Comparative Investigation and Trends of Respiratory Viruses using Wastewater-Based Epidemiological Surveillance in Patras, Greece

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Wastewater-based epidemiology (WBE) has emerged as a powerful, non-invasive method for tracking viral transmission within communities. While initially focused on SARS-CoV-2, WBE now offers the potential for multiplex surveillance of a broader range of respiratory pathogens. This study applied WBE to monitor the circulation of six major respiratory viruses such as Human adenovirus (HAdV), SARS-CoV-2, Influenza A and B, Respiratory Syncytial Virus (RSV) A/B, and Rhinoviruses, over a six-month period (ISO weeks 2022-40 to 2023-13) in the city of Patras, Greece. Weekly composite samples from a central wastewater treatment plant were analyzed via quantitative PCR, and viral genome concentrations were normalized per 100,000 inhabitants. The results revealed distinct circulation patterns: HAdV and SARS-CoV-2 were detected consistently throughout the period, while Influenza A peaked during the winter months, followed by Influenza B and RSV in early 2023. Rhinoviruses displayed intermittent peaks, indicating multiple waves or persistent low-level transmission. Correlation analyses showed strong positive associations between influenza viruses, RSV, and SARS-CoV-2, suggesting synchronized seasonal trends. Hierarchical cluster analysis classified the viruses into three distinct groups: (1) an epidemic cluster including Influenza A/B, RSV, and Rhinoviruses; (2) a persistently present cluster represented by HAdV; and (3) a separate episodic cluster characterized by SARS-CoV-2. These groupings reflect differences in viral epidemiology and shedding behaviour. This study confirms the effectiveness of WBE in tracking the temporal dynamics of multiple respiratory viruses and provides evidence of its utility in supplementing traditional clinical surveillance systems. The consistent detection of underreported pathogens such as HAdV underscores the added value of environmental monitoring for public health preparedness and early warning applications. These findings advocate for the integration of WBE into routine respiratory virus surveillance frameworks. Figures Figure 1 Figure 2 1. Introduction Since the end of the COVID-19 pandemic, the use of wastewater-based epidemiology (WBE) has accelerated exponentially. It has been used to detect and epidemiologically monitor the presence of SARS-CoV-2. In addition to distinguishing infectious diseases, the distinct presence of various pharmaceutical and chemical components has been used to assess drug use patterns and assess collective population exposure. The potential of WBE is amply illustrated by its ability to predict or prevent potential outbreaks in a community before patients develop clinical symptoms and up to three weeks before diagnostic clinical cases (Sims & Kasprzyk-Hordern, 2020 ). The economic feasibility of the methodology is underlined by its ability to provide a timely snapshot of the course and presence of a pathogen in the population, contributing to the epidemiological surveillance of the disease, accompanying the clinical recording (hospital admissions or recorded cases) by the health systems of the countries. In investigating the bioethical issues and the protection of personal data of the epidemiological surveillance of wastewater, the competent courts have concluded that no issue arises regarding wastewater that ends up in the public sewer network of large cities and populations (Doorn et al. 2022; Gable et al. 2020 ). Currently, several countries have established national WBE frameworks for SARS-CoV-2 enforcement, which were formalised by Commission guidance in March 2021, and efforts are now underway to integrate additional emerging pathogens or persistent pathogens, their strains or variants, into countries’ epidemiological protection systems (Tavazzi et al. 2023 ). Furthermore, the latent period of the disease, which can extend up to two weeks before the onset of symptoms, introduces time lags between the onset of the disease and the subsequent reporting of clinical outcomes. These observations collectively suggest that urban wastewater within communities may harbour the virus at significant concentrations. Throughout the pandemic, WBE has emerged as a promising tool for providing insights into the prevalence and course of the disease, highlighting its potential as a valuable adjunct to surveillance efforts (Ahmed et al. 2020 , Dumke et al. 2022 ). The rationale behind the selection of specific respiratory viruses is presented in the following section. Human adenoviruses (HAdV), recognized, are prominent pathogens associated with a diverse array of human afflictions, including respiratory illnesses, gastroenteritis, conjunctivitis, and chronic systemic infections, and are particularly notable among immunocompromised individuals (Osuolale et al. 2025). Characterized by their exclusive human host tropism, adenoviruses are ubiquitously present in terrestrial and aquatic environments. Instances of adenovirus outbreaks have been documented across various settings, spanning military facilities, recreational water venues, healthcare institutions, and residential care facilities (Flint & Nemerow, 2017 ) The pervasive presence of these viruses in wastewater and aquatic ecosystems underscores their heightened prevalence compared to that of other enteric viruses. Owing to their environmental stability and robust detectability, human adenoviruses are valuable indicators of wastewater contamination and offer insights into the presence of other viral pathogens (Bofill-Mas et al. 2006 ) Extensive research underscores the proclivity of adenoviruses to manifest in conspicuously elevated concentrations relative to their viral counterparts, rendering them promising candidates as biomarkers within aquatic ecosystems (Albinana-Gimenez et al. 2009 ). Temporal and geographical variations in adenovirus serotype prevalence underscore the dynamic nature of adenovirus epidemiology. Documented alterations in serotype prevalence across different regions suggest the potential emergence of novel strains and the displacement of existing strains. Despite adenovirus outbreaks predominantly occurring during winter or early spring, infections occur year-round without distinct seasonality, particularly within enclosed communities where epidemic trends tend to escalate (Lynch et al. 2016) HAdV can be transmitted through airborne routes. Adenoviruses responsible for respiratory infections, such as types 3, 4, 7 and 21 - are known to spread through respiratory droplets expelled when an infected person coughs, sneezes or talks. These droplets can be inhaled by people nearby or sit on surfaces, leading to indirect transmission. HAdV types 3, 4, 7 and 21 have been strongly associated with outbreaks of acute respiratory disease (ARD), particularly in crowded settings such as military barracks, schools and healthcare facilities. For example, studies have shown that HAdV-3 and HAdV-7 are major causes of severe respiratory infections in children, sometimes leading to life-threatening conditions. Similarly, HAdV-21 has been implicated in severe respiratory disease epidemics (Zaki et al. 2020 ). Research indicates that HAdV-7 infections can result in more severe disease outcomes compared to other types. A study published in BMC Infectious Diseases found that HAdV-7 infection caused more severe pneumonia, respiratory failure, and longer hospitalization periods compared to HAdV-3. This highlights the virulence of certain adenovirus types and the need for vigilant monitoring and preventive strategies (Fu et al. 2019 ). Respiratory Syncytial Virus (RSV) is a common pathogen in children and increasingly recognized in adults, especially the elderly. It primarily causes upper respiratory infections but can lead to bronchiolitis in young children and, in rare cases, progress to pneumonia, respiratory failure, apnea, or death. Treatment is mostly supportive. Passive immunization is available for at-risk children, such as premature infants or those with cardiac, pulmonary, or neuromuscular conditions. One antiviral treatment exists, but its use is limited due to cost, side effects, and limited efficacy, and is reserved for high-risk patients (Hernroth eta al 2002, Corman et al. 2012 ). RSV is a single-stranded, negative-sense RNA virus from the Paramyxoviridae family and Pneumovirus genus. Discovered in chimpanzees in 1955, it was soon identified in humans (Sims et al. 2020). RSV infects about 90% of children by age two and frequently affects older children and adults due to weak long-term immunity. While most infections are mild, up to 40% of primary infections in children under one cause bronchiolitis. Globally, Respiratory syncytial virus (RSV) is estimated to cause approximately 33 million episodes of acute lower respiratory infections globally in young children annually, resulting in around 3 million hospitalizations and up to 118,000–199,000 deaths, predominantly in low- and middle-income settings. (Public Health Agency of Canada, 2024 ). In temperate climates, RSV incidence typically peaks during winter‑spring, while tropical regions exhibit more variable seasonal patterns. High‑risk groups include premature infants, children with underlying health conditions, and the elderly, who face increased risk of severe outcomes and hospitalization. (WHO, 2025) Influenza is a contagious viral infection affecting the upper and lower respiratory tract. It spreads through respiratory droplets and contaminated surfaces. Infected individuals are contagious even before symptoms appear and remain so for 5–7 days. While most recover in a few days, serious complications like pneumonia can occur, especially in young children, the elderly, pregnant women, and immunocompromised individuals. Symptoms include fever, cough, sore throat, and runny nose. Seasonal flu outbreaks occur mainly in autumn and winter, spreading rapidly across populations and varying in severity by age group (Hewitt et al. 2013 ; Martin et al. 2023 ; Rashed et al. 2022 ). Influenza A and B viruses cause annual epidemics worldwide. Outbreaks in the Northern Hemisphere usually occur from October to March, and from April to August in the Southern Hemisphere. In tropical regions, flu circulates year-round. Seasons dominated by H3N2 are typically more severe, particularly for children and older adults. The WHO tracks global influenza trends and virus strains monthly (Mattei et al. 2024). Finally, discovered in the 1950s, Human Rhinoviruses (HRVs) are mostly known as the leading cause of the “common cold”; they are ubiquitous, and HRV infections occur year-round (Prado et al. 2014 ) HRVs, members of the family Picornaviridae and the genus Enterovirus. HRV replicates in nasal and posterior nasopharynx mucosa (Bivins et al 2021 ). Transmission is mainly attributed to hand contact between persons or through fomites. Oral or aerosol transmission seems to be rare and dependent on viral particles concentration in the droplets. Viral loads in saliva are about 30 times lower than in nasal secretions (Kumblathan et al. 2021). Studying rhinoviruses is important for several reasons, both from a clinical and public health perspective. Although typically mild, rhinovirus infections result in significant healthcare visits, school/work absences, and productivity losses, moreover, they are also frequently involved in co-infections with other respiratory pathogens, complicating clinical outcomes. This study aims to monitor the most common and airborne-transmitted respiratory viruses, through Wastewater-Based Epidemiology (WBE), and to conduct a comparative investigation and trend analysis. The goal is to identify circulation patterns and evaluate the potential of WBE as a tool for community-level surveillance of these viruses. This study is a continuation of previous research article of Anastopoulou et al, 2024 . 2. Materials and Methods 2.1 Wastewater Treatment Plant of Patras The urban Wastewater Treatment Plant (WWTP) of Patras includes both municipal waste and rainwater, making the network type mixed. Considering the spatial characteristics of the city, the biological treatment system serves a total of 168.034 inhabitants, and the maximum daily wastewater supply reaches 43,000 m3/d. Based on the information of the Special Secretariat of Water, the average incoming load from sewage is 11,359 Kg BOD 5 /day while the maximum is 13,207 Kg BOD 5 /day. The average of the incoming sewage supply amounts to 37,745 m3/day with a maximum value of 43,075 m3/day. Primary and secondary treatment, nitrogen and phosphorus removal, biological disinfection, chlorination and sand filters are applied in these facilities. 2.2 Sampling strategy Sampling was carried out by the technical staff of the WWTP of Municipality of Patras. The samples were composite, 24-hours, and were collected every Monday, Tuesday and Thursday, over a period of 6 months, from the beginning of October 2022 (ISO week 2022-40) until the end of March 2023 (ISO week 2023-13), covering the whole period. Total of 76 samples were collected. The selection of the specific days was based on the need to capture a variety of conditions and obtain an overall representative sampling. Moreover, based on the official epidemiological data of Greece on the presence and circulation of respiratory viruses in the community, this period of the year, covering autumn, winter and early spring months, can give us an overall image of the circulation of the viruses selected to study. 2.3 Extraction and RNA Purification Method The Total Nucleic Acid Extraction was performed using Wizard® Enviro Total Nucleic Acid Kit (Promega, Wisconsin, United States). This method was adopted, enabling direct collection and concentration of total nucleic acids from 40ml wastewater and process carried following the protocol presented in the research article of Anastopoulou et al, 2024 . Furthermore, the One Step PCR inhibitor removal kit (Zymo, Irvine, CA, USA) was employed to eliminate the inhibitory effects present in the samples. 2.4 Real‑Time qPCR Assays For the detection and quantification of viruses, q-PCR assays were conducted using a Thermocycler Stratagene Mx30005P (Thermo Scientific, Waltham, MA, USA). The protocols employed were in accordance with manufacturers’ instructions. enhancing result reliability and mitigating potential inhibitory effects. A predetermined quantity of the virus, designated as the Positive Amplification Control, provided by the Greek National Public Health Laboratory (KEDY), used as the positive control sample, while PCR grade water (No Template Control) served as the negative control sample in each run. For the HadV PCR reaction, the reaction mixture comprised 12.5 µL of TaqMan™ Universal PCR Master Mix (Thermo Fisher Scientific, Woolston, Warrington, UK), 0.5 µL of each primer, and 1 µL of RNase-free water (Jena Bioscience, Lobstedter, Germany). A total of 15 µL of reaction mix and 10 µL of the isolated sample were added to each PCR reaction tube. For the Influenza A and B viruses, multiplexed and for the detection of RSV A/B and Rhinoviruses the One Step RT-qPCR kit (Enzyquest, Heraklion, Crete, Greece) was used. Primer and probe sequences for the target genes are summarized in Table 1 , reference indicated with slight modifications. For the SARS-CoV 2 reaction the primer sets nCoV_IP2 and nCoV_IP4 were multiplexed depicted in research article of Anastopoulou et al, 2024 . Detailed cycling conditions are provided in Table 2 . Multiplexed assay used for the detection of Influenza A and Influenza B. All samples were analyzed in triplicates and in 1:10 dilutions for the assessment of inhibition effect on the qPCR reaction. Table 1 Primers used for qPCR assays Virus Primer/Probe name Sequence (5′–3′) Reference HAdV HAdF 5’-CWTACATGCACATCKCSG G-3’ (Heim et al. 2003 ) HAdR 5’-CRCGGGCRAAYTGCACCAG-3’ HAdPr 5’-[FAM]-CCGGGCTCAGGTACTCCG AGGCGTCCT-[BHQ1]-3’ Influenza A IAV M FW (ABI) 5’-CAAGACCAATCYTGTCACCTCTGAC − 3’ (Mercier et al. 2022 ) IAV M RV(ABI) 5’- GCATTYTGGACAAAVCGTCTACG-3’ IAV M probe (IDT) 5’-[FAM]- TGCAGTCCTCGCTCACTGGGCACG -[BHQ1]-3’ Influenza B IBV NS FW (ABI) 5’-TCCTCAAYTCACTCTTCGACG-3’ (Mercier et al. 2022 ) IBV NS RV (ABI) 5’-CGGTGCTCTTGACCAAATTGG-3’ IBV NS probe (IDT) 5’-[HEX]-CCAATTCGAGCAGCTGAAACTGCGGTG-[BHQ1]-3’ RSV A/B RSV A/B FW 5’-CTCCAGAATAYAGGCATGAYTCTCC-3’ (Hughes et al 2022 ) RSV A/B RV 5’-GCYCTYCTAATYACWGCTGTAAGAC-3’ RSV A/B Probe 5’-[HEX]-TAACCAAATTAGCAGCAGGAGATAGATCAG-[BHQ1]-3’ Rhinoviruses Primer Pic-1 5’-TCCTCCGGCCCCTGAAT-3’ (Do, et al. 2010 ) Primer Pic-3 5’-GAAACACGGACACCCAAAGTAGT-3’ Probe Pic-5 5’-[FAM]-YGGCTAACCYWAACCC-[BHQ1]-3’ Table 2 Thermal profile of real time qPCR assays Virus Steps Thermal Profile Number of Cycles HAdV assay Hot Start 2 min at 50 o C 1 Enzyme Activation 10 min at 95 o C 1 Annealing & extension 15 seconds at 95 o C 45 1 min at 60 o C Influenza A/ Influenza B multiplexed, RSV A/B and Rhinoviruses assay multiplexed Reverse Transcription (RT) 15 min at 55 o C 1 RT inactivation/ Hot Start Taq DNA polymerase activation 2min at 95°C 1 Cycle denaturation, Annealing & extension 15sec at 95°C 45 1 min at 60 o C 2.5 Quantification of viral load The quantification of genome copies on respiratory viruses was conducted using standard curves established for the respective target genes. The standard curve was generated based on a control sample containing 10^7 genome copies, (gc)/µl, which underwent serial tenfold dilutions. For HAdV, the Limit of Detection (LOD) was determined to be 2509 gc/L of wastewater, for Influenza A, 2151 gc/L, for Influenza B 3819 gc/L, for RSV A/B 2397 gc/L and for Rhinoviruses 6346 gc/L. The efficiency of the procedure was assessed using the equation Efficiency. For HadV the slope was calculated as -3.317, with a Y-intercept value of 39.97, resulting in an efficiency of 100.2%. For Influenza A standard curve characteristics are, slope: -3,52, y intercept: 41,35, Rsq: 0,993 and Efficiency: 92,2%. For Influenza B standard curve characteristics are, slope: -3,419, y intercept: 45,58, Rsq: 0,993 and Efficiency = 96,1%. For Rhinoviruses standard curve characteristics are, slope: -3,00, y intercept: 42,92, Rsq: 0,991 and Efficiency: 115,3%. For RSV A/B standard curve characteristics are: slope: -3,22, y intercept = 40,88, Rsq = 0,988, efficiency = 104,3%. Ct values were recorded for all samples and Mean Ct values per sample used for the quantification. The virus concentration was expressed as Genome Copies per Liter using the provided equations, depicted on research article of Anastopoulou et al, 2024 . 2.6 Physicochemical parameters To support the interpretation of viral RNA signals in wastewater-based surveillance, a set of key physicochemical parameters was measured in the influent wastewater samples. These parameters provide essential context regarding the wastewater matrix, which can influence viral particle stability, concentration efficiency, and detection sensitivity. The selected parameters included pH, electrical conductivity, chemical oxygen demand (COD), biological oxygen demand (BOD), total nitrogen, suspended solids, and ammonium. These indicators were chosen for their relevance to both general wastewater quality and their potential impact on virus partitioning, adsorption, detection sensitivity and recovery efficiency during sample processing. (Bivins et al., 2020 ) Physicochemical parameters of the influent wastewater samples were measured in samples taken and are shown in Table 3 . Table 3 Physicochemical parameters of wastewater samples Physicochemical parameters of wastewater samples Mean Range Average daily supply (m 3 /day) 36.357 35.800–36.500 PH 7,47 7,19 − 7,68 Conductivity (µS/cm) 1.399 1.223–1.653 COD (mg/L O 2 ) 374 228–594 BOD (mg/L O 2 ) 229 148–328 Total Nitrogen (mg/L N) 51 39–71 Suspended Solids (mg/L) 161 105–275 Ammonium (mg/L NH 4 -N) 37 29–56 2.7 Normalization of Data The concentration (Genome Copies/L) of each virus detected per sample in the influent wastewater samples was normalized per 100,000 residents based on the average daily flow rate (m 3 /d) of the WWTP and the estimated real-time population served by the plant. Ammonium loads were used as an anthropogenic marker to estimate the size of the real-time population served. A population equivalent (PE) of 7.0 g NH 4 -N per day per person was applied, as this is the value estimated for Greek cities and used by the Greek National Wastewater Epidemiology Network ( https://apth.mnss.eu/ ) The real-time population served was calculated by dividing the concentration of NH 4 -N that was determined in the influent samples with the average NH 4 -N excreted daily per resident, according to Eq. 1. Normalized concentrations of the individual compounds per 100,000 inhabitants were calculated as depicted in equation [1]. 2.8 Statistical Analysis For the statistical analysis Mean values obtained from all samples of each iso week for each virus used to represent each iso week. Possible correlations between all viruses detected through the course of time was investigated, including Sars-CoV-2 data from previous research (Anastopoulou et al, 2024 ). In addition, further investigation was conducted to explore a possible correlation between the viruses and the officially reported COVID-19 cases of the city of Patras. Spearman's rho correlation was conducted to investigate the association between viral load and meteorological data. Hierarchical cluster analysis for the viruses was conducted to explore temporal similarities among the six monitored respiratory viruses, allowing the identification of distinct clusters based on their weekly circulation patterns. Moreover, hierarchical cluster analysis of weekly virus concentrations was performed to investigate whether ISO weeks can be grouped according to the viral load. These correlations are performed using the IBM SPSS Statistics 27 statistical analysis software and graphs conducted using Excel 2016 (Microsoft). 3. Results Throughout the six-month surveillance period, the analysis of 76 wastewater samples exhibited complete positivity for HAdV and SARS-CoV 2, for Influenza A 51,3% positivity (n = 39/76), for Influenza B 19,7% positivity (n = 15/76), for RSV A/B, 39,5% positivity (n = 30/76) and for Rhinoviruses 44,7% positivity, (n = 34/76). All mean values of viral genome copies normalized per 100.000 inhabitants per ISO week are depicted in Supplementary Table 1. The chart in Fig. 2 provides an additional dimension for visualizing the data in the course of time. The horizontal axis delineates the epidemiological weeks, as per the ISO week calendar system, while the vertical axis represents the concentration of viral genome copies per liter normalized per 100.000 inhabitants. It's important to note that the ISO week calendar system is a standardized leap week system established by the International Organization for Standardization (ISO) and can provide us an overview of the presence of viruses in the community. To explore potential associations between the respiratory viruses detected in wastewater samples, Spearman’s rho two-tailed correlation test was performed. This non-parametric statistical method was chosen due to its suitability for assessing monotonic relationships between variables without assuming normal distribution. The analysis revealed several statistically significant correlations. A significant positive correlation was observed between HAdV and RSV A/B, with a p-value < 0.05. Furthermore, stronger positive correlations were found at a higher level of significance, p < 0.01 between Influenza A and Rhinovirus, Influenza A and RSV A/B, Influenza B and Rhinovirus, and Influenza B and SARS-CoV-2. The hierarchical cluster analysis of respiratory viruses based on temporal concentration profiles revealed three main clusters. The first cluster included Influenza A, Influenza B, RSV, and Rhinoviruses, which showed similar seasonal behavior. SARS-CoV-2 formed a second distinct cluster due to its episodic high peaks. HAdV constituted a separate third cluster, reflecting its persistent and stable detection pattern across the entire observation period. Hierarchical cluster analysis of weekly virus concentrations identified three distinct temporal clusters. Cluster 1 corresponded to the peak epidemic phase with concurrent high circulation of RSV, Influenza A and B, and SARS-CoV-2. Cluster 2 reflected transitional periods with mixed viral trends, while Cluster 3 captured the early or late weeks of the monitoring period, characterized by low or isolated virus detection, predominantly HAdV. 4. Discussion Following the conclusion of the COVID-19 pandemic and up to the present, wastewater epidemiology has demonstrated considerable significance as a dual-purpose tool for both preemptive measures and immediate detection of potential community-level pandemics. The temporal trends of viral genome copies normalized per 100,000 inhabitants provide a clear view of the dynamic circulation of respiratory viruses within the community across the study period. According to the findings of the present research, HAdV, exhibited the most persistent and elevated signal throughout the entire monitoring period, maintaining high viral loads (~ 10¹²–10¹⁴ gc/100,000) even during periods of low activity for other viruses. This sustained presence indicates widespread and continuous adenovirus circulation, which may be attributed to its environmental stability and prolonged shedding. Although weekly public bulletins issued by the National Public Health Organization (NPHO) for 2022–2023 did not specifically report adenovirus activity, reflecting a surveillance emphasis on influenza, RSV, and SARS‑CoV‑2, our wastewater analysis from Patras revealed persistent and elevated HAdV levels. This discrepancy suggests that adenovirus transmission was likely occurring in the community but remained under-detected by conventional clinical reporting systems. Adenoviruses are commonly found in human feces and exhibit resilience against chemical or physical pollutants (Hewitt et al, 2024), partly accounting for the elevated positivity rates observed. The detection of adenovirus in wastewater during the sampling period aligns with existing literature, affirming its environmental resilience and stable presence, devoid of seasonal patterns (Lynch et al. 2016). HAdV genome copies can correlate with physicochemical parameters in wastewater samples, studies have shown significant differences in the presence of adenovirus in water and the values for nitrites, phosphates, and fixed and total solids (Silva et al. 2011 ). Adenovirus has been identified as the best indicator for evaluating the efficiency of wastewater treatment plants in eliminating viruses (Martin et al. 2023 ). Therefore, the presence of HAdV genome copies can be used as an indicator of viral pollution in wastewater samples (Rashed et al. 2022 ). Influenza A and B viruses showed distinct seasonal peaks, with Influenza A peaking prominently in the winter months (weeks 2022–50 to 2023–4), followed by Influenza B, which demonstrated a delayed but similarly sharp increase during early 2023. These seasonal spikes are consistent with known influenza epidemiology and validate the sensitivity of wastewater surveillance in capturing community-level influenza activity. RSV showed elevated concentrations during late autumn and early winter (peaking around week 2022–46), aligning with the typical RSV seasonality. Rhinoviruses displayed a broader temporal distribution with intermittent peaks, particularly around weeks 2022–44 and 2023–4, suggesting multiple transmission waves or persistent low-level circulation. The positive correlation that was observed between HAdV and RSV A/B, is suggesting a possible concurrent circulation pattern or similar shedding dynamics in the population. Furthermore, positive significant correlations between Influenza A and Rhinovirus, Influenza A and RSV A/B, Influenza B and Rhinovirus, and Influenza B and SARS-CoV-2 may indicate overlapping seasonal trends or shared transmission drivers, reinforcing the value of multiplex wastewater-based surveillance for tracking co-circulating respiratory pathogens. The positive results of SARS-CoV 2 were expected when epidemiological surveillance was carried out from the beginning of autumn, continued during the winter and reached the beginning of spring. These seasons both in literature and based on the recording of clinical cases are considered peak months of the virus and they are extensively presented in research article of Anastopoulou et al. 2022. Furtnermore, the hierarchical cluster analysis grouped the six respiratory viruses into three distinct clusters based on their temporal distribution patterns across the observation period. Influenza A, Influenza B, RSV, and Rhinoviruses clustered together, indicating similar seasonal circulation and synchronized peaks during the colder months. In contrast, HAdV and SARS-CoV-2 each formed separate clusters, reflecting distinct epidemiological behavior. HAdV exhibited persistent detection with unique fluctuations, while SARS-CoV-2 demonstrated continuous presence with sharp, high-magnitude peaks, particularly in late 2022 and early 2023. The hierarchical clustering results of the respiratory viruses offer deeper insight into the epidemiological dynamics of respiratory viruses at the community level. The grouping of Influenza A, Influenza B, RSV, and Rhinoviruses into a single cluster suggests shared seasonal drivers, likely linked to colder temperatures, increased indoor activity, and school-term transmission patterns (Polo et al., 2021 ; Chen et al., 2020 ). In contrast, the unique clustering of SARS-CoV-2 and another of HAdV reflects their divergent behavior: SARS-CoV-2 presented sharp episodic peaks likely associated with variant waves and public health policy shifts, while HAdV maintained persistent levels possibly due to environmental resistance and prolonged fecal shedding (Martin et al., 2023 ). Hierarchical cluster analysis based on viral genome concentrations across weeks revealed three distinct temporal patterns of virus circulation. Cluster 1 encompassed weeks characterized by high viral activity, notably between weeks 2023-1 to 2023-5, corresponding to the peak of the winter season. This cluster exhibited elevated levels of influenza A, influenza B, and RSV, reflecting a typical epidemic period. Cluster 2 represented a transitional phase, likely aligning with autumn and early spring, marked by moderate and fluctuating viral loads, particularly SARS-CoV-2 and rhinoviruses, suggesting mixed or overlapping transmission dynamics. Finally, Cluster 3 was associated with weeks of low circulation, such as 2022-41 to 2022-47, where HAdV remained the only consistently detected virus, highlighting its environmental stability and shedding persistence even in inter-epidemic periods. This structure agrees with recent literature. Boehm et al. ( 2023 ) reported the detection of multiple respiratory viruses such as RSV, influenza viruses, rhinovirus, seasonal coronaviruses, human metapneumovirus, and adenovirus in wastewater solids, emphasizing that viruses such as HAdV exhibited unique circulation patterns compared to the seasonal peaks of influenza and RSV. Similarly, a multi-virus wastewater surveillance study revealed cyclical temporal trends, with maximum dissimilarity observed between sampling points roughly 23 weeks apart, corresponding to transitions between epidemic (winter) and inter-epidemic (summer) periods (Carducci et al. 2024 ). These seasonal waves were further reinforced by Swiss surveillance findings, which demonstrated that SARS-CoV-2, RSV, and influenza viruses clustered together temporally, while HAdV and rhinoviruses were persistently present at lower background levels, indicative of distinct epidemiological dynamics (Baumgartner et al. 2025 )., thus in our study rhinoviruses showed persistent presence but was calorized by the analysis within the group of influenza A, B and RSV. Collectively, these studies support the temporal clustering observed in our analysis, in which epidemic clusters (e.g., influenza and RSV) were clearly separated from background-persistent clusters (e.g., HAdV and SARS-CoV-2), underscoring the value of wastewater-based surveillance for differentiating co-circulating viral patterns across seasons. Data retrieved from the National Public Health Organization of Greece (EODY) was used to explore potential correlations between community respiratory pathogen positivity and normalized viral load in wastewater samples from Patras, spanning ISO week 2022-50 to ISO week 2023-13. Specifically, the dataset included positivity rates for SARS-CoV-2, influenza viruses, and respiratory syncytial virus (RSV) derived from non-sentinel community testing conducted by EODY’s Mobile Health Units (KOMY). These units perform rapid antigen testing (Rapid Ag) for SARS-CoV-2 in individuals who voluntarily present for testing, whether symptomatic or asymptomatic. For molecular surveillance of the three aforementioned pathogens, a random subset of symptomatic individuals with influenza-like illness is selected using an algorithm that ensures geographical and demographic representation across Greece. It is important to note that this sampling framework does not produce a representative sample of the general population. However, it may provide a useful indicator of percent positivity trends within the community. To assess the relationship between clinical surveillance data and wastewater-based epidemiology (WBE), Spearman's rho correlation was conducted between weekly normalized viral load in wastewater and aforementioned weekly pathogen positivity rates, for the three viruses. No significant correlations were found between the wastewater SARS-CoV-2 levels and positivity rates of SARS-CoV-2, influenza, or RSV in the community during the study period. Positivity rates are depicted in Supplementary Table S2. Reasons for lack of Significant Correlation can be explained by the following facts: The clinical testing data from the Mobile Health Units (KOMY) is based on voluntary participation and is not representative of the general population. This self-selection bias can distort observed positivity rates and limit their comparability to population-wide wastewater signals. Viral load in wastewater may precede or lag clinical case detection due to differences in viral shedding, incubation period, test-seeking behavior, and reporting delays and final (Peccia et al. 2020 ). Nevertheless, we observe consistency in the trends across the datasets: SARS-CoV-2 is detected at relatively stable levels in wastewater, which is reflected in the recorded test positivity rates. A similar pattern is observed for influenza (considering influenza A and B combined), where wastewater signals align with test positivity. Additionally, the gradual decline in RSV detection in wastewater is also mirrored by a corresponding decrease in RSV test positivity rates. To summarize, the trends observed in the figure support the feasibility and effectiveness of wastewater-based surveillance in tracking the presence and intensity of multiple respiratory viruses simultaneously. These patterns mirror known seasonal behaviors while also highlighting unique co-circulation dynamics, such as overlapping peaks of RSV and Influenza A, which were also statistically supported by the correlation analysis. This underlines the importance of integrating wastewater surveillance into routine public health monitoring frameworks for early warning and comprehensive pathogen tracking. Furthermore, wastewater-based epidemiology (WBE) continues to demonstrate early warning potential, as temporal signals often precede or complement clinical surveillance, particularly for SARS-CoV-2 (Sims & Kasprzyk-Hordern, 2020 ). However, limitations persist, including virus-specific variability in shedding, environmental degradation rates, and challenges in differentiating viable versus fragmented viral genomes (Wade et al., 2022 ; Polo et al., 2021 ). Despite this, the application of WBE as a multiplex surveillance tool for monitoring co-circulating respiratory pathogens is increasingly recognized as a cost-effective and population-level approach to pandemic preparedness. 5. Conclusion This study demonstrates the applicability and reliability of wastewater-based epidemiology (WBE) for the simultaneous monitoring of multiple respiratory viruses, including HAdV, SARS-CoV-2, Influenza A and B, RSV A/B, and Rhinoviruses, at the community level in Patras, Greece. The consistent detection of HAdV and SARS-CoV-2, along with the seasonal peaks observed for Influenza A, Influenza B, and RSV, confirms the capacity of WBE to reflect viral circulation trends corresponding to clinical and environmental patterns. Hierarchical clustering and correlation analyses revealed distinct epidemiological behaviors, with some viruses showing persistent detection and others displaying synchronized epidemic peaks. The study also highlights the environmental persistence of HAdV. These findings underscore the critical role of WBE in complementing conventional epidemiological tools by providing timely, population-wide insights into the dynamics of viral transmission, supporting early warning systems and informed public health interventions. Continued integration of WBE into routine surveillance frameworks can enhance preparedness and response strategies for future respiratory pathogen outbreaks. Declarations Acknowledgements The authors would like to express their gratitude to the National Public Health Organization of Greece (NPHO) for financially supporting the research activities, as well as to the Network of Collaborating Laboratories for wastewater-based epidemiological surveillance of the major cities of Greece. Conflict of interests The authors declare no competing interests. Author Contribution Conceptualization, A.V and Z.A .; methodology, A.V and Z.A .; software, Z.A.; validation, R.F., Z.A. and A.V.; investigation, Z.A., K.A.K, R.F. and A.V.; resources, A.V.; data curation, Z.A., K.A.K, R.F. and A.V.; writing—original draft preparation, Z.A., K.A.K, R.F. and A.V.; writing—review and editing, A.V.; visualization, R.F. and A.V.; supervision, A.V.; project administration, Z.A and A.V.; funding acquisition, A.V. All authors have read and agreed to the published version of the manuscript. References Ahmed, W., Angel, N., Edson, J., Bibby, K., Bivins, A., O’Brien, J. 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M., Thakali, O., Hegazy, N., Jia, J. J., Zhang, Z., ... & Delatolla, R. (2022). Wastewater surveillance of influenza activity: Early detection, surveillance, and subtyping in city and neighbourhood communities. Scientific Reports, 12, Article 20076. https://doi.org/10.1038/s41598-022-20076-z Osuolale, O., & Okoh, A. (2015). Incidence of human adenoviruses and hepatitis A virus in the final effluent of selected wastewater treatment plants in Eastern Cape Province, South Africa. Virology Journal, 12(1), 1–9. Peccia, J., Zulli, A., Brackney, D. E., Grubaugh, N. D., Kaplan, E. H., Casanovas-Massana, A., Ko, A. I., Malik, A. A., Wang, D., Wang, M., Warren, J. L., Weinberger, D. M., Arnold, W., & Omer, S. B. (2020). Measurement of SARS-CoV-2 RNA in wastewater tracks community infection dynamics. Nature Biotechnology, 38(10), 1164–1167. https://doi.org/10.1038/s41587-020-0684-z Polo, D., et al. (2021). 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Food and Environmental Virology, 14(3), 246–257. https://doi.org/10.1007/s12560-022-09554-5 Reddy, V. S., Natchiar, S. K., Stewart, P. L., & Nemerow, G. R. (2010). Crystal structure of human adenovirus at 3.5 Å resolution. Science, 329(5995), 1071–1075. https://doi.org/10.1126/science.1187292 Silva, H. D., Santos, S. F. O., Lima, A. P., Silveira-Lacerda, E. P., Anunciação, C. E., & Garcíazapata, M. T. A. (2011). Correlation Analysis of the Seasonality of Adenovirus Gene Detection and Water Quality Parameters Based on Yearly Monitoring. Water Quality, Exposure and Health, 3(2), 101–107. Sims, N., & Kasprzyk-Hordern, B. (2020). Future perspectives of wastewater-based epidemiology: Monitoring infectious disease spread and resistance to the community level. Environment International, 139, 105689. https://doi.org/10.1016/j.envint.2020.105689 Tavazzi, S., Cacciatori, C., Comero, S., Fatta-Kassinos, D., Karaolia, P., Iakovides, I. C., ... & Gawlik, B. M. (2023). 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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-7262979","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":496066743,"identity":"095b5f75-a9df-4bf4-816b-0cc0984f6619","order_by":0,"name":"Zoi Anastopoulou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABD0lEQVRIiWNgGAWjYFACxgYkTgEDAz+ITiggQgsPmDRgYJAE8RMMiLAMrsXgAJSBC8i3Nzcw/NxhZ2/P3nvwMY+BTeLm86sTPzwwYJDnFzuA3Vk9BxsYe88kJ/bwnEs25jFIS9x24+1mCaDDDGfOTsCqhVkisYGBt405gUcix0yax+AwUMvZDSAtCQa3sWthA2ph/NtWbw/XsnnG2c0/8GnhAWph5m07zNgD07KBv3cbXlskeA42HJZtO57Yc+ZcsuEcgzTjGTd4t1kkGEjg9It8e/vDh2/bqu3Z23sPPnhTYSPb3392880fFTby/NLYtYDAAagbYRaDVUrgVI7sLSjNf4AY1aNgFIyCUTCCAAANl1u6BNJYJwAAAABJRU5ErkJggg==","orcid":"","institution":"University of Patras","correspondingAuthor":true,"prefix":"","firstName":"Zoi","middleName":"","lastName":"Anastopoulou","suffix":""},{"id":496066744,"identity":"edc6d5a3-6cac-4b79-aba1-80441d735a47","order_by":1,"name":"Rafail Fokas","email":"","orcid":"","institution":"University of Patras","correspondingAuthor":false,"prefix":"","firstName":"Rafail","middleName":"","lastName":"Fokas","suffix":""},{"id":496066745,"identity":"8a26288e-4965-4628-820e-ea8f4f687f63","order_by":2,"name":"Kalypso-Angeliki Koukouvini","email":"","orcid":"","institution":"University of Patras","correspondingAuthor":false,"prefix":"","firstName":"Kalypso-Angeliki","middleName":"","lastName":"Koukouvini","suffix":""},{"id":496066746,"identity":"4f64041d-1304-4202-bdb0-1c89593b6352","order_by":3,"name":"Apostolos Vantarakis","email":"","orcid":"","institution":"University of Patras","correspondingAuthor":false,"prefix":"","firstName":"Apostolos","middleName":"","lastName":"Vantarakis","suffix":""}],"badges":[],"createdAt":"2025-07-31 13:53:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7262979/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7262979/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12560-026-09683-5","type":"published","date":"2026-02-25T15:57:30+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88559025,"identity":"6d0af182-021c-44fe-a0c0-69e5fe06b522","added_by":"auto","created_at":"2025-08-07 17:24:39","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":201665,"visible":true,"origin":"","legend":"\u003cp\u003eGeographical depiction of the WWTP of Municipality of Patras.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7262979/v1/9f14ddde2f3b8163f3a31019.jpg"},{"id":88559024,"identity":"75a38a56-5fd6-4dd8-9e79-5cb797ed0a68","added_by":"auto","created_at":"2025-08-07 17:24:39","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":95065,"visible":true,"origin":"","legend":"\u003cp\u003eEpidemiological Curve of HAdV and SARS-CoV 2, Influenza A and B, RSV A/B and Rhinoviruses, during 2022 and 2023 ISO weeks normalized per 100.000 inhabitants, based on Wastewater surveillance of city of Patras, Greece.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7262979/v1/0f5c5d30310e6e3abbe48304.jpg"},{"id":103766324,"identity":"390762b4-c4f0-4e7f-8fc1-14daa5b86445","added_by":"auto","created_at":"2026-03-02 16:13:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":980615,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7262979/v1/795eae33-423d-4f21-afd4-4f7c4a24d191.pdf"},{"id":88559027,"identity":"628dba56-aa22-448c-a69c-07f6f6d125ad","added_by":"auto","created_at":"2025-08-07 17:24:39","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":52595,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTablesRespiratoryViruses.docx","url":"https://assets-eu.researchsquare.com/files/rs-7262979/v1/c615c2d5bcba371c3e53b331.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative Investigation and Trends of Respiratory Viruses using Wastewater-Based Epidemiological Surveillance in Patras, Greece","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSince the end of the COVID-19 pandemic, the use of wastewater-based epidemiology (WBE) has accelerated exponentially. It has been used to detect and epidemiologically monitor the presence of SARS-CoV-2. In addition to distinguishing infectious diseases, the distinct presence of various pharmaceutical and chemical components has been used to assess drug use patterns and assess collective population exposure. The potential of WBE is amply illustrated by its ability to predict or prevent potential outbreaks in a community before patients develop clinical symptoms and up to three weeks before diagnostic clinical cases (Sims \u0026amp; Kasprzyk-Hordern, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The economic feasibility of the methodology is underlined by its ability to provide a timely snapshot of the course and presence of a pathogen in the population, contributing to the epidemiological surveillance of the disease, accompanying the clinical recording (hospital admissions or recorded cases) by the health systems of the countries. In investigating the bioethical issues and the protection of personal data of the epidemiological surveillance of wastewater, the competent courts have concluded that no issue arises regarding wastewater that ends up in the public sewer network of large cities and populations (Doorn et al. 2022; Gable et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCurrently, several countries have established national WBE frameworks for SARS-CoV-2 enforcement, which were formalised by Commission guidance in March 2021, and efforts are now underway to integrate additional emerging pathogens or persistent pathogens, their strains or variants, into countries\u0026rsquo; epidemiological protection systems (Tavazzi et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, the latent period of the disease, which can extend up to two weeks before the onset of symptoms, introduces time lags between the onset of the disease and the subsequent reporting of clinical outcomes. These observations collectively suggest that urban wastewater within communities may harbour the virus at significant concentrations. Throughout the pandemic, WBE has emerged as a promising tool for providing insights into the prevalence and course of the disease, highlighting its potential as a valuable adjunct to surveillance efforts (Ahmed et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Dumke et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe rationale behind the selection of specific respiratory viruses is presented in the following section. Human adenoviruses (HAdV), recognized, are prominent pathogens associated with a diverse array of human afflictions, including respiratory illnesses, gastroenteritis, conjunctivitis, and chronic systemic infections, and are particularly notable among immunocompromised individuals (Osuolale et al. 2025). Characterized by their exclusive human host tropism, adenoviruses are ubiquitously present in terrestrial and aquatic environments. Instances of adenovirus outbreaks have been documented across various settings, spanning military facilities, recreational water venues, healthcare institutions, and residential care facilities (Flint \u0026amp; Nemerow, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eThe pervasive presence of these viruses in wastewater and aquatic ecosystems underscores their heightened prevalence compared to that of other enteric viruses. Owing to their environmental stability and robust detectability, human adenoviruses are valuable indicators of wastewater contamination and offer insights into the presence of other viral pathogens (Bofill-Mas et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) Extensive research underscores the proclivity of adenoviruses to manifest in conspicuously elevated concentrations relative to their viral counterparts, rendering them promising candidates as biomarkers within aquatic ecosystems (Albinana-Gimenez et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Temporal and geographical variations in adenovirus serotype prevalence underscore the dynamic nature of adenovirus epidemiology. Documented alterations in serotype prevalence across different regions suggest the potential emergence of novel strains and the displacement of existing strains. Despite adenovirus outbreaks predominantly occurring during winter or early spring, infections occur year-round without distinct seasonality, particularly within enclosed communities where epidemic trends tend to escalate (Lynch et al. 2016)\u003c/p\u003e\u003cp\u003eHAdV can be transmitted through airborne routes. Adenoviruses responsible for respiratory infections, such as types 3, 4, 7 and 21 - are known to spread through respiratory droplets expelled when an infected person coughs, sneezes or talks. These droplets can be inhaled by people nearby or sit on surfaces, leading to indirect transmission. HAdV types 3, 4, 7 and 21 have been strongly associated with outbreaks of acute respiratory disease (ARD), particularly in crowded settings such as military barracks, schools and healthcare facilities. For example, studies have shown that HAdV-3 and HAdV-7 are major causes of severe respiratory infections in children, sometimes leading to life-threatening conditions. Similarly, HAdV-21 has been implicated in severe respiratory disease epidemics (Zaki et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Research indicates that HAdV-7 infections can result in more severe disease outcomes compared to other types. A study published in BMC Infectious Diseases found that HAdV-7 infection caused more severe pneumonia, respiratory failure, and longer hospitalization periods compared to HAdV-3. This highlights the virulence of certain adenovirus types and the need for vigilant monitoring and preventive strategies (Fu et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRespiratory Syncytial Virus (RSV) is a common pathogen in children and increasingly recognized in adults, especially the elderly. It primarily causes upper respiratory infections but can lead to bronchiolitis in young children and, in rare cases, progress to pneumonia, respiratory failure, apnea, or death. Treatment is mostly supportive. Passive immunization is available for at-risk children, such as premature infants or those with cardiac, pulmonary, or neuromuscular conditions. One antiviral treatment exists, but its use is limited due to cost, side effects, and limited efficacy, and is reserved for high-risk patients (Hernroth eta al 2002, Corman et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). RSV is a single-stranded, negative-sense RNA virus from the Paramyxoviridae family and Pneumovirus genus. Discovered in chimpanzees in 1955, it was soon identified in humans (Sims et al. 2020). RSV infects about 90% of children by age two and frequently affects older children and adults due to weak long-term immunity. While most infections are mild, up to 40% of primary infections in children under one cause bronchiolitis. Globally, Respiratory syncytial virus (RSV) is estimated to cause approximately 33\u0026nbsp;million episodes of acute lower respiratory infections globally in young children annually, resulting in around 3\u0026nbsp;million hospitalizations and up to 118,000\u0026ndash;199,000 deaths, predominantly in low- and middle-income settings. (Public Health Agency of Canada, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In temperate climates, RSV incidence typically peaks during winter‑spring, while tropical regions exhibit more variable seasonal patterns. High‑risk groups include premature infants, children with underlying health conditions, and the elderly, who face increased risk of severe outcomes and hospitalization. (WHO, 2025)\u003c/p\u003e\u003cp\u003eInfluenza is a contagious viral infection affecting the upper and lower respiratory tract. It spreads through respiratory droplets and contaminated surfaces. Infected individuals are contagious even before symptoms appear and remain so for 5\u0026ndash;7 days. While most recover in a few days, serious complications like pneumonia can occur, especially in young children, the elderly, pregnant women, and immunocompromised individuals. Symptoms include fever, cough, sore throat, and runny nose. Seasonal flu outbreaks occur mainly in autumn and winter, spreading rapidly across populations and varying in severity by age group (Hewitt et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Martin et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Rashed et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Influenza A and B viruses cause annual epidemics worldwide. Outbreaks in the Northern Hemisphere usually occur from October to March, and from April to August in the Southern Hemisphere. In tropical regions, flu circulates year-round. Seasons dominated by H3N2 are typically more severe, particularly for children and older adults. The WHO tracks global influenza trends and virus strains monthly (Mattei et al. 2024).\u003c/p\u003e\u003cp\u003eFinally, discovered in the 1950s, Human Rhinoviruses (HRVs) are mostly known as the leading cause of the \u0026ldquo;common cold\u0026rdquo;; they are ubiquitous, and HRV infections occur year-round (Prado et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) HRVs, members of the family Picornaviridae and the genus Enterovirus. HRV replicates in nasal and posterior nasopharynx mucosa (Bivins et al \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Transmission is mainly attributed to hand contact between persons or through fomites. Oral or aerosol transmission seems to be rare and dependent on viral particles concentration in the droplets. Viral loads in saliva are about 30 times lower than in nasal secretions (Kumblathan et al. 2021). Studying rhinoviruses is important for several reasons, both from a clinical and public health perspective. Although typically mild, rhinovirus infections result in significant healthcare visits, school/work absences, and productivity losses, moreover, they are also frequently involved in co-infections with other respiratory pathogens, complicating clinical outcomes.\u003c/p\u003e\u003cp\u003eThis study aims to monitor the most common and airborne-transmitted respiratory viruses, through Wastewater-Based Epidemiology (WBE), and to conduct a comparative investigation and trend analysis. The goal is to identify circulation patterns and evaluate the potential of WBE as a tool for community-level surveillance of these viruses. This study is a continuation of previous research article of Anastopoulou et al, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Wastewater Treatment Plant of Patras\u003c/h2\u003e\n \u003cp\u003eThe urban Wastewater Treatment Plant (WWTP) of Patras includes both municipal waste and rainwater, making the network type mixed. Considering the spatial characteristics of the city, the biological treatment system serves a total of 168.034 inhabitants, and the maximum daily wastewater supply reaches 43,000 m3/d. Based on the information of the Special Secretariat of Water, the average incoming load from sewage is 11,359 Kg BOD\u003csup\u003e5\u003c/sup\u003e/day while the maximum is 13,207 Kg BOD\u003csup\u003e5\u003c/sup\u003e/day. The average of the incoming sewage supply amounts to 37,745 m3/day with a maximum value of 43,075 m3/day. Primary and secondary treatment, nitrogen and phosphorus removal, biological disinfection, chlorination and sand filters are applied in these facilities.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Sampling strategy\u003c/h2\u003e\n \u003cp\u003eSampling was carried out by the technical staff of the WWTP of Municipality of Patras. The samples were composite, 24-hours, and were collected every Monday, Tuesday and Thursday, over a period of 6 months, from the beginning of October 2022 (ISO week 2022-40) until the end of March 2023 (ISO week 2023-13), covering the whole period. Total of 76 samples were collected. The selection of the specific days was based on the need to capture a variety of conditions and obtain an overall representative sampling. Moreover, based on the official epidemiological data of Greece on the presence and circulation of respiratory viruses in the community, this period of the year, covering autumn, winter and early spring months, can give us an overall image of the circulation of the viruses selected to study.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Extraction and RNA Purification Method\u003c/h2\u003e\n \u003cp\u003eThe Total Nucleic Acid Extraction was performed using Wizard\u0026reg; Enviro Total Nucleic Acid Kit (Promega, Wisconsin, United States). This method was adopted, enabling direct collection and concentration of total nucleic acids from 40ml wastewater and process carried following the protocol presented in the research article of Anastopoulou et al, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e. Furthermore, the One Step PCR inhibitor removal kit (Zymo, Irvine, CA, USA) was employed to eliminate the inhibitory effects present in the samples.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Real‑Time qPCR Assays\u003c/h2\u003e\n \u003cp\u003eFor the detection and quantification of viruses, q-PCR assays were conducted using a Thermocycler Stratagene Mx30005P (Thermo Scientific, Waltham, MA, USA). The protocols employed were in accordance with manufacturers\u0026rsquo; instructions. enhancing result reliability and mitigating potential inhibitory effects. A predetermined quantity of the virus, designated as the Positive Amplification Control, provided by the Greek National Public Health Laboratory (KEDY), used as the positive control sample, while PCR grade water (No Template Control) served as the negative control sample in each run.\u003c/p\u003e\n \u003cp\u003eFor the HadV PCR reaction, the reaction mixture comprised 12.5 \u0026micro;L of TaqMan\u0026trade; Universal PCR Master Mix (Thermo Fisher Scientific, Woolston, Warrington, UK), 0.5 \u0026micro;L of each primer, and 1 \u0026micro;L of RNase-free water (Jena Bioscience, Lobstedter, Germany). A total of 15 \u0026micro;L of reaction mix and 10 \u0026micro;L of the isolated sample were added to each PCR reaction tube.\u003c/p\u003e\n \u003cp\u003eFor the Influenza A and B viruses, multiplexed and for the detection of RSV A/B and Rhinoviruses the One Step RT-qPCR kit (Enzyquest, Heraklion, Crete, Greece) was used.\u003c/p\u003e\n \u003cp\u003ePrimer and probe sequences for the target genes are summarized in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, reference indicated with slight modifications. For the SARS-CoV 2 reaction the primer sets nCoV_IP2 and nCoV_IP4 were multiplexed depicted in research article of Anastopoulou et al, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e. Detailed cycling conditions are provided in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. Multiplexed assay used for the detection of Influenza A and Influenza B. All samples were analyzed in triplicates and in 1:10 dilutions for the assessment of inhibition effect on the qPCR reaction.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePrimers used for qPCR assays\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVirus\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePrimer/Probe name\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSequence (5\u0026prime;\u0026ndash;3\u0026prime;)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eHAdV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHAdF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo;-CWTACATGCACATCKCSG G-3\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e(Heim et al. \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHAdR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo;-CRCGGGCRAAYTGCACCAG-3\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHAdPr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo;-[FAM]-CCGGGCTCAGGTACTCCG AGGCGTCCT-[BHQ1]-3\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eInfluenza A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIAV M FW (ABI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo;-CAAGACCAATCYTGTCACCTCTGAC \u0026minus;\u0026thinsp;3\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e(Mercier et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIAV M RV(ABI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo;- GCATTYTGGACAAAVCGTCTACG-3\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIAV M probe (IDT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo;-[FAM]- TGCAGTCCTCGCTCACTGGGCACG -[BHQ1]-3\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eInfluenza B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIBV NS FW (ABI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo;-TCCTCAAYTCACTCTTCGACG-3\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e(Mercier et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIBV NS RV (ABI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo;-CGGTGCTCTTGACCAAATTGG-3\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIBV NS probe (IDT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo;-[HEX]-CCAATTCGAGCAGCTGAAACTGCGGTG-[BHQ1]-3\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eRSV A/B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRSV A/B FW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo;-CTCCAGAATAYAGGCATGAYTCTCC-3\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e(Hughes et al \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRSV A/B RV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo;-GCYCTYCTAATYACWGCTGTAAGAC-3\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRSV A/B Probe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo;-[HEX]-TAACCAAATTAGCAGCAGGAGATAGATCAG-[BHQ1]-3\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eRhinoviruses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimer Pic-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo;-TCCTCCGGCCCCTGAAT-3\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e(Do, et al. \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimer Pic-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo;-GAAACACGGACACCCAAAGTAGT-3\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProbe Pic-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026rsquo;-[FAM]-YGGCTAACCYWAACCC-[BHQ1]-3\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThermal profile of real time qPCR assays\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVirus\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSteps\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eThermal Profile\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of Cycles\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eHAdV assay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHot Start\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 min at 50 \u003csup\u003eo\u003c/sup\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEnzyme Activation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 min at 95 \u003csup\u003eo\u003c/sup\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAnnealing \u0026amp; extension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 seconds at 95 \u003csup\u003eo\u003c/sup\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 min at 60 \u003csup\u003eo\u003c/sup\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eInfluenza A/ Influenza B multiplexed, RSV A/B and Rhinoviruses assay multiplexed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReverse Transcription (RT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 min at 55 \u003csup\u003eo\u003c/sup\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRT inactivation/ Hot Start Taq DNA polymerase activation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2min at 95\u0026deg;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCycle denaturation,\u003c/p\u003e\n \u003cp\u003eAnnealing \u0026amp; extension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15sec at 95\u0026deg;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 min at 60 \u003csup\u003eo\u003c/sup\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5 Quantification of viral load\u003c/h2\u003e\n \u003cp\u003eThe quantification of genome copies on respiratory viruses was conducted using standard curves established for the respective target genes. The standard curve was generated based on a control sample containing 10^7 genome copies, (gc)/\u0026micro;l, which underwent serial tenfold dilutions. For HAdV, the Limit of Detection (LOD) was determined to be 2509 gc/L of wastewater, for Influenza A, 2151 gc/L, for Influenza B 3819 gc/L, for RSV A/B 2397 gc/L and for Rhinoviruses 6346 gc/L. The efficiency of the procedure was assessed using the equation Efficiency. For HadV the slope was calculated as -3.317, with a Y-intercept value of 39.97, resulting in an efficiency of 100.2%. For Influenza A standard curve characteristics are, slope: -3,52, y intercept: 41,35, Rsq: 0,993 and Efficiency: 92,2%. For Influenza B standard curve characteristics are, slope: -3,419, y intercept: 45,58, Rsq: 0,993 and Efficiency\u0026thinsp;=\u0026thinsp;96,1%. For Rhinoviruses standard curve characteristics are, slope: -3,00, y intercept: 42,92, Rsq: 0,991 and Efficiency: 115,3%. For RSV A/B standard curve characteristics are: slope: -3,22, y intercept\u0026thinsp;=\u0026thinsp;40,88, Rsq\u0026thinsp;=\u0026thinsp;0,988, efficiency\u0026thinsp;=\u0026thinsp;104,3%. Ct values were recorded for all samples and Mean Ct values per sample used for the quantification. The virus concentration was expressed as Genome Copies per Liter using the provided equations, depicted on research article of Anastopoulou et al, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e2.6 Physicochemical parameters\u003c/h2\u003e\n \u003cp\u003eTo support the interpretation of viral RNA signals in wastewater-based surveillance, a set of key physicochemical parameters was measured in the influent wastewater samples. These parameters provide essential context regarding the wastewater matrix, which can influence viral particle stability, concentration efficiency, and detection sensitivity. The selected parameters included pH, electrical conductivity, chemical oxygen demand (COD), biological oxygen demand (BOD), total nitrogen, suspended solids, and ammonium. These indicators were chosen for their relevance to both general wastewater quality and their potential impact on virus partitioning, adsorption, detection sensitivity and recovery efficiency during sample processing. (Bivins et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\n \u003cp\u003ePhysicochemical parameters of the influent wastewater samples were measured in samples taken and are shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePhysicochemical parameters of wastewater samples\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePhysicochemical parameters\u003c/p\u003e\n \u003cp\u003eof wastewater samples\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAverage daily supply (m\u003csup\u003e3\u003c/sup\u003e/day)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.800\u0026ndash;36.500\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,19\u0026thinsp;\u0026minus;\u0026thinsp;7,68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConductivity (\u0026micro;S/cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.223\u0026ndash;1.653\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCOD (mg/L O\u003csub\u003e2\u003c/sub\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e228\u0026ndash;594\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBOD (mg/L O\u003csub\u003e2\u003c/sub\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e148\u0026ndash;328\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal Nitrogen (mg/L N)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u0026ndash;71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSuspended Solids (mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e105\u0026ndash;275\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmmonium (mg/L NH\u003csub\u003e4\u003c/sub\u003e-N)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u0026ndash;56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e2.7 Normalization of Data\u003c/h2\u003e\n \u003cp\u003eThe concentration (Genome Copies/L) of each virus detected per sample in the influent wastewater samples was normalized per 100,000 residents based on the average daily flow rate (m\u003csup\u003e3\u003c/sup\u003e/d) of the WWTP and the estimated real-time population served by the plant. Ammonium loads were used as an anthropogenic marker to estimate the size of the real-time population served. A population equivalent (PE) of 7.0 g NH\u003csub\u003e4\u003c/sub\u003e-N per day per person was applied, as this is the value estimated for Greek cities and used by the Greek National Wastewater Epidemiology Network (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://apth.mnss.eu/\u003c/span\u003e\u003c/span\u003e)\u003c/p\u003e\n \u003cp\u003eThe real-time population served was calculated by dividing the concentration of NH\u003csub\u003e4\u003c/sub\u003e-N that was determined in the influent samples with the average NH\u003csub\u003e4\u003c/sub\u003e-N excreted daily per resident, according to Eq.\u0026nbsp;1.\u003c/p\u003e\n \u003cp\u003eNormalized concentrations of the individual compounds per 100,000 inhabitants were calculated as depicted in equation [1].\u003c/p\u003e\n \u003cp\u003e\u003cimg 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\" width=\"673\" height=\"82\"\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e2.8 Statistical Analysis\u003c/h2\u003e\n \u003cp\u003eFor the statistical analysis Mean values obtained from all samples of each iso week for each virus used to represent each iso week. Possible correlations between all viruses detected through the course of time was investigated, including Sars-CoV-2 data from previous research (Anastopoulou et al, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). In addition, further investigation was conducted to explore a possible correlation between the viruses and the officially reported COVID-19 cases of the city of Patras. Spearman\u0026apos;s rho correlation was conducted to investigate the association between viral load and meteorological data. Hierarchical cluster analysis for the viruses was conducted to explore temporal similarities among the six monitored respiratory viruses, allowing the identification of distinct clusters based on their weekly circulation patterns. Moreover, hierarchical cluster analysis of weekly virus concentrations was performed to investigate whether ISO weeks can be grouped according to the viral load. These correlations are performed using the IBM SPSS Statistics 27 statistical analysis software and graphs conducted using Excel 2016 (Microsoft).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eThroughout the six-month surveillance period, the analysis of 76 wastewater samples exhibited complete positivity for HAdV and SARS-CoV 2, for Influenza A 51,3% positivity (n\u0026thinsp;=\u0026thinsp;39/76), for Influenza B 19,7% positivity (n\u0026thinsp;=\u0026thinsp;15/76), for RSV A/B, 39,5% positivity (n\u0026thinsp;=\u0026thinsp;30/76) and for Rhinoviruses 44,7% positivity, (n\u0026thinsp;=\u0026thinsp;34/76). All mean values of viral genome copies normalized per 100.000 inhabitants per ISO week are depicted in Supplementary Table\u0026nbsp;1. The chart in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e provides an additional dimension for visualizing the data in the course of time. The horizontal axis delineates the epidemiological weeks, as per the ISO week calendar system, while the vertical axis represents the concentration of viral genome copies per liter normalized per 100.000 inhabitants. It's important to note that the ISO week calendar system is a standardized leap week system established by the International Organization for Standardization (ISO) and can provide us an overview of the presence of viruses in the community.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo explore potential associations between the respiratory viruses detected in wastewater samples, Spearman\u0026rsquo;s rho two-tailed correlation test was performed. This non-parametric statistical method was chosen due to its suitability for assessing monotonic relationships between variables without assuming normal distribution. The analysis revealed several statistically significant correlations. A significant positive correlation was observed between HAdV and RSV A/B, with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Furthermore, stronger positive correlations were found at a higher level of significance, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 between Influenza A and Rhinovirus, Influenza A and RSV A/B, Influenza B and Rhinovirus, and Influenza B and SARS-CoV-2. The hierarchical cluster analysis of respiratory viruses based on temporal concentration profiles revealed three main clusters. The first cluster included Influenza A, Influenza B, RSV, and Rhinoviruses, which showed similar seasonal behavior. SARS-CoV-2 formed a second distinct cluster due to its episodic high peaks. HAdV constituted a separate third cluster, reflecting its persistent and stable detection pattern across the entire observation period. Hierarchical cluster analysis of weekly virus concentrations identified three distinct temporal clusters. Cluster 1 corresponded to the peak epidemic phase with concurrent high circulation of RSV, Influenza A and B, and SARS-CoV-2. Cluster 2 reflected transitional periods with mixed viral trends, while Cluster 3 captured the early or late weeks of the monitoring period, characterized by low or isolated virus detection, predominantly HAdV.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eFollowing the conclusion of the COVID-19 pandemic and up to the present, wastewater epidemiology has demonstrated considerable significance as a dual-purpose tool for both preemptive measures and immediate detection of potential community-level pandemics. The temporal trends of viral genome copies normalized per 100,000 inhabitants provide a clear view of the dynamic circulation of respiratory viruses within the community across the study period.\u003c/p\u003e\u003cp\u003eAccording to the findings of the present research, HAdV, exhibited the most persistent and elevated signal throughout the entire monitoring period, maintaining high viral loads (~\u0026thinsp;10\u0026sup1;\u0026sup2;\u0026ndash;10\u0026sup1;⁴ gc/100,000) even during periods of low activity for other viruses. This sustained presence indicates widespread and continuous adenovirus circulation, which may be attributed to its environmental stability and prolonged shedding. Although weekly public bulletins issued by the National Public Health Organization (NPHO) for 2022\u0026ndash;2023 did not specifically report adenovirus activity, reflecting a surveillance emphasis on influenza, RSV, and SARS‑CoV‑2, our wastewater analysis from Patras revealed persistent and elevated HAdV levels. This discrepancy suggests that adenovirus transmission was likely occurring in the community but remained under-detected by conventional clinical reporting systems. Adenoviruses are commonly found in human feces and exhibit resilience against chemical or physical pollutants (Hewitt et al, 2024), partly accounting for the elevated positivity rates observed. The detection of adenovirus in wastewater during the sampling period aligns with existing literature, affirming its environmental resilience and stable presence, devoid of seasonal patterns (Lynch et al. 2016). HAdV genome copies can correlate with physicochemical parameters in wastewater samples, studies have shown significant differences in the presence of adenovirus in water and the values for nitrites, phosphates, and fixed and total solids (Silva et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Adenovirus has been identified as the best indicator for evaluating the efficiency of wastewater treatment plants in eliminating viruses (Martin et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, the presence of HAdV genome copies can be used as an indicator of viral pollution in wastewater samples (Rashed et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eInfluenza A and B viruses showed distinct seasonal peaks, with Influenza A peaking prominently in the winter months (weeks 2022\u0026ndash;50 to 2023\u0026ndash;4), followed by Influenza B, which demonstrated a delayed but similarly sharp increase during early 2023. These seasonal spikes are consistent with known influenza epidemiology and validate the sensitivity of wastewater surveillance in capturing community-level influenza activity. RSV showed elevated concentrations during late autumn and early winter (peaking around week 2022\u0026ndash;46), aligning with the typical RSV seasonality. Rhinoviruses displayed a broader temporal distribution with intermittent peaks, particularly around weeks 2022\u0026ndash;44 and 2023\u0026ndash;4, suggesting multiple transmission waves or persistent low-level circulation. The positive correlation that was observed between HAdV and RSV A/B, is suggesting a possible concurrent circulation pattern or similar shedding dynamics in the population. Furthermore, positive significant correlations between Influenza A and Rhinovirus, Influenza A and RSV A/B, Influenza B and Rhinovirus, and Influenza B and SARS-CoV-2 may indicate overlapping seasonal trends or shared transmission drivers, reinforcing the value of multiplex wastewater-based surveillance for tracking co-circulating respiratory pathogens.\u003c/p\u003e\u003cp\u003eThe positive results of SARS-CoV 2 were expected when epidemiological surveillance was carried out from the beginning of autumn, continued during the winter and reached the beginning of spring. These seasons both in literature and based on the recording of clinical cases are considered peak months of the virus and they are extensively presented in research article of Anastopoulou et al. 2022.\u003c/p\u003e\u003cp\u003eFurtnermore, the hierarchical cluster analysis grouped the six respiratory viruses into three distinct clusters based on their temporal distribution patterns across the observation period. Influenza A, Influenza B, RSV, and Rhinoviruses clustered together, indicating similar seasonal circulation and synchronized peaks during the colder months. In contrast, HAdV and SARS-CoV-2 each formed separate clusters, reflecting distinct epidemiological behavior. HAdV exhibited persistent detection with unique fluctuations, while SARS-CoV-2 demonstrated continuous presence with sharp, high-magnitude peaks, particularly in late 2022 and early 2023.\u003c/p\u003e\u003cp\u003eThe hierarchical clustering results of the respiratory viruses offer deeper insight into the epidemiological dynamics of respiratory viruses at the community level. The grouping of Influenza A, Influenza B, RSV, and Rhinoviruses into a single cluster suggests shared seasonal drivers, likely linked to colder temperatures, increased indoor activity, and school-term transmission patterns (Polo et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Chen et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In contrast, the unique clustering of SARS-CoV-2 and another of HAdV reflects their divergent behavior: SARS-CoV-2 presented sharp episodic peaks likely associated with variant waves and public health policy shifts, while HAdV maintained persistent levels possibly due to environmental resistance and prolonged fecal shedding (Martin et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHierarchical cluster analysis based on viral genome concentrations across weeks revealed three distinct temporal patterns of virus circulation. Cluster 1 encompassed weeks characterized by high viral activity, notably between weeks 2023-1 to 2023-5, corresponding to the peak of the winter season. This cluster exhibited elevated levels of influenza A, influenza B, and RSV, reflecting a typical epidemic period. Cluster 2 represented a transitional phase, likely aligning with autumn and early spring, marked by moderate and fluctuating viral loads, particularly SARS-CoV-2 and rhinoviruses, suggesting mixed or overlapping transmission dynamics. Finally, Cluster 3 was associated with weeks of low circulation, such as 2022-41 to 2022-47, where HAdV remained the only consistently detected virus, highlighting its environmental stability and shedding persistence even in inter-epidemic periods. This structure agrees with recent literature. Boehm et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) reported the detection of multiple respiratory viruses such as RSV, influenza viruses, rhinovirus, seasonal coronaviruses, human metapneumovirus, and adenovirus in wastewater solids, emphasizing that viruses such as HAdV exhibited unique circulation patterns compared to the seasonal peaks of influenza and RSV. Similarly, a multi-virus wastewater surveillance study revealed cyclical temporal trends, with maximum dissimilarity observed between sampling points roughly 23 weeks apart, corresponding to transitions between epidemic (winter) and inter-epidemic (summer) periods (Carducci et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These seasonal waves were further reinforced by Swiss surveillance findings, which demonstrated that SARS-CoV-2, RSV, and influenza viruses clustered together temporally, while HAdV and rhinoviruses were persistently present at lower background levels, indicative of distinct epidemiological dynamics (Baumgartner et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2025\u003c/span\u003e)., thus in our study rhinoviruses showed persistent presence but was calorized by the analysis within the group of influenza A, B and RSV. Collectively, these studies support the temporal clustering observed in our analysis, in which epidemic clusters (e.g., influenza and RSV) were clearly separated from background-persistent clusters (e.g., HAdV and SARS-CoV-2), underscoring the value of wastewater-based surveillance for differentiating co-circulating viral patterns across seasons.\u003c/p\u003e\u003cp\u003eData retrieved from the National Public Health Organization of Greece (EODY) was used to explore potential correlations between community respiratory pathogen positivity and normalized viral load in wastewater samples from Patras, spanning ISO week 2022-50 to ISO week 2023-13. Specifically, the dataset included positivity rates for SARS-CoV-2, influenza viruses, and respiratory syncytial virus (RSV) derived from non-sentinel community testing conducted by EODY\u0026rsquo;s Mobile Health Units (KOMY). These units perform rapid antigen testing (Rapid Ag) for SARS-CoV-2 in individuals who voluntarily present for testing, whether symptomatic or asymptomatic. For molecular surveillance of the three aforementioned pathogens, a random subset of symptomatic individuals with influenza-like illness is selected using an algorithm that ensures geographical and demographic representation across Greece. It is important to note that this sampling framework does not produce a representative sample of the general population. However, it may provide a useful indicator of percent positivity trends within the community. To assess the relationship between clinical surveillance data and wastewater-based epidemiology (WBE), Spearman's rho correlation was conducted between weekly normalized viral load in wastewater and aforementioned weekly pathogen positivity rates, for the three viruses. No significant correlations were found between the wastewater SARS-CoV-2 levels and positivity rates of SARS-CoV-2, influenza, or RSV in the community during the study period. Positivity rates are depicted in Supplementary Table S2. Reasons for lack of Significant Correlation can be explained by the following facts: The clinical testing data from the Mobile Health Units (KOMY) is based on voluntary participation and is not representative of the general population. This self-selection bias can distort observed positivity rates and limit their comparability to population-wide wastewater signals. Viral load in wastewater may precede or lag clinical case detection due to differences in viral shedding, incubation period, test-seeking behavior, and reporting delays and final (Peccia et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Nevertheless, we observe consistency in the trends across the datasets: SARS-CoV-2 is detected at relatively stable levels in wastewater, which is reflected in the recorded test positivity rates. A similar pattern is observed for influenza (considering influenza A and B combined), where wastewater signals align with test positivity. Additionally, the gradual decline in RSV detection in wastewater is also mirrored by a corresponding decrease in RSV test positivity rates.\u003c/p\u003e\u003cp\u003eTo summarize, the trends observed in the figure support the feasibility and effectiveness of wastewater-based surveillance in tracking the presence and intensity of multiple respiratory viruses simultaneously. These patterns mirror known seasonal behaviors while also highlighting unique co-circulation dynamics, such as overlapping peaks of RSV and Influenza A, which were also statistically supported by the correlation analysis. This underlines the importance of integrating wastewater surveillance into routine public health monitoring frameworks for early warning and comprehensive pathogen tracking. Furthermore, wastewater-based epidemiology (WBE) continues to demonstrate early warning potential, as temporal signals often precede or complement clinical surveillance, particularly for SARS-CoV-2 (Sims \u0026amp; Kasprzyk-Hordern, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, limitations persist, including virus-specific variability in shedding, environmental degradation rates, and challenges in differentiating viable versus fragmented viral genomes (Wade et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Polo et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Despite this, the application of WBE as a multiplex surveillance tool for monitoring co-circulating respiratory pathogens is increasingly recognized as a cost-effective and population-level approach to pandemic preparedness.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study demonstrates the applicability and reliability of wastewater-based epidemiology (WBE) for the simultaneous monitoring of multiple respiratory viruses, including HAdV, SARS-CoV-2, Influenza A and B, RSV A/B, and Rhinoviruses, at the community level in Patras, Greece. The consistent detection of HAdV and SARS-CoV-2, along with the seasonal peaks observed for Influenza A, Influenza B, and RSV, confirms the capacity of WBE to reflect viral circulation trends corresponding to clinical and environmental patterns. Hierarchical clustering and correlation analyses revealed distinct epidemiological behaviors, with some viruses showing persistent detection and others displaying synchronized epidemic peaks. The study also highlights the environmental persistence of HAdV. These findings underscore the critical role of WBE in complementing conventional epidemiological tools by providing timely, population-wide insights into the dynamics of viral transmission, supporting early warning systems and informed public health interventions. Continued integration of WBE into routine surveillance frameworks can enhance preparedness and response strategies for future respiratory pathogen outbreaks.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their gratitude to the National Public Health Organization of Greece (NPHO) for financially supporting the research activities, as well as to the Network of Collaborating Laboratories for wastewater-based epidemiological surveillance of the major cities of Greece.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, A.V and Z.A .; methodology, A.V and Z.A .; software, Z.A.; validation, R.F., Z.A. and A.V.; investigation, Z.A., K.A.K, R.F. and A.V.; resources, A.V.; data curation, Z.A., K.A.K, R.F. and A.V.; writing\u0026mdash;original draft preparation, Z.A., K.A.K, R.F. and A.V.; writing\u0026mdash;review and editing, A.V.; visualization, R.F. and A.V.; supervision, A.V.; project administration, Z.A and A.V.; funding acquisition, A.V. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhmed, W., Angel, N., Edson, J., Bibby, K., Bivins, A., O\u0026rsquo;Brien, J. W. \u0026amp; Mueller, J. F. (2020). First confirmed detection of SARS-CoV-2 in untreated wastewater in Australia: A proof of concept for the wastewater surveillance of COVID-19 in the community. Science of the Total Environment, 728, 138764. https://doi.org/10.1016/j.scitotenv.2020.138764\u003c/li\u003e\n\u003cli\u003eAlbinana-Gimenez, N., Miagostovich, M. P., Calgua, B., Huguet, J. M., Matia, L., \u0026amp; Girones, R. (2009). Analysis of adenoviruses and polyomaviruses quantified by qPCR as indicators of water quality in source and drinking-water treatment plants. 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The Open Microbiology Journal, 14(1), 48\u0026ndash;55. https://doi.org/10.2174/1874285802014010048\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"food-and-environmental-virology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"faev","sideBox":"Learn more about [Food and Environmental Virology](http://link.springer.com/journal/12560)","snPcode":"12560","submissionUrl":"https://submission.nature.com/new-submission/12560/3","title":"Food and Environmental Virology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7262979/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7262979/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe COVID-19 pandemic has underscored the importance of alternative epidemiological tools capable of providing real-time, population-level insights into infectious disease dynamics. Wastewater-based epidemiology (WBE) has emerged as a powerful, non-invasive method for tracking viral transmission within communities. While initially focused on SARS-CoV-2, WBE now offers the potential for multiplex surveillance of a broader range of respiratory pathogens. This study applied WBE to monitor the circulation of six major respiratory viruses such as Human adenovirus (HAdV), SARS-CoV-2, Influenza A and B, Respiratory Syncytial Virus (RSV) A/B, and Rhinoviruses, over a six-month period (ISO weeks 2022-40 to 2023-13) in the city of Patras, Greece. Weekly composite samples from a central wastewater treatment plant were analyzed via quantitative PCR, and viral genome concentrations were normalized per 100,000 inhabitants. The results revealed distinct circulation patterns: HAdV and SARS-CoV-2 were detected consistently throughout the period, while Influenza A peaked during the winter months, followed by Influenza B and RSV in early 2023. Rhinoviruses displayed intermittent peaks, indicating multiple waves or persistent low-level transmission. Correlation analyses showed strong positive associations between influenza viruses, RSV, and SARS-CoV-2, suggesting synchronized seasonal trends. Hierarchical cluster analysis classified the viruses into three distinct groups: (1) an epidemic cluster including Influenza A/B, RSV, and Rhinoviruses; (2) a persistently present cluster represented by HAdV; and (3) a separate episodic cluster characterized by SARS-CoV-2. These groupings reflect differences in viral epidemiology and shedding behaviour. This study confirms the effectiveness of WBE in tracking the temporal dynamics of multiple respiratory viruses and provides evidence of its utility in supplementing traditional clinical surveillance systems. The consistent detection of underreported pathogens such as HAdV underscores the added value of environmental monitoring for public health preparedness and early warning applications. These findings advocate for the integration of WBE into routine respiratory virus surveillance frameworks.\u003c/p\u003e","manuscriptTitle":"Comparative Investigation and Trends of Respiratory Viruses using Wastewater-Based Epidemiological Surveillance in Patras, Greece","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-07 17:24:35","doi":"10.21203/rs.3.rs-7262979/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-16T17:56:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-13T10:40:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"30773947757806477093914475363592723023","date":"2025-09-16T16:09:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"280924997241526428397955792710604295259","date":"2025-09-15T09:32:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-05T17:59:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"160117221742635830625544307640710808621","date":"2025-08-08T19:38:18+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-05T13:56:41+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-01T05:39:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-01T05:37:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"Food and Environmental Virology","date":"2025-07-31T13:51:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"food-and-environmental-virology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"faev","sideBox":"Learn more about [Food and Environmental Virology](http://link.springer.com/journal/12560)","snPcode":"12560","submissionUrl":"https://submission.nature.com/new-submission/12560/3","title":"Food and Environmental Virology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"ea10289c-4a6b-4e8e-90c5-c4c42ad10843","owner":[],"postedDate":"August 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-02T16:06:39+00:00","versionOfRecord":{"articleIdentity":"rs-7262979","link":"https://doi.org/10.1007/s12560-026-09683-5","journal":{"identity":"food-and-environmental-virology","isVorOnly":false,"title":"Food and Environmental Virology"},"publishedOn":"2026-02-25 15:57:30","publishedOnDateReadable":"February 25th, 2026"},"versionCreatedAt":"2025-08-07 17:24:35","video":"","vorDoi":"10.1007/s12560-026-09683-5","vorDoiUrl":"https://doi.org/10.1007/s12560-026-09683-5","workflowStages":[]},"version":"v1","identity":"rs-7262979","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7262979","identity":"rs-7262979","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}