Advancement of membrane separation technology for organic pollutant removal.

In the face of growing global freshwater scarcity, the imperative to recycle and reuse water becomes increasingly apparent across industrial, agricultural, and domestic sectors. Eliminating a range of organic pollutants in wastewater, from pesticides to industrial byproducts, presents a formidable challenge. Among the potential solutions, membrane technologies emerge as promising contenders for treating diverse organic contaminants from industrial, agricultural, and household origins. This paper explores cutting-edge membrane-based approaches, including reverse osmosis, nanofiltration, ultrafiltration, microfiltration, gas separation membranes, and pervaporation. Each technology's efficacy in removing distinct organic pollutants while producing purified water is scrutinized. This review delves into membrane fouling, discussing its influencing factors and preventative strategies. It sheds light on the merits, limitations, and prospects of these various membrane techniques, contributing to the advancement of wastewater treatment. It advocates for future research in membrane technology with a focus on fouling control and the development of energy-efficient devices. Interdisciplinary collaboration among researchers, engineers, policymakers, and industry players is vital for shaping water purification innovation. Ongoing research and collaboration position us to fulfill the promise of accessible, clean water for all.

Application of Skimmed-Milk Flocculation Method for Wastewater Surveillance of COVID-19 in Kathmandu, Nepal.

Wastewater surveillance (WS) has been used globally as a complementary tool to monitor the spread of coronavirus disease 2019 (COVID-19) throughout the pandemic. However, a concern about the appropriateness of WS in low- and middle-income countries (LMICs) exists due to low sewer coverage and expensive viral concentration methods. In this study, influent wastewater samples (n = 63) collected from two wastewater treatment plants (WWTPs) of the Kathmandu Valley between March 2021 and February 2022 were concentrated using the economical skimmed-milk flocculation method (SMFM). The presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was tested by qPCR using assays that target the nucleocapsid (N) and envelope (E) genes. Overall, 84% (53/63) of the total samples were positive for SARS-CoV-2 according to at least one of the tested assays, with concentrations ranging from 3.5 to 8.3 log10 gene copies/L, indicating the effectiveness of the SMFM. No correlation was observed between the total number of COVID-19 cases and SARS-CoV-2 RNA concentrations in wastewater collected from the two WWTPs (p > 0.05). This finding cautions the prediction of future COVID-19 waves and the estimation of the number of COVID-19 cases based on wastewater concentration in settings with low sewer coverage by WWTPs. Future studies on WS in LMICs are recommended to be conducted by downscaling to sewer drainage, targeting a limited number of houses. Overall, this study supports the notion that SMFM can be an excellent economical virus-concentrating method for WS of COVID-19 in LMICs.

Application of wastewater-based epidemiology for monitoring COVID-19 in hospital and housing wastewaters.

An alternative and complementary diagnostic method of surveillance is provided by wastewater-based surveillance (WBS), particularly in low-income nations like Nepal with scant wastewater treatment facilities and clinical testing infrastructure. In this study, a total of 146 water samples collected from two hospitals (n = 63) and three housing wastewaters (n = 83) from the Kathmandu Valley over the period of March 2021-Febraury 2022 were investigated for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using quantitative reverse transcription TaqMan PCR assays targeting the N and E genes. Of the total, 67 % (98/146) samples were positive for SARS-CoV-2 RNA either by using N- or E-gene assay, with concentrations ranging from 3.6 to 9.1 log10 copies/L. There was a significant difference found between positive ratio (Chi-square test, p < 0.05) and concentration (t-test, p = 0.009) of SARS-CoV-2 RNA detected from hospital wastewater and housing waters. Wastewater data are correlated with COVID-19 active cases, indicating significance in specific areas like the Hospital (APFH) (p < 0.05). According to the application of a bivariate linear regression model (p < 0.05), the concentrations of N gene may be used to predict the COVID-19 cases in the APFH. Remarkably, SARS-CoV-2 RNA was detected prior to, during, and following clinical case surges, implying that wastewater surveillance could serve as an early warning system for public health decisions. The significance of WBS in tracking and managing pandemics is emphasized by this study, especially in resource-constrained settings.

Developing wastewater-based surveillance schemes for multiple pathogens: The WastPan project in Finland.

Wastewater comprises multiple pathogens and offers a potential for wastewater-based surveillance (WBS) to track the prevalence of communicable diseases. The Finnish WastPan project aimed to establish wastewater-based pandemic preparedness for multiple pathogens (viruses, bacteria, parasites, fungi), including antimicrobial resistance (AMR). This article outlines WastPan's experiences in this project, including the criteria for target selection, sampling locations, frequency, analysis methods, and results communication. Target selection relied on epidemiological and microbiological evidence and practical feasibility. Within the WastPan framework, wastewater samples were collected between 2021 and 2023 from 10 wastewater treatment plants (WWTPs) covering 40 % of Finland's population. WWTP selection was validated for reported cases of Extended Spectrum Beta-lactamase-producing bacterial pathogens (Escherichia coli and Klebsiella pneumoniae) from the National Infectious Disease Register. The workflow included 24-h composite influent samples, with one fraction for culture-based analysis (bacteria and fungi) and the rest of the sample was reserved for molecular analysis (viruses, bacteria, antibiotic resistance genes, and parasites). The reproducibility of the monitoring workflow was assessed for SARS-CoV-2 through inter-laboratory comparisons using the N2 and N1 assays. Identical protocols were applied to same-day samples, yielding similar positivity trends in the two laboratories, but the N2 assay achieved a significantly higher detection rate (Laboratory 1: 91.5 %; Laboratory 2: 87.4 %) than the N1 assay (76.6 %) monitored only in Laboratory 2 (McNemar, p < 0.001 Lab 1, = 0.006 Lab 2). This result indicates that the selection of monitoring primers and assays may impact monitoring sensitivity in WBS. Overall, the current study recommends that the selection of sampling frequencies and population coverage of the monitoring should be based on pathogen-specific epidemiological characteristics. For example, pathogens that are stable over time may need less frequent annual sampling, while those that are occurring across regions may require reduced sample coverage. Here, WastPan successfully piloted WBS for monitoring multiple pathogens, highlighting the significance of one-litre community composite wastewater samples for assessing community health. The infrastructure established for COVID-19 WBS is valuable for monitoring various pathogens. The prioritization of the monitoring targets optimizes resource utilization. In the future legislative support in target selection, coverage determination, and sustained funding for WBS is recomended.

Antibiotic resistance monitoring in wastewater in the Nordic countries: A systematic review.

The Nordic countries (Denmark, Finland, Iceland, Norway, and Sweden) have effectively kept lower antibiotic-resistant bacterial (ARB) pathogen rates than many other countries. However, in recent years, these five countries have encountered a rise in ARB cases and challenges in treating infections due to the growing prevalence of ARB pathogens. Wastewater-based surveillance (WBS) is a valuable supplement to clinical methods for ARB surveillance, but there is a lack of comprehensive understanding of WBS application for ARB in the Nordic countries. This review aims to compile the latest state-of-the-art developments in WBS for ARB monitoring in the Nordic countries and compare them with clinical surveillance practices. After reviewing 1480 papers from the primary search, 54 were found relevant, and 15 additional WBS-related papers were included. Among 69 studies analyzed, 42 dedicated clinical epidemiology, while 27 focused on wastewater monitoring. The PRISMA review of the literature revealed that Nordic countries focus on four major WBS objectives of ARB: assessing ARB in the human population, identifying ARB evading wastewater treatment, quantifying removal rates, and evaluating potential ARB evolution during the treatment process. In both clinical and wastewater contexts, the most studied targets were pathogens producing carbapenemase and extended-spectrum beta-lactamase (ESBL), primarily Escherichia coli and Klebsiella spp. However, vancomycin-resistant Enterococcus (VRE) and methicillin-resistant Staphylococcus aureus (MRSA) have received more attention in clinical epidemiology than in wastewater studies, probably due to their lower detection rates in wastewater. Clinical surveillance has mostly used culturing, antibiotic susceptibility testing, and genotyping, but WBS employed PCR-based and metagenomics alongside culture-based techniques. Imported cases resulting from international travel and hospitalization abroad appear to have frequently contributed to the rise in ARB pathogen cases in these countries. The many similarities between the Nordic countries (e.g., knowledge exchange practices, antibiotic usage patterns, and the current ARB landscape) could facilitate collaborative efforts in developing and implementing WBS for ARB in population-level screening.

Structured Ethical Review for Wastewater-Based Testing in Support of Public Health.

Wastewater-based testing (WBT) for SARS-CoV-2 has rapidly expanded over the past three years due to its ability to provide a comprehensive measurement of disease prevalence independent of clinical testing. The development and simultaneous application of WBT measured biomarkers for research activities and for the pursuit of public health goals, both areas with well-established ethical frameworks. Currently, WBT practitioners do not employ a standardized ethical review process, introducing the potential for adverse outcomes for WBT professionals and community members. To address this deficiency, an interdisciplinary workshop developed a framework for a structured ethical review of WBT. The workshop employed a consensus approach to create this framework as a set of 11 questions derived from primarily public health guidance. This study retrospectively applied these questions to SARS-CoV-2 monitoring programs covering the emergent phase of the pandemic (3/2020-2/2022 (n = 53)). Of note, 43% of answers highlight a lack of reported information to assess. Therefore, a systematic framework would at a minimum structure the communication of ethical considerations for applications of WBT. Consistent application of an ethical review will also assist in developing a practice of updating approaches and techniques to reflect the concerns held by both those practicing and those being monitored by WBT supported programs.

Wastewater-based epidemiology of Campylobacter spp.: A systematic review and meta-analysis of influent, effluent, and removal of wastewater treatment plants.

Campylobacter spp. is one of the four leading causes of diarrhoeal diseases worldwide, which are generally mild but can be fatal in children, the elderly, and immunosuppressed persons. The existing disease surveillance for Campylobacter infections is usually based on untimely clinical reports. Wastewater surveillance or wastewater-based epidemiology (WBE) has been developed for the early warning of disease outbreaks and the detection of the emerging new variants of human pathogens, especially after the global pandemic of COVID-19. However, the WBE monitoring of Campylobacter infections in communities is rare due to a few large data gaps. This study is a meta-analysis and systematic review of the prevalence of Campylobacter spp. in various wastewater samples, primarily the influent of wastewater treatment plants. The results showed that the overall prevalence of Campylobacter spp. was 53.26 % in influent wastewater and 52.97 % in all types of wastewater samples. The mean concentration in the influent was 3.31 ± 0.39 log10 gene copies or most probable number (MPN) per 100 mL. The detection method combining culture and PCR yielded the highest positive rate of 90.86 %, while RT-qPCR and qPCR were the two most frequently used quantification methods. In addition, the Campylobacter concentration in influent wastewater showed a seasonal fluctuation, with the highest concentration in the autumn at 3.46 ± 0.41 log10 gene copies or MPN per 100 mL. Based on the isolates of all positive samples, Campylobacter jejuni (62.34 %) was identified as the most prevalent species in wastewater, followed by Campylobacter coli (30.85 %) and Campylobacter lari (4.4 %). These findings provided significant data to further develop and optimize the wastewater surveillance of Campylobacter spp. infections. In addition, large data gaps were found in the decay of Campylobacter spp. in wastewater, indicating insufficient research on the persistence of Campylobacter spp. in wastewater.

Response of wastewater-based epidemiology predictor for the second wave of COVID-19 in Ahmedabad, India: A long-term data Perspective.

In this work, we present an eight-month longitudinal study of wastewater-based epidemiology (WBE) in Ahmedabad, India, where wastewater surveillance was introduced in September 2020 after the successful containment of the first wave of COVID-19 to predict the resurge of the infection during the second wave of the pandemic. The study aims to elucidate the weekly resolution of the SARS-CoV-2 RNA data for eight months in wastewater samples to predict the COVID-19 situation and identify hotspots in Ahmedabad. A total of 287 samples were analyzed for SARS-CoV-2 RNA using RT-PCR, and Spearman's rank correlation was applied to depict the early warning potential of WBE. During September 2020 to April 2021, the increasing number of positive wastewater influent samples correlated with the growing number of confirmed clinical cases. It also showed clear evidence of early detection of the second wave of COVID-19 in Ahmedabad (March 2021). 258 out of a total 287 samples were detected positive with at least two out of three SARS-CoV-2 genes (N, ORF- 1 ab, and S). Monthly variation represented a significant decline in all three gene copies in October compared to September 2020, followed by an abrupt increase in November 2020. A similar increment in the gene copies was observed in March and April 2021, which would be an indicator of the second wave of COVID-19. A lead time of 1-2 weeks was observed in the change of gene concentrations compared with clinically confirmed cases. Measured wastewater ORF- 1 ab gene copies ranged from 6.1 x 102 (October 2020) to 1.4 x 104 (November 2020) copies/mL, and wastewater gene levels typically lead to confirmed cases by one to two weeks. The study highlights the value of WBE as a monitoring tool to predict waves within a pandemic, identify local disease hotspots within a city, and guide rapid management interventions.

Structured Ethical Review for Wastewater-Based Testing.

Wastewater-based testing (WBT) for SARS-CoV-2 has rapidly expanded over the past three years due to its ability to provide a comprehensive measurement of disease prevalence independent of clinical testing. The development and simultaneous application of the field blurred the boundary between measuring biomarkers for research activities and for pursuit of public health goals, both areas with well-established ethical frameworks. Currently, WBT practitioners do not employ a standardized ethical review process (or associated data management safeguards), introducing the potential for adverse outcomes for WBT professionals and community members. To address this deficiency, an interdisciplinary group developed a framework for a structured ethical review of WBT. The workshop employed a consensus approach to create this framework as a set of 11-questions derived from primarily public health guidance because of the common exemption of wastewater samples to human subject research considerations. This study retrospectively applied the set of questions to peer- reviewed published reports on SARS-CoV-2 monitoring campaigns covering the emergent phase of the pandemic from March 2020 to February 2022 (n=53). Overall, 43% of the responses to the questions were unable to be assessed because of lack of reported information. It is therefore hypothesized that a systematic framework would at a minimum improve the communication of key ethical considerations for the application of WBT. Consistent application of a standardized ethical review will also assist in developing an engaged practice of critically applying and updating approaches and techniques to reflect the concerns held by both those practicing and being monitored by WBT supported campaigns. Synopsis: Development of a structured ethical review facilitates retrospective analysis of published studies and drafted scenarios in the context of wastewater-based testing.

Unveiling indicator, enteric, and respiratory viruses in aircraft lavatory wastewater using adsorption-extraction and Nanotrap® Microbiome A Particles workflows.

The effective detection of viruses in aircraft wastewater is crucial to establish surveillance programs for monitoring virus spread via aircraft passengers. This study aimed to compare the performance of two virus concentration workflows, adsorption-extraction (AE) and Nanotrap® Microbiome A Particles (NMAP), in detecting the prevalence and concentrations of 15 endogenous viruses including ssDNA, dsDNA, ssRNA in 24 aircraft lavatory wastewater samples. The viruses tested included two indicator viruses, four enteric viruses, and nine respiratory viruses. The results showed that cross-assembly phage (crAssphage), human polyomavirus (HPyV), rhinovirus A (RhV A), and rhinovirus B (RhV B) were detected in all wastewater samples using both workflows. However, enterovirus (EV), human norovirus GII (HNoV GII), human adenovirus (HAdV), bocavirus (BoV), parechovirus (PeV), epstein-barr virus (EBV). Influenza A virus (IAV), and respiratory syncytial virus B (RsV B) were infrequently detected by both workflows, and hepatitis A virus (HAV), influenza B virus (IBV), and respiratory syncytial virus B (RsV A) were not detected in any samples. The NMAP workflow had greater detection rates of RNA viruses (EV, PeV, and RsV B) than the AE workflow, while the AE workflow had greater detection rates of DNA viruses (HAdV, BoV, and EBV) than the NMAP workflow. The concentration of each virus was also analyzed, and the results showed that crAssphage had the highest mean concentration (6.76 log10 GC/12.5 mL) followed by HPyV (5.46 log10 GC/12.5 mL using the AE workflow, while the mean concentrations of enteric and respiratory viruses ranged from 2.48 to 3.63 log10 GC/12.5 mL. Using the NMAP workflow, the mean concentration of crAssphage was 5.18 log10 GC/12.5 mL and the mean concentration of HPyV was 4.20 log10 GC/12.5 mL, while mean concentrations of enteric and respiratory viruses ranged from 2.55 to 3.74 log10 GC/12.5 mL. Significantly higher (p < 0.05) mean concentrations of crAssphage and HPyV were observed when employing the AE workflow in comparison to the NMAP workflow. Conversely, the NMAP workflow yielded significantly greater (p < 0.05) concentrations of RhV A, and RhV B compared to the AE workflow. The findings of this study can aid in the selection of an appropriate concentration workflow for virus surveillance studies and contribute to the development of efficient virus detection methods.

A comparative analysis employing a gene- and genome-centric metagenomic approach reveals changes in composition, function, and activity in waterworks with different treatment processes and source water in Finland.

The emergence and development of next-generation sequencing technologies (NGS) has made the analysis of the water microbiome in drinking water distribution systems (DWDSs) more accessible and opened new perspectives in microbial ecology studies. The current study focused on the characterization of the water microbiome employing a gene- and genome-centric metagenomic approach to five waterworks in Finland with different raw water sources, treatment methods, and disinfectant. The microbial communities exhibit a distribution pattern of a few dominant taxa and a large representation of low-abundance bacterial species. Changes in the community structure may correspond to the presence or absence and type of disinfectant residual which indicates that these conditions exert selective pressure on the microbial community. The Archaea domain represented a small fraction (up to 2.5%) and seemed to be effectively controlled by the disinfection of water. Their role particularly in non-disinfected DWDS may be more important than previously considered. In general, non-disinfected DWDSs harbor higher microbial richness and maintaining disinfectant residual is significantly important for ensuring low microbial numbers and diversity. Metagenomic binning recovered 139 (138 bacterial and 1 archaeal) metagenome-assembled genomes (MAGs) that had a >50% completeness and <10% contamination consisting of 20 class representatives in 12 phyla. The presence and occurrence of nitrite-oxidizing bacteria (NOB)-like microorganisms have significant implications for nitrogen biotransformation in drinking water systems. The metabolic and functional complexity of the microbiome is evident in DWDSs ecosystems. A comparative analysis found a set of differentially abundant taxonomic groups and functional traits in the active community. The broader set of transcribed genes may indicate an active and diverse community regardless of the treatment methods applied to water. The results indicate a highly dynamic and diverse microbial community and confirm that every DWDS is unique, and the community reflects the selection pressures exerted at the community structure, but also at the levels of functional properties and metabolic potential.

Phenotypic and genotypic characteristics of beta-lactamase dominant with CARBA, AmpC, and ESBL-producing bacteria in municipal wastewater influent in Helsinki, Finland.

OBJECTIVES: Analysing samples of municipal wastewater influent (before treatment) can help to map the status of antibiotic-resistant bacteria (ARB) at the population level in sewershed communities and may also help in predicting the public health risks of ARB in surface water because of the outfall of wastewater. In this study, we investigated the bacterial isolates carrying beta-lactamase genes in wastewater and compared their genotypic and phenotypic characteristics. METHODS: A total of 399 bacterial isolates grown on CHROMagarESBL (n = 207) and CHROMagarKPC (n = 192) from composite wastewater influent samples (n = 7) from the Viikinmäki wastewater treatment plant (Helsinki) were subcultured, nucleic acid was extracted, and the prevalence of different beta-lactamase genes was screened with multiplex polymerase chain reaction (PCR). All PCR-positive isolates were identified with MALDI-TOF. RESULTS: A total of 32.6% of isolates (130 of 399) were PCR positive for at least one resistance gene, and 13% of these positive isolates out of 130 had at least three resistance genes. Among the 22 detected genes, blaGES group was the most prevalent, at 25.8% (n = 198; many isolates carried multiple genes), followed by blaMOX (13.1%) and blaTEM (10.1%) as most frequently detected. Furthermore, out of 18 different bacterial species/genera detected as carrying beta-lactamase genes, A. hydrophila/caviae (28.5%), Enterobacter spp. (16.9%), and E. coli (14.6%) were the most prevalent. Enterobacter spp., Aeromonas spp., and K. cryocescens potentially carried AmpC genes, and E. coli carried ESBL genes. CONCLUSION: We recorded a huge variety of beta-lactamases (blaAmpC, blaESBL, and blaCARBA) genes in many potential pathogens that probably originated from both enteric and environmental sources.

Correlation of Dengue and Meteorological Factors in Bangladesh: A Public Health Concern.

Dengue virus (DENV) is an enveloped, single-stranded RNA virus, a member of the Flaviviridae family (which causes Dengue fever), and an arthropod-transmitted human viral infection. Bangladesh is well known for having some of Asia's most vulnerable Dengue outbreaks, with climate change, its location, and it's dense population serving as the main contributors. For speculation about DENV outbreak characteristics, it is crucial to determine how meteorological factors correlate with the number of cases. This study used five time series models to observe the trend and forecast Dengue cases. Current data-based research has also applied four statistical models to test the relationship between Dengue-positive cases and meteorological parameters. Datasets were used from NASA for meteorological parameters, and daily DENV cases were obtained from the Directorate General of Health Service (DGHS) open-access websites. During the study period, the mean of DENV cases was 882.26 ± 3993.18, ranging between a minimum of 0 to a maximum of 52,636 daily confirmed cases. The Spearman's rank correlation coefficient between climatic variables and Dengue incidence indicated that no substantial relationship exists between daily Dengue cases and wind speed, temperature, and surface pressure (Spearman's rho; r = -0.007, p > 0.05; r = 0.085, p > 0.05; and r = -0.086, p > 0.05, respectively). Still, a significant relationship exists between daily Dengue cases and dew point, relative humidity, and rainfall (r = 0.158, p < 0.05; r = 0.175, p < 0.05; and r = 0.138, p < 0.05, respectively). Using the ARIMAX and GA models, the relationship for Dengue cases with wind speed is -666.50 [95% CI: -1711.86 to 378.86] and -953.05 [-2403.46 to 497.36], respectively. A similar negative relation between Dengue cases and wind speed was also determined in the GLM model (IRR = 0.98). Dew point and surface pressure also represented a negative correlation in both ARIMAX and GA models, respectively, but the GLM model showed a positive association. Additionally, temperature and relative humidity showed a positive correlation with Dengue cases (105.71 and 57.39, respectively, in the ARIMAX, 633.86, and 200.03 in the GA model). In contrast, both temperature and relative humidity showed negative relation with Dengue cases in the GLM model. In the Poisson regression model, windspeed has a substantial significant negative connection with Dengue cases in all seasons. Temperature and rainfall are significantly and positively associated with Dengue cases in all seasons. The association between meteorological factors and recent outbreak data is the first study where we are aware of the use of maximum time series models in Bangladesh. Taking comprehensive measures against DENV outbreaks in the future can be possible through these findings, which can help fellow researchers and policymakers.

Antibiotic resistance genes, mobile elements, virulence genes, and phages in cultivated ESBL-producing Escherichia coli of poultry origin in Kwara State, North Central Nigeria.

The paucity of information on the genomic diversity of drug-resistant bacteria in most food-producing animals, including poultry in Nigeria, has led to poor hazard characterization and the lack of critical control points to safeguard public health. Hence, this study used whole genome sequencing (WGS) to assess the presence and the diversity of antibiotic resistance genes, mobile genetic elements, virulence genes, and phages in Extended Spectrum Beta Lactamase producing Escherichia coli (ESBL - E. coli) isolates obtained from poultry via the EURL guideline of 2017 in Ilorin, Nigeria. The prevalence of ESBL - E. coli in poultry was 10.5 % (n = 37/354). The phenotypic antibiotic susceptibility testing showed that all the ESBL- E. coli isolates were multi-drug resistant (MDR). The in-silico analysis of the WGS raw-read data from 11 purposively selected isolates showed that the isolates had a wide array of ARGs that conferred resistance to beta-lactam antibiotics, and 8 other classes of antibiotics (fluoroquinolones, foliate pathway antagonists, aminoglycoside, phenicol, tetracycline, epoxide, macrolides, and rifamycin). All the ARGs were in the bacterial chromosome except in two isolates where plasmid-mediated quinolone resistance (PMQR) was detected. Two isolates carried the gyrAp.S83L mutation which confers resistance to certain fluoroquinolones. The mobilome consisted of several Col-plasmids and the predominant IncF plasmids belonged to the IncF64:A-:B27 sequence type. The virulome consisted of genes that function as adhesins, iron acquisition genes, toxins, and protectins. Intact phages were found in 8 of the 11 isolates and the phageome consisted of representatives of four families of viruses: Myoviridae (62.5 %, n = 5/8), Siphoviridae (37.5 %, n = 3/8), Inoviridae (12.5 %, n = 1), and Podoviridae (12.5 %, n = 1/8). ESBL - E. coli isolates harboured 1-5 intact phages and no ARGs were identified on any of the phages. Although five of the isolates belonged to phylogroup A, the isolates were diverse as they belonged to different serotype and sequence types. Our findings demonstrate the high genomic diversity of ESBL - E. coli of poultry origin in Ilorin, Nigeria. These diverse isolates harbor clinically relevant ARGs, mobile elements, virulence genes, and phages that may have detrimental zoonotic potentials on human health.

Effects of temperature and light exposure on the decay characteristics of fecal indicators, norovirus, and Legionella in mesocosms simulating subarctic river water.

Knowledge of the decay characteristics of health-related microbes in surface waters is important for modeling the transportation of waterborne pathogens and for assessing their public health risks. Although water temperature and light exposure are major factors determining the decay characteristics of enteric microbes in surface waters, such effects have not been well studied in subarctic surface waters. This study comprehensively evaluated the effect of temperature and light on the decay characteristics of health-related microbes [Escherichia coli, enterococci, microbial source tracking markers (GenBac3 & HF183 assays), coliphages (F-specific and somatic), noroviruses GII and Legionella spp.] under simulated subarctic river water conditions. The experiments were conducted in four different laboratory settings (4 °C/dark, 15 °C/dark, 15 °C/light, and 22 °C/light). The T90 values (time required for a 90 % reduction in the population of a target) of all targets were higher under cold and dark (2.6-51.3 days depending upon targets) than under warm and light conditions (0.6-3.5 days). Under 4 °C/dark (simulated winter) water conditions, F-specific coliphages had 27.2 times higher, and coliform bacteria had 3.3 times higher T90 value than under 22 °C/light (simulated summer) water conditions. Bacterial molecular markers also displayed high variation in T90 values, with the greatest difference between 4 °C/dark and 22 °C/light recorded for HF183 DNA (20.6 times) and the lowest difference for EC23S857 RNA (6.6 times). E. coli, intestinal enterococci, and somatic coliphages were relatively more sensitive to light than water temperature, but F-specific coliphages, norovirus, and all bacterial rDNA and rRNA markers were relatively more sensitive to temperature than light exposure. Due to the slow microbial decay in winter under subarctic conditions, the microbial quality of river water might remain low for a long time after a sewage spill. This increased risk associated with fecal pollution during winter may deserve more attention, especially when river waters are used for drinking water production.

A 30-day follow-up study on the prevalence of SARS-COV-2 genetic markers in wastewater from the residence of COVID-19 patient and comparison with clinical positivity.

Wastewater based epidemiology (WBE) is an important tool to fight against COVID-19 as it provides insights into the health status of the targeted population from a small single house to a large municipality in a cost-effective, rapid, and non-invasive way. The implementation of wastewater based surveillance (WBS) could reduce the burden on the public health system, management of pandemics, help to make informed decisions, and protect public health. In this study, a house with COVID-19 patients was targeted for monitoring the prevalence of SARS-CoV-2 genetic markers in wastewater samples (WS) with clinical specimens (CS) for a period of 30 days. RT-qPCR technique was employed to target nonstructural (ORF1ab) and structural-nucleocapsid (N) protein genes of SARS-CoV-2, according to a validated experimental protocol. Physiological, environmental, and biological parameters were also measured following the American Public Health Association (APHA) standard protocols. SARS-CoV-2 viral shedding in wastewater peaked when the highest number of COVID-19 cases were clinically diagnosed. Throughout the study period, 7450 to 23,000 gene copies/1000 mL were detected, where we identified 47 % (57/120) positive samples from WS and 35 % (128/360) from CS. When the COVID-19 patient number was the lowest (2), the highest CT value (39.4; i.e., lowest copy number) was identified from WS. On the other hand, when the COVID-19 patients were the highest (6), the lowest CT value (25.2 i.e., highest copy numbers) was obtained from WS. An advance signal of increased SARS-CoV-2 viral load from the COVID-19 patient was found in WS earlier than in the CS. Using customized primer sets in a traditional PCR approach, we confirmed that all SARS-CoV-2 variants identified in both CS and WS were Delta variants (B.1.617.2). To our knowledge, this is the first follow-up study to determine a temporal relationship between COVID-19 patients and their discharge of SARS-CoV-2 RNA genetic markers in wastewater from a single house including all family members for clinical sampling from a developing country (Bangladesh), where a proper sewage system is lacking. The salient findings of the study indicate that monitoring the genetic markers of the SARS-CoV-2 virus in wastewater could identify COVID-19 cases, which reduces the burden on the public health system during COVID-19 pandemics.

Monkeypox outbreak: Wastewater and environmental surveillance perspective.

Monkeypox disease (MPXD), a viral disease caused by the monkeypox virus (MPXV), is an emerging zoonotic disease endemic in some countries of Central and Western Africa but seldom reported outside the affected region. Since May 2022, MPXD has been reported at least in 74 countries globally, prompting the World Health Organization to declare the MPXD outbreak a Public Health Emergency of International Concern. As of July 24, 2022; 92 % (68/74) of the countries with reported MPXD cases had no historical MPXD case reports. From the One Health perspective, the spread of MPXV in the environment poses a risk not only to humans but also to small mammals and may, ultimately, spread to potent novel host populations. Wastewater-based surveillance (WBS) has been extensively utilized to monitor communicable diseases, particularly during the ongoing COVID-19 pandemic. It helped in monitoring infectious disease caseloads as well as specific viral variants circulating in communities. The detection of MPXV DNA in lesion materials (e.g. skin, vesicle fluid, crusts), skin rashes, and various body fluids, including respiratory and nasal secretions, saliva, urine, feces, and semen of infected individuals, supports the possibility of using WBS as an early proxy for the detection of MPXV infections. WBS of MPXV DNA can be used to monitor MPXV activity/trends in sewerage network areas even before detecting laboratory-confirmed clinical cases within a community. However, several factors affect the detection of MPXV in wastewater including, but not limited to, routes and duration time of virus shedding by infected individuals, infection rates in the relevant affected population, environmental persistence, the processes and analytical sensitivity of the used methods. Further research is needed to identify the key factors that impact the detection of MPXV biomarkers in wastewater and improve the utility of WBS of MPXV as an early warning and monitoring tool for safeguarding human health. In this review, we shortly summarize aspects of the MPXV outbreak relevant to wastewater monitoring and discuss the challenges associated with WBS.

Prevalence of methicillin-resistant Staphylococcus aureus carriage among healthcare workers in South Asia in non-outbreak settings: A systematic review and meta-analysis.

BACKGROUND: This study aimed to estimate the pooled prevalence and sub-group-specific prevalence of Methicillin-resistant Staphylococcus aureus (MRSA) carrier rate among Healthcare Workers (HCWs) in South Asia. METHODOLOGY: We considered prospective and cross-sectional studies published in the English language with participants ≥50 by searching different electronic databases to locate the relevant articles that reported the epidemiology of MRSA. The participants were healthy South Asian nationality HCWs (asymptomatic for any infectious disease) of any age and gender with a definitive diagnosis of MRSA carriage. The result was synthesized for the pooled prevalence of MRSA carriers among HCWs using 95% confidence interval (CI) with DerSimonian and Laird random-effects models. RESULTS: The pooled prevalence of MRSA carriage among HCWs was 9.23% (95%CI; 6.50%, 12.35%) with a range from 0.67% to 36.06%. The prevalence in India, Nepal, Pakistan, Sri Lanka, and Bangladesh was 5.65% (95%CI; 3.65%, 8.03%), 8.83% (95%CI; 6.77%, 11.11%), 17.20% (95%CI; 10.70%, 24.85%), 22.56% (95%CI; 4.93%, 47.83%), and 4.93% (95%CI; 1.88%, 9.20%) respectively. The pooled prevalence of MRSA carriage among nurses and doctors was 8.90% (95%CI; 6.00%, 12.24%) and 6.53% (95%CI; 3.63%, 10.06%) respectively. CONCLUSION: The findings from our study suggests that if the propagation of MRSA continues, then it can lead to a situation of an outbreak. Hence, proper preventive measures are to be adopted to prevent this outbreak.

Effects of fine particulate matter (PM2.5) and meteorological factors on the daily confirmed cases of COVID-19 in Bangkok during 2020-2021, Thailand.

The ongoing global pandemic caused by the SARS-CoV-2 virus, known as COVID-19, has disrupted public health, businesses, and economies worldwide due to its widespread transmission. While previous research has suggested a possible link between environmental factors and increased COVID-19 cases, the evidence regarding this connection remains inconclusive. The purpose of this research is to determine whether or not there is a connection between the presence of fine particulate matter (PM2.5) and meteorological conditions and COVID-19 infection rates in Bangkok, Thailand. The study employs a statistical method called Generalized Additive Model (GAM) to find a positive and non-linear association between RH, AH, and R and the number of verified COVID-19 cases. The impacts of the seasons (especially summer) and rainfall on the trajectory of COVID-19 cases were also highlighted, with an adjusted R-square of 0.852 and a deviance explained of 85.60%, both of which were statistically significant (p < 0.05). The study results assist in preventing the future seasonal spread of COVID-19, and public health authorities may use these findings to make informed decisions and assess their policies.

Association between Global Monkeypox Cases and Meteorological Factors.

The emergence of an outbreak of Monkeypox disease (MPXD) is caused by a contagious zoonotic Monkeypox virus (MPXV) that has spread globally. Yet, there is no study investigating the effect of climatic changes on MPXV transmission. Thus, studies on the changing epidemiology, evolving nature of the virus, and ecological niche are highly paramount. Determination of the role of potential meteorological drivers including temperature, precipitation, relative humidity, dew point, wind speed, and surface pressure is beneficial to understand the MPXD outbreak. This study examines the changes in MPXV cases over time while assessing the meteorological characteristics that could impact these disparities from the onset of the global outbreak. To conduct this data-based research, several well-accepted statistical techniques including Simple Exponential Smoothing (SES), Auto-Regressive Integrated Moving Average (ARIMA), Automatic forecasting time-series model (Prophet), and Autoregressive Integrated Moving Average with Explanatory Variables (ARIMAX) were applied to delineate the correlation of the meteorological factors on global daily Monkeypox cases. Data on MPXV cases including affected countries spanning from 6 May 2022, to 9 November 2022, from global databases and meteorological data were used to evaluate the developed models. According to the ARIMAX model, the results showed that temperature, relative humidity, and surface pressure have a positive impact [(51.56, 95% confidence interval (CI): -274.55 to 377.68), (17.32, 95% CI: -83.71 to 118.35) and (23.42, 95% CI: -9.90 to 56.75), respectively] on MPXV cases. In addition, dew/frost point, precipitation, and wind speed show a significant negative impact on MPXD cases. The Prophet model showed a significant correlation with rising MPXD cases, although the trend predicts peak values while the overall trend increases. This underscores the importance of immediate and appropriate preventive measures (timely preparedness and proactive control strategies) with utmost priority against MPXD including awareness-raising programs, the discovery, and formulation of effective vaccine candidate(s), prophylaxis and therapeutic regimes, and management strategies.