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

Monitoring SARS-CoV-2 RNA in wastewater from a shared septic system and sub-sewershed sites to expand COVID-19 disease surveillance

Wastewater-based epidemiology has expanded as a tool for collecting COVID-19 surveillance data, but there is limited information on the feasibility of this form of surveillance within decentralized wastewater systems (e.g., septic systems). This study assessed SARS-CoV-2 RNA concentrations in wastewater samples from a septic system servicing a mobile home park (66 households) and from two pumping stations serving a similarly sized (71 households) and a larger (1,000 households) neighborhood within a nearby sewershed over 35 weeks in 2020. Also, raw wastewater from a hospital in the same sewershed was sampled. The mobile home park samples had the highest detection frequency (39/39 days) and mean concentration of SARS-CoV-2 RNA (2.7 × 107 gene copies/person/day for the N1) among the four sampling sites. N1 gene and N2 gene copies were highly correlated across mobile home park samples (Pearson's r = 0.93, p < 0.0001). In the larger neighborhood, new COVID-19 cases were reported every week during the sampling period; however, we detected SARS-CoV-2 RNA in 12% of the corresponding wastewater samples. The results of this study suggest that sampling from decentralized wastewater infrastructure can be used for continuous monitoring of SARS-CoV-2 infections.

Inadequate sanitation in healthcare facilities: A comprehensive evaluation of toilets in major hospitals in Dhaka, Bangladesh

BACKGROUND

Lack of access to functional and hygienic toilets in healthcare facilities (HCFs) is a significant public health issue in low- and middle-income countries (LMICs), leading to the transmission of infectious diseases. Globally, there is a lack of studies characterising toilet conditions and estimating user-to-toilet ratios in large urban hospitals in LMICs. We conducted a cross-sectional study in 10-government and two-private hospitals to explore the availability, functionality, cleanliness, and user-to-toilet ratio in Dhaka, Bangladesh.

METHODS

From Aug-Dec 2022, we undertook infrastructure assessments of toilets in selected hospitals. We observed all toilets and recorded attributes of intended users, including sex, disability status, patient status (in-patient/out-patient/caregiver) and/or staff (doctor/nurse/cleaner/mixed-gender/shared). Toilet functionality was defined according to criteria used by the WHO/UNICEF Joint-Monitoring Programme in HCFs. Toilet cleanliness was assessed, considering visible feces on any surface, strong fecal odor, presence of flies, sputum, insects, and rodents, and solid waste.

RESULTS

Amongst 2875 toilets, 2459 (86%) were observed. Sixty-eight-percent of government hospital toilets and 92% of private hospital toilets were functional. Only 33% of toilets in government hospitals and 56% in private hospitals were clean. A high user-to-toilet ratio was observed in government hospitals' outpatients service (214:1) compared to inpatients service (17:1). User-to-toilet ratio was also high in private hospitals' outpatients service (94:1) compared to inpatients wards (19:1). Only 3% of toilets had bins for menstrual-pad disposal and <1% of toilets had facilities for disabled people.

CONCLUSION

A high percentage of unclean toilets coupled with high user-to-toilet ratio hinders the achievement of SDG by 2030 and risks poor infection-control. Increasing the number of usable, clean toilets in proportion to users is crucial. The findings suggest an urgent call for attention to ensure basic sanitation facilities in Dhaka's HCFs. The policy makers should allocate resources for adequate toilets, maintenance staff, cleanliness, along with strong leadership of the hospital administrators.

Meta-analysis of the SARS-CoV-2 positivity rate in municipal wastewater

The aim of this study is to conduct a systematic analysis of the SARS-CoV-2 levels in urban sewage and evaluate the associated positivity rates, thereby developing comprehensive insights into the epidemic situation and providing valuable inputs for the development of effective disease prevention and control strategies. The PubMed, Scopus, Embase, China National Knowledge Infrastructure, Wanfang Database, and VIP databases were systematically searched based on the predefined retrieval strategy. The literature published up to February 2023 was meticulously screened according to the predetermined inclusion and exclusion criteria, and the relevant data were extracted for subsequent integration. The quality assessment of the included studies adhered to the rigorous Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement guidelines. The meta-analysis was conducted using Stata 17.0 software. The meta-analysis included a total of 34 studies, encompassing 8429 municipal wastewater samples. A random effects model was employed for the analysis, revealing an overall SARS-CoV-2 positivity rate of 53.7% in the municipal wastewater samples. The subgroup analyses demonstrated significant regional variations in the SARS-CoV-2 positivity rate in municipal wastewater, with Africa exhibiting the highest rate at 62.5% (95% confidence interval [CI] 47.4 ~ 76.0%) and Oceania displaying the lowest at 33.3% (95% CI 22.0 ~ 46.3%). However, the subgroup analyses based on the sampling site, strain prevalence period, and laboratory testing method did not yield any statistically significant differences. The SARS-CoV-2 positivity rate in wastewater is relatively high globally, although it exhibits regional disparities. Regions with larger populations and lower economic levels demonstrate higher viral detection rates in sewage. Different types of wastewater sampling sites can be employed to monitor distinct aspects of the COVID-19 pandemic. Continuous surveillance of SARS-CoV-2 in wastewater plays a pivotal role in complementing clinical data, helping to track outbreak progression across diverse regions.

Modeled and measured SARS-CoV-2 virus in septic tank systems for wastewater surveillance

SARS-CoV-2 wastewater surveillance (WWS) at wastewater treatment plants (WWTPs) can reveal sewered community COVID-19 prevalence. For unsewered areas using septic tank systems (STSs) or holding tanks, how to conduct WWS remains unexplored. Here, two large STSs serving Zuma Beach (Malibu, CA) were studied. Supernatant and sludge SARS-CoV-2 concentrations from the directly-sampled STSs parameterized a dynamic solid-liquid separation, mass balance-based model for estimating the infection rate of users. Pumped septage before hauling and upon WWTP disposal was also sampled and assessed. Most (96%) STS sludge samples contained SARS-CoV-2 N1 and N2 genes, with concentrations exceeding the supernatant and increasing with depth while correlating with total suspended solids (TSS). The trucked septage contained N1 and N2 genes which decayed (coefficients: 0.09-0.29 h-1) but remained detectable. Over approximately 5 months starting in December 2020, modeled COVID-19 prevalence estimations among users ranged from 8 to 18%, mirroring a larger metropolitan area for the first 2 months. The approaches herein can inform public health intervention and augment conventional WWS in that: (1) user infection rates for communal holding tanks are estimable and (2) pumped and hauled septage can be assayed to infer where disease is spreading in unsewered areas.

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.

Exposure of adult zebrafish (Danio rerio) to SARS-CoV-2 at predicted environmentally relevant concentrations: Outspreading warns about ecotoxicological risks to freshwater fish

While the multifaceted social, economic, and public health impacts associated with the COVID-19 pandemic are known, little is known about its effects on non-target aquatic ecosystems and organisms. Thus, we aimed to evaluate the potential ecotoxicity of SARS-CoV-2 lysate protein (SARS.CoV2/SP02.2020.HIAE.Br) in adult zebrafish (Danio rerio) at predicted environmentally relevant concentrations (0.742 and 2.226 pg/L), by 30 days. Although our data did not show locomotor alterations or anxiety-like or/and anxiolytic-like behavior, we noticed that exposure to SARS-CoV-2 negatively affected habituation memory and social aggregation of animals in response to a potential aquatic predator (Geophagus brasiliensis). An increased frequency of erythrocyte nuclear abnormalities was also observed in animals exposed to SARS-CoV-2. Furthermore, our data suggest that such changes were associated with a redox imbalance [↑ROS (reactive oxygen species), ↑H2O2 (hydrogen peroxide), ↓SOD (superoxide dismutase), and ↓CAT (catalase)], cholinesterasic effect [↑AChE (acetylcholinesterase) activity], as well as the induction of an inflammatory immune response [↑NO (nitric oxide), ↑IFN-γ (interferon-gamma), and ↓IL-10 (interleukin-10)]. For some biomarkers, we noticed that the response of the animals to the treatments was not concentration-dependent. However, principal component analysis (PCA) and the "Integrated Biomarker Response" index (IBRv2) indicated a more prominent ecotoxicity of SARS-CoV-2 at 2.226 pg/L. Therefore, our study advances knowledge about the ecotoxicological potential of SARS-CoV-2 and reinforces the presumption that the COVID-19 pandemic has negative implications beyond its economic, social, and public health impacts.

Wastewater early warning system for SARS-CoV-2 outbreaks and variants in a Coruña, Spain

Wastewater-based epidemiology has been widely used as a cost-effective method for tracking the COVID-19 pandemic at the community level. Here we describe COVIDBENS, a wastewater surveillance program running from June 2020 to March 2022 in the wastewater treatment plant of Bens in A Coruña (Spain). The main goal of this work was to provide an effective early warning tool based in wastewater epidemiology to help in decision-making at both the social and public health levels. RT-qPCR procedures and Illumina sequencing were used to weekly monitor the viral load and to detect SARS-CoV-2 mutations in wastewater, respectively. In addition, own statistical models were applied to estimate the real number of infected people and the frequency of each emerging variant circulating in the community, which considerable improved the surveillance strategy. Our analysis detected 6 viral load waves in A Coruña with concentrations between 10³ and 10⁶ SARS-CoV-2 RNA copies/L. Our system was able to anticipate community outbreaks during the pandemic with 8-36 days in advance with respect to clinical reports and, to detect the emergence of new SARS-CoV-2 variants in A Coruña such as Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (B.1.1.529 and BA.2) in wastewater with 42, 30, and 27 days, respectively, before the health system did. Data generated here helped local authorities and health managers to give a faster and more efficient response to the pandemic situation, and also allowed important industrial companies to adapt their production to each situation. The wastewater-based epidemiology program developed in our metropolitan area of A Coruña (Spain) during the SARS-CoV-2 pandemic served as a powerful early warning system combining statistical models with mutations and viral load monitoring in wastewater over time.

SARS-CoV-2 surveillance-based on municipal solid waste leachate in Brazil

Municipal solid waste leachate-based epidemiology is an alternative viral tracking tool that applies fresh truck leachate as an early warning of public health emergencies. This study aimed to investigate the potential of SARS-CoV-2 surveillance based on solid waste fresh truck leachate. Twenty truck leachate samples were ultracentrifugated, nucleic acid extracted, and real-time RT-qPCR SARS-CoV-2 N1/N2 applied. Viral isolation, variant of concern (N1/N2) inference, and whole genome sequencing were also performed. SARS-CoV-2 was detected on 40% (8/20) of samples, with a concentration from 2.89 to 6.96 RNA Log10 100 mL-1. The attempt to isolate SARS-CoV-2 and recover the whole genome was not successful; however, positive samples were characterized as possible pre-variant of concern (pre-VOC), VOC Alpha (B.1.1.7) and variant of interest Zeta (P.2). This approach revealed an alternative tool to infer SARS-CoV-2 in the environment and may help the management of local surveillance, health, and social policies.

SARS-CoV-2 surveillance in medical and industrial wastewater-a global perspective: a narrative review

The novel coronavirus SARS-CoV-2 has spread at an unprecedented rate since late 2019, leading to the global COVID-19 pandemic. During the pandemic, being able to detect SARS-CoV-2 in human populations with high coverage quickly is a huge challenge. As SARS-CoV-2 is excreted in human excreta and thus exposed to the aqueous environment through sewers, the goal is to develop an ideal, non-invasive, cost-effective epidemiological method for detecting SARS-CoV-2. Wastewater surveillance has gained widespread interest and is increasingly being investigated as an effective early warning tool for monitoring the spread and evolution of the virus. This review emphasizes important findings on SARS-CoV-2 wastewater-based epidemiology (WBE) in different continents and techniques used to detect SARS-CoV-2 in wastewater during the period 2020-2022. The results show that WBE is a valuable population-level method for monitoring SARS-CoV-2 and is a valuable early warning alert. It can assist policymakers in formulating relevant policies to avoid the negative impacts of early or delayed action. Such strategy can also help avoid unnecessary wastage of medical resources, rationalize vaccine distribution, assist early detection, and contain large-scale outbreaks.