Epidemiological Analysis of Viral Diarrhea in Yantai, Shandong, China (2017-2020): Insights into Seasonal Patterns and Viral Agents

Epidemiological Analysis of Viral Diarrhea in Yantai, Shandong, China (2017-2020): Insights into Seasonal Patterns and Viral Agents | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Epidemiological Analysis of Viral Diarrhea in Yantai, Shandong, China (2017-2020): Insights into Seasonal Patterns and Viral Agents peihua niu, Jiaming Huang, Zhenlu Sun, Ying Li, Yiming Zhao, Xiaoyu Yang, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6543048/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study aimed to investigate the epidemiological characteristics of viral diarrhea in Yantai City, Shandong Province, from 2017 to 2020. A total of 2,773 suspected cases of infectious diarrhea were collected from healthcare institutions across 13 districts and counties in Yantai. Specimens were tested for astrovirus, enteric adenovirus, norovirus genogroups I and II (GI and GII), rotavirus, and sapovirus using nucleic acid detection kits. Positive cases were analyzed to characterize the pathogen spectrum and epidemiological features. Statistical analyses were conducted using chi-square and Mann–Whitney U tests. The detection rates of viral diarrhea were higher during spring and winter. The positivity rates for astrovirus, adenovirus, norovirus GI, norovirus GII, rotavirus, and sapovirus were 1.23%, 3.64%, 1.44%, 8.11%, 17.42%, and 0.61%, respectively. Among these, rotavirus and norovirus GII showed consistently high detection rates across the study period. Children under six years of age had the highest pathogen detection rates, with rotavirus being the predominant agent. The viral spectrum remained relatively consistent across age groups, and no significant changes in age distribution were observed over time. In conclusion, viral diarrhea in Yantai exhibited a clear seasonal pattern, with peaks in spring and winter. The overall detection rate showed an upward trend followed by a decline, with notable changes occurring between 2018 and 2019. Rotavirus was the most prevalent pathogen identified. Children under six years old represented the most affected population. These findings highlight the importance of strengthened surveillance for infectious diarrhea, particularly viral diarrhea among young children. Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION Infectious diarrhea remains a major global public health concern, characterized by high morbidity and considerable mortality, particularly among children. It is caused by a broad range of pathogens, including bacteria, viruses, and parasites, and poses a persistent threat to human health and survival. According to the World Health Organization, an estimated 1.7 billion cases of childhood diarrhea occur annually, making it the second leading cause of death among children under the age of five [ 1 ]. Although gastrointestinal infections continue to impose a healthcare burden in high-income countries, the impact is disproportionately greater in low- and middle-income countries, where access to clean water, sanitation, and timely medical care may be limited [ 2 , 3 ]. Given that China has the second-largest population of children globally, strengthening the surveillance and management of diarrheal diseases represents a public health priority of critical importance. Among the etiological agents of infectious diarrhea, viruses constitute the leading cause, particularly in pediatric populations. The most common viral pathogens include astrovirus (AstV), enteric adenovirus (EAdV), norovirus (NV) genogroups I and II (GI and GII), rotavirus (RV), and sapovirus (SaV) [ 4 ]. Understanding the epidemiological profiles and transmission dynamics of these viruses is essential for effective prevention, timely diagnosis, and informed public health interventions targeting viral diarrhea. Since the resolution of the COVID-19 pandemic, there has been a notable gap in local epidemiological data on diarrheal pathogens in Yantai, Shandong Province. Surveillance data specific to this region have been limited, despite the importance of regional variation in pathogen distribution. To address this gap and support the development of targeted control measures, this study investigates the distribution and seasonal characteristics of six key viral pathogens associated with diarrhea in Yantai between 2017 and 2020. By characterizing the pathogen spectrum and associated epidemiological trends, the study aims to provide an evidence base for enhanced surveillance strategies and inform public health policy for the prevention and management of viral diarrheal diseases. Materials and methods Participant Recruitment and Specimen Collection From 2017 to 2020, suspected cases of infectious diarrhea were collected from various medical institutions across 13 districts and counties in Yantai, Shandong Province. These cases were organized and analyzed by the Yantai Center for Disease Control and Prevention. Fecal specimens were centrally collected and tested, while epidemiological data were gathered on-site by local medical institutions. Both clinical and laboratory diagnoses were conducted in accordance with the Diagnostic Criteria for Infectious Diarrhea (WS271-2007). This study was reviewed and approved by the Ethics Committee of Preventive Medicine at the Yantai Center for Disease Control and Prevention (Ethics Approval No. YYLLS 2023-30). Written informed consent was obtained from the guardians of all participants. Nucleic Acid Extraction A small quantity of fecal matter—approximately the size of a mung bean—or 50–100 microliters of liquid stool was mixed with 500 microliters of isotonic sodium chloride solution to prepare a 10–20% suspension. The mixture was centrifuged at 8,000 rpm for 5 minutes. From the resulting supernatant, 200 microliters were extracted and processed using an automated nucleic acid extractor with a commercially available reagent kit (Shengxiang Biotech Co., Ltd., Hunan, China). All procedures were carried out in accordance with the manufacturer's instructions. Nucleic Acid Detection Nucleic acid detection of six viral pathogens associated with infectious diarrhea, including AstV, EAdV, NV GI, NV GII, RV, and SaV, was performed using a commercial detection kit (BioGerm Medical Technology Co., Ltd., Shanghai, China). All procedures were carried out in strict accordance with the manufacturer’s instructions. Statistical Analysis Data were presented as counts and percentages. Median values were reported alongside interquartile ranges (IQRs). Group comparisons were conducted using chi-square tests and Mann–Whitney U tests. A P -value of less than 0.05 was considered statistically significant. Results Detection of Six Pathogens During the study period, a total of 2,773 cases meeting the Diagnostic Criteria for Infectious Diarrhea (WS271-2007) were included for analysis. The annual distribution of reported cases was as follows: 751 cases (27.08%) in 2017, 740 cases (26.69%) in 2018, 731 cases (26.36%) in 2019, and 551 cases (19.87%) in 2020. Among these, 802 cases (28.92%) tested positive for at least one viral pathogen. Of these, 710 cases (25.60%) were positive for a single virus, while 92 cases (3.32%) showed evidence of co-infection. Specifically, 86 cases (3.10%) involved co-infection with two pathogens, and 6 cases (0.22%) involved three-pathogen co-infections (see Table 1 and Table 2 ). Table 1 Annual Case Distribution and Pathogen Detection Rates for Infectious Diarrhea in Yantai City, Shandong Province, 2017–2020 Item 2017 n = 751 2018 n = 740 2019 n = 731 2020 n = 551 Total n = 2773 Gender Male 410(54.59) 409(55.27) 407(55.68) 286(51.91) 1512(54.43) Female 341(45.41) 331(44.73) 324(44.32) 265(48.09) 1261(45.47) Age (years) < 1 112(14.91) 77(10.41) 55(7.52) 53(9.62) 297(10.71) 1–2 132(17.58) 165(22.3) 190(25.99) 70(12.7) 557(20.09) 3–5 19(2.53) 28(3.78) 49(6.7) 32(5.81) 128(4.62) 6–17 25(3.33) 34(4.59) 49(6.7) 58(10.53) 166(5.99) 18–29 85(11.32) 72(9.73) 63(8.62) 58(10.53) 278(10.03) 30–39 61(8.12) 70(9.46) 54(7.39) 45(8.17) 230(8.29) 40–49 59(7.86) 53(7.16) 56(7.66) 44(7.99) 212(7.65) 50–59 85(11.32) 78(10.54) 76(10.4) 53(9.62) 292(10.53) 60–69 92(12.25) 92(12.43) 82(11.22) 82(14.88) 348(12.55) > 70 81(10.79) 71(9.59) 57(7.8) 56(10.16) 265(9.56) Positive 247(32.89) 270(36.49) 177(24.21) 108(19.6) 802(28.92) Single infection 225(29.96) 227(30.68) 155(21.2) 103(18.69) 710(25.6) Co-infection 22(2.93) 43(5.81) 22(3.01) 5(0.91) 92(3.32) Pathogen AstV 16(2.13) 11(1.49) 7(0.96) 0(0) 34(1.23) EAdV 33(4.39) 49(6.62) 17(2.33) 2(0.36) 101(3.64) NV GI 11(1.46) 12(1.62) 12(1.64) 5(0.91) 40(1.44) NV GII 68(9.05) 52(7.03) 45(6.16) 60(10.89) 225(8.11) RV 140(18.64) 184(24.86) 116(15.87) 43(7.8) 483(17.42) SaV 3(0.4) 9(1.22) 2(0.27) 3(0.54) 17(0.61) Note: Percentages are based on the total number of cases tested each year. Single infection refers to cases where only one pathogen was detected; co-infection refers to cases where two or more pathogens were detected simultaneously. Data are presented as n(%). Table 2 Co-infection Rates of Viral Pathogens in Infectious Diarrhea Cases in Yantai City, 2017–2020 Pathogen Number of detections Detection rate(%) NV GII + RV 33 1.19 EAdV + RV 22 0.79 AstV + RV 7 0.25 NV GI + NV GII 6 0.22 RV + SaV 4 0.14 NV GI + RV 3 0.11 NV GI + NV GII + RV 3 0.11 EAdV + NV GII + RV 3 0.11 AstV + SaV 3 0.11 EAdV + SaV 2 0.07 AstV + EAdV 2 0.07 AstV + NV GII 2 0.07 EAdV + NV GI 1 0.04 Note: The table lists the combinations of pathogens detected in co-infections and presents the number of detections alongside the corresponding percentage of total cases. Rotavirus (RV) was the most frequently detected pathogen, identified in 483 cases (17.42%), followed by norovirus genogroup II (NV GII), detected in 225 cases (8.11%). These two pathogens exhibited persistently high detection rates throughout the study period. The most common co-infection was NV GII and RV, found in 33 cases (1.19%), followed by enteric adenovirus (EAdV) and RV, observed in 22 cases (0.79%). Noteworthy triple co-infections included NV GI, NV GII, and RV, as well as EAdV, NV GII, and RV, each detected in 3 cases (0.11%) (Table 2 ). Gender Distribution of viral diarrhea Cases Of the 2,773 reported cases, 1,512 (54.43%) were male and 1,261 (45.57%) were female. The overall detection rate of viral diarrhea was 29.96% (453/1,512) in males and 27.68% (349/1,261) in females. Statistical analysis revealed no significant difference in viral diarrhea incidence between genders. Similarly, the detection rates for each of the six viral pathogens did not differ significantly between male and female patients (Table 3 ). Table 3 Gender-Based Comparison of Viral Pathogen Detection in Infectious Diarrhea Cases in Yantai City, 2017–2020 Gender Number of cases AstV EAdV NV GI NV GII RV SaV Total Male 1512 17 56 23 128 274 12 453 Female 1261 17 45 17 97 209 5 349 \(\:{\chi\:}^{2}\) - 0.130 0.008 0.049 0.453 1.040 1.188 1.635 P value - 0.719 0.930 0.825 0.501 0.308 0.276 0.201 Note: It compares the detection rates of various viral pathogens causing infectious diarrhea between male and female patients in Yantai City from 2017 to 2020. It lists the number of cases per gender and the detection counts for specific pathogens (AstV, EAdV, NV GI, NV GII, RV, SaV). Statistical analysis results ( \(\:{\chi\:}^{2}\) and P value) indicate the significance of differences in pathogen prevalence by gender. "-" means no data. Relationship Between Viral Diarrhea and Age The age of patients ranged from 10 days to 99 years, with a median age of 28 years (interquartile range: 1–57 years). Of the total cases, 450 (39.20%) were under 18 years of age, while 352 (21.66%) were 18 years or older. Statistical analysis revealed a significant difference in the incidence of viral diarrhea between minors and adults ( χ² =99.795, P = 1.690×10⁻²³). The detection rate of viral pathogens increased during early childhood, peaking before the age of three, and generally declined with advancing age. Toddlers (ages 1–2 years) constituted the largest age group, accounting for 557 cases (20.09%), followed by individuals aged 60–69 years (348 cases, 12.55%) and infants under one year (297 cases, 10.71%). The highest detection rate was observed in the toddler group (264 cases, 47.40%), followed by preschool children aged 3–5 years (detection rate: 39.06%) and infants (30.98%) (Fig. 1 ). The median age of detection varied across viral pathogens, reflecting differences in age-related susceptibility. Median ages were 28 years for AstV, 2 years for EAdV, 31 years for NV GI, 17 years for NV GII, 2 years for RV, and 2 years for SaV. Violin plot analyses demonstrated that EAdV, RV, NV GII, and SaV predominantly affected infants and young children, whereas AstV and NV GI were more evenly distributed across all age groups (Fig. 2 A). Age-stratified analysis of the pathogen spectrum revealed that RV was the most frequently detected virus in infants, toddlers, preschool-aged children, and adults, while NV GII was most prevalent among school-age children (Fig. 2 B). The age distribution patterns of the six pathogens remained stable throughout the study period (Fig. 2 C). No statistically significant year-to-year variation was observed in age-specific prevalence based on the Mann–Whitney U test, indicating a consistent age-related distribution over time (Table 4 ). Table 4 Annual Comparison of Age Distribution Among Patients with viral diarrhea Pathogens in Yantai City, 2017–2020 Pathogen 2017 ~ 2018 2018 ~ 2019 2019 ~ 2020 AstV 0.786 0.785 - EAdV 0.913 0.071 0.152 NV GI 0.951 0.839 1 NV GII 0.514 0.309 0.275 RV 0.921 0.238 0.805 SaV 0.513 0.287 0.139 Note: It provides a year-by-year comparison of the age distribution of patients infected with six key pathogens causing viral diarrhea in Yantai City from 2017 to 2020. The table showcases changes in pathogen prevalence across different age groups over the years, underlining the shifts in epidemiological patterns. "-" means no data. Relationship Between Viral Diarrhea and Time Between January 2017 and December 2020, the overall detection rates of the six studied viral pathogens followed a consistent seasonal pattern. Infections typically began to rise in September or October each year, peaked between January and March of the following year, and subsequently declined. This temporal distribution indicates a marked seasonality, with higher detection rates during the winter and early spring months (Fig. 3 ). The highest monthly detection rates observed during the study period were 60.61% (40/66) in 2017, 69.64% (39/56) in 2018, 41.03% (16/39) in 2019, and 80.77% (21/26) in 2020. Chi-square analysis showed significant interannual variation in detection rates, particularly between 2018 and 2019 ( P ₍₂₀₁₉₋₂₀₁₈₎ = 0.004, χ² = 8.461) and between 2019 and 2020 ( P ₍₂₀₂₀₋₂₀₁₉₎ = 0.001, χ² = 10.132). No significant difference was observed between 2017 and 2018 ( P ₍₂₀₁₈₋₂₀₁₇₎ = 0.395, χ² = 0.724). Peak detection months were primarily in spring (February and March) for 2017 and 2019, and in winter (December and January) for 2018 and 2020. Conversely, the lowest detection rates were generally recorded in autumn (September or October) for 2017 to 2019, and in May for 2020 (Fig. 3 ). The overall detection rate of viral diarrhea during the study period was 28.92% (802/2,773), with yearly rates of 32.9% in 2017 (247/751), 36.5% in 2018 (270/740), 24.2% in 2019 (177/731), and 19.6% in 2020 (108/551) (Table 1 ). This trend reflects an initial increase followed by a decline, with the most significant change occurring between 2018 and 2019 (Table 5 ). At the individual virus level, the detection rate of AstV showed a gradual year-over-year decline. In contrast, detection rates of EAdV, NV GI, and RV initially increased before declining in the later years, mirroring the overall trend. Detection rates for SaV remained relatively stable over the four-year period (Fig. 4 A, Table 5 ). Table 5 Yearly Detection Rates and Statistical Analysis of Six Pathogens Causing viral diarrhea, 2017–2020 Pathogen 2017 ~ 2018 2018 ~ 2019 2019 ~ 2020 AstV 0.460(0.545) 0.493(0.47) 0.055(3.688) EAdV 0.076(3.143) 1.164×10 − 4 (14.851) 0.008(6.999) NV GI 0.972(0.001) 1(3.489×10 − 32 ) 0.373(0.794) NV GII 0.179(1.806) 0.570(0.323) 0.003(8.742) RV 0.004(8.125) 2.478×10 − 5 (17.782) 2.125×10 − 5 (18.074) SaV 0.140(2.175) 0.073(3.224) 0.751(0.101) Total 0.160(1.973) 4.182×10 − 7 (25.609) 0.058(3.604) Note: It displays the annual detection rates of six key pathogens causing viral diarrhea in Yantai City from 2017 to 2020, alongside the statistical analysis comparing yearly changes. Detection rates are presented with corresponding P values and chi-square ( \(\:{\chi\:}^{2}\) ) statistics to assess the significance of year-over-year variations. A P value < 0.05 indicates statistically significant differences in detection rates between years. P values before parentheses and \(\:{\chi\:}^{2}\) within parentheses. RV was the most consistently detected pathogen, present in 46 out of 48 months. The only months without RV detection were July and September 2020. NV GII was the second most frequently detected virus, appearing in 44 out of 48 months. In contrast, SaV had the lowest frequency, detected in only 12 out of 48 months. RV was the predominant pathogen in 32 out of 48 months, followed by NV GII, which was the leading cause in 10 months (Fig. 4 B). Discussion Viral diarrhea continues to impose a substantial burden on global public health, disproportionately affecting the health and development of children. Although epidemiological surveillance plays a vital role in informing clinical diagnosis and guiding public health responses, comprehensive studies encompassing all age groups remain limited. This retrospective study analyzed the epidemiological characteristics of viral diarrhea across the entire population of Yantai, Shandong Province, from 2017 to 2020, with a focus on six common viral pathogens: AstV, EAdV, NV GI, NV GII, RV, and SaV. The overall detection rate of viral diarrhea in Yantai during the study period was 28.92%, which falls within the lower range of values reported in previous studies conducted across other regions of China. Reported detection rates have ranged from 18.80–46.87% [ 5 – 8 ], awhile a large-scale national prospective surveillance program reported a rate of 38.37% (58,620/152,792) [ 9 ]. The relatively lower detection rate observed in Yantai may reflect the impact of proactive local public health policies and healthcare infrastructure, although further improvements remain necessary. Notably, a significant decline in viral detection rates was observed between 2018 and 2019, whereas the changes between 2017 and 2018, and between 2019 and 2020, were not statistically significant. Interestingly, an uptick in detection was recorded at the end of 2020. These temporal dynamics suggest a possible weakening of viral diarrhea circulation in 2019 and 2020, potentially influenced by the onset of the COVID-19 pandemic. The implementation of non-pharmaceutical interventions-such as travel restrictions, school closures, and suspension of large public gatherings-likely played a role in disrupting the transmission of enteric viruses during this period. Additionally, studies have indicated that high expression of multiple integrins in the intestines of COVID-19 patients can reduce the incidence of diarrhea [ 10 ]. Research indicates that the monthly detection rate of viral diarrhea pathogens in Yantai follows a distinctive temporal trend—characterized by an initial decline followed by a resurgence, with seasonal peaks occurring in winter and spring. This seasonal pattern differs from those reported in other regions of China. For instance, surveillance data from Zhejiang Province show that diarrheal diseases are most prevalent during the summer and autumn months [ 5 ]. Similarly, in Beijing, detection rates of diarrheal pathogens tend to be highest in the summer, gradually rise again from November through March, and peak in February of the following year [ 8 ]. Understanding the seasonal trends of infectious diarrhea is essential for describing its epidemiological characteristics and aiding in diagnosis. However, the factors influencing the spread of diarrheal pathogens are complex. Diarrhea can be transmitted through contaminated food and water or person-to-person contact, with human behavior and climatic conditions, such as temperature and humidity, playing significant roles in its transmission [ 11 ]. Consequently, the epidemiological characteristics of diarrhea can be region-specific. The pathogen spectrum of viral diarrhea in Yantai closely mirrors that reported in other major urban centers across China, including Beijing, Zhejiang, Shanghai, and Shenzhen [ 5 – 8 ], as well as findings from a nationwide prospective surveillance study encompassing all age groups [ 9 ]. In this study, several instances of co-infection were identified, with dual and triple infections accounting for a combined multiple infection rate of 3.32%. The most common co-infection involved NV GII and RV, suggesting potential synergistic interactions or overlapping seasonal transmission windows between these two dominant pathogens. Of particular note, significant fluctuations in detection rates were observed in 2020. The positivity rates for AstV, EAdV, and RV declined markedly, whereas NV GI and SaV detection remained relatively stable. In contrast, the detection rate of NV GII increased substantially. This shift in the pathogen landscape warrants further investigation, as it may reflect changes in transmission dynamics, population immunity, or virus evolution-factors potentially influenced by public health interventions or behavioral changes during the COVID-19 pandemic period. Furthermore, the study shows that children under six years old have the highest pathogen detection rates, with RV being predominant. This finding aligns with results from Chongqing, Gansu, Lanzhou, Shenyang, and a national surveillance study [ 12 – 16 ]. Among all age groups, RV and NV GII were the most prevalent pathogens. Children are particularly vulnerable to infectious diarrhea due to their weaker immune systems, emphasizing the importance of enhanced monitoring to prevent outbreaks and facilitate interventions. Despite typically mild consequences in adults, they can transmit infections to children, representing a potential risk factor for pediatric diarrheal diseases. Thus, continued surveillance and research on infectious diarrhea in adults are also crucial. In summary, surveillance data from Yantai between 2017 and 2020 revealed that viral diarrhea exhibited a clear seasonal pattern, with incidence peaking during the winter and spring months. Among the six viral pathogens analyzed, RV was the most frequently detected and consistently dominant. Children under six years of age were identified as the most vulnerable population, emphasizing the need for targeted prevention and early intervention strategies in this demographic. While this study provides valuable insights into the local epidemiology of viral diarrhea, its relatively limited sample size and four-year study duration present constraints to generalizability. Future research involving larger populations and extended surveillance periods is essential to establish a more comprehensive understanding of pathogen distribution, transmission dynamics, and risk factors. Such efforts will enhance the effectiveness of public health interventions and inform clinical decision-making for the prevention, diagnosis, and management of infectious diarrhea.. Declarations Funding This study was conducted under the research project “2023 National Institute for Virus Disease Control and Prevention Youth Science Fund Project (IVDC-202303)”. Data availability Data are available from the corresponding author upon reasonable request. Author contributions Peihua Niu, Jiaming Huang, and Zhenlu Sun contributed equally as co-first authors. Peihua Niu and Jiaming Huang were responsible for drafting the manuscript, revising it, organizing the data, and performing the final review. Zhenlu Sun provided and analyzed the relevant data. Ying Li, Yiming Zhao, Xiaoyu Yang, Ping Cheng, Jianqiang Guo, Hongmei Zheng, and Meng Zhang contributed to the statistical analysis and proofreading. Xuejun Ma, Di Liu, Yi Yan, and Ji Wang, as corresponding authors, were responsible for revising and reviewing the manuscript. All authors have read and approved the final manuscript. They affirm that the work represents valid research and agree to be accountable for all aspects of the work, ensuring that questions related to accuracy or integrity were properly addressed. Conflict of interest The authors of this study unanimously assert no conflict of interest, ensuring the integrity and impartiality of the research outcomes presented. 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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-6543048","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":452014438,"identity":"b90e5d5b-7a01-4ba8-9eb4-66d9840b49dd","order_by":0,"name":"peihua niu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYDACZhCqkGBgOABiGICEEojRcoYkLSBdjG0MUC0MRGgxZ+cxe1w4zyKx7/gBxs8FBXfk+duTHzD83IFbi2Uzj7nxzG0SiTPPJDBLzzB4ZjjjzDMDxt4zuLUYHOYxk+bdJmFscIOBjZnH4DDjBokcqFPxapmD0GJPpJYGCTmYlkQitLCVG/Mck5CTPJPYLA3Ukgzyy8FefFrOH972mKemjofv+OGDn3n+HLbtb09++OAnHi1AwAalGRvgQgfwakBoGQWjYBSMglGAAwAApF9Io1OyI3UAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-5930-4234","institution":"Chinese Center for Disease Control and Prevention","correspondingAuthor":true,"prefix":"","firstName":"peihua","middleName":"","lastName":"niu","suffix":""},{"id":452014439,"identity":"b898d133-101a-46d8-97ce-84c323bd6ca9","order_by":1,"name":"Jiaming Huang","email":"","orcid":"","institution":"Wuhan Institute of Virology Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Jiaming","middleName":"","lastName":"Huang","suffix":""},{"id":452014440,"identity":"ba9d4554-572b-4176-9caf-17e009836378","order_by":2,"name":"Zhenlu Sun","email":"","orcid":"","institution":"Centers for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Zhenlu","middleName":"","lastName":"Sun","suffix":""},{"id":452014441,"identity":"927c4635-455e-4483-b27e-8d2a3d22d8fa","order_by":3,"name":"Ying Li","email":"","orcid":"","institution":"Wuhan Institute of Virology Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Li","suffix":""},{"id":452014442,"identity":"a583c12e-b6ca-4a03-a673-b6a026496cba","order_by":4,"name":"Yiming Zhao","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Yiming","middleName":"","lastName":"Zhao","suffix":""},{"id":452014443,"identity":"971ae16b-e974-43e1-add7-90392d5d01d4","order_by":5,"name":"Xiaoyu Yang","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Xiaoyu","middleName":"","lastName":"Yang","suffix":""},{"id":452014444,"identity":"e755eccf-cbfe-4c21-b8de-3de3592204e4","order_by":6,"name":"Ping Cheng","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Ping","middleName":"","lastName":"Cheng","suffix":""},{"id":452014445,"identity":"26415969-a3d0-4015-825c-7cab2d7e5028","order_by":7,"name":"Jianqiang Guo","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Jianqiang","middleName":"","lastName":"Guo","suffix":""},{"id":452014446,"identity":"3be4f608-262b-4eeb-abf9-1a6db7b35b27","order_by":8,"name":"Hongmei Zheng","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Hongmei","middleName":"","lastName":"Zheng","suffix":""},{"id":452014447,"identity":"da96d98a-db62-4918-9e55-4bcffe6b442e","order_by":9,"name":"Meng Zhang","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Meng","middleName":"","lastName":"Zhang","suffix":""},{"id":452014448,"identity":"f8f8d656-b1c0-4bd9-b19a-0e63410bc59f","order_by":10,"name":"Xuejun Ma","email":"","orcid":"","institution":"Chinese Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Xuejun","middleName":"","lastName":"Ma","suffix":""},{"id":452014449,"identity":"e12cc25c-3110-4692-b4dd-5dda3e70ec8b","order_by":11,"name":"Di Liu","email":"","orcid":"","institution":"Wuhan Institute of Virology Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Di","middleName":"","lastName":"Liu","suffix":""},{"id":452014450,"identity":"f088429c-e3ab-44a3-bce0-8bd2bb40e849","order_by":12,"name":"Yi Yan","email":"","orcid":"","institution":"Wuhan Institute of Virology Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Yan","suffix":""},{"id":452014451,"identity":"e459b588-545d-423b-82f3-28d63428e51b","order_by":13,"name":"Ji Wang","email":"","orcid":"https://orcid.org/0009-0001-7457-298X","institution":"Chinese Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Ji","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-04-28 02:08:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6543048/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6543048/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82354998,"identity":"dbe8d132-0bfa-4666-a833-b9c89b670d44","added_by":"auto","created_at":"2025-05-09 11:12:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":475670,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution and Positivity Rates of Viral Diarrhea by Age Group in Yantai City, 2017-2020. Age groups are divided into infants (\u0026lt;1 year), toddlers (1-3 years), preschool children (3-6 years), children (6-18 years), and adults (\u0026gt;18 years), with adults further categorized by decade up to 70+ years. Positivity rates for the viral pathogens are indicated alongside the distribution, providing insights into age-specific vulnerabilities to these viruses.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6543048/v1/87544ddc9044230fa648e8fb.png"},{"id":82356944,"identity":"88ca5d8b-f49a-4b18-bd3b-96aa41b8eb29","added_by":"auto","created_at":"2025-05-09 11:20:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2234806,"visible":true,"origin":"","legend":"\u003cp\u003eAge-Specific Pathogen Distribution in Cases of Viral Diarrhea in Yantai City, 2017-2020. A. Overall distribution of ages among patients infected with the six pathogens causing viral diarrhea. B. Pathogen Composition by Age Groups. Details the composition of pathogens within specific age groups, including infants (\u0026lt;1 year), toddlers (≥1 year and \u0026lt;3 years), preschoolers (≥3 years and \u0026lt;6 years), children (≥6 years and \u0026lt;18 years), and adults (≥18 years). C. Annual Trends in Age-Specific Pathogen Distribution. Illustrates the year-to-year variation in the distribution of pathogens across different age groups, reflecting changes in the epidemiological landscape of viral diarrhea in Yantai City from 2017 to 2020.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6543048/v1/ba9bbfafa82c51caab392f4f.png"},{"id":82355004,"identity":"66b381a2-27ef-43cc-89fe-4e4804897d8b","added_by":"auto","created_at":"2025-05-09 11:12:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1114176,"visible":true,"origin":"","legend":"\u003cp\u003eEpidemiological Trends of Viral Diarrhea in Yantai City, 2017-2020. The bar graph represents the total number of gastroenteritis cases reported each year, while the overlaid line graph indicates the annual positivity rates of the six key viral pathogens (AstV, EAdV, NV GI, NV GII, RV, and SaV)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6543048/v1/7c3938b024d856bf455f6e1b.png"},{"id":82355009,"identity":"2d35d602-c721-4d53-a6d8-226530585c6d","added_by":"auto","created_at":"2025-05-09 11:12:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1078667,"visible":true,"origin":"","legend":"\u003cp\u003eEpidemiological Characteristics of the Six Pathogens Causing Viral Diarrhea. A. Detection rates of the six pathogens causing viral diarrhea over the years, with markers indicating the \u003cem\u003eP\u003c/em\u003e-values of the chi-square test. \"ns\" represents\u003cem\u003e P\u003c/em\u003e\u0026gt;0.05, \"*\" represents 0.01\u0026lt;\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05, \"**\" represents 0.001\u0026lt;\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01, and \"***\" represents \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001. B. Monthly detection rates of the six pathogens causing viral diarrhea.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6543048/v1/4b1c3672bbf8303fb80f2373.png"},{"id":83461926,"identity":"e200b112-ac1a-4969-b7ca-79fd8a34957a","added_by":"auto","created_at":"2025-05-26 16:42:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5470476,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6543048/v1/1c8ed659-879d-4601-9619-5a75db71d782.pdf"}],"financialInterests":"","formattedTitle":"Epidemiological Analysis of Viral Diarrhea in Yantai, Shandong, China (2017-2020): Insights into Seasonal Patterns and Viral Agents","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eInfectious diarrhea remains a major global public health concern, characterized by high morbidity and considerable mortality, particularly among children. It is caused by a broad range of pathogens, including bacteria, viruses, and parasites, and poses a persistent threat to human health and survival. According to the World Health Organization, an estimated 1.7\u0026nbsp;billion cases of childhood diarrhea occur annually, making it the second leading cause of death among children under the age of five [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Although gastrointestinal infections continue to impose a healthcare burden in high-income countries, the impact is disproportionately greater in low- and middle-income countries, where access to clean water, sanitation, and timely medical care may be limited [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Given that China has the second-largest population of children globally, strengthening the surveillance and management of diarrheal diseases represents a public health priority of critical importance.\u003c/p\u003e \u003cp\u003eAmong the etiological agents of infectious diarrhea, viruses constitute the leading cause, particularly in pediatric populations. The most common viral pathogens include astrovirus (AstV), enteric adenovirus (EAdV), norovirus (NV) genogroups I and II (GI and GII), rotavirus (RV), and sapovirus (SaV) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Understanding the epidemiological profiles and transmission dynamics of these viruses is essential for effective prevention, timely diagnosis, and informed public health interventions targeting viral diarrhea. Since the resolution of the COVID-19 pandemic, there has been a notable gap in local epidemiological data on diarrheal pathogens in Yantai, Shandong Province. Surveillance data specific to this region have been limited, despite the importance of regional variation in pathogen distribution. To address this gap and support the development of targeted control measures, this study investigates the distribution and seasonal characteristics of six key viral pathogens associated with diarrhea in Yantai between 2017 and 2020. By characterizing the pathogen spectrum and associated epidemiological trends, the study aims to provide an evidence base for enhanced surveillance strategies and inform public health policy for the prevention and management of viral diarrheal diseases.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipant Recruitment and Specimen Collection\u003c/h2\u003e \u003cp\u003eFrom 2017 to 2020, suspected cases of infectious diarrhea were collected from various medical institutions across 13 districts and counties in Yantai, Shandong Province. These cases were organized and analyzed by the Yantai Center for Disease Control and Prevention. Fecal specimens were centrally collected and tested, while epidemiological data were gathered on-site by local medical institutions. Both clinical and laboratory diagnoses were conducted in accordance with the \u003cem\u003eDiagnostic Criteria for Infectious Diarrhea\u003c/em\u003e (WS271-2007). This study was reviewed and approved by the Ethics Committee of Preventive Medicine at the Yantai Center for Disease Control and Prevention (Ethics Approval No. YYLLS 2023-30). Written informed consent was obtained from the guardians of all participants.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eNucleic Acid Extraction\u003c/h3\u003e\n\u003cp\u003eA small quantity of fecal matter\u0026mdash;approximately the size of a mung bean\u0026mdash;or 50\u0026ndash;100 microliters of liquid stool was mixed with 500 microliters of isotonic sodium chloride solution to prepare a 10\u0026ndash;20% suspension. The mixture was centrifuged at 8,000 rpm for 5 minutes. From the resulting supernatant, 200 microliters were extracted and processed using an automated nucleic acid extractor with a commercially available reagent kit (Shengxiang Biotech Co., Ltd., Hunan, China). All procedures were carried out in accordance with the manufacturer's instructions.\u003c/p\u003e\n\u003ch3\u003eNucleic Acid Detection\u003c/h3\u003e\n\u003cp\u003eNucleic acid detection of six viral pathogens associated with infectious diarrhea, including AstV, EAdV, NV GI, NV GII, RV, and SaV, was performed using a commercial detection kit (BioGerm Medical Technology Co., Ltd., Shanghai, China). All procedures were carried out in strict accordance with the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData were presented as counts and percentages. Median values were reported alongside interquartile ranges (IQRs). Group comparisons were conducted using chi-square tests and Mann\u0026ndash;Whitney U tests. A \u003cem\u003eP\u003c/em\u003e-value of less than 0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDetection of Six Pathogens\u003c/h2\u003e \u003cp\u003eDuring the study period, a total of 2,773 cases meeting the \u003cem\u003eDiagnostic Criteria for Infectious Diarrhea\u003c/em\u003e (WS271-2007) were included for analysis. The annual distribution of reported cases was as follows: 751 cases (27.08%) in 2017, 740 cases (26.69%) in 2018, 731 cases (26.36%) in 2019, and 551 cases (19.87%) in 2020. Among these, 802 cases (28.92%) tested positive for at least one viral pathogen. Of these, 710 cases (25.60%) were positive for a single virus, while 92 cases (3.32%) showed evidence of co-infection. Specifically, 86 cases (3.10%) involved co-infection with two pathogens, and 6 cases (0.22%) involved three-pathogen co-infections (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\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\u003eAnnual Case Distribution and Pathogen Detection Rates for Infectious Diarrhea in Yantai City, Shandong Province, 2017\u0026ndash;2020\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;751\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;740\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;731\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;551\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;2773\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e410(54.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e409(55.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e407(55.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e286(51.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1512(54.43)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e341(45.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e331(44.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e324(44.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e265(48.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1261(45.47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\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\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e112(14.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77(10.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55(7.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53(9.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e297(10.71)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e132(17.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e165(22.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e190(25.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70(12.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e557(20.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19(2.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28(3.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49(6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32(5.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e128(4.62)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25(3.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34(4.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49(6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58(10.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e166(5.99)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e85(11.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72(9.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63(8.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58(10.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e278(10.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61(8.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70(9.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54(7.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45(8.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e230(8.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59(7.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53(7.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56(7.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44(7.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e212(7.65)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e85(11.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78(10.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e76(10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53(9.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e292(10.53)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92(12.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92(12.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e82(11.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82(14.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e348(12.55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81(10.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71(9.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57(7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56(10.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e265(9.56)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e247(32.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e270(36.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e177(24.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e108(19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e802(28.92)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e225(29.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e227(30.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e155(21.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e103(18.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e710(25.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22(2.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43(5.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22(3.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5(0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e92(3.32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathogen\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\u003eAstV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16(2.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11(1.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7(0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e34(1.23)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEAdV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33(4.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49(6.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17(2.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(0.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e101(3.64)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNV GI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11(1.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12(1.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12(1.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5(0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e40(1.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNV GII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68(9.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52(7.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45(6.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60(10.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e225(8.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e140(18.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e184(24.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e116(15.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43(7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e483(17.42)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSaV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3(0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9(1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2(0.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(0.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17(0.61)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: Percentages are based on the total number of cases tested each year. Single infection refers to cases where only one pathogen was detected; co-infection refers to cases where two or more pathogens were detected simultaneously. Data are presented as n(%).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCo-infection Rates of Viral Pathogens in Infectious Diarrhea Cases in Yantai City, 2017\u0026ndash;2020\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathogen\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of detections\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDetection rate(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNV GII\u0026thinsp;+\u0026thinsp;RV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEAdV\u0026thinsp;+\u0026thinsp;RV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAstV\u0026thinsp;+\u0026thinsp;RV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNV GI\u0026thinsp;+\u0026thinsp;NV GII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRV\u0026thinsp;+\u0026thinsp;SaV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNV GI\u0026thinsp;+\u0026thinsp;RV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNV GI\u0026thinsp;+\u0026thinsp;NV GII\u0026thinsp;+\u0026thinsp;RV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEAdV\u0026thinsp;+\u0026thinsp;NV GII\u0026thinsp;+\u0026thinsp;RV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAstV\u0026thinsp;+\u0026thinsp;SaV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEAdV\u0026thinsp;+\u0026thinsp;SaV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAstV\u0026thinsp;+\u0026thinsp;EAdV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAstV\u0026thinsp;+\u0026thinsp;NV GII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEAdV\u0026thinsp;+\u0026thinsp;NV GI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: The table lists the combinations of pathogens detected in co-infections and presents the number of detections alongside the corresponding percentage of total cases.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRotavirus (RV) was the most frequently detected pathogen, identified in 483 cases (17.42%), followed by norovirus genogroup II (NV GII), detected in 225 cases (8.11%). These two pathogens exhibited persistently high detection rates throughout the study period. The most common co-infection was NV GII and RV, found in 33 cases (1.19%), followed by enteric adenovirus (EAdV) and RV, observed in 22 cases (0.79%). Noteworthy triple co-infections included NV GI, NV GII, and RV, as well as EAdV, NV GII, and RV, each detected in 3 cases (0.11%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGender Distribution of viral diarrhea Cases\u003c/h3\u003e\n\u003cp\u003eOf the 2,773 reported cases, 1,512 (54.43%) were male and 1,261 (45.57%) were female. The overall detection rate of viral diarrhea was 29.96% (453/1,512) in males and 27.68% (349/1,261) in females. Statistical analysis revealed no significant difference in viral diarrhea incidence between genders. Similarly, the detection rates for each of the six viral pathogens did not differ significantly between male and female patients (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGender-Based Comparison of Viral Pathogen Detection in Infectious Diarrhea Cases in Yantai City, 2017\u0026ndash;2020\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of cases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAstV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEAdV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNV GI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNV GII\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSaV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e453\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e349\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\chi\\:}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.635\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.719\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eNote: It compares the detection rates of various viral pathogens causing infectious diarrhea between male and female patients in Yantai City from 2017 to 2020. It lists the number of cases per gender and the detection counts for specific pathogens (AstV, EAdV, NV GI, NV GII, RV, SaV). Statistical analysis results (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\chi\\:}^{2}\\)\u003c/span\u003e\u003c/span\u003e and P value) indicate the significance of differences in pathogen prevalence by gender. \"-\" means no data.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eRelationship Between Viral Diarrhea and Age\u003c/h3\u003e\n\u003cp\u003eThe age of patients ranged from 10 days to 99 years, with a median age of 28 years (interquartile range: 1\u0026ndash;57 years). Of the total cases, 450 (39.20%) were under 18 years of age, while 352 (21.66%) were 18 years or older. Statistical analysis revealed a significant difference in the incidence of viral diarrhea between minors and adults (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e=99.795, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.690\u0026times;10⁻\u0026sup2;\u0026sup3;).\u003c/p\u003e \u003cp\u003eThe detection rate of viral pathogens increased during early childhood, peaking before the age of three, and generally declined with advancing age. Toddlers (ages 1\u0026ndash;2 years) constituted the largest age group, accounting for 557 cases (20.09%), followed by individuals aged 60\u0026ndash;69 years (348 cases, 12.55%) and infants under one year (297 cases, 10.71%). The highest detection rate was observed in the toddler group (264 cases, 47.40%), followed by preschool children aged 3\u0026ndash;5 years (detection rate: 39.06%) and infants (30.98%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe median age of detection varied across viral pathogens, reflecting differences in age-related susceptibility. Median ages were 28 years for AstV, 2 years for EAdV, 31 years for NV GI, 17 years for NV GII, 2 years for RV, and 2 years for SaV. Violin plot analyses demonstrated that EAdV, RV, NV GII, and SaV predominantly affected infants and young children, whereas AstV and NV GI were more evenly distributed across all age groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAge-stratified analysis of the pathogen spectrum revealed that RV was the most frequently detected virus in infants, toddlers, preschool-aged children, and adults, while NV GII was most prevalent among school-age children (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). The age distribution patterns of the six pathogens remained stable throughout the study period (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). No statistically significant year-to-year variation was observed in age-specific prevalence based on the Mann\u0026ndash;Whitney U test, indicating a consistent age-related distribution over time (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnnual Comparison of Age Distribution Among Patients with viral diarrhea Pathogens in Yantai City, 2017\u0026ndash;2020\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathogen\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017\u0026thinsp;~\u0026thinsp;2018\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026thinsp;~\u0026thinsp;2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2019\u0026thinsp;~\u0026thinsp;2020\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAstV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEAdV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNV GI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNV GII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.275\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.805\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSaV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.513\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: It provides a year-by-year comparison of the age distribution of patients infected with six key pathogens causing viral diarrhea in Yantai City from 2017 to 2020. The table showcases changes in pathogen prevalence across different age groups over the years, underlining the shifts in epidemiological patterns. \"-\" means no data.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRelationship Between Viral Diarrhea and Time\u003c/h2\u003e \u003cp\u003eBetween January 2017 and December 2020, the overall detection rates of the six studied viral pathogens followed a consistent seasonal pattern. Infections typically began to rise in September or October each year, peaked between January and March of the following year, and subsequently declined. This temporal distribution indicates a marked seasonality, with higher detection rates during the winter and early spring months (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe highest monthly detection rates observed during the study period were 60.61% (40/66) in 2017, 69.64% (39/56) in 2018, 41.03% (16/39) in 2019, and 80.77% (21/26) in 2020. Chi-square analysis showed significant interannual variation in detection rates, particularly between 2018 and 2019 (\u003cem\u003eP\u003c/em\u003e₍₂₀₁₉₋₂₀₁₈₎ = 0.004, χ\u0026sup2; = 8.461) and between 2019 and 2020 (\u003cem\u003eP\u003c/em\u003e₍₂₀₂₀₋₂₀₁₉₎ = 0.001, χ\u0026sup2; = 10.132). No significant difference was observed between 2017 and 2018 (\u003cem\u003eP\u003c/em\u003e₍₂₀₁₈₋₂₀₁₇₎ = 0.395, χ\u0026sup2; = 0.724). Peak detection months were primarily in spring (February and March) for 2017 and 2019, and in winter (December and January) for 2018 and 2020. Conversely, the lowest detection rates were generally recorded in autumn (September or October) for 2017 to 2019, and in May for 2020 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe overall detection rate of viral diarrhea during the study period was 28.92% (802/2,773), with yearly rates of 32.9% in 2017 (247/751), 36.5% in 2018 (270/740), 24.2% in 2019 (177/731), and 19.6% in 2020 (108/551) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This trend reflects an initial increase followed by a decline, with the most significant change occurring between 2018 and 2019 (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). At the individual virus level, the detection rate of AstV showed a gradual year-over-year decline. In contrast, detection rates of EAdV, NV GI, and RV initially increased before declining in the later years, mirroring the overall trend. Detection rates for SaV remained relatively stable over the four-year period (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eYearly Detection Rates and Statistical Analysis of Six Pathogens Causing viral diarrhea, 2017\u0026ndash;2020\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathogen\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017\u0026thinsp;~\u0026thinsp;2018\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u0026thinsp;~\u0026thinsp;2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2019\u0026thinsp;~\u0026thinsp;2020\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAstV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.460(0.545)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.493(0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.055(3.688)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEAdV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.076(3.143)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.164\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e(14.851)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.008(6.999)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNV GI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.972(0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1(3.489\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;32\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.373(0.794)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNV GII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.179(1.806)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.570(0.323)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003(8.742)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.004(8.125)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.478\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e(17.782)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.125\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e(18.074)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSaV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.140(2.175)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.073(3.224)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.751(0.101)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.160(1.973)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.182\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e(25.609)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.058(3.604)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: It displays the annual detection rates of six key pathogens causing viral diarrhea in Yantai City from 2017 to 2020, alongside the statistical analysis comparing yearly changes. Detection rates are presented with corresponding \u003cem\u003eP\u003c/em\u003e values and chi-square ( \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\chi\\:}^{2}\\)\u003c/span\u003e\u003c/span\u003e) statistics to assess the significance of year-over-year variations. A \u003cem\u003eP\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates statistically significant differences in detection rates between years. \u003cem\u003eP\u003c/em\u003e values before parentheses and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\chi\\:}^{2}\\)\u003c/span\u003e\u003c/span\u003e within parentheses.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRV was the most consistently detected pathogen, present in 46 out of 48 months. The only months without RV detection were July and September 2020. NV GII was the second most frequently detected virus, appearing in 44 out of 48 months. In contrast, SaV had the lowest frequency, detected in only 12 out of 48 months. RV was the predominant pathogen in 32 out of 48 months, followed by NV GII, which was the leading cause in 10 months (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eViral diarrhea continues to impose a substantial burden on global public health, disproportionately affecting the health and development of children. Although epidemiological surveillance plays a vital role in informing clinical diagnosis and guiding public health responses, comprehensive studies encompassing all age groups remain limited. This retrospective study analyzed the epidemiological characteristics of viral diarrhea across the entire population of Yantai, Shandong Province, from 2017 to 2020, with a focus on six common viral pathogens: AstV, EAdV, NV GI, NV GII, RV, and SaV.\u003c/p\u003e \u003cp\u003eThe overall detection rate of viral diarrhea in Yantai during the study period was 28.92%, which falls within the lower range of values reported in previous studies conducted across other regions of China. Reported detection rates have ranged from 18.80\u0026ndash;46.87% [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], awhile a large-scale national prospective surveillance program reported a rate of 38.37% (58,620/152,792) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The relatively lower detection rate observed in Yantai may reflect the impact of proactive local public health policies and healthcare infrastructure, although further improvements remain necessary. Notably, a significant decline in viral detection rates was observed between 2018 and 2019, whereas the changes between 2017 and 2018, and between 2019 and 2020, were not statistically significant. Interestingly, an uptick in detection was recorded at the end of 2020. These temporal dynamics suggest a possible weakening of viral diarrhea circulation in 2019 and 2020, potentially influenced by the onset of the COVID-19 pandemic. The implementation of non-pharmaceutical interventions-such as travel restrictions, school closures, and suspension of large public gatherings-likely played a role in disrupting the transmission of enteric viruses during this period. Additionally, studies have indicated that high expression of multiple integrins in the intestines of COVID-19 patients can reduce the incidence of diarrhea [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eResearch indicates that the monthly detection rate of viral diarrhea pathogens in Yantai follows a distinctive temporal trend\u0026mdash;characterized by an initial decline followed by a resurgence, with seasonal peaks occurring in winter and spring. This seasonal pattern differs from those reported in other regions of China. For instance, surveillance data from Zhejiang Province show that diarrheal diseases are most prevalent during the summer and autumn months [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Similarly, in Beijing, detection rates of diarrheal pathogens tend to be highest in the summer, gradually rise again from November through March, and peak in February of the following year [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Understanding the seasonal trends of infectious diarrhea is essential for describing its epidemiological characteristics and aiding in diagnosis. However, the factors influencing the spread of diarrheal pathogens are complex. Diarrhea can be transmitted through contaminated food and water or person-to-person contact, with human behavior and climatic conditions, such as temperature and humidity, playing significant roles in its transmission [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Consequently, the epidemiological characteristics of diarrhea can be region-specific.\u003c/p\u003e \u003cp\u003eThe pathogen spectrum of viral diarrhea in Yantai closely mirrors that reported in other major urban centers across China, including Beijing, Zhejiang, Shanghai, and Shenzhen [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], as well as findings from a nationwide prospective surveillance study encompassing all age groups [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In this study, several instances of co-infection were identified, with dual and triple infections accounting for a combined multiple infection rate of 3.32%. The most common co-infection involved NV GII and RV, suggesting potential synergistic interactions or overlapping seasonal transmission windows between these two dominant pathogens. Of particular note, significant fluctuations in detection rates were observed in 2020. The positivity rates for AstV, EAdV, and RV declined markedly, whereas NV GI and SaV detection remained relatively stable. In contrast, the detection rate of NV GII increased substantially. This shift in the pathogen landscape warrants further investigation, as it may reflect changes in transmission dynamics, population immunity, or virus evolution-factors potentially influenced by public health interventions or behavioral changes during the COVID-19 pandemic period.\u003c/p\u003e \u003cp\u003eFurthermore, the study shows that children under six years old have the highest pathogen detection rates, with RV being predominant. This finding aligns with results from Chongqing, Gansu, Lanzhou, Shenyang, and a national surveillance study [\u003cspan additionalcitationids=\"CR13 CR14 CR15\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Among all age groups, RV and NV GII were the most prevalent pathogens. Children are particularly vulnerable to infectious diarrhea due to their weaker immune systems, emphasizing the importance of enhanced monitoring to prevent outbreaks and facilitate interventions. Despite typically mild consequences in adults, they can transmit infections to children, representing a potential risk factor for pediatric diarrheal diseases. Thus, continued surveillance and research on infectious diarrhea in adults are also crucial.\u003c/p\u003e \u003cp\u003eIn summary, surveillance data from Yantai between 2017 and 2020 revealed that viral diarrhea exhibited a clear seasonal pattern, with incidence peaking during the winter and spring months. Among the six viral pathogens analyzed, RV was the most frequently detected and consistently dominant. Children under six years of age were identified as the most vulnerable population, emphasizing the need for targeted prevention and early intervention strategies in this demographic. While this study provides valuable insights into the local epidemiology of viral diarrhea, its relatively limited sample size and four-year study duration present constraints to generalizability. Future research involving larger populations and extended surveillance periods is essential to establish a more comprehensive understanding of pathogen distribution, transmission dynamics, and risk factors. Such efforts will enhance the effectiveness of public health interventions and inform clinical decision-making for the prevention, diagnosis, and management of infectious diarrhea..\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted under the research project \u0026ldquo;2023 National Institute for Virus Disease Control and Prevention Youth Science Fund Project (IVDC-202303)\u0026rdquo;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePeihua Niu, Jiaming Huang, and Zhenlu Sun contributed equally as co-first authors. Peihua Niu and Jiaming Huang were responsible for drafting the manuscript, revising it, organizing the data, and performing the final review. Zhenlu Sun provided and analyzed the relevant data. Ying Li, Yiming Zhao, Xiaoyu Yang, Ping Cheng, Jianqiang Guo, Hongmei Zheng, and Meng Zhang contributed to the statistical analysis and proofreading. Xuejun Ma, Di Liu, Yi Yan, and Ji Wang, as corresponding authors, were responsible for revising and reviewing the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors have read and approved the final manuscript. They affirm that the work represents valid research and agree to be accountable for all aspects of the work, ensuring that questions related to accuracy or integrity were properly addressed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors of this study unanimously assert no conflict of interest, ensuring the integrity and impartiality of the research outcomes presented.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eIaniro G, Rizzatti G, Plomer M et al (2018) Bacillus clausii for the Treatment of Acute Diarrhea in Children: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. 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J Infect 71:19\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jinf.2015.03.001\u003c/span\u003e\u003cspan address=\"10.1016/j.jinf.2015.03.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6543048/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6543048/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study aimed to investigate the epidemiological characteristics of viral diarrhea in Yantai City, Shandong Province, from 2017 to 2020. A total of 2,773 suspected cases of infectious diarrhea were collected from healthcare institutions across 13 districts and counties in Yantai. Specimens were tested for astrovirus, enteric adenovirus, norovirus genogroups I and II (GI and GII), rotavirus, and sapovirus using nucleic acid detection kits. Positive cases were analyzed to characterize the pathogen spectrum and epidemiological features. Statistical analyses were conducted using chi-square and Mann\u0026ndash;Whitney U tests. The detection rates of viral diarrhea were higher during spring and winter. The positivity rates for astrovirus, adenovirus, norovirus GI, norovirus GII, rotavirus, and sapovirus were 1.23%, 3.64%, 1.44%, 8.11%, 17.42%, and 0.61%, respectively. Among these, rotavirus and norovirus GII showed consistently high detection rates across the study period. Children under six years of age had the highest pathogen detection rates, with rotavirus being the predominant agent. The viral spectrum remained relatively consistent across age groups, and no significant changes in age distribution were observed over time. In conclusion, viral diarrhea in Yantai exhibited a clear seasonal pattern, with peaks in spring and winter. The overall detection rate showed an upward trend followed by a decline, with notable changes occurring between 2018 and 2019. Rotavirus was the most prevalent pathogen identified. Children under six years old represented the most affected population. These findings highlight the importance of strengthened surveillance for infectious diarrhea, particularly viral diarrhea among young children.\u003c/p\u003e","manuscriptTitle":"Epidemiological Analysis of Viral Diarrhea in Yantai, Shandong, China (2017-2020): Insights into Seasonal Patterns and Viral Agents","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-09 11:12:10","doi":"10.21203/rs.3.rs-6543048/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ccd7061f-eb36-40a4-829e-9f7cf81cafcb","owner":[],"postedDate":"May 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-26T16:42:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-09 11:12:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6543048","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6543048","identity":"rs-6543048","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}