Wastewater-based epidemiology has gained attention throughout the world for detection of SARS-CoV-2 RNA in wastewater to supplement clinical testing. Raw wastewater consists of small particles, or solids, suspended in liquid. Methods have been developed to measure SARS-CoV-2 RNA in the liquid and the solid fraction of wastewater, with some studies reporting higher concentrations in the solid fraction. To investigate this relationship further, six laboratories collaborated to conduct a study across five publicly owned treatment works (POTWs) where both primary settled solids obtained from primary clarifiers and raw wastewater influent samples were collected and quantified for SARS-CoV-2 RNA. Settled solids and influent samples were processed by participating laboratories using their respective methods and retrospectively paired based on date of collection. SARS-CoV-2 RNA concentrations, on a mass equivalent basis, were higher in settled solids than in influent by approximately three orders of magnitude. Concentrations in matched settled solids and influent were positively and significantly correlated at all five POTWs. RNA concentrations in both settled solids and influent were correlated to COVID-19 incidence rates in the sewersheds and thus representative of disease occurrence; the settled solids methods appeared to produce a comparable relationship between SARS-CoV-2 RNA concentration measurements and incidence rates across all POTWs. Settled solids and influent methods showed comparable sensitivity, N gene detection frequency, and calculated empirical incidence rate lower limits. Analysis of settled solids for SARS-CoV-2 RNA has the advantage of using less sample volume to achieve similar sensitivity to influent methods.
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Prevalence of SARS-CoV-2 genes in water reclamation facilities: From influent to anaerobic digester
Several treatment plants were sampled for raw influent, primary clarifier sludge, return activated sludge (RAS), and anaerobically digested sludge throughout nine weeks during the summer of the COVID-19 pandemic. Primary clarifier sludge had a significantly higher number of SARS-CoV-2 gene copy number per liter (GC/L) than other sludge samples, within a range from 1.0x105 to 1.0x106 GC/L. Gene copy numbers in raw influent significantly correlated with gene copy numbers in RAS in Silver Creek (p-value = 0.007, R2 = 0.681) and East Canyon (p-value = 0.009, R2 = 0.775) WRFs; both of which lack primary clarifiers or industrial pretreatment processes. This data indicates that SARS-CoV-2 gene copies tend to partition into primary clarifier sludges, at which point a significant portion of them are removed through sedimentation. Furthermore, it was found that East Canyon WRF gene copy numbers in influent were a significant predictor of daily cases (p-value = 0.0322, R2 = 0.561), and gene copy numbers in RAS were a significant predictor of weekly cases (p-value = 0.0597, R2 = 0.449). However, gene copy numbers found in primary sludge samples from other plants significantly predicted the number of COVID-19 cases for the following week (t = 2.279) and the week after that (t = 2.122). These data indicate that SARS-CoV-2 extracted from WRF biosolids may better suit epidemiological monitoring that exhibits a time lag. It also supports the observation that primary sludge removes a significant portion of SARS-CoV-2 marker genes. In its absence, RAS can also be used to predict the number of COVID-19 cases due to direct flow through from influent. This research represents the first of its kind to thoroughly examine SARS-CoV-2 gene copy numbers in biosolids throughout the wastewater treatment process and the relationship between primary, return activated, and anaerobically digested sludge and reported positive COVID-19 cases.
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- Award ID(s):
- 2029515
- NSF-PAR ID:
- 10324033
- Editor(s):
- Not Known
- Date Published:
- Journal Name:
- Science of the total environment
- Volume:
- 796
- Issue:
- 148905
- ISSN:
- 1879-1026
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Wastewater surveillance has proven to be an effective tool to monitor the transmission and emergence of infectious agents at a community scale. Workflows for wastewater surveillance generally rely on concentration steps to increase the probability of detection of low-abundance targets, but preconcentration can substantially increase the time and cost of analyses while also introducing additional loss of target during processing. To address some of these issues, we conducted a longitudinal study implementing a simplified workflow for SARS-CoV-2 detection from wastewater, using a direct column-based extraction approach. Composite influent wastewater samples were collected weekly for 1 year between June 2020 and June 2021 in Athens-Clarke County, Georgia, USA. Bypassing any concentration step, low volumes (280 µl) of influent wastewater were extracted using a commercial kit, and immediately analyzed by RT-qPCR for the SARS-CoV-2 N1 and N2 gene targets. SARS-CoV-2 viral RNA was detected in 76% (193/254) of influent samples, and the recovery of the surrogate bovine coronavirus was 42% (IQR: 28%, 59%). N1 and N2 assay positivity, viral concentration, and flow-adjusted daily viral load correlated significantly with per-capita case reports of COVID-19 at the county-level (ρ = 0.69–0.82). To compensate for the method’s high limit of detection (approximately 106–107 copies l−1 in wastewater), we extracted multiple small-volume replicates of each wastewater sample. With this approach, we detected as few as five cases of COVID-19 per 100 000 individuals. These results indicate that a direct-extraction-based workflow for SARS-CoV-2 wastewater surveillance can provide informative and actionable results.
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Funk, Sebastian (Ed.)Simultaneously controlling COVID-19 epidemics and limiting economic and societal impacts presents a difficult challenge, especially with limited public health budgets. Testing, contact tracing, and isolating/quarantining is a key strategy that has been used to reduce transmission of SARS-CoV-2, the virus that causes COVID-19 and other pathogens. However, manual contact tracing is a time-consuming process and as case numbers increase a smaller fraction of cases’ contacts can be traced, leading to additional virus spread. Delays between symptom onset and being tested (and receiving results), and a low fraction of symptomatic cases being tested and traced can also reduce the impact of contact tracing on transmission. We examined the relationship between increasing cases and delays and the pathogen reproductive number R t , and the implications for infection dynamics using deterministic and stochastic compartmental models of SARS-CoV-2. We found that R t increased sigmoidally with the number of cases due to decreasing contact tracing efficacy. This relationship results in accelerating epidemics because R t initially increases, rather than declines, as infections increase. Shifting contact tracers from locations with high and low case burdens relative to capacity to locations with intermediate case burdens maximizes their impact in reducing R t (but minimizing total infections may be more complicated). Contact tracing efficacy decreased sharply with increasing delays between symptom onset and tracing and with lower fraction of symptomatic infections being tested. Finally, testing and tracing reductions in R t can sometimes greatly delay epidemics due to the highly heterogeneous transmission dynamics of SARS-CoV-2. These results demonstrate the importance of having an expandable or mobile team of contact tracers that can be used to control surges in cases. They also highlight the synergistic value of high capacity, easy access testing and rapid turn-around of testing results, and outreach efforts to encourage symptomatic cases to be tested immediately after symptom onset.more » « less
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Abstract Children less than 18 years of age account for an estimated 2%–5% of reported severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) cases globally. Lower prevalence of coronavirus disease 2019 (COVID‐19) among children, in addition to higher numbers of mild and asymptomatic cases, continues to provide challenges in determining appropriate prevention and treatment courses. Here, we summarize the current evidence on the transmission, clinical presentation, complications and risk factors in regard to SARS‐CoV‐2 in children, and highlight crucial gaps in knowledge going forward. Based on current evidence, children are rarely the primary source of secondary transmission in the household or in child care and school settings and are more likely to contract the virus from an adult household member. Higher transmission rates are observed in older children (10–19 years old) compared with younger children ( <10 years old). While increasing incidence of COVID‐19 in neonates raises the suspicion of vertical transmission, it is unlikely that breast milk is a vehicle for transmission from mother to infant. The vast majority of clinical cases of COVID‐19 in children are mild, but there are rare cases that have developed complications such as multisystem inflammatory syndrome in children, which often presents with severe cardiac symptoms requiring intensive care. Childhood obesity is associated with a higher risk of infection and a more severe clinical presentation. Although immediate mortality rates among children are low, long‐term respiratory, and developmental implications of the disease remain unknown in this young and vulnerable population.
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/doi.org/10.1016/j.scitotenv.2021.148905
