Feasibility of neighborhood and building scale wastewater-based genomic epidemiology for pathogen surveillance.
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ABSTRACT:
SUBMITTER: Spurbeck RR
PROVIDER: S-EPMC8542657 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Wastewater-based epidemiology (WBE) has been used to analyze markers in wastewater treatment plant (WWTP) influent to characterize emerging chemicals, drug use patterns, or disease spread within communities. This approach can be particularly helpful in understanding outbreaks of disease like the novel Coronavirus disease-19 (COVID-19) when combined with clinical datasets. In this study, three RT-ddPCR assays (N1, N2, N3) were used to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in weekly samples from nine WWTPs in southeastern Virginia. In the first several weeks of sampling, SARS-CoV-2 detections were sporadic. Frequency of detections and overall concentrations of RNA within samples increased from mid March into late July. During the twenty-one week study, SARS-CoV-2 concentrations ranged from 101 to 104 copies 100 mL-1 in samples where viral RNA was detected. Fluctuations in population normalized loading rates in several of the WWTP service areas agreed with known outbreaks during the study. Here we propose several ways that data can be presented spatially and temporally to be of greatest use to public health officials. As the COVID-19 pandemic wanes, it is likely that communities will see increased incidence of small, localized outbreaks. In these instances, WBE could be used as a pre-screening tool to better target clinical testing needs in communities with limited resources.
| S-EPMC7424388 | biostudies-literature
Project description:Since 2020, developed countries have rapidly shared both publicly and academically relevant wastewater surveillance information. Data on SARS-CoV-2 circulation is pivotal for guiding public health policies and improving the COVID-19 pandemic response. Conversely, low- and middle-income countries, such as Latin America and the Caribbean, showed timid activities in the Wastewater-Based Epidemiology (WBE) context. In these countries, isolated groups perform viral wastewater monitoring, and the data are unevenly shared or accessible to health agencies and the scientific community. This manuscript aims to highlight the relevance of a multiparty effort involving research, public health, and governmental agencies to support usage of WBE methodology to its full potential during the COVID-19 pandemic as part of a joint One Health surveillance approach. Thus, in this study, we explored the results obtained from wastewater surveillance in different regions of Brazil as a part of the COVID-19 Wastewater Monitoring Network ANA (National Water Agency), MCTI (Ministry of Science, Technology, and Innovations) and MS (Ministry of Health). Over the epidemiological weeks of 2021 and early 2022, viral RNA concentrations in wastewater followed epidemiological trends and variations. The highest viral loads in wastewater samples were detected during the second Brazilian wave of COVID-19. Corroborating international reports, our experience demonstrated usefulness of the WBE approach in viral surveillance. Wastewater surveillance allows hotspot identification, and therefore, early public health interventions. In addition, this methodology allows tracking of asymptomatic and oligosymptomatic individuals, who are generally underreported, especially in emerging countries with limited clinical testing capacity. Therefore, WBE undoubtedly contributes to improving public health responses in the context of this pandemic, as well as other sanitary emergencies.
| S-EPMC9295330 | biostudies-literature
Project description:The presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater produced interest in its use for sentinel surveillance at a community level and as a complementary approach to syndromic surveillance. With this work, we set the foundations for wastewater-based epidemiology (WBE) in Portugal by monitoring the trends of SARS-CoV-2 RNA circulation in the community, on a nationwide perspective during different epidemiological phases of the pandemic. The Charité assays (E_Sarbecco, RdRP, and N_Sarbecco) were applied to monitor, over 32-weeks (April to December 2020), the dynamics of SARS-CoV-2 RNA at the inlet of five wastewater treatment plants (WWTP), which together serve more than two million people in Portugal. Raw wastewater from three Coronavirus disease 2019 (COVID-19) reference hospitals was also analyzed during this period. In total, more than 600 samples were tested. For the first weeks, detection of SARS-CoV-2 RNA was sporadic, with concentrations varying from 103 to 105 genome copies per liter (GC/L). Prevalence of SARS-CoV-2 RNA increased steeply by the end of May into late June, mainly in Lisboa e Vale do Tejo region (LVT), during the reopening phase. After the summer, with the reopening of schools in mid-September and return to partial face-to-face work, a pronounced increase of SARS-CoV-2 RNA in wastewater was detected. In the LVT area, SARS-CoV-2 RNA load agreed with reported trends in hotspots of infection. Synchrony between trends of SARS-CoV-2 RNA in raw wastewater and daily new COVID-19 cases highlights the value of WBE as a surveillance tool, particularly after the phasing out of the epidemiological curve and when hotspots of disease re-emerge in the population which might be difficult to spot based solely on syndromic surveillance and contact tracing. This is the first study crossing several epidemiological stages highlighting the long-term use of WBE for SARS-CoV-2.
| S-EPMC8432975 | biostudies-literature
Project description:Population datasets and the Internet are playing an ever-growing role in the way cancer information is made available to providers, patients, and their caregivers. The Surveillance, Epidemiology, and End Results Cancer Survival Calculator (SEER*CSC) is a Web-based cancer prognostic tool that uses SEER data, a large population dataset, to provide physicians with highly valid, evidence-based prognostic estimates for increasing shared decision-making and improving patient-provider communication of complex health information.The aim of this study was to develop, test, and implement SEER*CSC.An iterative approach was used to develop the SEER*CSC. Based on input from cancer patient advocacy groups and physicians, an initial version of the tool was developed. Next, providers from 4 health care delivery systems were recruited to do formal usability testing of SEER*CSC. A revised version of SEER*CSC was then implemented in two health care delivery sites using a real-world clinical implementation approach, and usage data were collected. Post-implementation follow-up interviews were conducted with site champions. Finally, patients from two cancer advocacy groups participated in usability testing.Overall feedback of SEER*CSC from both providers and patients was positive, with providers noting that the tool was professional and reliable, and patients finding it to be informational and helpful to use when discussing their diagnosis with their provider. However, use during the small-scale implementation was low. Reasons for low usage included time to enter data, not having treatment options in the tool, and the tool not being incorporated into the electronic health record (EHR). Patients found the language in its current version to be too complex.The implementation and usability results showed that participants were enthusiastic about the use and features of SEER*CSC, but sustained implementation in a real-world clinical setting faced significant challenges. As a result of these findings, SEER*CSC is being redesigned with more accessible language for a public facing release. Meta-tools, which put different tools in context of each other, are needed to assist in understanding the strengths and limitations of various tools and their place in the clinical decision-making pathway. The continued development and eventual release of prognostic tools should include feedback from multidisciplinary health care teams, various stakeholder groups, patients, and caregivers.
| S-EPMC5544898 | biostudies-other
Project description:With the economic and practical limits of medical screening for SARS-CoV-2/COVID-19 coming sharply into focus worldwide, scientists are turning now to wastewater-based epidemiology (WBE) as a potential tool for assessing and managing the pandemic. We employed computational analysis and modeling to examine the feasibility, economy, opportunities and challenges of enumerating active coronavirus infections locally and globally using WBE. Depending on local conditions, detection in community wastewater of one symptomatic/asymptomatic infected case per 100 to 2,000,000 non-infected people is theoretically feasible, with some practical successes now being reported from around the world. Computer simulations for past, present and emerging epidemic hotspots (e.g., Wuhan, Milan, Madrid, New York City, Teheran, Seattle, Detroit and New Orleans) identified temperature, average in-sewer travel time and per-capita water use as key variables. WBE surveillance of populations is shown to be orders of magnitude cheaper and faster than clinical screening, yet cannot fully replace it. Cost savings worldwide for one-time national surveillance campaigns are estimated to be in the million to billion US dollar range (US$), depending on a nation's population size and number of testing rounds conducted. For resource poor regions and nations, WBE may represent the only viable means of effective surveillance. Important limitations of WBE rest with its inability to identify individuals and to pinpoint their specific locations. Not compensating for temperature effects renders WBE data vulnerable to severe under-/over-estimation of infected cases. Effective surveillance may be envisioned as a two-step process in which WBE serves to identify and enumerate infected cases, where after clinical testing then serves to identify infected individuals in WBE-revealed hotspots. Data provided here demonstrate this approach to save money, be broadly applicable worldwide, and potentially aid in precision management of the pandemic, thereby helping to accelerate the global economic recovery that billions of people rely upon for their livelihoods.
| S-EPMC7175865 | biostudies-literature
Project description:SARS-CoV-2 pandemic is having a devastating effect on human lives. Recent reports have shown that majority of the individuals recovered from COVID-19 have serious health complications, which is going to be a huge economic burden globally. Given the wide-spread transmission of SARS-CoV-2 it is almost impossible to test every individual in densely populated countries. Recent reports have shown that sewage-based surveillance can be used as holistic approach to understand the spread of the pandemic within a population or area. Here we have estimated the spread of SARS-CoV-2 in the city of Hyderabad, India, which is a home for nearly 10 million people. The sewage samples were collected from all the major sewage treatment plants (STPs) and were processed for detecting the viral genome using the standard Reverse Transcription Polymerase Chain Reaction (RT-PCR) method. Interestingly, inlet samples of STPs were positive for SARS-CoV-2, while the outlets were negative, which indicates that the standard sewage treatment methods are efficient in eliminating the SARS-CoV-2 viral particles. Based on the detected viral gene copies per litre and viral particle shedding per individual, the total number of individuals exposed to SARS-CoV-2 was estimated. Through this study we suggest that sewage-based surveillance is an effective approach to study the infection dynamics, which helps in efficient management of the SARS-CoV-2 spread.
| S-EPMC7787060 | biostudies-literature
Project description:Community wastewater surveillance is an established means to measure health threats. Exposure to toxic metals as one of the key environmental contaminants has been attracting public health attention as exposure can be related to contamination across air, water, and soil as well as associated with individual factors. This research uses Jefferson County, Kentucky, as an urban exposome case study to analyze sub-county metal concentrations in wastewater as a possible indicator of community toxicant exposure risk, and to test the feasibility of using wastewater to identify potential community areas of elevated metals exposure. Variability in wastewater metal concentrations were observed across the county; 19 of the 26 sites had one or more metal results greater than one standard deviation above the mean and were designated areas of concern. Additionally, thirteen of the nineteen sites were of increased concern with levels greater than two standard deviations above the mean. This foundational research found variability in several instances between smaller nested upstream contributing neighborhood sewersheds when measured in the associated downstream treatment plant. Wastewater provides an opportunity to look at integrated toxicology to complement other toxicology data, looking at where people live and what toxicants need to be focused on to protect the health of people in that area.
| S-EPMC10557802 | biostudies-literature
Project description:SARS-CoV-2 RNA quantification in wastewater is an important tool for monitoring the prevalence of COVID-19 disease on a community scale which complements case-based surveillance systems. As novel variants of concern (VOCs) emerge there is also a need to identify the primary circulating variants in a community, accomplished to date by sequencing clinical samples. Quantifying variants in wastewater offers a cost-effective means to augment these sequencing efforts. In this study, SARS-CoV-2 N1 RNA concentrations and daily loadings were determined and compared to case-based data collected as part of a national surveillance programme to determine the validity of wastewater surveillance to monitor infection spread in the greater Dublin area. Further, sequencing of clinical samples was conducted to determine the primary SARS-CoV-2 lineages circulating in Dublin. Finally, digital PCR was employed to determine whether SARS-CoV-2 VOCs, Alpha and Delta, were quantifiable from wastewater. No lead or lag time was observed between SARS-CoV-2 wastewater and case-based data and SARS-CoV-2 trends in Dublin wastewater significantly correlated with the notification of confirmed cases through case-based surveillance preceding collection with a 5-day average. This demonstrates that viral RNA in Dublin's wastewater mirrors the spread of infection in the community. Clinical sequence data demonstrated that increased COVID-19 cases during Ireland's third wave coincided with the introduction of the Alpha variant, while the fourth wave coincided with increased prevalence of the Delta variant. Interestingly, the Alpha variant was detected in Dublin wastewater prior to the first genome being sequenced from clinical samples, while the Delta variant was identified at the same time in clinical and wastewater samples. This work demonstrates the validity of wastewater surveillance for monitoring SARS-CoV-2 infections and also highlights its effectiveness in identifying circulating variants which may prove useful when sequencing capacity is limited.
| S-EPMC9110007 | biostudies-literature
Project description: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.
| S-EPMC10412881 | biostudies-literature
Project description:The presence of SARS-CoV-2 in the feces of infected patients and wastewater has drawn attention, not only to the possibility of fecal-oral transmission but also to the use of wastewater as an epidemiological tool. The COVID-19 pandemic has highlighted problems in evaluating the epidemiological scope of the disease using classical surveillance approaches, due to a lack of diagnostic capacity, and their application to only a small proportion of the population. As in previous pandemics, statistics, particularly the proportion of the population infected, are believed to be widely underestimated. Furthermore, analysis of only clinical samples cannot predict outbreaks in a timely manner or easily capture asymptomatic carriers. Threfore, community-scale surveillance, including wastewater-based epidemiology, can bridge the broader community and the clinic, becoming a valuable indirect epidemiological prediction tool for SARS-CoV-2 and other pandemic viruses. This article summarizes current knowledge and discusses the critical factors for implementing wastewater-based epidemiology of COVID-19.
| S-EPMC7480445 | biostudies-literature