Wastewater surveillance to infer COVID-19 transmission: A systematic review.
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ABSTRACT:
SUBMITTER: Shah S
PROVIDER: S-EPMC8423771 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The COVID-19 disease, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a rapidly emerging pandemic which has enforced extreme containment measures worldwide. In the absence of a vaccine or efficient treatment, cost-effective epidemiological surveillance strategies are urgently needed. Here, we have used RT-qPCR for SARS-CoV-2 detection in a series of longitudinal metropolitan wastewaters samples collected from February to April 2020, during the earliest stages of the epidemic in the Region of Valencia, Spain. We were able to consistently detect SARS-CoV-2 RNA in samples taken in late February, when communicated cases in that region were only incipient. We also find that the wastewater viral RNA context increased rapidly and anticipated the subsequent ascent in the number of declared cases. Our results strongly suggest that the virus was undergoing community transmission earlier than previously believed, and suggest that wastewater analysis could be sensitive and cost-effective strategy for COVID-19 epidemiological surveillance. Routine implementation of this surveillance tool would significantly improve our preparedness against new or re-occurring viral outbreaks.
| S-EPMC7462597 | biostudies-literature
Project description:The evident shedding of the SARS-CoV-2 RNA particles from infected individuals into the wastewater opened up a tantalizing array of possibilities for prediction of COVID-19 prevalence prior to symptomatic case identification through community testing. Many countries have therefore explored the use of wastewater metrics as a surveillance tool, replacing traditional direct measurement of prevalence with cost-effective approaches based on SARS-CoV-2 RNA concentrations in wastewater samples. Two important aspects in building prediction models are: time over which the prediction occurs and space for which the predicted case numbers is shown. In this review, our main focus was on finding mathematical models which take into the account both the time-varying and spatial nature of wastewater-based metrics into account. We used six main characteristics as our assessment criteria: i) modelling approach; ii) temporal coverage; iii) spatial coverage; iv) sample size; v) wastewater sampling method; and vi) covariates included in the modelling. The majority of studies in the early phases of the pandemic recognized the temporal association of SARS-CoV-2 RNA concentration level in wastewater with the number of COVID-19 cases, ignoring their spatial context. We examined 15 studies up to April 2023, focusing on models considering both temporal and spatial aspects of wastewater metrics. Most early studies correlated temporal SARS-CoV-2 RNA levels with COVID-19 cases but overlooked spatial factors. Linear regression and SEIR models were commonly used (n = 10, 66.6 % of studies), along with machine learning (n = 1, 6.6 %) and Bayesian approaches (n = 1, 6.6 %) in some cases. Three studies employed spatio-temporal modelling approach (n = 3, 20.0 %). We conclude that the development, validation and calibration of further spatio-temporally explicit models should be done in parallel with the advancement of wastewater metrics before the potential of wastewater as a surveillance tool can be fully realised.
| S-EPMC10694161 | biostudies-literature
Project description:Hospital-onset COVID-19 infections (HOCIs) are associated with excess morbidity and mortality in patients and healthcare workers. The aim of this review was to explore and describe the current literature in HOCI surveillance. Medline, EMBASE, the Cochrane Database of Systematic Reviews, the Cochrane Register of Controlled Trials, and MedRxiv were searched up to 30 November 2020 using broad search criteria. Articles of HOCI surveillance systems were included. Data describing HOCI definitions, HOCI incidence, types of HOCI identification surveillance systems, and level of system implementation were extracted. A total of 292 citations were identified. Nine studies on HOCI surveillance were included. Six studies reported on the proportion of HOCI among hospitalized COVID-19 patients, which ranged from 0 to 15.2%. Six studies provided HOCI case definitions. Standardized national definitions provided by the UK and US governments were identified. Four studies included healthcare workers in the surveillance. One study articulated a multimodal strategy of infection prevention and control practices including HOCI surveillance. All identified HOCI surveillance systems were implemented at institutional level, with eight studies focusing on all hospital inpatients and one study focusing on patients in the emergency department. Multiple types of surveillance were identified. Four studies reported automated surveillance, of which one included real-time analysis, and one included genomic data. Overall, the study quality was limited by the observational nature with short follow-up periods. In conclusion, HOCI case definitions and surveillance methods were developed pragmatically. Whilst standardized case definitions and surveillance systems are ideal for integration with existing routine surveillance activities and adoption in different settings, we acknowledged the difficulties in establishing such standards in the short-term.
| S-EPMC8278304 | biostudies-literature
Project description:IntroductionSARS-CoV-2 RNA is excreted in feces of most patients, therefore viral load in wastewater can be used as a surveillance tool to develop an early warning system to help and manage future pandemics.MethodsWe collected wastewater from 24 random locations at Bangkok city center and 26 nearby suburbs from July to December 2020. SARS-CoV-2 RNA copy numbers were measured using real-time polymerase chain reaction (PCR).ResultsSARS-CoV-2 RNA was detected in wastewater from both the city center and suburbs. Except for July, there were no significant differences in copy numbers between the city center and suburbs. Between October and November, a sharp rise in copy number was observed in both places followed by two to three times increase in December, related to SARS-CoV-2 cases reported for same month.ConclusionsOur study provided the first dataset related to SARS-CoV-2 viral RNA in the wastewater of Bangkok. Our results suggest that wastewater could be used as a complementary source for detecting viral RNA and predicting upcoming outbreaks and waves.
| S-EPMC8111879 | biostudies-literature
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:SARS-CoV-2 wastewater-based surveillance (WBS) offers a tool for cost-effective oversight of a population's infections. In the past two years, WBS has proven to be crucial for managing the pandemic across different geographical regions. However, the changing context of the pandemic due to high levels of COVID-19 vaccination warrants a closer examination of its implication towards SARS-CoV-2 WBS. Two main questions were raised: 1) Does vaccination cause shedding of viral signatures without infection? 2) Does vaccination affect the relationship between wastewater and clinical data? To answer, we review historical reports of shedding from viral vaccines in use prior to the COVID-19 pandemic including for polio, rotavirus, influenza and measles infection and provide a perspective on the implications of different COVID-19 vaccination strategies with regard to the potential shedding of viral signatures into the sewershed. Additionally, we reviewed studies that looked into the relationship between wastewater and clinical data and how vaccination campaigns could have affected the relationship. Finally, analyzing wastewater and clinical data from the Netherlands, we observed changes in the relationship concomitant with increasing vaccination coverage and switches in dominant variants of concern. First, that no vaccine-derived shedding is expected from the current commercial pipeline of COVID-19 vaccines that may confound interpretation of WBS data. Secondly, that breakthrough infections from vaccinated individuals contribute significantly to wastewater signals and must be interpreted in light of the changing dynamics of shedding from new variants of concern.
| S-EPMC9783150 | biostudies-literature
Project description:Wastewater-Based Epidemiology is a tool to face and mitigate COVID-19 outbreaks by evaluating conditions in a specific community. This study aimed to analyze the microbiome profiles using nanopore technology for full-length 16S rRNA sequencing in wastewater samples collected from a penitentiary (P), a residential care home (RCH), and a quarantine or health care facilities (HCF). During the study, the wastewater samples from the RCH and the P were negative for SARS-CoV-2 based on qPCRs, except during the fourth week when was detected. Unexpectedly, the wastewater microbiome from RCH and P prior to week four was correlated with the samples collected from the HCF, suggesting a core bacterial community is expelled from the digest tract of individuals infected with SARS-CoV-2. The microbiota of wastewater sample positives for SARS-CoV-2 was strongly associated with enteric bacteria previously reported in patients with risk factors for COVID-19. We provide novel evidence that the wastewater microbiome associated with gastrointestinal manifestations appears to precede the SARS-CoV-2 detection in sewage. This finding suggests that the wastewaters microbiome can be applied as an indicator of community-wide SARS-CoV-2 surveillance.
| S-EPMC7546644 | biostudies-literature
Project description:ObjectiveThe objective of this study was to identify the potential and definite sources of transmission of coronavirus disease 2019 (COVID-19).MethodsDue to time constraints and the acute nature of the pandemic, we searched only PubMed/Medline from inception until January 28, 2021. We analyzed the level of evidence and risk of bias in each category and made suggestions accordingly.ResultsThe virus was traced from its potential origin via possible ways of transmission to the last host. Symptomatic human-to-human transmission remains the driver of the epidemic, but asymptomatic transmission can potentially contribute in a substantial manner. Feces and fomites have both been found to contain viable virus; even though transmission through these routes has not been documented, their contribution cannot be ruled out. Finally, transmission from pregnant women to their children has been found to be low (up to 3%).ConclusionEven though robust outcomes cannot be easily assessed, medical personnel must maintain awareness of the main routes of transmission (via droplets and aerosols from even asymptomatic patients). This is the first attempt to systematically review the existing knowledge to produce a paper with a potentially significant clinical impact.
| S-EPMC8102883 | biostudies-literature
Project description:Infectious diseases caused by antibiotic-resistant bacterial (ARB) pathogens are a serious threat to human and animal health. The active surveillance of ARB using an integrated one-health approach can help to reduce the emergence and spread of ARB, reduce the associated economic impact, and guide antimicrobial stewardship programs. Wastewater surveillance (WWS) of ARB provides composite samples for a total population, with easy access to the mixed community microbiome. This concept is emerging rapidly, but the clinical utility, sensitivity, and uniformity of WWS of ARB remain poorly understood especially in relation to clinical evidence in sewershed communities. Here, we systematically searched the literature to identify studies that have compared findings from WWS of ARB and antibiotic resistance genes (ARG) with clinical evidence in parallel, thereby evaluating how likely WWS of ARB and ARG can relate to the clinical cases in communities. Initially, 2,235 articles were obtained using the primary search keywords, and 1,219 articles remained after de-duplication. Among these, 35 articles fulfilled the search criteria, and an additional 13 relevant articles were included by searching references in the primary literature. Among the 48 included papers, 34 studies used a culture-based method, followed by 11 metagenomics, and three PCR-based methods. A total of 28 out of 48 included studies were conducted at the single sewershed level, eight studies involved several countries, seven studies were conducted at national or regional scales, and five at hospital levels. Our review revealed that the performance of WWS of ARB pathogens has been evaluated more frequently for Escherichia coli, Enterococcus spp., and other members of the family Enterobacteriaceae, but has not been uniformly tested for all ARB pathogens. Many wastewater-based ARB studies comparing the findings with clinical evidence were conducted to evaluate the public health risk but not to relate with clinical evidence and to evaluate the performance of WWS of ARB. Indeed, relating WWS of ARB with clinical evidence in a sewershed is not straightforward, as the source of ARB in wastewater cannot be only from symptomatic human individuals but can also be from asymptomatic carriers as well as from animal sources. Further, the varying fates of each bacterial species and ARG within the sewerage make the aim of connecting WWS of ARB with clinical evidence more complicated. Therefore, future studies evaluating the performance of many AMR pathogens and their genes for WWS one by one can make the process simpler and the interpretation of results easier.
| S-EPMC9798455 | biostudies-literature
Project description:BackgroundIn November 2020, the World Health Organization (WHO) created interim guidance on how to integrate testing for SARS-CoV-2 into existing influenza surveillance systems. Influenza-like illness (ILI) and severe acute respiratory illness (SARI) case definitions have been used to specify the case definition of COVID-19 for surveillance purposes. This review aims to assess whether the common clinical features of COVID-19 have changed to the point that the criteria used to identify both COVID-19 and influenza in surveillance programs needs to be altered.MethodsA systematic review of reviews following PRISMA-P guidelines was conducted using the "COVID-19 evidence review" database from August 19, 2020, to August 19, 2021. Reviews providing pooled estimates of the prevalence of clinical features of COVID-19 within the general population, diagnosed by polymerase chain reaction or rapid diagnostic test, were included. These were critically appraised and sensitivity analysis was undertaken to examine potential causes of bias.ResultsFourteen reviews were identified, including three on adults only and three on children only. For all reviews, combined fever (median prevalence = 73.0%, IQR = 58.3-78.7) and cough (45.1%, IQR = 28.9-54.0) were the most common features. These were followed by loss of taste or smell (45.1%, IQR = 28.9-54.0), hypoxemia (33%, one review), fatigue (26.4%, IQR = 9.0-39.4) and expectoration (23.9%, IQR = 23.3-25.5). Fever and cough continued to be the most prevalent features for adults and children, with subsequent symptoms being similar for adults only. However, the pattern differed for children, with headache (34.3%, IQR = 18-50.7) and nasal congestion (20%, one review) being the third and fourth commonest symptoms.ConclusionsThe prevalent features found in this recent review were the same as the ones identified at the beginning of the pandemic. Therefore, the current approach of using the ILI and SARI criteria which incorporate fever and cough will identify COVID-19 cases in addition to influenza. Interestingly, children may present with different features, as headaches and nasal congestion were more common in this group. Future research could examine this further and investigate whether symptomology changes with new variants of COVID-19.
| S-EPMC9107308 | biostudies-literature