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Objective: Wastewater Based Surveillance (WBS) has emerged as a novel monitoring tool for tracking and estimating the dissemination of the Novel Coronavirus Disease 2019 (COVID-19) within communities., Study Design: The goal of this review is to assess the factors that influence estimations of SARS-CoV-2 RNA concentration estimations in wastewater., Systematic Review: The goal of this review is to assess the factors that influence estimations of SARS-CoV-2 RNA concentration estimations in wastewater., Methods: A literature search was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis for Scoping Reviews (PRISMA-ScR) criteria in the electronic databases Scopus, PubMed, Google Scholar, and Medline. The overall quality, sample methodologies, quantification methods, and estimating approaches of selected papers were assessed., Results: Our findings reveal that 16 out of 24 articles (67 %) focused on physiochemical analyses. This review showed that sampling strategies and laboratory methodologies play a crucial role in the detection of SARS-CoV-2 RNA in wastewater samples. Moreover, we found that WBS-based estimation of COVID-19 is influenced by several factors such as wastewater temperature, shedding rate, and population size., Conclusion: This review reveals that the identified parameters require adjustments to achieve optimum conditions that accurately predict community infections. Including these factors that influence the estimation of SARS-CoV-2 RNA concentration in wastewater is essential for developing effective public health strategies to combat the spread of COVID-19., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The final point-of-drinking water (FPODW) exposure to Vibrio and waterborne pathogens remains a misaim surveillance target. Therefore, the current study purposed to estimate the global and regional prevalence of Vibrio pathogens in FPODW. Vibrio-FPODW data derived from integrated databases per PRISMA protocol were fitted to a random-intercept-logistic mixed-effects and meta-regression models. The global FPODW Vibrio prevalence was 5.13% (95%CI: 2.24-11.30) with 7.76% (6.84-8.78) cross-validated value. Vibrio prevalence in different FPODW varied with the highest in unclassified (13.98%, 3.98-38.95), household stored (6.42%, 1.16-28.69), municipal (4.39%, 1.54-11.90), and bottled (1.06%, 0.00-98.57) FPODW. Regionally, FPODW Vibrio prevalence varied significantly with highest in Africa (6.31%, 0.49-47.88), then Asia (4.83%, 2.01-11.18). Similarly, it varied significantly among income classification with the highest from low-income (8.77%, 0.91-50.05), then lower-middle-income (6.16%, 2.75-13.20), upper-middle-income (0.23%, 0.00-82.04), and 0.94% (0.19-2.72) in high-income economies. Among the WHO region, it varied significantly from 1.41% (0.17-10.45) in Eastern Mediterranean, 6.31% (0.49-47.88) in Africa to 8.86% (3.85-19.06) in South-East Asia and declining among SDI-quintiles from 11.64% (3.29-33.83) in Low-SDI, 10.59% (4.58-22.61) in High-middle-SDI to 0.26% (0.01-9.09) in Middle-SDI. FPODW Vibrio prevalence was 7.31% (2.94-17.03) in the low-GHSIG, followed by 4.55% (0.00-100.00) in the upper-GHSIG, and 2.21% (0.31-14.24) in middle-GHSIG; rural (4.18%, 0.06-76.17) and urban (5.28%, 2.35-11.44) settings. Also, sample size, SDI, SDI-quintiles, and nation significantly explained 14.12%, 10.91%, 30.35%, and 87.65% variance in FPODW Vibrio prevalence, respectively as a univariate influence. Additionally, 11.90% variance in FPODW Vibrio prevalence explained mortality rate attributed to unsafe WASH services. In conclusion, the study revealed a substantial high FPODW prevalence of Vibrio calling for initiative-taking and intentional surveillances of waterborne pathogens at the neglected stage across nations in order to achieve sustainably the SDG 3., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests or relationships that could influence the results reported in this study., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Helicobacter pylori (Hp) transmission dynamics via drinking water (DW) has a far much higher direct and indirect public health disease burden than previously thought. This study aimed to assess the global prevalence of Hp in DW, distributions across regions and socioeconomic indices (continent, world bank income, Human Development Index (HDI), Sustainable Development Index (SuDI), Socio-Demographic Index (SDI) quintile, and WHO regions). Hp-DW related data mined from five databases until 10/12/2022 according to PRISMA standard were quality-appraised and fitted to a generalized linear mixed-effects model. Sub-group analysis and meta-regression-modelling coupled with a 1000-permutation test ( ⁎ ) were conducted. The global prevalence of Hp in DW was 15.7% (95% confidence interval [CI]: 7.98-27.5), which varied significantly by sampling methods (Moore swabbing (61.0% [0.00-100.0]) vs. grab sampling (13.68%[6.99-25.04])) and detection technique (non-culture (21.35%[9.13-42.31]) vs. cultured-based methods (Psubgroup < 0.01)). The period 1990-99 had the highest prevalence (41.24% [0.02-99.97]). Regarding regional designations, Hp prevalence in DW was significantly different being highest in North America (61.82% [41.03-79.02]) by continents, AMR (42.66% [20.81-67.82]) by WHO group, high HDI (24.64% [10.98-46.43]) by HDI group and North America (61.90% [2.79-98.93]) by world bank region (Psubgroup < 0.01). Generally, sample preparation, SuDI grouping, and detection/confirmation techniques, have significant effects on the detection/prevalence of Hp in DW (Psubgroup < 0.01). Hp prevalence in DW was not significantly different among rural and urban DW (Psubgroup = 0.90), world bank income groups (Psubgroup = 0.15), and SDI quintiles (Psubgroup = 0.07). Among the predictors examined, only sample size (p < 0.1, R ∗ 2 (coefficient of determinant) = 15.29%), continent (p ∗ val = 0.04), HDI (p ∗ val = 0.02), HDI group (p ∗ val = 0.05), and microbiological methods (p < 0.1; R ∗ 2 =28.09 %) predicted Hp prevalence in DW robustly. In conclusion, Hp prevalence is still endemic in DW regardless of the regional designations/improve DW supplies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Laribacter hongkongensis is a human pathogen harboured in food and environmental matrices. This present study aimed to meta-analysed the prevalence of L. hongkongensis in humans, aquatic products, food/non-food animals, and environmental waters to provide update information on the pathogen. Nine electronic databases were systematically searched for articles on L. hongkongensis and a random-effects-model meta-analysis on its prevalence was conducted. Assessment of heterogeneities and publication biases across the studies was determined by using the I 2 statistic and Egger's regression/rank correlation tests of funnel plot, respectively. Furthermore, a meta-regression model was explored to unravel factors influencing the prevalence. A total of 39 documents were identified, of which, 33 articles were included as 98 sub-studies for the meta-analysis, and 87 sub-studies for subgroup-analysis. Overall, the prevalence of L. hongkongesis in human, aquatic products, food/non-food animals, and environmental waters was 8.5% (95% CI: 5.8-11.7). The leave-one-out influence analysis yielded a pooled prevalence of L. hongkongensis ranging from 8.1% (95% CI: 5.4-11.3) - 8.8% (95% CI: 5.8-12.3). Sub-group analysis found that the prevalence of L. hongkongensis was highest in Amphibian (54.6%, 95% CI: 41.3-67.6), followed by Pisces (7.9%, 95% CI: 5.3-10.9), Avian (0.5%, 95% CI: 0-5.8), and Mammal (0.5%, 95% CI: 0-3.6). In addition, Egger's regression-test of funnel plot suggests presence of publication (z = 4.2, p < 0.0001) in mammal subgroup. Multivariate meta-regression showed that the prevalence was significantly influenced by source type, class, and identification/detection method with the source type, class, and detection method specifically accounted for 25.49%, 11.28%, and 3.84% of the heterogeneity, respectively. Conclusively, the prevalence of L. hongkongensis decrease in order of Amphibian (54.6%), Pisces (7.9%), Avian (0.5%) and Mammal (0.5%). Aquatic products and environments are essential sources of the pathogen., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The emerging torque teno virus (TTV) has been identified as a biohazard marker of anthropocentric pollution and contamination in drinking water, natural water and wastewater systems (DWNWWS). Therefore, this study aimed at assessing prevalence of TTV in DWNWWS. The study systematically identified and meta-analyzed published studies on TTV prevalence in DWNWWS hosted in Dimensions, Google Scholar, PubMed, Web of Science, and Scopus databases using a random-effects model and mixed-effects meta-regression model for sensitivity analysis. Furthermore, the meta-analysis was stratified to estimate water type-specific TTV prevalence. The study found a total of 58 articles, of which 13 articles subdivided into 31 studies with 374 TTV positive cases and 862 total sample sizes were systematically reviewed and meta-analyzed. The pooled prevalence of TTV in DWNWWS was 37.18% (95%CI: 23.76-55.55%). Prevalence of TTV was significantly different across water types and it was 56.67% (95%CI: 36.94-75.46%) in wastewater, 26.72% (95%CI: 6.87-52.56%) in river water, and 17.17% (95%CI: 0.54-45.39%) in drinking water. TTV incidence in seawater and groundwater was 0% and 25.0% respectively. Funnel plots constructed and associated statistics of rank correlation test and Egger's regression test in this study, show lack of publication bias in the pooled prevalence of TTV in DWNWWS. Although, sample type (QM(df = 1) = 6.9656, p = 0.0083) and concentration methods (QM(df = 1) = 3.8055, p = 0.0511) significantly moderated and accounted for 15.39% and 6.00% of heterogeneity in the prevalence of TTV in DWNWWS respectively. In conclusion, research focus/monitoring activities on TTV is generally inadequate and potential risk of TTV in DWNWWS is underappreciated in most nations; the analyzed studies were from 7 countries (USA, Japan, Italy, Iran, Germany, Egypt, and Brazil). Finally, inefficient concentration method severely influences the prevalence of TTV in DWNWWS and could give rise to underestimation of TTV and mar TTV-based source-tracking of anthropogenic pollutions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Spatio-temporal distribution of pathogens in freshwater is driven by environmental variables (EVs), natural, and human-induced activities and the spread of infections and disease outbreaks are triggered significantly by these processes. The role of EVs and anthropogenic activities on the distribution of Plesiomonas shigelloides is not well understood; hence this study aimed at modelling the effects of EVs and anthropogenic gradients on the densities of Plesiomonas in freshwaters and freshwater quality. Three freshwaters were sampled from February to December 2017. The EVs and Plesiomonas densities of the freshwaters were determined using standard techniques, while partial least square path modelling and correlation analysis were performed on the data collected. Factors underpinning the quality of the freshwaters were identified through principal component analysis (PCA). Most EVs fell within the bounds of recommended permissible limits except turbidity, TSS, salinity and TDS. Results revealed a significant increase of Plesiomonas densities with an increase in the magnitude of path coefficients and intensities of anthropogenic activities along the freshwaters. The distribution of Plesiomonas correlated with temperature (r = 0.69, p < 0.01), TSS (r = 0.30, p < 0.01), TBS (r = 0.28, p < 0.01), and BOD (r = 0.39, p < 0.01). Similarly, a significant correlation existed between conductivity and TDS (r = 0.97, p < 0.01) and salinity (r = 0.99, p < 0.01). Network analysis of EVs identified three closed networks essential for freshwaters quality and Plesiomonas distribution with nodes of variables under synergistic latent influences. Overall, PCA identified four drivers of the freshwater quality and in part, Plesiomonas density; namely, nutrient loading; thermal and organic pollutions, aesthetic pollution, and pH modulators. Higher component score indicated a greater impact of nutrient loading on the freshwater quality. The study concluded that Plesiomonas distribution is largely shaped by anthropogenic gradients and EVs in rivers, and these may play a major role in its dissemination along freshwater milieus., (Copyright © 2019 Elsevier B.V. All rights reserved.)