Factors affecting detection and estimation of SARS-CoV-2 RNA concentration of COVID-19 positive cases in wastewater influent: A systematic review.

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.

Human norovirus contamination challenge in fresh produce: a global prevalence and meta-analytic assessment.

AIMS: Among fresh produce (FP)-associated foodborne infections, human noroviruses (HNoV) are the leading causative agent. The present study aimed to assess the prevalence of HNoV in FP. METHODS AND RESULTS: FP-associated HNoV records mined from 5 repositories until 25/05/2022 according to PRISMA standards were appraised, fitted to a generalized linear mixed-effects model and subgroup analysed by sample type, genogroup, and geographical location. Further, heterogeneity was assessed in the model coupled with a leave-one-out-cross-validation. The overall prevalence of HNoV in FP was 9.3% (95% confidence interval [CI] 3.7-21.7. HNoV prevalence was higher in fruits (9.8%[3.7-23.5]) than vegetables (9.4%[3.1-25.3]). Regarding geographical distribution, FP-associated HNoV prevalence varied from Africa (25.8%, 5.7-66.7), Asia (23.2%[4.6-65.0]), Europe (5.6%[0.7-33.9]), North America (12.4%[1.8-52.7]) to South America (7.5%[0.0-100.0]). HNoV GI overall prevalence in FP was 5.3% (2.5-11.1) and varied by sample type (fruits: 4.9%[1.7-13.2]; vegetables: 5.8%[1.6-18.8]). While the occurrence of GII in FP was 1.7% (0.7-3.9) and varied by sample type (fruits: 2.5%[1.0-6.5]; vegetables: 0.9%[0.2-4.9]), GIGII (detection of both GI and GII) was 0.3% (0.1-1.0) with 0.4% (0.1-2.2) and 0.2% (0.0-1.5) in fruits and vegetables, respectively. In all cases, the test for sample/regional prevalence differences were not significantly different with the exception of GII regional prevalence differences (p = 0.03). CONCLUSIONS: This study suggests that FP represents a critical vehicle for HNoV dissemination, a global and a high risk for public health.

Socioeconomic indices guided linear mixed-effects and meta-regression modelling of the temporal, global and regional prevalence of Helicobacter pylori in environmental waters: A class I carcinogen.

Environmental waters (EW) substantially lend to the transmission of Helicobacter pylori (Hp). But the increase in Hp infections and antimicrobial resistance is often attributed to socioeconomic status. The connection between socioeconomic status and Hp prevalence in EW is however yet to be investigated. This study aimed to assess the impacts of socioeconomic indices (SI: continent, world bank region (WBR), world bank income (WBI), WHO region, Socio-demographic Index (SDI quintile), Sustainable Development Index (SuDI), and Human Development Index (HDI)) on the prevalence of Hp in EW. Hp-EW data were fitted to a generalized linear mixed-effects model and SI-guided meta-regression models with a 1000-resampling test. The worldwide prevalence of Hp in EW was 21.76% [95% confidence interval [CI]: 10.29-40.29], which declined significantly from 59.52% [43.28-74.37] in 1990-99 to 19.36% [3.99-58.09] in 2010-19 and with increasing trend in 2020-22 (33.33%, 22.66-45.43). Hp prevalence in EW was highest in North America (45.12%, 17.07-76.66), then Europe (22.38%, 5.96-56.74), South America (22.09%, 13.76-33.49), Asia (2.98%, 0.02-85.17), and Africa (2.56%, 0.00-99.99). It was negligibly different among sampling settings, WBI, and WHO regions demonstrating highest prevalence in rural location [42.62%, 3.07-94.56], HIEs [32.82%, 13.19-61.10], and AMR [39.43%, 19.92-63.01], respectively. However, HDI, sample size, and microbiological method robustly predict Hp prevalence in EW justifying 26.08%, 21.15%, and 16.44% of the true difference, respectively. In conclusion, Hp is highly prevalence in EW across regional/socioeconomic strata and thus challenged the uses of socioeconomic status as surrogate for hygienic/sanitary practices in estimating Hp infection prevalence.

Hibiscus sabdariffa (Roselle) calyx: a systematic and meta-analytic review of memory-enhancing, anti-neuroinflammatory and antioxidative activities.

BACKGROUND: In this study, we summarized the preclinical investigations of the neuroprotective activities of Hibiscus sabdariffa (HSD) extract via its effect on memory function, neuroinflammation and oxidative damage in the central nervous system, which may help to guide future studies. METHODS: Preclinical studies that investigated the effect of HSD extract on memory impairment, neuroinflammation and oxidative stress-induced neuronal damage were searched systematically in PubMed, EBSCOhost (including MEDLINE, CINAHL, APA PsycInfo, etc.), Web of Science (WoS) and Scopus. Parameters and indexes included Morris water maze, passive avoidance test, acetylcholinesterase activity, interleukin 1 (IL-1), tumour necrosis factor-alpha (TNF-α), MAPK, malondialdehyde (MDA), glutathione (GSH), reactive oxygen species (ROS) and mitochondria membrane potential (MMP). RESULTS: A total of 285 documents were identified; however, only ten articles were included and used for meta-analysis. The meta-analytic outcome revealed that HSD did not show any significant effect on memory function, neuroinflammatory biomarkers (IL-1, MAPK) and oxidative stress (GSH, MDA, ROS and MMP) in neuronal cells and tissues. CONCLUSIONS: Individual study revealed that HSD showed improved memory function, attenuated neuroinflammation and prevented oxidative damage to neurons. However, a conflicting result was observed from the meta-analytic outcomes which showed that HSD has no significant effect on cognitive impairment, neuroinflammation and oxidative stress-induced neuronal damage. However the contradiction in this finding may be associated with small number of studies included. Hence, more studies on the memory-enhacing effects and anti-neuroinflammatory activity of HSD in preclinical and clinical model are required to validate its neuroprotective effect.

Arcobacter species in milk contamination: a prevalence-based systematic review and meta-analysis.

AIMS: Milk is consumed raw or minimally processed and plays a role in the dissemination of pathogens of public health concerns. The present investigation is aimed at assessing the occurrence of pathogenic Arcobacter species in 2945 milk samples. METHODS AND RESULTS: Arcobacter data systematically retrieved from 5 repositories until 20/02/2022 according to PRISMA principles was logit transformed and fitted using a generalized linear mixed-effects model. The between-study heterogeneity was estimated as I2-value. Leave-one-out-cross-validation and funnel plot with Egger's tests was used to assess the hardiness and bias in the model. The global prevalence of Arcobacter genus in the milk was 12% [95%-CI: 7-19%; I2 = 87.3%, 95%-CI: 83.0-90.6%] and no publication bias observed (Eggers' test: p = 0.112). Arcobacter genus prevalence in milk was 13% (95%-CI: 5-30%), 10% (95%-CI: 1-46%), and 9% (95%-CI: 4-19%) in Europe, South America, and Asia, respectively. A. butzleri was the most prevalent (8% [95%-CI: 4-13%]), then A. cryaerophilus (0.6% [95%-CI: 0.2-33.2%]) and A. skirrowii (0.19% [95%-CI: 0.03-1.2%]). Also species-specific prevalence of A. butzleri, A. cryaerophilus, and A. skirrowii varied continentally, but the test for species-specific/continental differences were not significantly different (p > 0.5).

Arcobacter species in milk contamination: a prevalence-based systematic review and meta-analysis.

AIMS: Milk is consumed raw or minimally processed and plays a role in the dissemination of pathogens of public health concerns. The present investigation is aimed at assessing the occurrence of pathogenic Arcobacter species in 2945 milk samples. METHODS AND RESULTS: Arcobacter data systematically retrieved from five repositories until 20 February 2022 according to PRISMA principles were logit transformed and fitted using a generalized linear mixed-effects model. The between-study heterogeneity was estimated as I2-value. Leave-one-out cross-validation and funnel plot with Egger's tests were used to assess the hardiness and bias in the model. The global prevalence of Arcobacter genus in the milk was 12% [95% confidence interval (CI): 7-19%; I2 = 87.3%, 95% CI: 83.0-90.6%] and no publication bias observed (Egger's test: P = 0.112). Arcobacter genus prevalence in milk was 13% (95% CI: 5-30%), 10% (95% CI: 1-46%), and 9% (95% CI: 4-19%) in Europe, South America, and Asia, respectively. Arcobacter butzleri was the most prevalent [8% (95% CI: 4-13%)], followed by A. cryaerophilus [0.6% (95% CI: 0.2-33.2%)] and A. skirrowii [0.19% (95% CI: 0.03-1.2%)]. Also, species-specific prevalence of A. butzleri, A. cryaerophilus, and A. skirrowii varied continentally, but the test for species-specific/continental differences was not significantly different (P > 0.5).

Prevalence of Laribacter hongkongensis in food and environmental matrices: A systematic review and meta-analysis.

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 I2 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.

Global bibliometric meta-analytic assessment of research trends on microbial chlorine resistance in drinking water/water treatment systems.

Chlorine is the commonest and cheapest disinfectant used in drinking water and wastewater treatment at household, municipal and industrial levels. However, the uprising of microbial chlorine resistance (MCR) pose critical public health hazard concerns; because, its potentiate exposure to difficult-to-treat resistant pathogens. Therefore, this study aimed at evaluating the burden of MCR in drinking water/wastewater treatment and distribution systems (DWWTDS) via science mapping of research productivity (authors, countries, institutions), thematic conceptual framework, disciplines, research networks and associated intellectual landscape. MCR data were mined from Scopus and Web of Science based on optimized algorithms with the root key term "chlorine* resistant*'' and analysed for pre-set indicator variables. Results revealed 1127 documents from 442 journals and 1430% average growth rate (AGR) of research articles from 2017 to 2019 on MCR. Country-wise, the USA (n = 299), China (n = 119), and Japan (n = 43) ranked in the 1st, 2nd, and 3rd positions respectively, among the top participating countries in MCR research. MCR research had considerable performance in public health and sustainable concern subjects namely, Environmental Sciences & Ecology, Engineering, Microbiology, Water Resources, Biotechnology & Applied Microbiology, Food Science & Technology, Public, Environ & Occupational Health, Chemistry, Infectious Diseases, and Marine & Freshwater Biology; and with noticeable AGR in Environmental Sciences & Ecology (330%) and Infectious Diseases (130%). The study found biofilm-related thrusts (n = 90, 270% AGR) as main research hotspots on MCR. Overall, the study identified and discussed four important thematic areas of public health challenges in MCR that could promote increasing waterborne diseases due to (re)emerging pathogens, enteric viruses and dissemination in DWWTDS. In conclusion, this study provides comprehensive overview of the growing burden of MCR in DWWTDS and standout as a primer of information for researchers on MCR. It recommends direct, intentional and integrated research priorities on MCR to overcome accompanying public health and environmental threats. In addition, chlorine resistance in waterborne fungi have not received research attention. Research activities related to fungal chlorine resistance will be an invaluable future direction in DWWTDS and guide against exposure to waterborne pathogenic fungi and mycotoxins. It is unknown whether chlorine resistance can be acquired by horizontal gene transfer in microorganisms and future research should elucidate this important thrust.

Global and regional prevalence of Cronobacter sakazakii in powdered milk and flour.

Cronobacter sakazakii (Cz) infections linked with powdered milk/flour (PMF) are on the increase in recent times. The current study aimed at assessing worldwide and regional prevalence of Cz in PMF. Cz-PMF-directed data were conscientiously mined in four mega-databases via topic-field driven PRISMA protocol without any restriction. Bivariate analysis of datasets was conducted and then fitted to random-intercept logistic mixed-effects regressions with leave-one-study-out-cross-validation (LOSOCV). Small-study effects were assayed via Egger's regression tests. Contributing factors to Cz contamination/detection in PMF were determined using 1000-permutation-bootstrapped meta-regressions. A total of 3761 records were found out of which 68 studies were included. Sample-size showed considerable correlation with Cz positivity (r = 0.75, p = 2.5e-17), Milkprod2020 (r = 0.33, p = 1.820e-03), and SuDI (r = - 0.30, p = 4.11e-03). The global prevalence of Cz in PMF was 8.39% (95%CI 6.06-11.51, PI: 0.46-64.35) with LOSOCV value of 7.66% (6.39-9.15; PI: 3.10-17.70). Cz prevalence in PMF varies significantly (p < 0.05) with detection methods, DNA extraction method, across continents, WHO regions, and world bank regions. Nation, detection method, world bank region, WHO region, and sample size explained 53.88%, 19.62%, 19.03%, 15.63%, and 9.22% of the true differences in the Cz prevalence in PMF, respectively. In conclusion, the results indicated that national will power in the monitoring and surveillance of Cz in PMF matched with adequate sample size and appropriate detection methods will go a long way in preventing Cz contamination and infections.

Global and regional final point-of-drinking water prevalence of Vibrio pathogens: a systematic analysis with socioeconomic, global health security, and WASH indices-guided meta-regressions.

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.

Global and regional prevalence of Helicobacter pylori in drinking waters: A sustainable, human development and socio-demographic indices based meta-regression-modelling.

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.

Prevalence of Listeria monocytogenes in milk in Africa: a generalized logistic mixed-effects and meta-regression modelling.

Listeria outbreaks and food recalls is on the raise globally. Milk particularly is highly susceptible to Listeria as its production and storage adequately support Listeria growth. The extent of milk contamination with Listeria monocytogenes (Lm) and preventative actions to halt milk associated outbreaks in Africa are unknown. Hence, this study aimed at assessing the national and subregional prevalence of Lm in milk in Africa and identify impacting factors via generalized logistic mixed-effects (GLMEs) and meta-regression modelling. Lm-milk-specific data acquired from primary studies according to standard protocol were fitted using a GLMEs. The GLMEs was subjected to leave-one-study-out-cross-validation (LOSOCV). Factors impacting Lm prevalence in milk were assayed via a 1000-permutation-assisted meta-regression-modelling. The pooled prevalence of Lm in milk in Africa was 4.35% [2.73-6.86] with a prediction interval (PI) of 0.14-59.86% and LOSOCV value of 2.43% [1.62-3.62; PI: 0.32-16.11%]. Western Africa had the highest prevalence [20.13%, 4.13-59.59], then Southern Africa [5.85%, 0.12-75.72], Northern Africa [4.67%, 2.82-7.64], Eastern Africa [1.91%, 0.64-5.55], and there was no record from Central Africa. In term of country, Lm prevalence in milk significantly (p < 0.01) varied from 0.00 to 90.00%. Whereas the Lm prevalence was negligibly different (p = 0.77) by milk type, raw-milk had the highest prevalence [5.26%], followed by fermented-milk [4.76%], boiled-milk [2.90%], pasteurized-milk [1.64%], and powdered-milk [1.58%]. DNA extraction approach did not significantly (p = 0.07) affect Lm prevalence (Boiling [7.82%] versus Kit [7.24%]) as well as Lm detection method (p = 0.10; (ACP [3.64%] vs. CP [8.92%] vs. CS [2.27%] vs. CSP [6.82%]). Though a bivariate/multivariate combination of all tested variables in meta-regression explained 19.68-68.75% (R2) variance in Lm prevalence in milk, N, nation, and subregion singly/robustly accounted for 17.61% (F1;65 = 7.5994; p = 0.005), 63.89% (F14;52 = 4.2028; p = 0.001), and 16.54% (F3;63 = 3.4743; p = 0.026), respectively. In conclusion, it is recommended that adequate sample size should be prioritized in monitoring Lm in milk to prevent spuriously high or low prevalence to ensure robust, plausible, and credible estimate. Also, national efforts/interests and commitments to Lm monitoring should be awaken.

Using machine learning models to predict the effects of seasonal fluxes on Plesiomonas shigelloides population density.

Seasonal variations (SVs) affect the population density (PD), fate, and fitness of pathogens in environmental water resources and the public health impacts. Therefore, this study is aimed at applying machine learning intelligence (MLI) to predict the impacts of SVs on P. shigelloides population density (PDP) in the aquatic milieu. Physicochemical events (PEs) and PDP from three rivers acquired via standard microbiological and instrumental techniques across seasons were fitted to MLI algorithms (linear regression (LR), multiple linear regression (MR), random forest (RF), gradient boosted machine (GBM), neural network (NN), K-nearest neighbour (KNN), boosted regression tree (BRT), extreme gradient boosting (XGB) regression, support vector regression (SVR), decision tree regression (DTR), M5 pruned regression (M5P), artificial neural network (ANN) regression (with one 10-node hidden layer (ANN10), two 6- and 4-node hidden layers (ANN64), and two 5- and 5-node hidden layers (ANN55)), and elastic net regression (ENR)) to assess the implications of the SVs of PEs on aquatic PDP. The results showed that SVs significantly influenced PDP and PEs in the water (p < 0.0001), exhibiting a site-specific pattern. While MLI algorithms predicted PDP with differing absolute flux magnitudes for the contributing variables, DTR predicted the highest PDP value of 1.707 log unit, followed by XGB (1.637 log unit), but XGB (mean-squared-error (MSE) = 0.0025; root-mean-squared-error (RMSE) = 0.0501; R2 =0.998; medium absolute deviation (MAD) = 0.0275) outperformed other models in terms of regression metrics. Temperature and total suspended solids (TSS) ranked first and second as significant factors in predicting PDP in 53.3% (8/15) and 40% (6/15), respectively, of the models, based on the RMSE loss after permutations. Additionally, season ranked third among the 7 models, and turbidity (TBS) ranked fourth at 26.7% (4/15), as the primary significant factor for predicting PDP in the aquatic milieu. The results of this investigation demonstrated that MLI predictive modelling techniques can promisingly be exploited to complement the repetitive laboratory-based monitoring of PDP and other pathogens, especially in low-resource settings, in response to seasonal fluxes and can provide insights into the potential public health risks of emerging pathogens and TSS pollution (e.g., nanoparticles and micro- and nanoplastics) in the aquatic milieu. The model outputs provide low-cost and effective early warning information to assist watershed managers and fish farmers in making appropriate decisions about water resource protection, aquaculture management, and sustainable public health protection.

Machine learning-guided determination of Acinetobacter density in waterbodies receiving municipal and hospital wastewater effluents.

A smart artificial intelligent system (SAIS) for Acinetobacter density (AD) enumeration in waterbodies represents an invaluable strategy for avoidance of repetitive, laborious, and time-consuming routines associated with its determination. This study aimed to predict AD in waterbodies using machine learning (ML). AD and physicochemical variables (PVs) data from three rivers monitored via standard protocols in a year-long study were fitted to 18 ML algorithms. The models' performance was assayed using regression metrics. The average pH, EC, TDS, salinity, temperature, TSS, TBS, DO, BOD, and AD was 7.76 ± 0.02, 218.66 ± 4.76 µS/cm, 110.53 ± 2.36 mg/L, 0.10 ± 0.00 PSU, 17.29 ± 0.21 °C, 80.17 ± 5.09 mg/L, 87.51 ± 5.41 NTU, 8.82 ± 0.04 mg/L, 4.00 ± 0.10 mg/L, and 3.19 ± 0.03 log CFU/100 mL respectively. While the contributions of PVs differed in values, AD predicted value by XGB [3.1792 (1.1040-4.5828)] and Cubist [3.1736 (1.1012-4.5300)] outshined other algorithms. Also, XGB (MSE = 0.0059, RMSE = 0.0770; R2 = 0.9912; MAD = 0.0440) and Cubist (MSE = 0.0117, RMSE = 0.1081, R2 = 0.9827; MAD = 0.0437) ranked first and second respectively, in predicting AD. Temperature was the most important feature in predicting AD and ranked first by 10/18 ML-algorithms accounting for 43.00-83.30% mean dropout RMSE loss after 1000 permutations. The two models' partial dependence and residual diagnostics sensitivity revealed their efficient AD prognosticating accuracies in waterbodies. In conclusion, a fully developed XGB/Cubist/XGB-Cubist ensemble/web SAIS app for AD monitoring in waterbodies could be deployed to shorten turnaround time in deciding microbiological quality of waterbodies for irrigation and other purposes.

Prevalence, multiple antibiotic resistance and virulence profile of methicillin-resistant Staphylococcus aureus (MRSA) in retail poultry meat from Edo, Nigeria.

Introduction: Staphylococcus aureus causes staphylococcal food poisoning and several difficult-to-treat infections. The occurrence and dissemination of methicillin-resistance S. aureus (MRSA) in Nigeria is crucial and well documented in hospitals. However, findings on MRSA from meat in the country are yet to be adequately reported. The current study determined the prevalence, virulence profile and antibiogram characteristics of MRSA from a raw chicken product from retail outlets within Edo. Methods: A total of 368 poultry meat samples were assessed for MRSA using a standard culture-based approach and characterized further using a molecular method. The antimicrobial susceptibility profile of the isolates was determined using the disc diffusion method. The biofilm profile of the isolates was assayed via the crystal violet microtitre-plate method. Virulence and antimicrobial resistance genes were screened using polymerase chain reaction via specific primers. Results: Of the samples tested, 110 (29.9%) were positive for MRSA. All the isolates were positive for deoxyribonuclease (DNase), coagulase and beta-hemolysis production. Biofilm profile revealed 27 (24.55%) weak biofilm formers, 18 (16.36%) moderate biofilm formers, and 39 (35.45%) strong biofilm formers. The isolates harboured 2 and ≤17 virulence genes. Enterotoxin gene profiling revealed that 100 (90.9%) isolates harboured one or more genes. Resistance against the tested antibiotics followed the order: tetracycline 64(58.2%), ciprofloxacin 71(64.6%), trimethoprim 71(64.6%) and rifampin 103(93.6%). A total of 89 isolates were multidrug-resistant, while 3 isolates were resistant to all 22 antibiotics tested. The isolates harboured antimicrobial-resistant determinants such as methicillin-resistant gene (mecA), tetracycline resistance genes (tetK, tetL), erythromycin resistance genes (ermA, ermC), trimethoprim resistance gene (dfrK). All the staphylococcal cassette chromosome mec (SCCmec) IVa and SCCmec V positive isolates harboured the Panton-Valentine Leukocidin Gene (PVL). Conclusion: In conclusion, S. aureus was resistant to commonly used antibiotics; a concern to public health concerning the transmission of these pathogens after consuming these highlight the significance of antimicrobial and enterotoxigenic monitoring of S. aureus in food chains.

Occurrence and Molecular Characterization of Multidrug-Resistant Vegetable-Borne Listeria monocytogenes Isolates.

Fresh vegetables play a significant role in the human diet. However, ready-to-eat (RTE) vegetables have been associated with increasing foodborne outbreaks including L. monocytogenes, which is a common human pathogen associated with foodborne infections resulting in listeriosis. This study aims to assess the resistance of vegetable-borne L. monocytogenes to antibiotics. L. monocytogenes was isolated and molecularly characterized using polymerase chain reaction (PCR) from 17 RTE vegetable samples. The confirmed L. monocytogenes was further assessed for phenotypic and genotypic antibiotic resistance using the disc diffusion test and PCR primers targeting six antibiotic classes and thirty-one related antibiotic resistance genes (ARGs), respectively. The results revealed that Listeria counts ranged from 1.60 to 3.44 log10 CFU/g in the samples. The isolates exhibited high resistance against penicillin G, erythromycin, vancomycin, tetracycline, trimethoprim-sulfamethoxazole, and nitrofurantoin among the 108 isolates tested. A total of 71 multiple antibiotic resistance (MAR) phenotypes were observed in the isolates, which ranged from resistance to 3 to 13 antibiotics. The MAR index was ˃0.2 in 97% of the isolates. Some of the highly detected ARG subtypes included SulI (100%), TEM (76.9%), tetA (59%), and tetM (54.7%). The findings show a high occurrence of multidrug-resistant L. monocytogenes and clinical ARGs in fresh vegetables, which constitutes an immediate danger for the health security of the public.

Systematic and meta-analysis of Mycobacterium avium subsp. paratuberculosis related type 1 and type 2 diabetes mellitus.

Global increase in diabetes (DM) prevalence necessitated the need to establish the association between DM and environmental triggers including MAP (Mycobacterium avium subsp. paratuberculosis) that have been postulated to play a role in DM etiopathology for effective management. The present investigation aimed to assess the odds ratio (OR) presenting the association between MAP and DM. MAP-related DM studies were systematically retrieved from 6 databases until 31 September 2021 according to PRISMA principles for data abstraction. The abstracted dataset was fitted to the fixed-effects (FE) and random-effects (RE) models using the Mantel-Haenszel approach. Sixteen studies involving 2072 participants (1152 DM patients (957 type 1 diabetes mellitus (T1DM) & 195 type 2 diabetes mellitus (T2DM)) and 920 healthy controls) met the inclusion criteria. Results revealed a significant association between anti-MAP antibodies (abs) seroprevalence and T1DM (FE: OR 7.47, 95% CI 5.50-10.14, p value < 0.0001; RE: OR 7.92, 95% CI 4.39-14.31, p < 0.0001) and MAP DNA with T1DM (FE: OR 4.70 (95% CI 3.10-7.13, p value < 0.0001), RE: OR 3.90 (95% CI 0.93-16.38, p value = 0.06)). Both anti-MAP abs and MAP DNA based meta-analyses had medium heterogeneity (I2 = 47.2-61.0%). Meanwhile, no significant association between MAP and T2DM (FE: OR 1.13, 95% CI 0.54-2.37, p value = 0.74; RE: OR 1.19; 95% CI 0.34-4.12, p value = 0.69), its OR magnitude exceeded 1 and prediction interval (0.09-15.29) suggest possibility of association between the duo in the future. The leave-one-out sensitivity analysis depicts a robust meta-analysis in all cases. In conclusion, the study manifests a positive association between MAP and T1DM, highlighting that MAP prevention and environmental control would indubitably revolutionize T1DM management. Also, its projects possible link between MAP and T2DM as more data becomes available. However, it remains elusive whether MAP triggers T1/T2DM or a mere comorbidity in T1/T2DM. Epidemiological activities to fill the global/regional data gaps on MAP-related T1DM and T2DM are advocated in order to assess the burden of MAP-related DM and improve their clinical management.

Systematic review and meta-analysis of Mycobacterium avium subsp. paratuberculosis as environmental trigger of multiple sclerosis.

Mycobacterium avium subsp. paratuberculosis (MAP) has been identified as one of the environmental agents that causes multiple sclerosis (MS). The global prevalence of MS has been upsurging over the years; however, efforts to divulge the role of MAP in MS have been limited. As a result, the present study aimed at assessing the odd ratios (ORs) associated MAP with the risk of MS. MAP-related MS data were obtained from 6 databases using the terms 'multiple sclerosis' or 'MS' and 'paratuberculosis' without regard for time or language restrictions following PRISMA standards. A total of 2,538 participants' data from 12 studies presenting anti-MAP antibodies and MAP DNA from 4 studies were fitted in random-effects (RE) and fixed-effects (FE) meta-analytic models. Furthermore, the between-study heterogeneity was measured using I2-values with a significant limit set at an I² > 75%. Analytical rigor and publication bias was determined using leave-one-out-analytics, Egger's tests, and p-curve analysis. In the FE and RE models, anti-MAP antibodies data significantly associated MS risk with MAP as 10.71 OR (95%-CI [7.78; 14.74], p-value < 0.0001) and 12.76 OR (95%-CI [8.13; 20.02], p-value < 0.0001) respectively, with an I2 value of 34.9% (95%-CI [0.0%; 67.2%]; p-value = 0.11). Similarly, the MAP DNA dataset in FE significantly present MS risk due to MAP as 5.53 OR (95%-CI [3.54; 8.66], p-value< 0.0001) while, RE showed 5.27 OR (95%-CI [3.22; 8.60], p = 0.0017), with an I2-value = 0.0% (95%-CI [0.0%; 84.7%]; p-value = 0.71). Eggers' test, on the other hand, found publication bias in anti-MAP antibodies data (intercept = 1.61, 95% CI: 0.45 - 2.77, t = 2.72, p = 0.021), but not in MAP DNA dataset (intercept = -5.57, 95% CI: -20.44 - 9.29, t = -0.74, p = 0.54). The robustness of the meta-analyses was demonstrated by all sensitivity analyses. In addition, there is no evidence of p-hacking observed (right-skewness test (PFull < 0.001, PHalf <0.001; statistical power ≥ 94% (95%-CI: 72.5%-99%)). In conclusion, the synthesis revealed a strong association between MAP and MS, indicating that MAP is a significant environmental agent that may trigger MS. Thus, early screening of MAP in MS cases may assist in the therapeutic approach to its management/treatment. Therefore, future studies should be tailored towards the role of MAP in the severity of MS phenotypes, as well as address global data gaps and low disease surveillance.

Prevalence of emerging torque teno virus (TTV) in drinking water, natural waters and wastewater networks (DWNWWS): A systematic review and meta-analysis of the viral pollution marker of faecal and anthropocentric contaminations.

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.

Human norovirus contamination in water sources: A systematic review and meta-analysis.

The human norovirus (HNoV), on a global scale, is the prevailing cause of contagious viral gastroenteritis outbreaks, with more than 200 000 deaths annually. This study aimed at assessing specific prevalence of HNoV pollution in different water sources and their roles in the dissemination of HNoV, with a view to refocus water sources and sewage management options for policy making towards public health safety. In this regard, we conducted a systematic review and meta-analysis (SR/MA) of the prevalence of HNoV in water sources. We searched PubMed, Google Scholar, Scopus and Web of Science for studies on HNoV prevalence in water sources without temporal restriction, till January 30, 2021. We conducted a random-effects meta-analysis of the HNoV prevalence and stratified the study by water type, continent, gross national income (GNI) group and genogroup. Further, a mixed-effects meta-regression model was performed for sensitivity analysis. The literature search identified 61 studies on water source-based HNoV (WsHNoV) prevalence. The pooled WsHNoV prevalence was 31.7% (95%CI: 25.1-38.5) but varied according to water sources types; river water showing the highest estimate at 43.5% (95%CI: 33.9-53.4), followed by estuarine water (30.6%, 95%CI: 12.5-52.2), composite water (27.9%, 95%CI: 13.5-44.9), marine water (25.9%, 95%CI: 10.0-45.6), groundwater (19.7%, 95%CI: 9.4-32.3) and lake water (2.2%, 95%CI: 0-25.8). Further, the findings indicated the highest WsHNoV prevalence in Africa as 55.9% (95% CI: 28.2-81.9), followed by Asia (31.6%, 95% CI: 22.3-41.6), Europe (29.8%, 95% CI: 17.9-43.2), North America (27.7%, 95% CI: 11.2-47.6) and South America (27.1%, 95%CI: 0.09-49.4). The WsHNoV prevalence stratified by GNI group was 40.6% (95%CI: 27.9-53.9) in middle-income countries and 28.7% (95%CI: 21.7-36.1) in high-income countries respectively. The prevalence of GI, GII and GI & GII genogroup in natural water was 16.4% (95%CI: 12.0-21.3), 20.6% (95%CI: 15.7-25.8) and 12.8% (95%CI: 6.9-20.6) respectively. Evidently, prevalence of the HNoV genogroup in water sources mirrors the pattern of HNoV gastroenteritis and GII genogroup dominance worldwide. In conclusion, public health efforts against waterborne diseases should prioritize water resource/sewage management options and policies towards ardent water sources pollution prevention.