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A year since the declaration of the global coronavirus disease 2019 (COVID-19) pandemic, there were over 110 million cases and 2.5 million deaths. Learning from methods to track community spread of other viruses such as poliovirus, environmental virologists and those in the wastewater-based epidemiology (WBE) field quickly adapted their existing methods to detect SARS-CoV-2 RNA in wastewater. Unlike COVID-19 case and mortality data, there was not a global dashboard to track wastewater monitoring of SARS-CoV-2 RNA worldwide. This study provides a 1-year review of the “COVIDPoops19” global dashboard of universities, sites, and countries monitoring SARS-CoV-2 RNA in wastewater. Methods to assemble the dashboard combined standard literature review, Google Form submissions, and daily, social media keyword searches. Over 200 universities, 1400 sites, and 55 countries with 59 dashboards monitored wastewater for SARS-CoV-2 RNA. However, monitoring was primarily in high-income countries (65%) with less access to this valuable tool in low- and middle-income countries (35%). Data were not widely shared publicly or accessible to researchers to further inform public health actions, perform meta-analysis, better coordinate, and determine equitable distribution of monitoring sites. For WBE to be used to its full potential during COVID-19 and beyond, show us the data.

 

Abstract Since the start of the coronavirus disease-2019 (COVID-19) pandemic, there has been interest in using wastewater monitoring as an approach for disease surveillance. A significant uncertainty that would improve the interpretation of wastewater monitoring data is the intensity and timing with which individuals shed RNA from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into wastewater. By combining wastewater and case surveillance data sets from a university campus during a period of heightened surveillance, we inferred that individual shedding of RNA into wastewater peaks on average 6 days (50% uncertainty interval (UI): 6–7; 95% UI: 4–8) following infection, and that wastewater measurements are highly overdispersed [negative binomial dispersion parameter, k = 0.39 (95% credible interval: 0.32–0.48)]. This limits the utility of wastewater surveillance as a leading indicator of secular trends in SARS-CoV-2 transmission during an epidemic, and implies that it could be most useful as an early warning of rising transmission in areas where transmission is low or clinical testing is delayed or of limited capacity. 

Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA has demonstrated useful correlation with both coronavirus disease 2019 (COVID-19) cases and clinical testing positivity at the community level. Wastewater surveillance on college campuses has also demonstrated promising predictive capacity for the presence and absence of COVID-19 cases. However, to date, such monitoring has most frequently relied upon composite samplers and reverse transcription quantitative PCR (RT-qPCR) techniques, which limits the accessibility and scalability of wastewater surveillance, particularly in low-resource settings. In this study, we trialed the use of tampons as passive swabs for sample collection and reverse transcription loop-mediated isothermal amplification (RT-LAMP), which does not require sophisticated thermal cycling equipment, to detect SARS-CoV-2 RNA in wastewater. Results for the workflow were available within three hours of sample collection. The RT-LAMP assay is approximately 20 times less analytically sensitive than RT-droplet digital PCR. Nonetheless, during a building-level wastewater surveillance campaign concurrent with independent weekly clinical testing of all students, the method demonstrated a three-day positive predictive value (PPV) of 75% (excluding convalescent cases) and same-day negative predictive value (NPV) of 80% for incident COVID-19 cases. These predictive values are comparable to that reported by wastewater monitoring using RT-qPCR. These observations suggest that even with lower analytical sensitivity the tampon swab and RT-LAMP workflow offers a cost-effective and rapid approach that could be leveraged for scalable building-level wastewater surveillance for COVID-19 potentially even in low-resource settings. 

Understanding the movement of antimicrobial resistance genes (ARGs) in the environment is critical to managing their spread. To assess potential ARG transport through the air via urban bioaerosols in cities with poor sanitation, we quantified ARGs and a mobile integron (MI) in ambient air over periods spanning rainy and dry seasons in Kanpur, India ( n = 53), where open wastewater canals (OCWs) are prevalent. Gene targets represented major antibiotic groups—tetracyclines ( tetA ), fluoroquinolines ( qnrB ), and beta-lactams ( bla TEM )—and a class 1 mobile integron ( intI1 ). Over half of air samples located near, and up to 1 km from OCWs with fecal contamination ( n = 45) in Kanpur had detectable targets above the experimentally determined limits of detection (LOD): most commonly intI1 and tetA (56% and 51% of samples, respectively), followed by bla TEM (8.9%) and qnrB (0%). ARG and MI densities in these positive air samples ranged from 6.9 × 10 1 to 5.2 × 10 3 gene copies/m 3 air. Most (7/8) control samples collected 1 km away from OCWs were negative for any targets. In comparing experimental samples with control samples, we found that intI1 and tetA densities in air are significantly higher ( P = 0.04 and P = 0.01, respectively, alpha = 0.05) near laboratory-confirmed fecal contaminated waters than at the control site. These data suggest increased densities of ARGs and MIs in bioaerosols in urban environments with inadequate sanitation. In such settings, aerosols may play a role in the spread of AR.