The episodic outbreak of COVID-19 due to SARS-CoV-2 is severely affecting the economy, and the global count of infected patients is increasing. The actual number of patients had been underestimated due to limited facilities for testing as well as asymptomatic nature of the expression of COVID-19 on individual basis. Tragically, for emerging economies with high population density, the situation has been more complex due to insufficient testing facilities for diagnosis of the disease. However, the recent reports about persistent shedding of viral RNA of SARS-CoV-2 in the human feces have created a possibility to track the prevalence and trends of the disease in communities, known as wastewater-based epidemiology (WBE). In this article, we highlight the current limitations and future prospects for WBE to manage pandemics.

Wastewater surveillance for pathogens using the reverse transcription-polymerase chain reaction (RT-PCR) is an effective, resource-efficient tool for gathering additional community-level public health information, including the incidence and/or prevalence and trends of coronavirus disease-19 (COVID-19). Surveillance of SARS-CoV-2 in wastewater may provide an early-warning signal of COVID-19 infections in a community. The capacity of the world’s environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is rapidly increasing. However, there are no standardized protocols nor harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can lead to false-positive and -negative errors in the surveillance of SARS-CoV-2, culminating in recommendations and strategies that can be implemented to identify and mitigate these errors. Recommendations include, stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, amplification inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly during a low incidence of SARS-CoV-2 in wastewater. Corrective and confirmatory actions must be in place for inconclusive and/or potentially significant results (e.g., initial onset or reemergence of COVID-19 in a community). It will also be prudent to perform inter-laboratory comparisons to ensure results are reliable and interpretable for ongoing and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance was demonstrated during this global crisis. In the future, wastewater will play an important role in the surveillance of a range of other communicable diseases.

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.

Introduction Air pollution is a global issue that poses a significant threat to public health. Children, due to their developing physiology, are particularly susceptible to the inhalation of environmental pollutants. Exposure can trigger immune modulation and organ damage, increasing susceptibility to respiratory diseases. Therefore, we aim to examine the association between heavy metal and particulate matter exposure with tuberculosis in children. Methods and analysis As a case–control study, we will include children diagnosed with pulmonary tuberculosis (n=60) and matched healthy controls (n=80) recruited from the same communities in Dhaka, Bangladesh. Exposure data for both cases and controls will be collected by a trained field team conducting home visits. They will administer an exposure questionnaire, measure child anthropometry, collect blood and household dust samples and instal 48-hour air quality monitors. The blood samples will be analysed by inductively coupled plasma mass spectrometry for serum heavy metal concentrations (lead, cadmium, arsenic, mercury and chromium), as a representative marker of exposure, and the presence of inflammatory biomarkers. Descriptive and inferential statistics, including independent samples t-tests, analysis of variance and conditional regression analysis, will be used to quantify heavy metal and particulate matter exposure status in tuberculosis cases compared with healthy controls, while accounting for potential confounders. Dust samples and air quality results will be analysed to understand household sources of heavy metal and particulate matter exposure. To test the study hypothesis, there is a positive association between exposure and tuberculosis diseases, we will also measure the accumulated effect of simultaneous exposures using Bayesian statistical modelling. Ethics and dissemination This study has been approved by International Centre for Diarrhoeal Disease Research, Bangladesh’s Institutional Review Board (PR-22030). The study findings will be disseminated at conferences and published in peer-reviewed journals.