Tracking the effects of the COVID-19 pandemic on viral gastroenteritis through wastewater-based retrospective analyses

Viral concentration method biases in the detection of viral profiles in wastewater

Viral detection methodologies used for wastewater-based epidemiology (WBE) studies have a broad range of efficacies. The complex matrix and low viral particle load in wastewater emphasize the importance of the concentration method. This study focused on comparing three commonly used virus concentration methods: polyethylene glycol precipitation (PEG), immuno-magnetic nanoparticles (IMNP), and electronegative membrane filtration (EMF). Influent and effluent wastewater samples were processed by the methods and analyzed by DNA/RNA quantification and sequencing for the detection of human viruses. SARS-COV-2, Astrovirus, and Hepatitis C virus were detected by all the methods in both sample types. PEG precipitation resulted in the detection of 20 types of viruses in influent and 16 types in effluent samples. The corresponding number of virus types detected was 21 and 11 for IMNP, and 16 and 8 for EMF. Certain viruses were unique to only one concentration method. For example, PEG detected three types of viruses in influent and six types in effluent compared to IMNP, which detected seven types in influent and one type in effluent samples. However, the EMF method appeared to be the least effective, detecting three types in influent and none in effluent samples. Rotavirus was detected in influent sample using IMNP method, whereas EMF and PEG methods failed to yield a similar outcome. Consequently, the potential false negative results pose a risk to the credibility of WBE applications. Therefore, implementation of a proper concentration technique is critical to minimize method biases and ensure accurate viral profiling in WBE studies.IMPORTANCEIn recent years, significant research efforts have been focused on the development of viral detection methodology for wastewater-based epidemiology studies, showing a range of variability in detection efficacies. A proper methodology is essential for an appropriate evaluation of disease prevalence and community health in such studies and necessitates designing a concentration method based on the target pathogenic virus. There remains a need for comparative performance evaluations of methods in the context of detection efficiencies. This study highlights the significant impact of sample matrix, viral structure, and nucleic acid composition on the efficacy of viral concentration methods. Assessing WBE techniques to ensure accurate detection and understanding of viral presence within wastewater samples is critical for revealing viral profiles in municipality wastewater samples.

Wastewater-based effective reproduction number and prediction under the absence of shedding information

Estimating effective reproduction number (Re) and predicting disease incidences are essential to formulate effective strategies for disease control. Although recent studies developed models for inferring Re from wastewater-based data, they require information on shedding dynamics. Here, we proposed a framework of Re estimation and prediction without shedding information. The framework consists of a space-state model for smoothing wastewater-based data and a renewal equation modified for wastewater-based data. The applicability of the framework was tested with simulated data and real-world data on Influenza A virus (IAV) and SARS-CoV-2 concentration in wastewater in 2022/2023 season in the USA. We confirmed the state-space model effectively fits various simulated epidemic curves and real-world data. In simulations, we found wastewater-based Re (Reww) closely aligns with instantaneous clinical Re when shedding dynamics are rapid. For more prolonged shedding, Reww approximates a smoothed Re over time. We also observed the necessary sampling frequency to trace dynamics of wastewater concentration and Reww accurately in the framework varies depending on the precision of detection methods, the epidemic status, the transmissibility of infectious diseases, and shedding dynamics. By applying our framework to real-world data, we found Reww for SARS-CoV-2 showed similar trend and values to clinically-based Re. Reww for IAV ranged from 0.66 to 1.52 with a clear peak in the winter season, which agrees with previously reported Re. We also succeeded in predicting wastewater concentration in a few weeks from available wastewater-based data. These results indicate that our framework potentially enables near real-time monitoring of approximated Re and prediction of infectious disease dynamics through wastewater surveillance, which limits the delay between infection and reporting. Our framework is useful especially for regions where reliable clinical surveillance is not available and notifiable surveillance is abolished, and can be expanded to multiple infectious diseases that have been detected from wastewater.

Beyond COVID-19: Wastewater-based epidemiology for multipathogen surveillance and normalization strategies

Wastewater-based epidemiology (WBE) is a critical tool for monitoring community health. Although much attention has focused on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a causative agent of coronavirus disease 2019 (COVID-19), other pathogens also pose significant health risks. This study quantified the presence of SARS-CoV-2, influenza A virus (Inf-A), and noroviruses of genogroups I (NoV-GI) and II (NoV-GII) in wastewater samples collected weekly (n = 170) from July 2023 to February 2024 from five wastewater treatment plants (WWTPs) in Yamanashi Prefecture, Japan, by quantitative PCR. Inf-A RNA exhibited localized prevalence with positive ratios of 59 %-82 % in different WWTPs, suggesting regional outbreaks within specific areas. NoV-GI (94 %, 160/170) and NoV-GII (100 %, 170/170) RNA were highly prevalent, with NoV-GII (6.1 ± 0.8 log10 copies/L) consistently exceeding NoV-GI (5.4 ± 0.7 log10 copies/L) RNA concentrations. SARS-CoV-2 RNA was detected in 100 % of the samples, with mean concentrations of 5.3 ± 0.5 log10 copies/L in WWTP E and 5.8 ± 0.4 log10 copies/L each in other WWTPs. Seasonal variability was evident, with higher concentrations of all pathogenic viruses during winter. Non-normalized and normalized virus concentrations by fecal indicator bacteria (Escherichia coli and total coliforms), an indicator virus (pepper mild mottle virus (PMMoV)), and turbidity revealed significant positive associations with the reported disease cases. Inf-A and NoV-GI + GII RNA concentrations showed strong correlations with influenza and acute gastroenteritis cases, particularly when normalized to E. coli (Spearman's ρ = 0.70-0.81) and total coliforms (ρ = 0.70-0.81), respectively. For SARS-CoV-2, non-normalized concentrations showed a correlation of 0.61, decreasing to 0.31 when normalized to PMMoV, suggesting that PMMoV is unsuitable. Turbidity normalization also yielded suboptimal results. This study underscored the importance of selecting suitable normalization parameters tailored to specific pathogens for accurate disease trend monitoring using WBE, demonstrating its utility beyond COVID-19 surveillance.

Epidemics and diversity of norovirus variants with acute gastroenteritis outbreak in Hongshan District, Wuhan City, China, 2021-2023

BACKGROUND

Norovirus is the predominant pathogen causing foodborne illnesses and acute gastroenteritis (AGE) outbreaks worldwide, imposing a significant disease burden. This study aimed to investigate the epidemiological characteristics and genotypic diversity of norovirus outbreaks in Hongshan District, Wuhan City.

METHODS

A total of 463 AGE cases from 39 AGE-related outbreaks in Hongshan District between January 1, 2021, and June 30, 2023, were included in the study. Reverse transcription-polymerase chain reaction (RT-PCR) was used to identify norovirus types GI and GII in anal swab samples from all cases. Norovirus-positive samples were sequenced and analyzed for the open reading frame (ORF) 1/ORF2 hinge region.

RESULTS

26 norovirus infectious outbreaks were reported among 39 acute diarrheal outbreaks, including 14 outbreaks in kindergartens, 8 in elementary schools, and 4 in universities. Based on clinical symptoms and epidemiological investigations, a total of 1295 individuals were identified as having been exposed to norovirus, yielding an attack rate of 35.75 %. A higher proportion of outbreaks was observed during the winter and spring seasons (38.46 %). Additionally, norovirus-positive samples were subjected to sequencing and analysis of the open reading frame (ORF) 1/ORF2 hinge region. Genotypic data for norovirus was successfully obtained from 18 (69.23 %) of the infectious outbreaks, revealing 10 distinct recombinant genotypes. GII.4 Sydney 2012 [P31] and GII.17[P17] were the predominant strains in 2021 and 2022, GII.3 [P12] emerged as the dominant strain in 2023.

CONCLUSION

Norovirus outbreaks in Hongshan District predominantly occurred in crowded educational institutions, with peaks in the cold season and a high attack rate in universities. GII.3 [P12] has become the locally predominant strain.

The impact of COVID-19 pandemic on the incidence of acute gastroenteritis outbreaks in Catalonia (Spain)

We carried out a retrospective study of acute gastroenteritis (AGE) outbreaks reported between 1 January 2015 and 31 December 2021 in Catalonia (Spain) to compare the incidence from 2015 to 2019 with that observed from 2020 to 2021. We observed a higher incidence rate of outbreaks during the prepandemic period (16.89 outbreaks/1,000,000 person-years) than during the pandemic period (6.96 outbreaks/1,000,000 person-years) (rate ratio (RR) 0.41; 95% confidence interval (CI) 0.34 to 0.51). According to the aetiology of the outbreak, those of viral aetiology decreased from 7.82 to 3.38 outbreaks/1,000,000 person-years (RR 2.31; 95% CI 1.72 to 3.12), and those of bacterial aetiology decreased from 5.01 to 2.78 outbreaks/1,000,000 person-years (RR 1.80; 95% CI 1.29 to 2.52). There was a great reduction in AGE outbreaks in Catalonia. This reduction may have been due to the effect of the nonpharmaceutical measures applied to reduce the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but the collapse of the healthcare system and epidemiological surveillance services may also have had a strong influence.