longer periods to validate the consistency of the results, as well as examine other potential influences such as geographic location, climatic factors, socioeconomic status, and cultural practices on the transmission of respiratory diseases. Studies need to be expanded to fully capture the long-term trends and changes in pathogen profiles. Conclusion To understand the changes in respiratory viral profiles among children in Baiyin, China, during this period, it is essential to consider the impact of evolving outbreak prevention and control measures, alongside the disruptions caused by the COVID-19 pandemic. These findings highlight the potential to glean valuable insights from the experiences of COVID-19 prevention and control, which could be instrumental in mitigating the risks that respiratory viruses pose to children's health. Abbreviations COVID-19 Coronavirus disease 2019 SARS-CoV-2 Severe acute respiratory syndrome coronavirus 2 SARI Severe acute respiratory infection IFV Influenza virus HRSV Human respiratory syncytial virus HRV Human rhinovirus HPIV Human parainfluenza virus HMPV Human metapneumovirus HADV Human adenovirus EV Enterovirus ) HCOV Human coronavirus PHSW Public Health and Social Measure HF High frequency NPIs Non-Pharmaceutical Interventions ARTIs Acute Respiratory Tract Infections Declarations Acknowledgements We thank all the participants of this study. Availability of data and materials All data geneerated or analyzed during this study are included in this published article. Fundings This work was supported by the Gansu Provincial Key Research and Development Program-Social Development Field Program Project (Grant NO. 23YFFA0051) and the Gansu Provincial Health Industry Science and Technology Innovation Major Project (Grant NO. GSWSKY2024-022). Ethics approval and consent to participate This study was approved by the Ethical Committee of Gansu Provincial Center for Disease Control and Prevention, and carried out strictly in accordance with the Declaration of Helsinki. Informed consent was obtained from all participants and from their legal guardians who were aged ≤16 years. Data were stored and analyzed anonymously. Inclusion criteria: ①age≤16 years old; ②symptoms consistent with acute infection (at least one of the following): fever, chills, abnormal white blood cell distribution count (decreased or increased);③clinical symptoms (at least one of the following): runny nose, coughing and sputum, wheezing, pharyngeal and laryngeal edema or soreness, chest tightness and chest pain, fatigue, abdominal pain and diarrhea. Nasopharyngeal swab specimens were collected by qualified medical staff of the sentinel hospitals in strict accordance with the monitoring program, and case information was collected. Specimens were stored at 4 ℃ for 24 h after collection and transported to the laboratory, and specimens sent for examination for more than 24 h were stored at -70℃. Constent to participate Informed consent was obtained from the parents or guardians of all participants. The parents or guardians were informed of the laboratory results of pathogen detection. Constent for publication Not applicable Competing interests The authos declare no competing interests. Clinical trial number Not applicable. Authors ' contributions Biao Wang: method design, experimental manipulation, first draft writing, software processing, review and editorial writing; Hui Zhang: experimental manipulation, software processing, data management, first draft writing; Xiaoshu Zhang: program design, obtaining grants; Maoxing Dong: program design, project management; Shu Liang: program design, project management; Huan Wei: experimental manipulation; Miao Wang: experimental manipulation; Huimin Zhang: experimental manipulation. All authors read and approved the final manuscript. References Choi Eunjin, Ha Kee-Soo, Song Dae Jin, et al. Clinical and laboratory profiles of hospitalized children with acute respiratory virus infection. Korean journal of pediatrics, 2018, 61(6):180-186. https://doi.org/ 10.3345/kjp.2018.61.6.180. WHO. Coronavirus disease 2019 ( COVID-19) Situation Report-51 [EB/OL]. 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BMC Infect Dis 23:467. https://doi.org/10.1186/s12879-023-08247-3. Price OH, Sullivan SG, Sutterby C et al (2019) Using routine test-ing data to understand circulation patterns of influenza A, respi-ratory syncytial virus and other respiratory viruses in Victoria, Australia. Epidemiol Infect 147:e221. https://doi.org/10.1017/S0950268819001055. Sun, Qian et al. “The circulating characteristics of common respiratory pathogens in Ningbo, China, both before and following the cessation of COVID-19 containment measures.” Scientific reports vol. 14,1 25876. 28 Oct. 2024,https://doi.org/ 10.1038/s41598-024-77456-w Takashita E, Kawakami C, Momoki T et al (2021) Increased risk of rhinovirus infection in children during the coronavirus dis-ease-19 pandemic. Influenza Other Respir Viruses 15:488-494. https://doi.org/10.1111/irv.12854. Wu A, Mihaylova VT, Landry ML et al (2020) Interference between rhinovirus and influenza a virus: a clinical data analysis and experimental infection study. Lancet Microbe 1:e254-e262. https://doi.org/10.1016/s2666-5247(20)30114-2. Sarfo JO, Amoadu M, Gyan TB, et al. Acute lower respiratory infections among children under five in Sub-Saharan Africa: a scoping review of prevalence and risk factors. BMC Pediatr. 2023;23(1):225. Published 2023 May 6. https://doi.org/ 10.1186/s12887-023-04033-x. Zeng Y, Wan Y, Yuan Z, Fang Y. Healthcare-Seeking Behavior among Chinese Older Adults: Patterns and Predictive Factors. Int J Environ Res Public Health. 2021;18(6):2969. Published 2021 Mar 14. https://doi.org/ 10.3390/ijerph18062969. Yin Y, Lai M, Zhou S, et al. Effects and interaction of temperature and relative humidity on the trend of influenza prevalence: a multi-central study based on 30 provinces in mainland China from 2013 to 2018. Infect Dis Model. 2023;8(3):822-831. Published 2023 Jul 8. https://doi.org/ 10.1016/j.idm.2023. 07.005. Cao R, Du Y, Tong J et al (2023) Influence of COVID-19 pan-demic on the virus spectrum in children with respiratory infec-tion in Xuzhou, China: a long-term active surveillance study from 2015 to 2021. BMC Infect Dis 23:467. https://doi.org/10.1186/s12879-023-08247-3. Ong HH, Andiappan AK, Duan K et al (2022) Transcriptomics of rhinovirus persistence reveals sustained expression of RIG-I and interferon-stimulated genes in nasal epithelial cells in vitro. Allergy 77:2778-2793. https://doi.org/10.1111/all.15280. Fourgeaud J, Toubiana J, Chappuy H, et al. Impact of public health measures on the post-COVID-19 respiratory syncytial virus epidemics in France. eur J Clin Microbiol Infect Dis. 2021;40(11):2389-2395. https://doi.org/ 10.1007/s10096-021-04323-1. Huh K, Jung J, Hong J, et al. Impact of Nonpharmaceutical Interventions on the Incidence of Respiratory Infections During the Coronavirus Disease 2019 ( COVID-19) Outbreak in Korea: a Nationwide Surveillance Study. Clin Infect Dis. 2021;72(7):e184-e191. https://doi.org/ 10.1093/cid/ciaa1682. Swets MC, Russell CD, Harrison EM, et al. SARS-CoV-2 co-infection with influenza viruses, respiratory syncytial virus, or adenoviruses. lancet. 2022;. 399(10334):1463-1464. https://doi.org/ 10.1016/S0140-6736(22)00383-X. Jartti T, Jartti L, Ruuskanen O et al (2012) New respiratory viral infections. Curr Opin Pulm Med 18:271-278. https://doi.org/10.1097/ MCP.0b013e328351f8d4. Achten NB, Wu P, Bont L, et al. Interference Between Respiratory Syncytial Virus and Human Rhinovirus Infection in Infancy. j Infect Dis. 2017;215(7). 1102-1106. https://doi.org/ 10.1093/infdis/jix031. Dong M, Luo M, Li A, et al. Changes in the pathogenic spectrum of acute respiratory tract infections during the COVID-19 epidemic in Beijing, China: a large -scale active surveillance study. J Infect. 2021;83(5):607-635. https://doi.org/ 10.1016/j.jinf.2021.08.013. Chi H, Huang YC, Liu CC, et al. Characteristics and etiology of hospitalized pediatric community-acquired pneumonia in Taiwan. J Formos Med Assoc. 2020;. 119(10):1490-1499. https://doi.org/ 10.1016/j.jfma.2020.07.014. Piret J, Boivin G. Viral Interference between Respiratory Viruses. Emerg Infect Dis. 2022;28(2):273-281. https://doi.org/ 10.3201/eid2802.211727. van Asten L, Bijkerk P, Fanoy E, et al. Early occurrence of influenza A epidemics coincided with changes in occurrence of other respiratory virus infections. Influenza Other Respir Viruses. 2016;10(1):14-26. https://doi.org/ 10.1111/irv.12348. Nishimura N, Nishio H, Lee MJ, Uemura K. The clinical features of respiratory syncytial virus: lower respiratory tract infection after upper respiratory tract infection due to influenza virus. Pediatr Int. 2005;47(4):412-416. https://doi.org/ 10.1111/j.1442-200x.2005.02099.x. Gröndahl B, Ankermann T, von Bismarck P, et al. The 2009 pandemic influenza A (H1N1) coincides with changes in the epidemiology of other viral pathogens causing acute respiratory tract infections in children. Infection. 2014;42(2):303-308. https://doi.org/ 10.1007/s15010-013-0545-5. Green HK, Ellis J, Galiano M, et al, Pebody RG. Critical care surveillance: insights into the impact of the 2010/11 influenza season relative to the 2009/ 10 pandemic season in England. Euro Surveill. 2013;18(23):20499. Published 2013 Jun 6. https://doi.org/ 10.2807/ese.18.23.20499-en. Mak GC, Wong AH, Ho WY, et al. The impact of pandemic influenza A (H1N1) 2009 on the circulation of respiratory viruses 2009-2011. Influenza Other Respir Viruses. 2012;6(3):e6-e10. https://doi.org/ 10.1111/j.1750-2659.2011.00323.x. Tanner H, Boxall E, Osman H. Respiratory viral infections during the 2009-2010 winter season in Central England, UK: incidence and patterns of multiple virus co-infections. Eur J Clin Microbiol Infect Dis. 2012;31(11):3001-3006. https://doi.org/ 10.1007/s10096-012-1653-3. Additional Declarations No competing interests reported. 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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-5777259","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":447937066,"identity":"9c7f0e5c-7a49-41e6-93ce-3a48bb163831","order_by":0,"name":"Biao Wang","email":"","orcid":"","institution":"Gansu Provincial Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Biao","middleName":"","lastName":"Wang","suffix":""},{"id":447937068,"identity":"921bfa7c-61ce-41e0-b783-b9f9cafe71ca","order_by":1,"name":"Hui Zhang","email":"","orcid":"","institution":"Gansu Provincial Center for Disease Control 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1","display":"","copyAsset":false,"role":"figure","size":158465,"visible":true,"origin":"","legend":"\u003cp\u003eDetection of each pathogen in different age groups (green line represents the average detection rate in 2021, purple line represents the average detection rate in 2022, and red line represents the average detection rate in 2023)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5777259/v1/7543ff597baf969b241b9168.png"},{"id":82046062,"identity":"dc270e76-7a23-45fd-bfe6-3f4cbe80cbbf","added_by":"auto","created_at":"2025-05-06 09:38:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":201602,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly Distribution of Detection Rates by Virus, 2021-2023 (green line represents the average detection rate in 2021, purple line represents the average detection rate in 2022, red line represents the average detection rate in 2023, and blue line represents the average detection rate in 2021-2023 )\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5777259/v1/87c6c1eb080ea0ec72e14d81.png"},{"id":82044611,"identity":"be569c3d-e90c-4aae-b185-37f4fb4484e0","added_by":"auto","created_at":"2025-05-06 09:30:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":95203,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in respiratory viral profiles in different age groups before and after the lifting of control measures (green indicates before the lifting of control measures, purple indicates after the lifting of control measures)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5777259/v1/3414cb2be1c612477e5c2497.png"},{"id":86699412,"identity":"c76b6f37-e65e-427a-ac9b-cb5f37d9f008","added_by":"auto","created_at":"2025-07-14 16:09:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1293584,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5777259/v1/b2be6eed-331e-42af-ba81-7b3287243e15.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Dynamics of respiratory virus transmission in children during and after COVID-19 outbreak control in Baiyin, China","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAcute respiratory infections (ARIs) are the leading cause of morbidity and mortality among children and infants worldwide, with viruses responsible for approximately 80% of these cases [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Since December 2019, the rapid global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), has triggered a pandemic with unprecedented and far-reaching impacts on society [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e][\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e][\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e][\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In response to the outbreak, countries around the world have implemented non-pharmacological interventions, including wearing face masks, maintaining social distancing, practicing hand hygiene, quarantining, closing schools and malls, and restricting travel to control the spread of the virus. Since the end of January 2020, the Chinese government has enacted a series of effective public health measures [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], followed by similar initiatives in many other countries [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Research has shown that these interventions not only effectively curtailed the spread of COVID-19 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] but also influenced the transmission of various other respiratory pathogens [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e][\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], leading to the early cessation of influenza virus (IFV) transmission in many Northern Hemisphere countries [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Additionally, the epidemic season for human respiratory syncytial virus (HRSV) has undergone significant changes, marked by a notable decline in its global detection rate. However, Sullivan et al. reported an increase in the detection rate of human rhinovirus (HRV) in Australia in May 2020, contrasting with the declining trends observed for most respiratory viruses [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This discrepancy highlights the evolving epidemiological trends of respiratory viruses that warrant further investigation. On December 7, 2022, China comprehensively adjusted and optimized its epidemic prevention and control strategy. Subsequently, the Omicron variant spread rapidly, leading to a peak in cases. Control measures were fully lifted, mask usage declined significantly, public activities resumed, and schools and public spaces reopened. To understand the changes in the spectrum of common respiratory viruses before and after the implementation of these control measures, this study investigates the detection rates of respiratory viruses in children in Baiyin, Gansu Province, China. Baiyin, located in northwest China, has a resident population of over 1.5\u0026nbsp;million people and is characterized by unique climatic and demographic features. However, its healthcare infrastructure is relatively underdeveloped, contributing to an increased disease burden in the region. To our knowledge, no prior studies have been conducted in this area. Therefore, this retrospective study analyzes respiratory viruses in clinical samples from children with severe acute respiratory infections (SARI) collected from January 2021 to December 2023 in Baiyin. We further examine the changes in respiratory virus profiles before and after the control measures for COVID-19, aiming to enhance preventive strategies for viral infections in children.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eSource of specimen\u003c/h2\u003e\n \u003cp\u003eIn this study, children hospitalized with acute respiratory tract infections in one hospital in Baiyin City, Gansu Province, from January 2020 to December 2023, were selected as study subjects. Inclusion criteria: ①age\u0026thinsp;\u0026le;\u0026thinsp;16 years old; ②symptoms consistent with acute infection (at least one of the following): fever, chills, abnormal white blood cell distribution count (decreased or increased); ③clinical symptoms (at least one of the following): runny nose, coughing and sputum, wheezing, pharyngeal and laryngeal edema or soreness, chest tightness and chest pain, fatigue, abdominal pain and diarrhea. Nasopharyngeal swab specimens were collected by qualified medical staff of the sentinel hospitals in strict accordance with the monitoring program, and case information was collected. Specimens were stored at 4 ℃ for 24 h after collection and transported to the laboratory, and specimens sent for examination for more than 24 h were stored at -70℃.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eReagents\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eIn this study, the total viral nucleic acid extraction reagent was the Rapid Nucleic Acid Extraction Kit by Magnetic Bead Method (Xi\u0026apos;an Tianlong Science and Technology Co., Ltd., China), the respiratory virus detection was the 22 respiratory pathogen nucleic acid detection kit (Beijing Jocheng Huisheng Biotechnology Co., Ltd., China), and the nucleic acid extraction instrument was the fully automated nucleic acid extractor (Xi\u0026apos;an Tianlong Science and Technology Co., Ltd., China), The instrument for respiratory virus detection was Q5 real-time fluorescence quantitative PCR instrument (ABI, USA)..\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eNucleic acid testing of specimens\u003c/h3\u003e\n\u003cp\u003eIn this study, Total viral nucleic acids were extracted from specimens using the Xi\u0026apos;an Tianlong Nucleic Acid Rapid Extraction Kit (Xi\u0026apos;an Tianlong Science and Technology Co., Ltd., China) according to the manufacturer\u0026apos;s instructions. Common respiratory viruses, including influenza virus (IFV), human respiratory syncytial virus (HRSV), human rhinovirus (HRV), human parainfluenza virus (HPIV), human metapneumovirus (HMPV), human adenovirus (HADV), enterovirus (EV), and human coronavirus (HCoV), were detected by quantitative real-time PCR (qPCR) using a 22-target respiratory pathogen nucleic acid detection kit\u003c/p\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eThe cases were grouped by age based on the collected demographic information: \u0026le;1 year, 1\u0026ndash;3 years, 3\u0026ndash;6 years, and \u0026gt;\u0026thinsp;6 years. IBM SPSS software (version 26.0) was used for the processing and statistical analysis. Data are presented as numbers and percentages (%). Continuous variables with normal distribution were compared using t-tests, whereas non-normally distributed variables were analyzed using the Mann-Whitney U test. Categorical data were analyzed using the chi-squared test or Fisher\u0026apos;s exact test. Chi-square tests and cross-tabulations were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs). Statistical significance was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Graphs were created using GraphPad Prism 8.0.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eDetection of respiratory viruses in children\u003c/h2\u003e \u003cp\u003eA total of 1,353 acute respiratory cases in children were collected from January 1, 2021, to December 31, 2023. There were 809 male (809/1353, 59.79%) and 544 female (544/1353, 40.21%) cases. The male to female ratio was 1.49:1. 363 cases were \u0026le;\u0026thinsp;1 year, 387 cases were 1\u0026ndash;3 years, 387 cases were 3\u0026ndash;6 years, and 216 cases were \u0026gt;\u0026thinsp;6 years. Except for the age groups\u0026thinsp;\u0026le;\u0026thinsp;1year and 1-3years,the difference in the detection rate of pathogens in the other age groups was statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.005).In 2021, there were 85 (85/315, 26.98%) positive specimens for either virus, with the top 3 viruses being HPIV, EV, and HRSV. 81 (81/315, 25.71%) of the 85 positive specimens were found to be infected with one virus, and 4 (4/315, 1.27%) were found to be infected with multiple viruses; In 2022, there were 160 (160/565, 28.32%) positive specimens for either virus, with the top 3 viruses being HADV, HRSV, and HPIV. 146 (146/565, 25.84%) of the 160 positive specimens that tested positive for one viral infection, and 14 (14/565, 2.48%) tested positive for one viral infection; and 2023, there were 213 positive specimens tested positive for multiple viral infections. There were 213 (213/473, 45.03%) virus-positive specimens, and the top three viruses were EV, IFV, and HADV. Of the 213 positive samples, one viral infection was detected in 186 (186/473, 39.32%), and multiple viral infections were detected in 27 (27/473, 5.71%), and the differences in detection rates between the years 2021\u0026ndash;2023 among the The difference in the detection rate of respiratory viruses was statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) The results are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\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\u003eOverall frequency of 8 respiratory pathogens in different years\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021 (n\u0026thinsp;=\u0026thinsp;315)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2022 (565)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2023 (473)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value (χ\u0026sup2;)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge positive,n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;1year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (3.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (7.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (5.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.017(8.1982)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1-3years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (10.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (10.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58 (12.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.678(0.777)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-6years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (9.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (7.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77 (16.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(21.108)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;6years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (3.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (2.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54 (11.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(45.122)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale (cases)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epositive, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57 (28.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78 (24.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e124 (42.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(25.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale (cases)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epositive, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (24.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82 (33.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89 (48.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(20.224)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathogens positive, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85 (26.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160 (28.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e213 (45.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(40.763)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (2.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (5.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001(13.754)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfluenza virus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (8.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(61.085)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman respiratory syncytial virus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (5.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (5.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (1.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.010(9.250)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman rhinovirus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (4.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (5.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005(10.579)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman parainfluenza virus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (14.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (5.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (5.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(27.777)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman metapneumovirus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (4.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (3.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.013(8.689)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman adenovirus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (6.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (7.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002(12.459)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnterovirus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (5.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56 (11.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(49.954)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman coronavirus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (3.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (6.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(16.721)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAge distribution of respiratory viruses in children\u003c/h2\u003e \u003cp\u003eIFV was not detected in two age groups,\u0026le;1 year and 3\u0026ndash;6 years, and had low positive detection rates in all other age groups in 2021 and 2022, but its positive detection rate increased with age in 2023 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). HRSV had positive detection rates in children in all age groups in 2023, except for children\u0026thinsp;\u0026gt;\u0026thinsp;6 years of age, which were lower than in 2021 and 2022 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). The positive detection rates of HRV and HADV in 2022 and 2023 showed an opposite trend in the age groups of \u0026le;\u0026thinsp;1 year and 3\u0026ndash;6 years (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec,f). Respiratory viral infections were more common in children aged 1\u0026ndash;3 years, with a clear umbrella distribution of HPIV, HMPV, EV, and HCOV (Fig .1d, e, g, h).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDetection of respiratory viruses before and after the lifting of control measures\u003c/h3\u003e\n\u003cp\u003eBefore and after the lifting of control measures, the difference in the positive detection rate of pathogens was statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.005) in all age groups except the \u0026le;\u0026thinsp;1 year and 1\u0026ndash;3 years age groups. Before the lifting of control measures, the total positive detection rate of respiratory viruses was 27.84%, and the mixed positive detection rate was 2.05%, and after the lifting of control measures, the total positive detection rate increased to 44.84% (OR:1.313, 95% CI:1.198\u0026ndash;1.438), and the mixed positive detection rate increased to 5.71% (OR:1.014\u0026ndash;1.064, 95% CI:1.014\u0026ndash;1.064). The positive detection rates for IFV, HRV, HMPV, HADV, EV, and HCOV were 0.68%, 3.52%, 2.84%, 4.55%, 2.84%, and 2.27%, respectively, before the control measures were lifted. After the control measures were lifted, the positive detection rates for IFV, HRV, HMPV, HADV, EV, and HCOV increased to 8.88% (OR:1.090, 95% CI:1.059\u0026ndash;1.122), 5.29% (OR:1.019, 95%CI:0.994\u0026ndash;1.044), 3.81% (OR:1.010,95% CI:0.989\u0026ndash;1.032),7.19% (OR:1.028, 95% CI: 0.999\u0026ndash;1.059),11.84% (OR:1.102, 95%CI:1.064\u0026ndash;1.141),and6.34% (OR:1.043, 95%CI: 1.017\u0026ndash;1.070), and the six viruses with positive detection rates were significantly higher than those before the lifting of controls, with a significant increase in the positive detection rate of three pathogens, IFV, EV and HCOV, and a non-significant increase in the positive detection rate of. However, after the control measures were lifted, the positive detection rates of HRSV and HPIV decreased from 5.34% and 8.41% before the control was lifted to 1.09% (OR: 0.965, 95% CI: 0.946\u0026ndash;0.985) and 5.71% (OR:0.971, 95% CI:0.943\u0026ndash;1.001), a nonsignificant decrease in the positive detection rate of HRSV and a nonsignificant increase in the positive detection rate of HPIV. HRSV was significantly reduced, and the positive detection rate of HPIV was not significantly reduced. The order of respiratory virus positivity in children before the lifting of control measures was HPIV\u0026thinsp;\u0026gt;\u0026thinsp;HRSV\u0026thinsp;\u0026gt;\u0026thinsp;HADV\u0026thinsp;\u0026gt;\u0026thinsp;HRV\u0026thinsp;\u0026gt;\u0026thinsp;HMPV\u0026thinsp;\u0026gt;\u0026thinsp;EV\u0026thinsp;\u0026gt;\u0026thinsp;HCOV\u0026thinsp;\u0026gt;\u0026thinsp;IFV; after the lifting of control measures, the order was EV\u0026thinsp;\u0026gt;\u0026thinsp;IFV\u0026thinsp;\u0026gt;\u0026thinsp;HADV\u0026thinsp;\u0026gt;\u0026thinsp;HCOV\u0026thinsp;\u0026gt;\u0026thinsp;HPIV\u0026thinsp;\u0026gt;\u0026thinsp;HRV\u0026thinsp;\u0026gt;\u0026thinsp;HMPV\u0026thinsp;\u0026gt;\u0026thinsp;HRSV. The results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOverall frequency of 8 respiratory pathogens in different years before and after the lifting of control measures\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021\u0026ndash;2022 (n\u0026thinsp;=\u0026thinsp;880)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2023 (473)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value (χ\u0026sup2;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge positive,n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003e\u0026le;\u0026thinsp;1year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 (6.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (5.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.338(0.920)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.960 to 1.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1-3years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94 (10.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (12.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.380(0.770)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.997 to 1.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-6years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 (8.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77 (16.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(20.583)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.049 to 1.146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;6years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (2.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (11.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(44.417)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.063 to 1.138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eMale (cases)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003epositive, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135 (26.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124 (42.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(23.973)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.156 to 1.445\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale (cases)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003epositive, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110 (30.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89 (48.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(17.269)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.157 to 1.583\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathogens positive, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e245 (27.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e213 (45.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(40.602)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.198 to 1.438\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e227 (25.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e186 (39.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(26.548)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.126 to 1.328\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (2.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (5.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(12.836)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.014 to 1.064\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfluenza virus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (8.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(60.419)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.059 to 1.122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman respiratory syncytial virus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (5.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (1.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.002(9.166)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.946 to 0.985\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman rhinovirus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (3.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (5.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.121(2.409)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.994 to 1.044\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman parainfluenza virus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74 (8.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (5.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.071(3.249)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.943 to 1.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman metapneumovirus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (2.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (3.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.335(0.930)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.989 to 1.032\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman adenovirus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (4.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (7.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.041(4.156)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.999 to 1.059\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnterovirus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (2.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (11.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(44.259)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.064 to 1.141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman coronavirus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (2.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (6.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001(14.317)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.017 to 1.070\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eMonthly distribution of respiratory viruses before and after lifting of control measures\u003c/h3\u003e\n\u003cp\u003eBoth before and after the lifting of controls, the positive detection rate of IFV was highest in February. However, the positive detection rate of IFV was significantly higher after the lifting of control measures (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). It is noteworthy that IFV was not detected in 2021 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea).The positive detection rate of HRSV showed a decreasing trend from January to August in 2021\u0026ndash;2022, and then increased from September onwards, however, after the lifting of the control measures, surprisingly, there were only two small peaks of epidemiology in June and October and they were lower than the average level before the lifting of the control measures (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). HRV was predominantly prevalent from June to September, and it is noteworthy that the peak of HRV prevalence shifted rightward from June before the lifting of the control measures to August after the lifting of the control measures (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). 2023 had no detectable HPIV in January and March-May, and the prevalence trend was in the form of the letter \u0026ldquo;W\u0026thinsp;+\u0026thinsp;V\u0026rdquo; before the lifting of the control measures, However, after the lifting of control measures, the epidemiological trend was \u0026ldquo;M+Ʌ\u0026rdquo; (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). HMPV epidemics appeared in February before the lifting of control measures and peaked in June, but after the lifting of control measures, the epidemiological trend began in May and peaked in July, which was a backward shift of the epidemiological peak (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). From 2021 to 2022, the positive detection rate of HADV declined rapidly from January, was lowest in February, and then began to rise again reaching a small peak in March and then began to decline, with no detections in May, followed by a yearly peak in June, and then the subsequent prevalence levels tumbled but were below the June level, whereas after the lifting of the control measures, the prevalence trend of HADV in the period from January to May and in October to December was the opposite of that before the lifting of the control measures, the opposite before the lifting of control measures, but the same epidemiologic trend from May to October. It is worth noting that although the epidemiological trends from May to October are the same, the peak of the epidemiological peak is shifted to the right (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef). Before the lifting of control measures, the epidemic of EV started in March and reached the peak in July, with an interruption in August, and then rose to October and then declined, with a detection in January 2023, no detection from February to April, and the level of prevalence in May gradually rose to the peak in August, and then declined. There was a gradual increase in prevalence levels in May to a peak in August, followed by a gradual decline. It is worth noting that although the overall epidemiological trend of EV was similar before and after the lifting of control measures, the peak of the epidemic was shifted to the right at the same time (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg), and the epidemiological trend of HCOV was similar throughout the year before and after the lifting of control measures, but the positive detection rate of HCOV after the lifting of control measures was much higher than that before the lifting of control measures (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eh). Neighbors were surprised by the low detection rate of all viruses except IFV from January to May 2023 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eChanges in respiratory viral profiles in different age groups before and after control measures were lifted\u003c/b\u003e \u003c/p\u003e \u003cp\u003eInformation on child cases was categorized into four groups based on age: \u0026le;1 year age group, 1\u0026ndash;3 years age group, 3\u0026ndash;6 years age group, and \u0026gt;\u0026thinsp;6 years. Before the control measures were lifted, in each age group, the top three pathogens were HRSV, HRV, and HADV in the \u0026le;\u0026thinsp;1 year group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea); HPIV, HRSV, HADV, and EV in the 1\u0026ndash;3 years group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb); HPIV, HRSV, and HADV in the 3\u0026ndash;6 years group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec); and HPIV, HRV, and EV in the \u0026gt;\u0026thinsp;6 years group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed). After the control measures were lifted, in each age group positive detection rates, the top three pathogens were, respectively, HPIV, IFV, and HCOV in the \u0026le;\u0026thinsp;1 year group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea); HCOV, HRV, HPIV, and EV in the 1\u0026ndash;3 years group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb); and EV, IFV, and HADV in the 3\u0026ndash;6 years group and in the \u0026gt;\u0026thinsp;6 years group. For HPIV positive detection rates, positive detection rates in both the 1\u0026ndash;3 years and 3\u0026ndash;6 years groups decreased, while the HRSV positive detection rate decreased in the \u0026le;\u0026thinsp;1 year, 1\u0026ndash;3 years, and 3\u0026ndash;6 years groups, and the detection rates of HRV, HMPV, HADV, and HCOV decreased in the 1 year group but increased at all other ages, including IFV. The HPIV was high in children under 3 years of age, both before and after the lifting of controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eViruses are the main pathogens that cause respiratory infections in children[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. As the COVID-19 pandemic developed, outbreaks in countries around the world gradually subsided. The resumption of global travel, relaxation of protective measures, and reopening of public places and schools have led to the resurgence of childhood respiratory viruses. Numerous studies have shown that the implementation of global NPIs has significantly reduced the incidence of most respiratory pathogens and altered the epidemiological characteristics[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e][\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study analyzed the detection of respiratory viruses in clinical samples of children with severe acute respiratory infections (SARI) from January 2021 to December 2023 in Baiyin City, Gansu Province, China. The results showed that the overall positive detection rate of common respiratory viruses among children in this study was 33.85% (458/1353), which was lower than that of Kunming in China (52.45%) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and Xuzhou in China (36%) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] but higher than that of Australia (32.10%) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], suggesting that there may be geographic variations in the prevalence of respiratory viruses in children. Before lifting the control measures, the positive detection rate of common respiratory viruses in the children was 27.84% (245/880), and there was no statistically significant difference in respiratory virus infection rate between the sexes of children ; after the lifting of control measures, the positive detection rate of common respiratory viruses in children was 45.03% (213/473), and there was no statistically significant difference in respiratory virus infection rate between the sexes of children. This may be due to the fact that respiratory virus transmission was restricted during the pandemic to control the spread of SARS-CoV-2 by increasing social distances, decreasing people's mobility, and other related PHSMs. Since December 2022, control measures were lifted, and normal production and life order resumed. The increase in people's mobility, the number of gatherings, and the decrease in the proportion of people wearing masks and the \"immunization debt\" during the control period created favorable conditions for the spread of respiratory viruses.\u003c/p\u003e \u003cp\u003eThe data showed that there was no significant change in the rate of respiratory virus positivity in children under 3 years of age before and after the lifting of controls, whereas the difference in the rate of positivity in children over 3 years of age was significant. This is because children over three years of age are school-age children in a broader sense than children under three years of age, and the increase in congregation after the lifting of controls has led to an increase in contact with children and other objects and a greater ability to move on their own, which may lead to an increased risk of infection from touching the mouth and nose. Before lifting the control measures, the order of respiratory virus positivity in children was as follows: HPIV\u0026thinsp;\u0026gt;\u0026thinsp;HRSV\u0026thinsp;\u0026gt;\u0026thinsp;HADV\u0026thinsp;\u0026gt;\u0026thinsp;HRV\u0026thinsp;\u0026gt;\u0026thinsp;HMPV\u0026thinsp;\u0026gt;\u0026thinsp;EV\u0026thinsp;\u0026gt;\u0026thinsp;HCOV\u0026thinsp;\u0026gt;\u0026thinsp;IFV, and after lifting the control measures: EV\u0026thinsp;\u0026gt;\u0026thinsp;IFV\u0026thinsp;\u0026gt;\u0026thinsp;HADV\u0026thinsp;\u0026gt;\u0026thinsp;HCOV\u0026thinsp;\u0026gt;\u0026thinsp;HPIV\u0026thinsp;\u0026gt;\u0026thinsp;HRV\u0026thinsp;\u0026gt;\u0026thinsp;HMPV\u0026thinsp;\u0026gt;\u0026thinsp;HRSV. The order of positive respiratory virus detection in this study changed significantly before and after lifting the controls, reflecting the susceptibility of controls to different viruses and their respective transmission dynamics after lifting. This may involve a number of factors, such as virus characteristics, immunization gaps, cross-immunization, climatic influences, and changes in host susceptibility. After the lifting of control measures, EV: increased contact between children and relaxation of hygiene practices may lead to rapid transmission of enteroviruses via the fecal-oral and respiratory routes, which can result in a rapid rise in the EV rank; IFV: coincides with the epidemic season for IFV. In addition, the fact that many people were not infected with influenza during the control period resulted in a large immune gap in the population, making them more susceptible to infection after the de-escalation. HADV: The rise in may indicate that its ability to spread through contact sequencing of HADV was unleashed after. The opening of schools and childcare centers and the de-escalation accelerated the spread of HADV. HCOV: The detection of coronavirus viruses other than SARS-CoV-2 may have increased, or the infection rate may have risen due to the decline in the immunity of the population; HPIV: Its decrease in sorting may be due to competing transmission of other viruses (EV and IFV) or to the effect of previously accumulated immunity on the suppression of HPIV transmission; HRV: The decline in HRV sorting may be due to a more prominent prevalence of other viruses, resulting in a relative decline in HRV sorting. HMPV: HMPV's sorting is still relatively backward, which may indicate that it has a relatively weak ability to transmit; HRSV: It is worth noting that RSV sorting declined significantly after the lifting of controls, which is consistent with the study conducted in Ningbo City, Zhejiang Province [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This may be attributed to the co-prevalence of other viruses interfering with RSV transmission, suppression of RSV prevalence by accumulated immunity during NPIs, etc., leading to a lower ranking.\u003c/p\u003e \u003cp\u003eBefore the lifting of control measures, the top three viruses were HPIV (8.41%), HRSV (5.34%), and HADV (4.55%); after the lifting of control measures, the top three viruses were EV (11.84%), IFV (8.88%), and HADV (7.19%), and the intensity of prevalence of EV and IFV exceeded that of HPIV and HRSV. EV has become the dominant viral pathogen. This may be due to factors such as the lifting of NPI measures, immune debt, interactions between viruses, and changes in behavioral patterns. The respiratory viruses with the highest detection rates differed from those reported in studies in other geographic regions of China [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], which may be attributed to the differences in the study population and sample size. In addition, control measures implemented during the outbreak may have altered the prevalence of certain viruses, and epidemiological interference between respiratory viruses can affect virus frequencies at both the host and population levels and interfere with the subsequent frequency and duration of a particular virus or virus type [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e][\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAfter lifting the control measures, the epidemiologic activity of five respiratory viruses (IFV, HRV, HMPV, HADV, EV, and HCOV) other than HRSV and HPIV increased. From the study results, it appears that after the lifting of control measures, HRV and HMPV epidemics peaked approximately 1\u0026ndash;3 months later than before the lifting of control measures, but this result needs to be verified by reviewing the pre-COVID-19 viruses for comparison. In addition, the single infection rate before the lifting of the control measures (25.80%) was significantly lower than that after the lifting of the control measures (39.32%). The lower total positive detection rate of the virus during the NPIs (27.84%) led to a significantly lower rate of mixed infections before the lifting of the control measures (2.08%) than after the lifting of the measures (5.71%), which may also be related to the social environment, the changes in the immunity of the population, the timing of the pathogen itself, changes in its activity patterns, population mobility, and natural environments, as well as the changes in its behavior. The change may also be related to the combination of multiple influencing factors such as social environment, changes in immunity of the population, the time of the pathogen's own activity, regularity, population mobility, and changes in the natural environment [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e][\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e][\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe positivity rates of HRSV and HPIV decreased after the lifting of control measures, whereas the IFV increased significantly, consistent with the results of the study by Zhang et al.[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. From January to May, after the lifting of controls, there was an interruption in the detection rate of most viruses and a rightward shift in the peak prevalence. It is possible that the rapid spread of SARS-CoV-2 after the lifting of controls suppressed the spread of other respiratory viruses during the same period, leading to a delay in the peak epidemiological activity of other pathogens. This suggests that the increased detection of SARS-CoV-2 may have produced some degree of interference at the host level, which led to a temporary reduction in host susceptibility to viral infections and induced a period of inappropriate immunity to other pathogens. The specific mechanism of interference may be related to the sustained upregulation of COVID-19 interferon-stimulated genes, chemokines, and cytokines [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe elevated IFV detection rate in this study was highly significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and similar to the results of multinational studies in the northern hemisphere [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e][\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This may be related to the higher virulence and pathogenicity of the original SARS-CoV-2 strain, which attacked the host more intensely and for a longer period of time [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], which in turn reduced the chances of influenza viruses infecting the host, and hence the absolute limitation of influenza activity in the first year of the COVID-19 pandemic. Reduced virulence and severity of the Delta and Omicron strains increased the probability of influenza infection in the host. This may explain why influenza activity increased after the delta pandemic, or it may be that the lifting of controls, increased congregational activity, decreased rates of mask wearing, and untimely vaccination during the control period created favorable conditions for influenza virus transmission and infection. Most of the viruses had the highest detection rate in the 1\u0026ndash;3 years group, consistent with the findings of Jartti et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], showing a clear umbrella distribution feature, which is consistent with the findings of Kunming, Yunnan Province, China [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Before the lifting of control measures, children were in a low prevalence state in the whole age group, which may be related to strict control measures. After lifting the control measures, the IFV infection rate showed a positive correlation with age, which may be because IFV antibody duration is short and socialization activities increase the risk of transmission. In contrast to IFV, HRSV showed a roughly negative correlation with age, and related studies showed that the activities of IFV and HRSV in the host body had interference [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The susceptible age group for EV changed from 1\u0026ndash;3 years before control lifting to 3\u0026ndash;6 years after control lifting. The reason may be that children in the 1\u0026ndash;3 years group before the lifting of control measures had relatively low immune function and were too small to ensure wearing of masks. After the lifting of control measures, children in the 3\u0026ndash;6 years group were more likely to come into contact with a variety of respiratory pathogens because their immune system had not yet matured fully and also because of their intensive living and daily routine environment and wide range of activities, which naturally resulted in a higher risk of infection. Specifically, the children were susceptible to respiratory pathogens both before and after lifting the control measures. This result is consistent with those of previous studies [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e][\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eChanges in the epidemiological patterns of respiratory multipathogens may pose a great challenge to clinical diagnosis and treatment. In general, the similarity of symptoms and signs of respiratory multipathogen infections makes it difficult to rapidly detect and identify specific respiratory pathogens, and the lack of specific therapeutic drugs and their empirical use may lead to increased drug resistance. In addition to non-pharmacological interventions to change the epidemiology of viruses, mutual interference between viruses is one of the hypotheses to change the epidemiology of viruses. Studies have demonstrated potential interference between different respiratory viruses [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. For example, surveillance of respiratory viral infections in Norway has shown that RSV is rarely detected during influenza epidemics, suggesting activity interference between the two [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Mutual interference between IFV and HRSV has also been reported in other countries during different winters [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e][\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. HRSV spread in Victoria, Australia, from 2002 to 2017, on average, 6 weeks earlier than IFV-A. During the 2009 influenza pandemic, shifts in influenza activity were associated with changes in seasonal HRSV activity, further supporting a negative interference effect between viruses [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e][\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e][\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. These findings suggest a positive or negative epidemiological pattern of correlation between respiratory viruses [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough we achieved better results, this study has some limitations. First, the study only included hospitalized children in a single region, which may not be fully representative of the wider population of children with ARTIs. Second, the role of respiratory multipathogen influences may change with an increase in the number of regions covered, the population of children, and the duration of future studies. Second, the study did not include data from other cities, which limits our ability to generalize the epidemiological model of respiratory multi-pathogens to a wider region. Finally, this study included only eight common respiratory viruses, which may have overlooked the infection burden of other pathogens. To overcome these limitations, future studies need to further explore more regions and track for longer periods to validate the consistency of the results, as well as examine other potential influences such as geographic location, climatic factors, socioeconomic status, and cultural practices on the transmission of respiratory diseases. Studies need to be expanded to fully capture the long-term trends and changes in pathogen profiles.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eTo understand the changes in respiratory viral profiles among children in Baiyin, China, during this period, it is essential to consider the impact of evolving outbreak prevention and control measures, alongside the disruptions caused by the COVID-19 pandemic. These findings highlight the potential to glean valuable insights from the experiences of COVID-19 prevention and control, which could be instrumental in mitigating the risks that respiratory viruses pose to children's health.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCOVID-19 \u0026nbsp; \u0026nbsp; Coronavirus disease 2019\u003c/p\u003e\n\u003cp\u003eSARS-CoV-2 \u0026nbsp; Severe acute respiratory syndrome coronavirus 2\u003c/p\u003e\n\u003cp\u003eSARI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Severe acute respiratory infection\u003c/p\u003e\n\u003cp\u003eIFV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Influenza virus\u003c/p\u003e\n\u003cp\u003eHRSV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Human respiratory syncytial virus\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHRV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Human rhinovirus\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHPIV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Human parainfluenza virus\u003c/p\u003e\n\u003cp\u003eHMPV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Human metapneumovirus\u003c/p\u003e\n\u003cp\u003eHADV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Human adenovirus\u003c/p\u003e\n\u003cp\u003eEV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Enterovirus )\u003c/p\u003e\n\u003cp\u003eHCOV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Human coronavirus\u003c/p\u003e\n\u003cp\u003ePHSW \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Public Health and Social Measure\u003c/p\u003e\n\u003cp\u003eHF \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; High frequency\u003c/p\u003e\n\u003cp\u003eNPIs \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Non-Pharmaceutical Interventions\u003c/p\u003e\n\u003cp\u003eARTIs \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Acute Respiratory Tract Infections\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all the participants of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data geneerated or analyzed during this study are included in this published article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFundings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Gansu Provincial Key Research and Development Program-Social Development Field Program Project (Grant NO. 23YFFA0051) and the Gansu Provincial Health Industry Science and Technology Innovation Major Project (Grant NO. GSWSKY2024-022).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethical Committee of Gansu Provincial Center for Disease Control and Prevention, and carried out strictly in accordance with the Declaration of Helsinki. \u0026nbsp; \u0026nbsp;Informed consent was obtained from all participants and from their legal guardians who were aged \u0026le;16 years. Data were stored and analyzed anonymously. Inclusion criteria: ①age\u0026le;16 years old; \u0026nbsp; \u0026nbsp;②symptoms consistent with acute infection (at least one of the following): fever, chills, abnormal white blood cell distribution count (decreased or increased);③clinical symptoms (at least one of the following): runny nose, coughing and sputum, wheezing, pharyngeal and laryngeal edema or soreness, chest tightness and chest pain, fatigue, abdominal pain and diarrhea. \u0026nbsp; \u0026nbsp; Nasopharyngeal swab specimens were collected by qualified medical staff of the sentinel hospitals in strict accordance with the monitoring program, and case information was collected. \u0026nbsp; \u0026nbsp; Specimens were stored at 4 ℃ for 24 h after collection and transported to the laboratory, and specimens sent for examination for more than 24 h were stored at -70℃.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConstent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from the parents or guardians of all participants. The parents or guardians were informed of the laboratory results of pathogen detection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConstent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authos declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u003c/strong\u003e\u003cstrong\u003e\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBiao Wang: method design, experimental manipulation, first draft writing, software processing, review and editorial writing; Hui Zhang: experimental manipulation, software processing, data management, first draft writing; Xiaoshu Zhang: program design, obtaining grants; Maoxing Dong: program design, project management; Shu Liang: program design, project management; Huan Wei: experimental manipulation; Miao Wang: experimental manipulation; Huimin Zhang: experimental manipulation. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChoi Eunjin, Ha Kee-Soo, Song Dae Jin, et al. Clinical and laboratory profiles of hospitalized children with acute respiratory virus infection. Korean journal of pediatrics, 2018, 61(6):180-186. https://doi.org/ 10.3345/kjp.2018.61.6.180.\u003c/li\u003e\n\u003cli\u003eWHO. Coronavirus disease 2019 ( COVID-19) Situation Report-51 [EB/OL]. ( 2020-03-11) [2020-03-15]. https: //www.who.int/docs/default-source/coronaviruse/situation-reports/20200311-sitreps-51-covid-19.pdf? Sfrsn=1ba62e57_10.\u003c/li\u003e\n\u003cli\u003eChen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395(10223):507-513. https://doi.org/ 10.1016/S0140-6736(20)30211-7.\u003c/li\u003e\n\u003cli\u003eLi Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. 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Changes in the pathogenic spectrum of acute respiratory tract infections during the COVID-19 epidemic in Beijing, China: a large -scale active surveillance study. J Infect. 2021;83(5):607-635. https://doi.org/ 10.1016/j.jinf.2021.08.013.\u003c/li\u003e\n\u003cli\u003eChi H, Huang YC, Liu CC, et al. Characteristics and etiology of hospitalized pediatric community-acquired pneumonia in Taiwan. J Formos Med Assoc. 2020;. 119(10):1490-1499. https://doi.org/ 10.1016/j.jfma.2020.07.014.\u003c/li\u003e\n\u003cli\u003ePiret J, Boivin G. Viral Interference between Respiratory Viruses. Emerg Infect Dis. 2022;28(2):273-281. https://doi.org/ 10.3201/eid2802.211727.\u003c/li\u003e\n\u003cli\u003evan Asten L, Bijkerk P, Fanoy E, et al. Early occurrence of influenza A epidemics coincided with changes in occurrence of other respiratory virus infections. Influenza Other Respir Viruses. 2016;10(1):14-26. https://doi.org/ 10.1111/irv.12348.\u003c/li\u003e\n\u003cli\u003eNishimura N, Nishio H, Lee MJ, Uemura K. The clinical features of respiratory syncytial virus: lower respiratory tract infection after upper respiratory tract infection due to influenza virus. Pediatr Int. 2005;47(4):412-416. https://doi.org/ 10.1111/j.1442-200x.2005.02099.x.\u003c/li\u003e\n\u003cli\u003eGr\u0026ouml;ndahl B, Ankermann T, von Bismarck P, et al. The 2009 pandemic influenza A (H1N1) coincides with changes in the epidemiology of other viral pathogens causing acute respiratory tract infections in children. Infection. 2014;42(2):303-308. https://doi.org/ 10.1007/s15010-013-0545-5.\u003c/li\u003e\n\u003cli\u003eGreen HK, Ellis J, Galiano M, et al, Pebody RG. Critical care surveillance: insights into the impact of the 2010/11 influenza season relative to the 2009/ 10 pandemic season in England. Euro Surveill. 2013;18(23):20499. Published 2013 Jun 6. https://doi.org/ 10.2807/ese.18.23.20499-en.\u003c/li\u003e\n\u003cli\u003eMak GC, Wong AH, Ho WY, et al. The impact of pandemic influenza A (H1N1) 2009 on the circulation of respiratory viruses 2009-2011. Influenza Other Respir Viruses. 2012;6(3):e6-e10. https://doi.org/ 10.1111/j.1750-2659.2011.00323.x.\u003c/li\u003e\n\u003cli\u003eTanner H, Boxall E, Osman H. Respiratory viral infections during the 2009-2010 winter season in Central England, UK: incidence and patterns of multiple virus co-infections. Eur J Clin Microbiol Infect Dis. 2012;31(11):3001-3006. https://doi.org/ 10.1007/s10096-012-1653-3.\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":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Children, Respiratory viruses, Coronavirus disease 2019, Preventive and control measures","lastPublishedDoi":"10.21203/rs.3.rs-5777259/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5777259/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose \u003c/strong\u003e\u0026nbsp;We aimed to study the changes in respiratory virus detection rates during the control of the COVID-19 outbreak and to elucidate possible epidemiologic disturbances after the lifting of control measures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods \u003c/strong\u003eSevere acute respiratory infection (SARI) specimens in hospitalized children were collected from 2021-2023 in Baiyin, China. We conducted real-time fluorescence quantitative PCR (RT-qPCR) to detect various respiratory viruses, including influenza virus (IFV), human respiratory syncytial virus (HRSV), human rhinovirus (HRV), human parainfluenza virus (HPIV), human metapneumovirus (HMPV), human adenovirus (HADV), enterovirus (EV), and human coronavirus (HCoV). The results were statistically analyzed by SPSS 26.0 software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults \u003c/strong\u003eA total of 1353 nasopharyngeal swab specimens were collected from children with acute respiratory tract infections (ARTIs) between 2021 and 2023. The male-to-female ratio was 1.49:1 and the overall viral detection rate was 33.85% (458/1353). Data were analyzed by comparing two distinct periods: before the lifting of the COVID-19 control measures (January 1, 2021 –December 6, 2022) and after the lifting of the control measures (December 7, 2022 – December 31, 2023). No statistically significant difference was observed in pathogen-positive detection rates between periods with and without control measures for the age groups ≤1 year (OR: 0.986, 95% CI:0.960-1.013) and 1-3 years (OR: 1.018, 95% CI:0.997-1.060). However, significant differences were found in the 3-6 years (OR:1.097, 95% CI:1.049-1.146) and \u0026gt;6 years (OR:1.099, 95%CI: 1.063-1.138) age groups, as well as in males (OR:1.293, 95%CI:1.156-1.445) and females (OR: 1.354, 95%CI:1.157-1.583). The overall positive detection rate of respiratory viruses increased significantly from 27.84% to 44.84% (OR:1.313, 95% CI:1.198-1.438) after the lifting of COVID-19 control measures. Before the lifting of control measures, the order of respiratory virus-positive detection rates in children was human parainfluenza virus (HPIV) \u0026gt; human respiratory syncytial virus (HRSV) \u0026gt; human adenovirus (HAdV) \u0026gt; human rhinovirus (HRV) \u0026gt; human metapneumovirus (HMPV) \u0026gt; enterovirus (EV) \u0026gt; human coronavirus (HCoV) \u0026gt; influenza virus (IFV). After lifting the control measures, the order was EV \u0026gt; IFV \u0026gt; HAdV \u0026gt; HCoV \u0026gt; HPIV \u0026gt; HRV \u0026gt; HMPV \u0026gt; HRSV. Compared with the period before lifting the control measures, a rightward shift in the peak detection time period was observed for HRV, HMPV, HAdV, and EV. After lifting the control measures, the positive detection rates of IFV (OR:1.090, 95%CI:1.059-1.122), EV (OR:1.102, 95%CI:1.064-1.141), and HCoV (OR:1.043, 95%CI:1.017-1.070) increased significantly. A significant decrease was seen in the positive detection rate for HRSV (OR:0.965, 95%CI:0.946-0.985); and a non-significant decrease in the positive detection rate for HPIV (OR:0.971, 95%CI:0.943-1.001).and no significant difference was seen in the positive detection rate for HMPV (OR:1.019, 95%CI:0.989-1.032).and HADV (OR:1.028, 95%CI:0.999-1.059).Notably, influenza virus rebounded significantly between January and February 2023.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions \u003c/strong\u003eThese findings help elucidate that social interventions can influence the prevalence of childhood respiratory viruses during a unique historical period. The implementation of the COVID-19 outbreak control measures may have curbed the spread of childhood respiratory viruses. Surveillance of respiratory pathogens must be strengthened after control measures are lifted to reduce the risk of respiratory viruses affecting children's health.\u003c/p\u003e","manuscriptTitle":"Dynamics of respiratory virus transmission in children during and after COVID-19 outbreak control in Baiyin, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-06 09:30:29","doi":"10.21203/rs.3.rs-5777259/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-02T03:28:37+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"41860026167902396063458440522340682125","date":"2025-05-20T07:37:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"70265834990503879405346900423474273854","date":"2025-05-17T05:01:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-16T03:07:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"190652567954523422276120403658392125474","date":"2025-05-16T02:55:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-08T08:08:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"319370940252184315055639266826326356044","date":"2025-05-04T08:35:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"61602549673578113890868168603590167156","date":"2025-04-29T08:50:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"70385993772504825288216636545177228772","date":"2025-04-28T04:44:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-25T09:43:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-25T06:43:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2025-04-19T12:36:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b6421c48-cd99-4826-820c-efb8b4c2a673","owner":[],"postedDate":"May 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-14T16:03:05+00:00","versionOfRecord":{"articleIdentity":"rs-5777259","link":"https://doi.org/10.1186/s12879-025-11285-8","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2025-07-07 15:57:04","publishedOnDateReadable":"July 7th, 2025"},"versionCreatedAt":"2025-05-06 09:30:29","video":"","vorDoi":"10.1186/s12879-025-11285-8","vorDoiUrl":"https://doi.org/10.1186/s12879-025-11285-8","workflowStages":[]},"version":"v1","identity":"rs-5777259","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5777259","identity":"rs-5777259","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}