Wastewater-based epidemiological surveillance to monitor the prevalence of SARS-CoV-2 in developing countries with onsite sanitation facilities

Wastewater surveillance for viral pathogens: A tool for public health

A focus on water quality has intensified globally, considering its critical role in sustaining life and ecosystems. Wastewater, reflecting societal development, profoundly impacts public health. Wastewater-based epidemiology (WBE) has emerged as a surveillance tool for detecting outbreaks early, monitoring infectious disease trends, and providing real-time insights, particularly in vulnerable communities. WBE aids in tracking pathogens, including viruses, in sewage, offering a comprehensive understanding of community health and lifestyle habits. With the rise in global COVID-19 cases, WBE has gained prominence, aiding in monitoring SARS-CoV-2 levels worldwide. Despite advancements in water treatment, poorly treated wastewater discharge remains a threat, amplifying the spread of water-, sanitation-, and hygiene (WaSH)-related diseases. WBE, serving as complementary surveillance, is pivotal for monitoring community-level viral infections. However, there is untapped potential for WBE to expand its role in public health surveillance. This review emphasizes the importance of WBE in understanding the link between viral surveillance in wastewater and public health, highlighting the need for its further integration into public health management.

Population infection estimation from wastewater surveillance for SARS-CoV-2 in Nagpur, India during the second pandemic wave

Wastewater-based epidemiology (WBE) has emerged as an effective environmental surveillance tool for predicting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease outbreaks in high-income countries (HICs) with centralized sewage infrastructure. However, few studies have applied WBE alongside epidemic disease modelling to estimate the prevalence of SARS-CoV-2 in low-resource settings. This study aimed to explore the feasibility of collecting untreated wastewater samples from rural and urban catchment areas of Nagpur district, to detect and quantify SARS-CoV-2 using real-time qPCR, to compare geographic differences in viral loads, and to integrate the wastewater data into a modified Susceptible-Exposed-Infectious-Confirmed Positives-Recovered (SEIPR) model. Of the 983 wastewater samples analyzed for SARS-CoV-2 RNA, we detected significantly higher sample positivity rates, 43.7% (95% confidence interval (CI) 40.1, 47.4) and 30.4% (95% CI 24.66, 36.66), and higher viral loads for the urban compared with rural samples, respectively. The Basic reproductive number, R0, positively correlated with population density and negatively correlated with humidity, a proxy for rainfall and dilution of waste in the sewers. The SEIPR model estimated the rate of unreported coronavirus disease 2019 (COVID-19) cases at the start of the wave as 13.97 [95% CI (10.17, 17.0)] times that of confirmed cases, representing a material difference in cases and healthcare resource burden. Wastewater surveillance might prove to be a more reliable way to prepare for surges in COVID-19 cases during future waves for authorities.

A scoping review of global SARS-CoV-2 wastewater-based epidemiology in light of COVID-19 pandemic

Recently, wastewater-based epidemiology (WBE) research has experienced a strong impetus during the Coronavirus disease 2019 (COVID-19) pandemic. However, a few technical issues related to surveillance strategies, such as standardized procedures ranging from sampling to testing protocols, need to be resolved in preparation for future infectious disease outbreaks. This review highlights the study characteristics, potential use of WBE and overview of methods, as well as methods utilized to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) including its variant in wastewater. A literature search was performed electronically in PubMed and Scopus according to PRISMA guidelines for relevant peer-reviewed articles published between January 2020 and March 2022. The search identified 588 articles, out of which 221 fulfilled the necessary criteria and are discussed in this review. Most global WBE studies were conducted in North America (n = 75, 34 %), followed by Europe (n = 68, 30.8 %), and Asia (n = 43, 19.5 %). The review also showed that most of the application of WBE observed were to correlate SARS-CoV-2 ribonucleic acid (RNA) trends in sewage with epidemiological data (n = 90, 40.7 %). The techniques that were often used globally for sample collection, concentration, preferred matrix recovery control and various sample types were also discussed. Overall, this review provided a framework for researchers specializing in WBE to apply strategic approaches to their research questions in achieving better functional insights. In addition, areas that needed more in-depth analysis, data collection, and ideas for new initiatives were identified.

Vibrio cholerae and Salmonella Typhi culture-based wastewater or non-sewered sanitation surveillance in a resource-limited region

BACKGROUND

In resource-limited regions, relying on individual clinical results to monitor community diseases is sometimes not possible. Establishing wastewater and non-sewered sanitation surveillance systems can offer opportunities to improve community health.

OBJECTIVE

We provide our experience of establishing a wastewater and non-sewered sanitation surveillance laboratory in Malawi, a resource-limited region, for Vibrio cholerae and Salmonella serotype Typhi.

METHODS

Three locations (inclusive of 8 discrete sample collection sites in total) in the Blantyre District were studied for nine weeks, from September 6 to November 1, 2022. Grab samples were collected weekly. We piloted locally available culture-based medical diagnostic methods for V. cholerae and S. Typhi in wastewater, followed by confirmation analysis of the isolates using reverse transcription polymerase chain reaction (RT-PCR).

RESULTS

Bacterial counts ranged from up to 106 colony-forming units/mL for V. cholerae and up to 107 colony-forming units/mL for S. Typhi. RT-PCR of the isolates showed that the available culture-based medical diagnostic methods were successful in detecting V. cholerae but were less accurate for S. Typhi in wastewater.

IMPACT STATEMENT

This experience serves as a catalyst for the development and validation of alternative wastewater surveillance analytical methods that are not dependent solely on RT-PCR. In this field trial conducted in Africa, new data-driven approaches were developed to promote early-level wastewater research and expand analysis options in resource-limited settings. Although culture-based methods are labor-intensive and have some limitations, we suggest initially leveraging the overlap with the locally available medical testing capacity for V. cholerae, whereas S. Typhi with RT-PCR may still be required. Wastewater analysis may be acceptable for V. cholerae and S. Typhi, which have a high degree of clinical case underreporting, fecal shedding, short incubation periods, and clear outbreak trends, predominantly in low- and middle-income countries.

Temporal assessment of SARS-CoV-2 detection in wastewater and its epidemiological implications in COVID-19 case dynamics

This research evaluated the relationship between daily new Coronavirus Disease 2019 (COVID-19) cases and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) concentrations in wastewater, followed by effects of differential SARS-CoV-2 shedding loads across various COVID-19 outbreaks. Linear regression analyses were utilized to examine the lead time of the SARS-CoV-2 signal in wastewater relative to new COVID-19 clinical cases. During the Delta wave, no lead time was evident, highlighting limited predictive capability of wastewater monitoring during this phase. However, significant lead times were observed during the Omicron wave, potentially attributed to testing capacity overload and subsequent case reporting delays or changes in shedding patterns. During the Post-Omicron wave (Febuary 23 to May 19, 2022), no lead time was discernible, whereas following the lifting of the COVID-19 state of emergency (May 30, 2022 to May 30, 2023), the correlation coefficient increased and demonstrated the potential of wastewater surveillance as an early warning system. Subsequently, we explored the virus shedding in wastewater through feces, operationalized as the ratio of SARS-CoV-2 concentrations to daily new COVID-19 cases. This ratio varied significantly across the Delta, Omicron, other variants and post-state-emergency phases, with the Kruskal-Wallis H test confirming a significant difference in medians across these stages (P < 0.0001). Despite its promise, wastewater surveillance of COVID-19 disease prevalence presents several challenges, including virus shedding variability, data interpretation complexity, the impact of environmental factors on viral degradation, and the lack of standardized testing procedures. Overall, our findings offer insights into the correlation between COVID-19 cases and wastewater viral concentrations, potential variation in SARS-CoV-2 shedding in wastewater across different pandemic phases, and underscore the promise and limitations of wastewater surveillance as an early warning system for disease prevalence trends.

Scenario-based assessment of emergency management of urban infectious disease outbreaks

Infectious diseases pose a severe threat to human health and are accompanied by significant economic losses. Studies of urban outbreaks of infectious diseases are diverse. However, previous studies have neglected the identification of critical events and the evaluation of scenario-based modeling of urban infectious disease outbreak emergency management mechanisms. In this paper, we aim to conduct an empirical analysis and scenario extrapolation using a questionnaire survey of 18 experts, based on the CIA-ISM method and scenario theory, to identify the key factors influencing urban infectious disease outbreaks. Subsequently, we evaluate the effectiveness of urban infectious disease outbreak emergency management mechanisms. Finally, we compare and verify the actual situation of COVID-19 in China, drawing the following conclusions and recommendations. (1) The scenario-based urban infectious disease emergency management model can effectively replicate the development of urban infectious diseases. (2) The establishment of an emergency command center and the isolation and observation of individuals exposed to infectious diseases are crucial factors in the emergency management of urban outbreaks of infectious disease.

Early Detection of Novel SARS-CoV-2 Variants from Urban and Rural Wastewater through Genome Sequencing and Machine Learning

Genome sequencing from wastewater has emerged as an accurate and cost-effective tool for identifying SARS-CoV-2 variants. However, existing methods for analyzing wastewater sequencing data are not designed to detect novel variants that have not been characterized in humans. Here, we present an unsupervised learning approach that clusters co-varying and time-evolving mutation patterns leading to the identification of SARS-CoV-2 variants. To build our model, we sequenced 3,659 wastewater samples collected over a span of more than two years from urban and rural locations in Southern Nevada. We then developed a multivariate independent component analysis (ICA)-based pipeline to transform mutation frequencies into independent sources with co-varying and time-evolving patterns and compared variant predictions to >5,000 SARS-CoV-2 clinical genomes isolated from Nevadans. Using the source patterns as data-driven reference "barcodes", we demonstrated the model's accuracy by successfully detecting the Delta variant in late 2021, Omicron variants in 2022, and emerging recombinant XBB variants in 2023. Our approach revealed the spatial and temporal dynamics of variants in both urban and rural regions; achieved earlier detection of most variants compared to other computational tools; and uncovered unique co-varying mutation patterns not associated with any known variant. The multivariate nature of our pipeline boosts statistical power and can support accurate and early detection of SARS-CoV-2 variants. This feature offers a unique opportunity for novel variant and pathogen detection, even in the absence of clinical testing.

Assessment of sewer connectivity in the United States and its implications for equity in wastewater-based epidemiology

Wastewater-based epidemiology is a promising public health tool that can yield a more representative view of the population than case reporting. However, only about 80% of the U.S. population is connected to public sewers, and the characteristics of populations missed by wastewater-based epidemiology are unclear. To address this gap, we used publicly available datasets to assess sewer connectivity in the U.S. by location, demographic groups, and economic groups. Data from the U.S. Census' American Housing Survey revealed that sewer connectivity was lower than average when the head of household was American Indian and Alaskan Native, White, non-Hispanic, older, and for larger households and those with higher income, but smaller geographic scales revealed local variations from this national connectivity pattern. For example, data from the U.S. Environmental Protection Agency showed that sewer connectivity was positively correlated with income in Minnesota, Florida, and California. Data from the U.S. Census' American Community Survey and Environmental Protection Agency also revealed geographic areas with low sewer connectivity, such as Alaska, the Navajo Nation, Minnesota, Michigan, and Florida. However, with the exception of the U.S. Census data, there were inconsistencies across datasets. Using mathematical modeling to assess the impact of wastewater sampling inequities on inferences about epidemic trajectory at a local scale, we found that in some situations, even weak connections between communities may allow wastewater monitoring in one community to serve as a reliable proxy for an interacting community with no wastewater monitoring, when cases are widespread. A systematic, rigorous assessment of sewer connectivity will be important for ensuring an equitable and informed implementation of wastewater-based epidemiology as a public health monitoring system.

Evaluating acute gastroenteritis-causing pathogen reduction in wastewater and the applicability of river water for wastewater-based epidemiology in the Kathmandu Valley, Nepal

Rapid urbanization and population growth without the implementation of proper waste management are capable of contaminating water sources, which can lead to acute gastroenteritis. This study examined the detection and reduction of five gastroenteritis-causing enteropathogens, Salmonella, Campylobacter coli, Campylobacter jejuni, Clostridium perfringens, and genogroup IV norovirus, and one respiratory pathogen, influenza A virus, in two municipal wastewater treatment plants (WWTP) using an oxidation ditch system (WWTP A; n = 20) and a stabilization pond system (WWTP B; n = 18) in the Kathmandu Valley, Nepal, collected between August 2017 and August 2019. All enteropathogens were detected in wastewater via quantitative PCR. The concentrations of the pathogens ranged from 5.7 to 7.9 log10 copies/L in WWTP A and from 4.9 to 8.1 log10 copies/L in WWTP B. The log10 reduction values of the pathogens ranged from 0.3 to 1.0 in WWTP A and from -0.1 to 0.2 in WWTP B. The association between the pathogen concentrations and the number of clinical cases in the corresponding week could not be evaluated; however, the consistent detection of pathogens in the wastewater despite low number of case reports suggested the use of wastewater-based epidemiology (WBE) for early warning of acute gastroenteritis (AGE) in the Kathmandu Valley. The pathogens were also detected in river water at approximately 7.0 log10 copies/L and exhibited no significant difference in concentration compared to wastewater, suggesting the applicability of river water for WBE of AGE. Insufficient treatment of all pathogens in the wastewater was observed, suggesting the need for full rehabilitation of the treatment plants. However, the influent may be utilized for early detection of AGE-causing pathogens in the city, whereas the river water may serve as an alternative in areas without connection to the WWTPs.

Global and genetic diversity of SARS-CoV-2 in wastewater

The analysis of SARS-CoV-2 in wastewater has enabled us to better understand the spread and evolution of the virus worldwide. To deepen our understanding of its epidemiological and genomic characteristics, we analyzed 10,147 SARS-CoV-2 sequences from 5 continents and 21 countries that were deposited in the GISAID database up until January 31, 2023. Our results revealed over 100 independent lineages of the virus circulating in water samples from March 2020 to January 2023, including variants of interest and concern. We observed four clearly defined periods of global distribution of these variants over time, with one variant being replaced by another. Interestingly, we found that SARS-CoV-2 water-borne sequences from different countries had a close phylogenetic relationship. Additionally, 40 SARS-CoV-2 water-borne sequences from Europe and the USA did not show any phylogenetic relationship with SARS-CoV-2 human sequences. We also identified a significant number of non-synonymous mutations, some of which were detected in previously reported cryptic lineages. Among the countries analyzed, France and the USA showed the highest degree of sequence diversity, while Austria reported the highest number of genomes (6,296). Our study provides valuable information about the epidemiological and genomic diversity of SARS-CoV-2 in wastewater, which can be employed to support public health initiatives and preparedness.

Fate-and-transport modeling of SARS-CoV-2 for rural wastewater-based epidemiology application benefit

Wastewater-based epidemiology (WBE) for the detection of agents of concern such as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been prevalent in literature since 2020. The majority of reported research focuses on large urban centers with few references to rural communities. In this research the EPA-Storm Water Management Model (EPA-SWMM) software was used to describe a small sewershed and identify the effects of temperature, temperature-affected decay rate, flow rate, flush time, fecal shedding rate, and historical infection rates during the spread of the Omicron variant of the SARS-CoV-2 virus within the sewershed. Due to the sewershed's relative isolation from the rest of the city, its wastewater quality behavior is similar to a rural sewershed. The model was used to assess city wastewater sampling campaigns to best appropriate field and or lab equipment when sampling wastewater. An important aspect of the assessment was the comparison of SARS-CoV-2 quantification methods with specifically between a traditional microbiological lab (practical quantitation limit, PQL, 1 GC/mL) versus what can be known from a field method (PQL 10 GC/mL). Understanding these monitoring choices will help rural communities make decisions on how to best implement the collection and testing for WBE agents of concern. An important outcome of this work is the knowledge that it is possible to simulate a WBE agent of concern with reasonable precision, if uncertainties are incorporated into model sensitivity. These ideas could form the basis for future mixed monitoring-modeling studies that will enhance its application and therefore adoption of WBE techniques in communities of many sizes and financial means.

Urine biomarkers for Alzheimer's disease: A new opportunity for wastewater-based epidemiology?

While Alzheimer's disease (AD) diagnosis, management, and care have become priorities for healthcare providers and researcher's worldwide due to rapid population aging, epidemiologic surveillance efforts are currently limited by costly, invasive diagnostic procedures, particularly in low to middle income countries (LMIC). In recent years, wastewater-based epidemiology (WBE) has emerged as a promising tool for public health assessment through detection and quantification of specific biomarkers in wastewater, but applications for non-infectious diseases such as AD remain limited. This early review seeks to summarize AD-related biomarkers and urine and other peripheral biofluids and discuss their potential integration to WBE platforms to guide the first prospective efforts in the field. Promising results have been reported in clinical settings, indicating the potential of amyloid β, tau, neural thread protein, long non-coding RNAs, oxidative stress markers and other dysregulated metabolites for AD diagnosis, but questions regarding their concentration and stability in wastewater and the correlation between clinical levels and sewage circulation must be addressed in future studies before comprehensive WBE systems can be developed.

Monitoring and evaluation practices and operational research during public health emergencies in southeast Asia region (2012-2022) - a systematic review

This systematic review aimed to explore the monitoring and evaluation (M&E) and operational research (OR) practices during public health emergencies (PHE) in the southeast Asian region (SEAR) over the last decade. We searched electronic databases and grey literature sources for studies published between 2012 and 2022. The studies written in English were included, and a narrative synthesis was undertaken. A total of 29 studies were included in this review. Among these 25 studies documented M&E and four studies documented OR practices. The majority of the studies were from India and Bangladesh, with no evidence found from Sri Lanka, Bhutan, Myanmar, and Timor-Leste. M&E of surveillance programs were identified among which PHE due to COVID-19 was most prevalent. M&E was conducted in response to COVID-19, cholera, Nipah, Ebola, Candida auris, and hepatitis A. OR practice was minimal and reported from India and Indonesia. India conducted OR on COVID-19 and malaria, whereas Indonesia focused on COVID-19 and influenza. While most SEAR countries have mechanisms for conducting M&E, there is a noticeable limitation in OR practices. There is a compelling need to develop a standard framework for M&E. Additionally, enhancing private sector engagement is crucial for strengthening preparedness against PHE. Furthermore, there is a necessity to increase awareness about the importance of conducting M&E and OR during PHE.

Combating antibiotic resistance using wastewater surveillance: Significance, applications, challenges, and future directions

The global increase of antibiotic resistance (AR) and resistant infections call for effective surveillance methods for understanding and mitigating (re)-emerging public health risks. Wastewater surveillance (WS) of antibiotic resistance is an emerging, but currently under-utilized decision-support tool in public health systems. Recent years have witnessed an increase in evidence linking antibiotic resistance in wastewaters to that of the community. To date, very few comprehensive reviews exist on the application of WS to understand AR and resistant infections in population. Current and emerging AR detection methods, and their merits and limitations are discussed. Wastewater surveillance has several merits relative to individual testing, including; (1) low per capita testing cost, (2) high spatial coverage, (3) low requirement for diagnostic equipment, and (4) detection of health threats ahead of real outbreaks. The applications of WS as an early warning system and decision support tool to understand and mitigate AR are discussed. Wastewater surveillance could be a tool of choice in low-income settings lacking resources and diagnostic facilities for individual testing. To demonstrate the utility of WS, empirical evidence from field case studies is presented. However, constraints still exist, including; (1) lack of standardized protocols, (2) the clinical utility and sensitivity of WS-based data, (3) uncertainties in relating WS data to pathogenic and virulent bacteria, and (4) whether or not AR in stools and ultimately wastewater represent the complete human resistome. Finally, further prospects are presented, include knowledge gaps on; (1) development of low-cost biosensors for AR, (2) development of WS protocols (sampling, processing, interpretation), (3) further pilot scale studies to understand the opportunities and limits of WS, and (4) development of computer-based analytical tools to facilitate rapid data collection, visualization and interpretation. Therefore, the present paper discusses the principles, opportunities, and constraints of wastewater surveillance applications to understand AR and safeguard public health.

Characterization of lignin and hemicellulose degrading bacteria isolated from cow rumen and forest soil: Unveiling a novel enzymatic model for rice straw deconstruction

Application of greener pretreatment technology using robust ligninolytic bacteria for short duration to deconstruct rice straw and enhance bioethanol production is currently lacking. The objective of this study is to characterize three bacterial strains isolated from the milieux of cow rumen and forest soil and explore their capabilities of breaking down lignocellulose - an essential process in bioethanol production. Using biochemical and genomic analyses these strains were identified as Bacillus sp. HSTU-bmb18, Bacillus sp. HSTU-bmb19, and Citrobacter sp. HSTU-bmb20. Genomic analysis of the strains unveiled validated model hemicellulases, multicopper oxidases, and pectate lyases. These enzymes exhibited interactions with distinct lignocellulose substrates, further affirmed by their stability in molecular dynamic simulations. A comprehensive expression of ligninolytic pathways, including β-ketoadipate, phenyl acetate, and benzoate, was observed within the HSTU-bmb20 genome. The strains secreted approximately 75-82 U/mL of cellulase, xylase, pectinase, and lignin peroxidase. FT-IR analysis of the bacterial treated rice straw fibers revealed that the intensity of lignin-related peaks decreased, while cellulose-related peaks sharpened. The values of crystallinity index for the untreated control and the treated rice straw with either HSTU-bmb18, or HSTU-bmb19, or HSTU-bmb20 were recorded to be 34.48, 28.49, 29.36, 31.75, respectively, which are much higher than that of 13.53 noted for those treated with the bacterial consortium. The ratio of fermentable cellulose in rice straw increased by 1.25-, 1.79-, 1.93- and 2.17-fold following treatments with HSTU-bmb18, HSTU-bmb20, HSTU-bmb19, and a mixed consortium of these three strains, respectively. These aggregative results suggested a novel model for rice straw deconstruction utilizing hydrolytic enzymes of the consortium, revealing superior efficacy compared to individual strains, and advancing cost-effective, affordable, and sustainable green technology.

Monkeypox virus (MPXV): A Brief account of global spread, epidemiology, virology, clinical features, pathogenesis, and therapeutic interventions

The largest monkeypox virus (MPXV) outbreak of the 21st century occurred in 2022, which caused epidemics in many countries. According to WHO, physical contact with infected persons, contaminated surfaces, or affected animals might be a source of this virus transmission. A febrile sickness including few symptoms found in MPX disease. Skin rash, lesions, fever, headache, fatigue, and muscle aches symptoms were observed commonly for this disease. Animal and in vitro, studies have shown that the antiviral medications cidofovir and brincidofovir are effective against MPXV. The first-generation vaccinia virus vaccine was developed in 1960, and it helped to protect against MPXV with its side effects. A second-generation vaccination with limitations was launched in 2000. However, the CDC advised vaccinations for risk groups in endemic countries, including positive patients and hospital employees. The JYNNEOS vaccine, administered in 2 doses, also provides protection from MPX. This article presents concisely the most recent findings regarding epidemiology, genomic transmission, signs and symptoms, pathogenesis, diagnosis, and therapeutic interventions for MPXV, which may be helpful to researchers and practitioners. WHO declared that MPX was no longer a global health emergency due to its declining case rate, and a number of countries have reported new incidences. Further research-based investigations must be carried out based on the 2022 outbreak.

Surveillance of multidrug-resistant tuberculosis in sub-Saharan Africa through wastewater-based epidemiology

The spread of multidrug-resistant tuberculosis (MDR-TB) is a serious public health issue, particularly in developing nations. The current methods of monitoring drug-resistant TB (DR-TB) using clinical diagnoses and hospital records are insufficient due to limited healthcare access and underreporting. This study proposes using Wastewater-Based Epidemiology (WBE) to monitor DR-TB in six African countries (Ghana, Nigeria, Kenya, Uganda, Cameroon, and South Africa) and examines the impact of treated wastewater on the spread of TB drug-resistant genes in the environment. Using droplet-digital polymerase chain reaction (ddPCR), the study evaluated untreated and treated wastewater samples in selected African countries for TB surveillance. There was a statistically significant difference in concentrations of genes conferring resistance to TB drugs in wastewater samples from the selected countries (p-value<0.05); South African samples exhibited the highest concentrations of 4.3(±2,77), 4.8(±2.96), 4.4(±3,10) and 4.7(±3,39) log copies/ml for genes conferring resistance to first-line TB drugs (katG, rpoB, embB and pncA respectively) in untreated wastewater. This may be attributed to the higher prevalence of TB/MDR-TB in SA compared to other African countries. Interestingly, genes conferring resistance to second-line TB drugs such as delamanid (ddn gene) and bedaquiline (atpE gene) were detected in relatively high concentrations (4.8(±3,67 and 3.2(±2,31 log copies/ml for ddn and atpE respectively) in countries, such as Cameroon, where these drugs are not part of the MDR-TB treatment regimens, perhaps due to migration or the unapproved use of these drugs in the country. The gene encoding resistance to streptomycin (rrs gene) was abundant in all countries, perhaps due to the common use of this antibiotic for infections other than TB. These results highlight the need for additional surveillance and monitoring, such as WBE, to gather data at a community level. Combining WBE with the One Health strategy and current TB surveillance systems can help prevent the spread of DR-TB in populations.

One Health and Global Health View of Antimicrobial Susceptibility through the "Eye" of Aeromonas: Systematic Review and Meta-Analysis

Antimicrobial resistance (AMR) is one of the most pressing public health concerns; therefore, it is imperative to advance our understanding of the factors influencing AMR from Global and One Health perspectives. To address this, Aeromonas populations were identified using 16S rRNA gene libraries among human, agriculture, aquaculture, drinking water, surface water, and wastewater samples, supporting its use as indicator bacteria to study AMR. A systematic review and meta-analysis was then performed from Global and One Health perspectives, including data from 221 articles describing 15 891 isolates from 57 countries. The interconnectedness of different environments was evident as minimal differences were identified between sectors among 21 different antimicrobials. However, resistance to critically important antibiotics (aztreonam and cefepime) was significantly higher among wastewater populations compared with clinical isolates. Additionally, isolates from untreated wastewater typically exhibited increased AMR compared with those from treated wastewater. Furthermore, aquaculture was associated with increased AMR to ciprofloxacin and tetracycline compared with wild-caught seafood. Using the World Health Organization AWaRe classifications, countries with lower consumption of "Access" compared to "Watch" drugs from 2000 to 2015 demonstrated higher AMR levels. The current analysis revealed negative correlations between AMR and anthropogenic factors, such as environmental performance indices and socioeconomic standing. Environmental health and sanitation were two of the environmental factors most strongly correlated with AMR. The current analysis highlights the negative impacts of "Watch" drug overconsumption, anthropogenic activity, absence of wastewater infrastructure, and aquaculture on AMR, thus stressing the need for proper infrastructure and global regulations to combat this growing problem.

M. AH, Fernandez S, Huang AT, Vatanaprasan P, Jay DJ, Saethang T, Luk-in S, Storer RJ, Ounjai P, Devanga Ragupathi NK, Kanthawee P, Sano D, Furukawa T, Sei K, Leelahavanichkul A, Kanjanabuch T, Hirankarn N, Higgins PG, Kicic A, Singer AC, Chatsuwan T, Trowsdale S, Abe S, McLellan AD, Ishikawa H. COVID-19 monitoring with sparse sampling of sewered and non-sewered wastewater in urban and rural communities

Equitable SARS-CoV-2 surveillance in low-resource communities lacking centralized sewers is critical as wastewater-based epidemiology (WBE) progresses. However, large-scale studies on SARS-CoV-2 detection in wastewater from low-and middle-income countries is limited because of economic and technical reasons. In this study, wastewater samples were collected twice a month from 186 urban and rural subdistricts in nine provinces of Thailand mostly having decentralized and non-sewered sanitation infrastructure and analyzed for SARS-CoV-2 RNA variants using allele-specific RT-qPCR. Wastewater SARS-CoV-2 RNA concentration was used to estimate the real-time incidence and time-varying effective reproduction number (Re). Results showed an increase in SARS-CoV-2 RNA concentrations in wastewater from urban and rural areas 14-20 days earlier than infected individuals were officially reported. It also showed that community/food markets were "hot spots" for infected people. This approach offers an opportunity for early detection of transmission surges, allowing preparedness and potentially mitigating significant outbreaks at both spatial and temporal scales.

Monitoring SARS-CoV-2 variants in wastewater of Dhaka City, Bangladesh: approach to complement public health surveillance systems

BACKGROUND

Wastewater-based epidemiological surveillance has been considered a powerful tool for early detection and monitoring of the dynamics of SARS-CoV-2 and its lineages circulating in a community. This study is aimed to investigate the complexity of SARS-CoV-2 infection dynamics in Dhaka city by examining its genetic variants in wastewater. Also, the study seeks to determine a connection between the SARS-CoV-2 variations detected in clinical testing and those found in wastewater samples.

RESULTS

Out of 504 samples tested in RT-qPCR, 185 (36.7%) tested positive for SARS-CoV-2 viral RNA. The median log10 concentration of SARS-CoV-2 N gene copies/Liter of wastewater (gc/L) was 5.2, and the median log10 concentration of ORF1ab was 4.9. To further reveal the genetic diversity of SARS-CoV-2, ten samples with ORF1ab real-time RT-PCR cycle threshold (Ct) values ranging from 28.78 to 32.13 were subjected to whole genome sequencing using nanopore technology. According to clade classification, sequences from wastewater samples were grouped into 4 clades: 20A, 20B, 21A, 21J, and the Pango lineage, B.1, B.1.1, B.1.1.25, and B.1.617.2, with coverage ranging from 94.2 to 99.8%. Of them, 70% belonged to clade 20B, followed by 10% to clade 20A, 21A, and 21J. Lineage B.1.1.25 was predominant in Bangladesh and phylogenetically related to the sequences from India, the USA, Canada, the UK, and Italy. The Delta variant (B.1.617.2) was first identified in clinical samples at the beginning of May 2021. In contrast, we found that it was circulating in the community and was detected in wastewater in September 2020.

CONCLUSION

Environmental surveillance is useful for monitoring temporal and spatial trends of existing and emerging infectious diseases and supports evidence-based public health measures. The findings of this study supported the use of wastewater-based epidemiology and provided the baseline data for the dynamics of SARS-CoV-2 variants in the wastewater environment in Dhaka, Bangladesh.

Risk of psychological distress by decrease in economic activity, gender, and age due to COVID-19: A multinational study

Introduction

Coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2-virus. COVID-19 has officially been declared as the latest in the list of pandemics by WHO at the start of 2020. This study investigates the associations among decrease in economic activity, gender, age, and psychological distress during the COVID-19 pandemic considering the economic status and education level of countries using multinational surveys.

Methods

Online self-report questionnaires were administered in 15 countries which were spontaneously participate to 14,243 respondents in August 2020. Prevalence of decrease in economic activity and psychological distress was stratified by age, gender, education level, and Human Development Index (HDI). With 7,090 of female (49.8%), mean age 40.67, 5,734 (12.75%) lost their job and 5,734 (40.26%) suffered from psychological distress.

Results

Associations among psychological distress and economic status, age, and gender was assessed using multivariate logistic regression, adjusted for country and education as random effects of the mixed model. We then measured the associations between HDI and age using multivariate logistic regression. Women had a higher prevalence of psychological distress than men with 1.067 Odds ratio, and younger age was significantly associated with decrease in economic activity for 0.998 for age increasing. Moreover, countries with lower HDI showed a higher prevalence of decrease in economic activity, especially at lower education levels.

Discussion

Psychological distress due to COVID-19 revealed a significant association with decrease in economic activity, women, and younger age. While the proportion of decrease in economic activity population was different for each country, the degree of association of the individual factors was the same. Our findings are relevant, as women in high HDI countries and low education level in lower HDI countries are considered vulnerable. Policies and guidelines for both financial aid and psychological intervention are recommended.

Dependency of sanitation infrastructure on the discharge of faecal coliform and SARS-CoV-2 viral RNA in wastewater from COVID and non-COVID hospitals in Dhaka, Bangladesh

The detection of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) RNA in wastewater can be used as an indicator of the presence of SARS-CoV-2 infection in specific catchment areas. We conducted a hospital-based study to explore wastewater management in healthcare facilities and analyzed SARS-CoV-2 RNA in the hospital wastewater in Dhaka city during the Coronavirus disease (COVID-19) outbreak between September 2020-January 2021. We selected three COVID-hospitals, two non-COVID-hospitals, and one non-COVID-hospital with COVID wards, conducted spot-checks of the sanitation systems (i.e., toilets, drainage, and septic-tank), and collected 90 untreated wastewater effluent samples (68 from COVID and 22 from non-COVID hospitals). E. coli was detected using a membrane filtration technique and reported as colony forming unit (CFU). SARS-CoV-2 RNA was detected using the iTaq Universal Probes One-Step kit for RT-qPCR amplification of the SARS-CoV-2 ORF1ab and N gene targets and quantified for SARS-CoV-2 genome equivalent copies (GEC) per mL of sample. None of the six hospitals had a primary wastewater treatment facility; two COVID hospitals had functional septic tanks, and the rest of the hospitals had either broken onsite systems or no containment of wastewater. Overall, 100 % of wastewater samples were positive with a high concentration of E. coli (mean = 7.0 log10 CFU/100 mL). Overall, 67 % (60/90) samples were positive for SARS-CoV-2. The highest SARS-CoV-2 concentrations (median: 141 GEC/mL; range: 13-18,214) were detected in wastewater from COVID-hospitals, and in non-COVID-hospitals, the median SARS-CoV-2 concentration was 108 GEC/mL (range: 30-1829). Our results indicate that high concentrations of E. coli and SARS-CoV-2 were discharged through the hospital wastewater (both COVID and non-COVID) without treatment into the ambient water bodies. Although there is no evidence for transmission of SARS-CoV-2 via wastewater, this study highlights the significant risk posed by wastewater from health care facilities in Dhaka for the many other diseases that are spread via faecal oral route. Hospitals in low-income settings could function as sentinel sites to monitor outbreaks through wastewater-based epidemiological surveillance systems. Hospitals should aim to adopt the appropriate wastewater treatment technologies to reduce the discharge of pathogens into the environment and mitigate environmental exposures.

ICT-based solution for efficient fecal sludge management: An experience from Bangladesh

In Bangladesh, people primarily depend on on-site sanitation facilities (OSSF) with an immense challenge in achieving safe sanitation due to unplanned infrastructure development, improper management of fecal sludge, and inadequate monitoring. The commitment of attaining Sustainable Development Goals (SDG) 6.2 (ensuring safe sanitation for all) by 2030 requires immediate attention in the management of fecal sludge for low-middle income countries. This paper presented the findings, challenges, and possible ways forward from a study conducted to provide data for Information and Communication Technology (ICT)-based fecal sludge management (FSM) at a municipality in the northwest of Bangladesh. A total of 18,808 households and 407 institutions in Saidpur municipality, a non-sewered town in Nilphamari district, were studied to understand the type of containment structures and on-ground desludging practices. The study showed around 10% of containments were connected to the drains illegally, 95% of the people in Saidpur practiced unsafe disposal, and 7% still practiced open defecation. To identify these malpractices, the study also implemented an ICT-based sustainable solution through a web application that enabled the local administrator to have a global look at the sanitation scenario of the municipality. The dashboard was developed to create a total sanitation monitoring system, identify defaulters, allow target-based safe managed sanitation service strategies, and ensure sustainability in FSM. The study highlighted the accessibility of vacuum truck services projecting through a spatial map and identified methods to empty the septic tanks where Vacutag services are unavailable by engaging local pit emptiers. The innovative approach of fecal sludge management will help not only to improve the existing sanitation practices but also raise community awareness to ensure sustainable sanitation system. Altogether, the web system will work as a medium to manage the faecal sludge for the existing co-compost plant where the faeces is converted into organic soil conditioner, creating prospects for a green business mechanism.

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.

Evaluation of intra- and inter-lab variability in quantifying SARS-CoV-2 in a state-wide wastewater monitoring network

In December 2019, SARS-CoV-2, the virus that causes coronavirus disease 2019, was first reported and subsequently triggered a global pandemic. Wastewater monitoring, a strategy for quantifying viral gene concentrations from wastewater influents within a community, has served as an early warning and management tool for the spread of SARS-CoV-2 in a community. Ohio built a collaborative statewide wastewater monitoring network that is supported by eight labs (university, government, and commercial laboratories) with unique sample processing workflows. Consequently, we sought to characterize the variability in wastewater monitoring results for network labs. Across seven trials between October 2020 and November 2021, eight participating labs successfully quantified two SARS-CoV-2 RNA targets and human fecal indicator virus targets in wastewater sample aliquots with reproducible results, although recovery efficiencies of spiked surrogates ranged from 3 to 75%. When SARS-CoV-2 gene fragment concentrations were adjusted for recovery efficiency and flow, the proportion of variance between laboratories was minimized, serving as the best model to account for between-lab variance. Another adjustment factor (alone and in different combinations with the above factors) considered to account for sample and measurement variability includes fecal marker normalization. Genetic quantification variability can be attributed to many factors, including the methods, individual samples, and water quality parameters. In addition, statistically significant correlations were observed between SARS-CoV-2 RNA and COVID-19 case numbers, supporting the notion that wastewater surveillance continues to serve as an effective monitoring tool. This study serves as a real-time example of multi-laboratory collaboration for public health preparedness for infectious diseases.

Variant-specific deleterious mutations in the SARS-CoV-2 genome reveal immune responses and potentials for prophylactic vaccine development

Introduction: Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has had a disastrous effect worldwide during the previous three years due to widespread infections with SARS-CoV-2 and its emerging variations. More than 674 million confirmed cases and over 6.7 million deaths have been attributed to successive waves of SARS-CoV-2 infections as of 29th January 2023. Similar to other RNA viruses, SARS-CoV-2 is more susceptible to genetic evolution and spontaneous mutations over time, resulting in the continual emergence of variants with distinct characteristics. Spontaneous mutations of SARS-CoV-2 variants increase its transmissibility, virulence, and disease severity and diminish the efficacy of therapeutics and vaccines, resulting in vaccine-breakthrough infections and re-infection, leading to high mortality and morbidity rates. Materials and methods: In this study, we evaluated 10,531 whole genome sequences of all reported variants globally through a computational approach to assess the spread and emergence of the mutations in the SARS-CoV-2 genome. The available data sources of NextCladeCLI 2.3.0 (https://clades.nextstrain.org/) and NextStrain (https://nextstrain.org/) were searched for tracking SARS-CoV-2 mutations, analysed using the PROVEAN, Polyphen-2, and Predict SNP mutational analysis tools and validated by Machine Learning models. Result: Compared to the Wuhan-Hu-1 reference strain NC 045512.2, genome-wide annotations showed 16,954 mutations in the SARS-CoV-2 genome. We determined that the Omicron variant had 6,307 mutations (retrieved sequence:1947), including 67.8% unique mutations, more than any other variant evaluated in this study. The spike protein of the Omicron variant harboured 876 mutations, including 443 deleterious mutations. Among these deleterious mutations, 187 were common and 256 were unique non-synonymous mutations. In contrast, after analysing 1,884 sequences of the Delta variant, we discovered 4,468 mutations, of which 66% were unique, and not previously reported in other variants. Mutations affecting spike proteins are mostly found in RBD regions for Omicron, whereas most of the Delta variant mutations drawn to focus on amino acid regions ranging from 911 to 924 in the context of epitope prediction (B cell & T cell) and mutational stability impact analysis protruding that Omicron is more transmissible. Discussion: The pathogenesis of the Omicron variant could be prevented if the deleterious and persistent unique immunosuppressive mutations can be targeted for vaccination or small-molecule inhibitor designing. Thus, our findings will help researchers monitor and track the continuously evolving nature of SARS-CoV-2 strains, the associated genetic variants, and their implications for developing effective control and prophylaxis strategies.

Occurrence and transport of SARS-CoV-2 in wastewater streams and its detection and remediation by chemical-biological methods

This paper explains the transmission of SARS-CoV and influences of several environmental factors in the transmission process. The article highlighted several methods of collection, sampling and monitoring/estimation as well as surveillance tool for detecting SARS-CoV in wastewater streams. In this context, WBE (Wastewater based epidemiology) is found to be the most effective surveillance tool. Several methods of genomic sequencing are discussed in the paper, which are applied in WBE, like qPCR-based wastewater testing, metagenomics-based analysis, next generation sequencing etc. Additionally, several types of biosensors (colorimetric biosensor, mobile phone-based biosensors, and nanomaterials-based biosensors) showed promising results in sensing SARS-CoV in wastewater. Further, this review paper outlined the gaps in assessing the factors responsible for transmission and challenges in detection and monitoring along with the remediation and disinfection methods of this virus in wastewater. Various methods of disinfection of SARS-CoV-2 in wastewater are discussed (primary, secondary, and tertiary phases) and it is found that a suite of disinfection methods can be used for complete disinfection/removal of the virus. Application of ultraviolet light, ozone and chlorine-based disinfectants are also discussed in the context of treatment methods. This study calls for continuous efforts to gather more information about the virus through continuous monitoring and analyses and to address the existing gaps and identification of the most effective tool/ strategy to prevent SARS-CoV-2 transmission. Wastewater surveillance can be very useful in effective surveillance of future pandemics and epidemics caused by viruses, especially after development of new technologies in detecting and disinfecting viral pathogens more effectively.

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.

Mpox, Caused by the MPXV of the Clade IIb Lineage, Goes Global

Mpox is a great public health concern worldwide currently; thus, a global primary epidemiological analysis of mpox and a phylogenetic analysis of currently circulating MPXV strains based on open-source data is necessary. A total of 83,419 confirmed cases with 72 deaths were reported from 7 May to 23 December 2022, representing an ongoing increasing trend. Mpox was largely restricted to being endemic in children in West Africa (WA) before 2022, and it mainly spread from animals to humans. Our analysis highlights that mpox has not only spread across regions within Africa but has also led to most infection events outside Africa. Currently, mpox has been dominated by human-to-human spread in 110 countries, with the majority of cases distributed in the non-endemic regions of Europe and North America. These data indicate that the geographic range, transmission route, vulnerable populations, and clinical manifestations of mpox have changed, which suggests that the niche of mpox has the potential to change. Remarkably, approximately 38,025 suspected mpox cases were recorded in West and Central Africa during 1970-2022, which implied that the epidemiology of mpox in the two regions remained cryptic, suggesting that strengthening the accuracy of molecular diagnosis on this continent is a priority. Moreover, 617 mpox genomes have been obtained from 12 different hosts; these data imply that the high host diversity may contribute to its ongoing circulation and global outbreak. Furthermore, a phylogenetic analysis of 175 MPXV genome sequences from 38 countries (regions) showed that the current global mpox outbreak was caused by multiple sub-clades in the clade IIb lineage. These data suggest that MPXV strains from the clade IIb lineage may play a predominated role in the spread of mpox worldwide, implying that the current mpox outbreak has a single infection source. However, further investigations into the origin of the new global mpox outbreak are necessary. Therefore, our analysis highlights that adjusted timely interventive measures and surveillance programs, especially using cheap and quick strategies such as wastewater monitoring the DNA of MPXV in Africa (WA), are important for uncovering this disease's transmission source and chain, which will help curb its further spread.

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.

Temporal Variation of SARS-CoV-2 Levels in Wastewater from a Meat Processing Plant

Wastewater-based surveillance (WBS) on SARS-CoV-2 has been proved to be an effective approach to estimate the prevalence of COVID-19 in communities and cities. However, its application was overlooked at smaller scale, such as a single facility. Meat processing plants are hotspots for COVID-19 outbreaks due to their unique environment that are favorable for the survival and persistence of SARS-CoV-2. This is the first known WBS study in meat processing plants. The goal was to understand the temporal variation of the SARS-CoV-2 levels in wastewater from a meat processing plant in Canada during a three-month campaign and to find any correlation with clinically confirmed cases in the surrounding city area. Higher SARS-CoV-2 concentrations and detection frequencies were observed in the solid fraction compared to the liquid fraction of the wastewater. The viruses can be preserved in the solid fraction of wastewater for up to 12 days. The wastewater virus level did not correlate to the city-wide COVID-19 cases due to the unmatching scales. WBS on SARS-CoV-2 in meat processing plants can be useful for identifying COVID-19 outbreaks in the facility and serve as an effective alternative when resources for routine individual testing are not available.

A bibliometric study on Marburg virus research with prevention and control strategies

Marburg virus (MARV) is a pathogenic zoonotic RNA virus etiologic for Marburg virus disease (MVD), a severe hemorrhagic fever. This is a rare disease, with a high fatality rate, that spreads via infected blood or body fluids or indirectly via fomites (contaminated objects and substances such as clothed, beds, personal protective equipment, or medical equipments). A few vaccines to protect against MARV are undergoing clinical trials, but there is not yet an approved vaccine against this disease. Eventually, prevention and control guidelines should be adhered to rigorously to alleviate this infection. This bibliometric analysis aimed to harness narrative evaluation, emphasizing the significance of quantitative approaches and delineating the most thought-provoking concerns for researchers using VOSviewer software (Centre for Science and Technology Studies, Leiden University, the Netherlands). “Marburg Virus” OR “MARV” AND “Diseases” search criteria were used for the analysis of articles published between 1962 and 2022. Co-occurrence analysis was carried out, which characterized different thematic clusters. From this analysis, we found that 1688 published articles, and the number of publications increased across that period annually, with a growth rate of 8.78%. It is also conspicuous that the number of publications in the United States reached its acme during this period (i.e., 714 publications, accounting for 42.29% of the total), and the United States Army Medical Research Institute of Infectious Diseases published the most literature (i.e., 146 papers). Our study found that the three pre-eminent authors of Marburg virus papers were “FELDMANN, HEINZ“ of the National Institute of Allergy and Infectious Diseases, United States, “BECKER, STEPHAN” of the Philipps University of Marburg, Germany, and “GEISBERT, THOMAS W” of the University of Texas Medical Branch, United States. In this study we found that “JOURNAL OF VIROLOGY” has published the most pertinent literature, totaling 88 articles, followed by “The journal of Infectious Diseases”, which published 76 relevant papers, and “VIRUSES”, which published 52 corresponding papers. The most cited paper on the Marburg virus was published in Nature Medicine, with 522 total citations and 29 citations/year. Studies of the changing epidemiology and evolving nature of the virus and its ecological niche are required; breakthrough and implementation of the efficacious vaccine candidate(s), prophylaxis and therapeutic alternatives and supervision strategies, unveiling awareness-raising programs, and developing apposite and timely preparedness, prevention, and proactive control strategies are of utmost importance.

Association of household fuel with acute respiratory infection (ARI) under-five years children in Bangladesh

In developing countries, acute respiratory infections (ARIs) cause a significant number of deaths among children. According to Bangladesh Demographic and Health Survey (BDHS), about 25% of the deaths in children under-five years are caused by ARI in Bangladesh every year. Low-income families frequently rely on wood, coal, and animal excrement for cooking. However, it is unclear whether using alternative fuels offers a health benefit over solid fuels. To clear this doubt, we conducted a study to investigate the effects of fuel usage on ARI in children. In this study, we used the latest BDHS 2017-18 survey data collected by the Government of Bangladesh (GoB) and estimated the effects of fuel use on ARI by constructing multivariable logistic regression models. From the analysis, we found that the crude (the only type of fuel in the model) odds ratio (OR) for ARI is 1.69 [95% confidence interval (CI): 1.06-2.71]. This suggests that children in families using contaminated fuels are 69.3% more likely to experience an ARI episode than children in households using clean fuels. After adjusting for cooking fuel, type of roof material, child's age (months), and sex of the child-the effect of solid fuels is similar to the adjusted odds ratio (AOR) for ARI (OR: 1.69, 95% CI: 1.05-2.72). This implies that an ARI occurrence is 69.2% more likely when compared to the effect of clean fuel. This study found a statistically significant association between solid fuel consumption and the occurrence of ARI in children in households. The correlation between indoor air pollution and clinical parameters of ARI requires further investigation. Our findings will also help other researchers and policymakers to take comprehensive actions by considering fuel type as a risk factor as well as taking proper steps to solve this issue.

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.

An opinion on Wastewater-Based Epidemiological Monitoring (WBEM) with Clinical Diagnostic Test (CDT) for detecting high-prevalence areas of community COVID-19 Infections

Wastewater-Based Epidemiological Monitoring (WBEM) is an efficient surveillance tool during the COVID-19 pandemic as it meets all requirements of a complete monitoring system including early warning, tracking the current trend, prevalence of the disease, detection of genetic diversity as well asthe up-surging SARS-CoV-2 new variants with mutations from the wastewater samples. Subsequently, Clinical Diagnostic Test is widely acknowledged as the global gold standard method for disease monitoring, despite several drawbacks such as high diagnosis cost, reporting bias, and the difficulty of tracking asymptomatic patients (silent spreaders of the COVID-19 infection who manifest nosymptoms of the disease). In this current reviewand opinion-based study, we first propose a combined approach) for detecting COVID-19 infection in communities using wastewater and clinical sample testing, which may be feasible and effective as an emerging public health tool for the long-term nationwide surveillance system. The viral concentrations in wastewater samples can be used as indicatorsto monitor ongoing SARS-CoV-2 trends, predict asymptomatic carriers, and detect COVID-19 hotspot areas, while clinical sampleshelp in detecting mostlysymptomaticindividuals for isolating positive cases in communities and validate WBEM protocol for mass vaccination including booster doses for COVID-19.

Anthropogenic Sewage Water Circuit as Vector for SARS-CoV-2 Viral ARN Transport and Public Health Assessment, Monitoring and Forecasting-Sibiu Metropolitan Area (Transylvania/Romania) Study Case

Water is a risk factor for epidemics of waterborne diseases with effects on human health. In 2019, new viral pneumonia cases occurred in China and spread worldwide. The aim of this study was to assess the feasibility and accuracy of a wastewater-based epidemiological (WBE) monitoring tool in a SARS-CoV-2 hot spot (Sibiu City metropolitan area), namely to highlight the correlation between the number of infections on the days of sampling and the amount of viral RNA detected in wastewater. Wastewater samples were collected once a week, and viral RNA was extracted and quantified. In parallel, the daily number of SARS-CoV-2 infections was obtained from the local council. The correlation between the number of infections and viruses detected in sewage was measured by Pearson correlation coefficients. The results show the amount of viral RNA in the wastewater is directly correlated with the number of infections reported in the week up to the sampling day and also the number of infections reported for the sampling day. Moreover, correlation coefficients show the amount of viral RNA in wastewater increases in advance of the increase in reported infection cases. Therefore, WBE can be used as a tool for monitoring virus spread trends in human communities and can help anticipate the trend of this type of viral infection.