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This study was conducted to evaluate the applicability of crAssphage, pepper mild mottle virus (PMMoV), and tobacco mosaic virus (TMV) as indicators of the reduction of human enteric viruses during wastewater treatment. Thirty-nine samples were collected from three steps at a wastewater treatment plant (raw sewage, secondary-treated sewage, and final effluent) monthly for a 13-month period. In addition to the three indicator viruses, eight human enteric viruses [human adenoviruses, JC and BK polyomaviruses, Aichi virus 1 (AiV-1), enteroviruses, and noroviruses of genogroups I, II, and IV] were tested by quantitative PCR. Indicator viruses were consistently detected in the tested samples, except for a few final effluents for crAssphage and TMV. The mean concentrations of crAssphage were significantly higher than those of most tested viruses. The concentrations of crAssphage in raw sewage were positively correlated with the concentrations of all tested human enteric viruses ( p <0.05), suggesting the applicability of crAssphage as a suitable indicator to estimate the concentrations of human enteric viruses in raw sewage. The reduction ratios of AiV-1 (1.8 ± 0.7 log 10 ) were the lowest among the tested viruses, followed by TMV (2.0 ± 0.3 log 10 ) and PMMoV (2.0 ± 0.4 log 10 ). Our findings suggested that the use of not only AiV-1 and PMMoV but also TMV as indicators of reductions in viral levels can be applicable during wastewater treatment.

Although the coronavirus disease (COVID-19) emergency status is easing, the COVID-19 pandemic continues to affect healthcare systems globally. It is crucial to have a reliable and population-wide prediction tool for estimating COVID-19-induced hospital admissions. We evaluated the feasibility of using wastewater-based epidemiology (WBE) to predict COVID-19-induced weekly new hospitalizations in 159 counties across 45 states in the United States of America (USA), covering a population of nearly 100 million. Using county-level weekly wastewater surveillance data (over 20 months), WBE-based models were established through the random forest algorithm. WBE-based models accurately predicted the county-level weekly new admissions, allowing a preparation window of 1-4 weeks. In real applications, periodically updated WBE-based models showed good accuracy and transferability, with mean absolute error within 4-6 patients/100k population for upcoming weekly new hospitalization numbers. Our study demonstrated the potential of using WBE as an effective method to provide early warnings for healthcare systems. Wastewater-based epidemiology is increasingly used to predict disease occurrence. Here, the authors use SARS-CoV-2 RNA concentrations in wastewater in machine learning models to predict COVID-19 related hospitalisation in the United States.

The free-living amoeba Naegleria fowleri (Nf) inhabits soil and natural waters worldwide: it is thermophilic and thrives at temperatures up to 45 °C and in a multitude of environments. Three deaths in Louisiana were attributed to primary amoebic meningoencephalitis (PAM) caused by Nf infection in 2011 and 2013. Following these incidents, public water systems are now monitored for the presence of Nf in Louisiana. From 2014 to 2018, 29% (27/93) of samples collected showed positive for Nf and 68% (63/93) showed all thermophilic amoeba culture. Ten raw water sources and 17 distribution water systems tested positive. The year 2017 showed the highest number of samples with Nf (n = 10) followed by nine samples in 2015. As climate change increases surface water temperatures, continued testing for Nf prevalence will be an important facet of water monitoring and will need to extend into locations farther north than the current most common range.

As the world continues to cope with the COVID-19 pandemic, emerging evidence indicates that respiratory transmission may not the only pathway in which the virus can be spread. This review paper aims to summarize current knowledge surrounding possible fecal–oral transmission of SARS-CoV-2. It covers recent evidence of proliferation of SARS-CoV-2 in the gastrointestinal tract, as well as presence and persistence of SARS-CoV-2 in water, and suggested future directions. Research indicates that SARS-CoV-2 can actively replicate in the human gastrointestinal system and can subsequently be shed via feces. Several countries have reported SARS-CoV-2 RNA fractions in wastewater systems, and various factors such as temperature and presence of solids have been shown to affect the survival of the virus in water. The detection of RNA does not guarantee infectivity, as current methods such as RT-qPCR are not yet able to distinguish between infectious and non-infectious particles. More research is needed to determine survival time and potential infectivity, as well as to develop more accurate methods for detection and surveillance.

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.

The occurrence of amoeba, Naegleria fowleri, in sediment samples from Lake Pontchartrain in Louisiana was investigated. This amoeba is pathogenic and can cause primary amoebic meningoencephalitis. In this study, quantitative polymerase chain reaction methods were used to test for the prevalence of Naegleria fowleri, HF183, and E. coli. N. fowleri was detected in 51.25% of our sediment samples. Illumina sequencing of sediment samples revealed ten different phyla, with Cyanobacteria being the most predominant at sites that generally presented with the highest median N. fowleri concentrations. N. fowleri was however strongly negatively correlated with HF183 (r = −0.859, p < 0.001). Whenever sediment E. coli concentrations were below 1.54 Log GC/g, there was only a 37.5% chance that N. fowleri would be detected in the same sample. When sediment E. coli concentrations exceeded 2.77 Log GC/g, the chances of detecting N. fowleri in the same sample increased to 90%, potentially suggesting predatory activity by the amoeba. The effect of temperature was observed to be different in relation to observed N. fowleri concentrations and detection rates. Although sediment samples collected during periods of higher temperatures had significantly lower mean N. fowleri concentrations (2.7 Log GC/g) compared to those collected at lower temperatures (3.7 Log GC/g, t(39) = 4.167, p < 0.001), higher N. fowleri detection rates in the overall samples were observed at higher temperatures (>19.1 °C) than at lower temperatures (<19.1 °C).

Prison populations are unlikely to have access to prompt, effective medical care as the general population. Therefore, vaccination and effective surveillance systems have been recommended to mitigate coronavirus disease 2019 (COVID-19) transmission in prison settings. This pilot study aimed to assess the application of wastewater-based epidemiology (WBE) in a prison to act as an early warning tool for COVID-19 transmission. In this study, weekly wastewater samples (n = 21) were collected for 21 weeks from a prison facility in New Orleans, LA, USA, and analyzed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the results were compared with the number of confirmed cases during the same period. SARS-CoV-2 was concentrated using two methods and quantified via RT-qPCR using CDC N1 and N2 assays. Overall, SARS-CoV-2 was detected in eight samples (38%). An equal number of samples tested positive for SARS-CoV-2 using the two concentrating methods, indicating the effectiveness of both methods for building-scale WBE. Despite limited clinical testing in the studied prison facility, instances of SARS-CoV-2 detection in wastewater prior to the diagnosis of COVID-19 depict the potential use of wastewater surveillance in detecting the presence of early and averting outbreaks in asymptomatic COVID-19 patients.

Background Treatment and prevention of wound infection continues to be a challenging issue in clinical settings of Nepal especially in the context of globally growing problem of antimicrobial resistance. Study on opportunistic pathogens and sensitivity to commonly prescribed local antimicrobial agents are cardinal to reduce the disease burden of wound infections. The aim of this study was to determine the prevalence and antimicrobial susceptibility pattern of methicillin resistant Staphylococcus aureus (MRSA) and extended spectrum β-lactamase (ESBL) producing bacteria from wound infections of patients at a tertiary care hospital in Nepal. Methods Pus specimens were processed using standard microbiological procedures. Antimicrobial susceptibility test was performed following the modified Kirby Bauer disc diffusion technique. Clinical information of patients was obtained from preformed questionnaire and hospital record. Results One hundred eighty two pus specimens from wounds of different body parts: leg, hand, backside, abdominal part, foot, breast and chest, head and neck region were collected and analyzed; 113 bacterial isolates were isolated showing the overall bacterial growth rate of 62%, where the highest rate was among patients of ≤10 years age group (82.1%). A higher rate (68.5%) of bacterial isolates were from inpatients ( p  < 0.05). Among 116 bacterial isolates, Staphylococcus aureus was the most predominant bacteria (56.9%) followed by Escherichia coli (8.6%), coagulase negative staphylococci (7.8%), Acinetobacter spp. (5.2%), Klebsiella pneumoniae (5.2%), Pseudomonas aeruginosa (4.3%), Enterococcus spp. (4.3%), Citrobacter freundii (2.6%), Proteus vulgaris (1.6%) and P. mirabilis (0.9%). Both Gram positive (73.3%) and negative (78.8%) isolates showed high frequency of sensitive to gentamycin. Conclusion Among S. aureus isolates , 60.6% were MRSA strains, whereas 40% of K. pneumoniae and 33.3% of C. freundii were ESBL producing bacteria followed by E. coli (25%). It is thus paramount to address the burden of silently and speedily increasing infections caused by drug resistant strains of MRSA and ESBL in Nepal.

Wastewater treatment plants (WWTPs) represent all known types of antibiotic resistance mechanisms and are considered as the critical points for the spread of antibiotic resistance genes (ARGs). The purpose of this study is to investigate the removal of a Class 1 integrase gene (intI1) and a selected set of ARGs (blaTEM, ermF, mecA, and tetA) at two conventional WWTPs by using chlorination in Louisiana, USA. We collected 69 wastewater samples (23 each from influent, secondary effluent, and final effluent) and determined the concentrations of ARGs by using quantitative polymerase chain reaction. All tested ARGs, except for mecA, were detected in 83–96% and 30–65% of influent and final effluent samples, respectively. Although the ARGs underwent approximately 3-log10 reduction, two WWTPs on an average still released 3.3 ± 1.7 log10 copies/mL of total ARGs studied in the effluents. Chlorination was found to be critical in the significant reduction of total ARGs (p < 0.05). Correlation analysis and the ability of intI1 to persist through the treatment processes recommend the use of intI1 as a marker of ARGs in effluents to monitor the spread of antibiotic resistance in effluents. Our study suggests that conventional WWTPs using chlorination do not favor the proliferation of antibiotic resistance bacteria and ARGs during wastewater treatment.

The emergence of new variants of SARS-CoV-2 associated with varying infectivity, pathogenicity, diagnosis, and effectiveness against treatments challenged the overall management of the COVID-19 pandemic. Wastewater surveillance (WWS), i.e., monitoring COVID-19 infections in communities through detecting viruses in wastewater, was applied to track the emergence and spread of SARS-CoV-2 variants globally. However, there is a lack of comprehensive understanding of the use and effectiveness of WWS for new SARS-CoV-2 variants. Here we systematically reviewed published articles reporting monitoring of different SARS-CoV-2 variants in wastewater by following the PRISMA guidelines and provided the current state of the art of this study area. A total of 80 WWS studies were found that reported different monitoring variants of SARS-CoV-2 until November 2022. Most of these studies (66 out of the total 80, 82.5%) were conducted in Europe and North America, i.e., resource-rich countries. There was a high variation in WWS sampling strategy around the world, with composite sampling (50/66 total studies, 76%) as the primary method in resource-rich countries. In contrast, grab sampling was more common (8/14 total studies, 57%) in resource-limited countries. Among detection methods, the reverse transcriptase polymerase chain reaction (RT-PCR)-based sequencing method and quantitative RT-PCR method were commonly used for monitoring SARS-CoV-2 variants in wastewater. Among different variants, the B1.1.7 (Alpha) variant that appeared earlier in the pandemic was the most reported (48/80 total studies), followed by B.1.617.2 (Delta), B.1.351 (Beta), P.1 (Gamma), and others in wastewater. All variants reported in WWS studies followed the same pattern as the clinical reporting within the same timeline, demonstrating that WWS tracked all variants in a timely way when the variants emerged. Thus, wastewater monitoring may be utilized to identify the presence or absence of SARS-CoV-2 and follow the development and transmission of existing and emerging variants. Routine wastewater monitoring is a powerful infectious disease surveillance tool when implemented globally.