Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance.
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ABSTRACT:
SUBMITTER: El-Malah SS
PROVIDER: S-EPMC9220754 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionWastewater-based surveillance is at the forefront of monitoring for community prevalence of COVID-19, however, continued uncertainty exists regarding the use of fecal indicators for normalization of the SARS-CoV-2 virus in wastewater. Using three communities in Ontario, sampled from 2021-2023, the seasonality of a viral fecal indicator (pepper mild mottle virus, PMMoV) and the utility of normalization of data to improve correlations with clinical cases was examined.MethodsWastewater samples from Warden, the Humber Air Management Facility (AMF), and Kitchener were analyzed for SARS-CoV-2, PMMoV, and crAssphage. The seasonality of PMMoV and flow rates were examined and compared by Season-Trend-Loess decomposition analysis. The effects of normalization using PMMoV, crAssphage, and flow rates were analyzed by comparing the correlations to clinical cases by episode date (CBED) during 2021.ResultsSeasonal analysis demonstrated that PMMoV had similar trends at Humber AMF and Kitchener with peaks in January and April 2022 and low concentrations (troughs) in the summer months. Warden had similar trends but was more sporadic between the peaks and troughs for PMMoV concentrations. Flow demonstrated similar trends but was not correlated to PMMoV concentrations at Humber AMF and was very weak at Kitchener (r = 0.12). Despite the differences among the sewersheds, unnormalized SARS-CoV-2 (raw N1-N2) concentration in wastewater (n = 99-191) was strongly correlated to the CBED in the communities (r = 0.620-0.854) during 2021. Additionally, normalization with PMMoV did not improve the correlations at Warden and significantly reduced the correlations at Humber AMF and Kitchener. Flow normalization (n = 99-191) at Humber AMF and Kitchener and crAssphage normalization (n = 29-57) correlations at all three sites were not significantly different from raw N1-N2 correlations with CBED.DiscussionDifferences in seasonal trends in viral biomarkers caused by differences in sewershed characteristics (flow, input, etc.) may play a role in determining how effective normalization may be for improving correlations (or not). This study highlights the importance of assessing the influence of viral fecal indicators on normalized SARS-CoV-2 or other viruses of concern. Fecal indicators used to normalize the target of interest may help or hinder establishing trends with clinical outcomes of interest in wastewater-based surveillance and needs to be considered carefully across seasons and sites.
| S-EPMC10499178 | biostudies-literature
Project description:BackgroundRespiratory tract infections have an enormous social economic impact, with high incidence of hospitalization and high costs. Adequate specimen collection is the first crucial step for the correct diagnosis of viral respiratory infections.ObjectivesThe present retrospective study aimed: i) to verify the cell yield obtained from sampling the nasal respiratory tract using mid-turbinate flocked swabs; ii) to evaluate the normalization of viral load, based on cell number; and iii) to compare the kinetics of viral infection obtained with normalized vs non-normalized viral load.Study designThe number of cells were quantified by real-time PCR in residual extract of nasal swabs tested for respiratory viruses detection and stored at -80 °C in a universal transport medium (UTM™).ResultsA total of 513 virus-positive and 226 virus-negative samples were analyzed. Overall, a median of 4.42 log10 β2-microgolubin DNA copy number/ml of UTM™ (range 1.17-7.26) was detected. A significantly higher number of cells was observed in virus-positive as compared to virus-negative samples (4.75 vs 3.76; p < 0.001). Viral loads expressed as log10 RNA copies/ml of UTM™ and log10 RNA copies/median number of cells were compared in virus-positive samples and a strict correlation (r = 0.89, p < 0.001) and agreement (R2 = 0.82) were observed. In addition, infection kinetics were compared using the two methods with a follow-up series of eight episodes of viral infection and the mean difference was -0.57 log10 (range -1.99 to 0.40).ConclusionsThe normalization of viral load using cellular load compliments the validation of real-time PCR results in the diagnosis of respiratory viruses but is not strictly needed.
| S-EPMC7173160 | biostudies-literature
Project description:The incubation period, or the time from infection to symptom onset, of COVID-19 has usually been estimated by using data collected through interviews with cases and their contacts. However, this estimation is influenced by uncertainty in the cases' recall of exposure time. We propose a novel method that uses viral load data collected over time since hospitalization, hindcasting the timing of infection with a mathematical model for viral dynamics. As an example, we used reported data on viral load for 30 hospitalized patients from multiple countries (Singapore, China, Germany, and Korea) and estimated the incubation period. The median, 2.5, and 97.5 percentiles of the incubation period were 5.85 days (95 % CI: 5.05, 6.77), 2.65 days (2.04, 3.41), and 12.99 days (9.98, 16.79), respectively, which are comparable to the values estimated in previous studies. Using viral load to estimate the incubation period might be a useful approach, especially when it is impractical to directly observe the infection event.
| S-EPMC7959696 | biostudies-literature
Project description:Wastewater-based epidemiology (WBE) has been deployed broadly as an early warning tool for emerging COVID-19 outbreaks. WBE can inform targeted interventions and identify communities with high transmission, enabling quick and effective responses. As the wastewater (WW) becomes an increasingly important indicator for COVID-19 transmission, more robust methods and metrics are needed to guide public health decision-making. This research aimed to develop and implement a mathematical framework to infer incident cases of COVID-19 from SARS-CoV-2 levels measured in WW. We propose a classification scheme to assess the adequacy of model training periods based on clinical testing rates and assess the sensitivity of model predictions to training periods. A testing period is classified as adequate when the rate of change in testing is greater than the rate of change in cases. We present a Bayesian deconvolution and linear regression model to estimate COVID-19 cases from WW data. The effective reproductive number is estimated from reconstructed cases using WW. The proposed modeling framework was applied to three Northern California communities served by distinct WW treatment plants. The results showed that training periods with adequate testing are essential to provide accurate projections of COVID-19 incidence.
| S-EPMC9597566 | biostudies-literature
Project description:Viruses are linked to a multitude of human illnesses and can disseminate widely in urbanized environments causing global adverse impacts on communities and healthcare infrastructures. Wastewater-based epidemiology was employed using metagenomics and quantitative polymerase chain reaction (qPCR) assays to identify enteric and non-enteric viruses collected from a large urban area for potential public health monitoring and outbreak analysis. Untreated wastewater samples were collected from November 2017 to February 2018 (n = 54) to evaluate the diversity of human viral pathogens in collected samples. Viruses were classified into virus types based on primary transmission routes and reviewed against viral associated diseases reported in the catchment area. Metagenomics detected the presence of viral pathogens that cause clinically significant diseases reported within the study area during the sampling year. Detected viruses belong to the Adenoviridae, Astroviridae, Caliciviridae, Coronaviridae, Flaviviridae, Hepeviridae, Herpesviridae, Matonaviridae, Papillomaviridae, Parvoviridae, Picornaviridae, Poxviridae, Retroviridae, and Togaviridae families. Furthermore, concentrations of adenovirus, norovirus GII, sapovirus, hepatitis A virus, human herpesvirus 6, and human herpesvirus 8 were measured in wastewater samples and compared to metagenomic findings to confirm detected viral genus. Hepatitis A virus obtained the greatest average viral load (1.86 × 107 genome copies/L) in wastewater samples compared to other viruses quantified using qPCR with a 100% detection rate in metagenomic samples. Average concentration of sapovirus (1.36 × 106 genome copies/L) was significantly greater than norovirus GII (2.94 × 104 genome copies/L) indicating a higher burden within the study area. Findings obtained from this study aid in evaluating the utility of wastewater-based epidemiology for identification and routine monitoring of various viruses in large communities. This methodology has the potential to improve public health responses to large scale outbreaks and viral pandemics.
| S-EPMC7342010 | biostudies-literature
Project description:IntroductionHIV surveillance programs do not typically collect comprehensive data on antiretroviral therapy (ART). We validated a population-based measure of ART initiation that uses HIV viral load (VL) results in the absence of data on ART.MethodsWe used CD4/VL data reported to NYC HIV Surveillance for persons aged ≥13 years and diagnosed with HIV from 2006 to 2012 to validate estimates of ART initiation date based on 3 ART initiation definitions: (1) ≥1-log decline in copies per milliliter between 2 VLs over 3 months; (2) ≥2-log decline in copies per milliliter between 2 VLs over 3 months; and (3) the earliest of either a ≥1-log decline in VL over 3 months, or a change from detectable VL to undetectable VL (<400 copies/mL) over any interval. We plotted median CD4 counts by quarter before and after ART initiation to compare estimated initiation date with nadir of the CD4 trajectory.ResultsA total of 24,348 persons were diagnosed with HIV in NYC from 2006 to 2012. In all, 12,123 persons had probable ART initiation based on ≥2-log decline, 12,719 based on ≥1-log decline, and 14,311 based on ≥1-log decline or detectable-undetectable change. Lowest median CD4 count occurred at the estimated ART initiation date for all 3 definitions. The definition based on a ≥1-log VL decline or a change from detectable to undetectable VL captured more ART initiations and identified earlier initiation dates.ConclusionsSerial VL measures are a valid source for estimating ART initiation. A definition that includes a ≥1-log VL decline or a change from detectable to undetectable VL performed best.
| S-EPMC5584788 | biostudies-literature
Project description:IntroductionIn South Africa, HIV patients with an elevated viral load (VL) should receive repeat VL testing after adherence counselling. We set out to use a national HIV Cohort to describe time to repeat viral load testing across South Africa and identify predictors of time to repeat testing.MethodsWe conducted a cohort study of prospectively collected laboratory data. HIV treatment guidelines have changed over time in South Africa, but call for repeat VL testing within six months if 400 to 1000 copies/mL and two to three months if >1000 copies/mL. We included patients with suppressed viral loads (indicating they are on ART) and a first elevated VL (>400 copies/mL) between April 2004 and December 2014. Follow-up began at first elevated VL and continued until repeat testing, loss to follow-up or December 2016. We calculated adjusted hazard ratios (aHR) using Cox proportional hazard models.ResultsOf 371,648 patients with a VL > 400, 83.9% (311,790) had a repeat VL, in a median (IQR) of 7.0 (4.1 to 12.2) months. Of those with a first viral load 400 to 1000 copies/mL, 56.4% had a repeat VL within guideline recommended six months (defined as up to nine months), whereas among those >1000 copies/mL only 47.7% had a repeat viral load within guideline recommended two to three months (defined as up to six months). We found a small increase in repeat testing associated with higher VL value (aHR 1.11; 95% CI: 1.10 to 1.12 comparing >1000 vs 400 to 1000 copies/mL) and very low CD4 counts at first elevated VL (aHR 1.16; 95% CI: 1.13 to 1.19 comparing CD4 < 50 vs <500 cells/mm3 ). We also found strong variation in time to repeat VL testing by province.ConclusionsMedian time to repeat viral load testing for those with an elevated viral load was longer than guidelines recommend. Future work should identify whether delays are due to patient or provider factors.
| S-EPMC7343337 | biostudies-literature
Project description:Wastewater based epidemiology (WBE) has become an important tool during the COVID-19 pandemic, however the relationship between SARS-CoV-2 RNA in wastewater treatment plant influent (WWTP) and cases in the community is not well-defined. We report here the development of a national WBE program across 28 WWTPs serving 50% of the population of Scotland, including large conurbations, as well as low-density rural and remote island communities. For each WWTP catchment area, we quantified spatial and temporal relationships between SARS-CoV-2 RNA in wastewater and COVID-19 cases. Daily WWTP SARS-CoV-2 influent viral RNA load, calculated using daily influent flow rates, had the strongest correlation (ρ > 0.9) with COVID-19 cases within a catchment. As the incidence of COVID-19 cases within a community increased, a linear relationship emerged between cases and influent viral RNA load. There were significant differences between WWTPs in their capacity to predict case numbers based on influent viral RNA load, with the limit of detection ranging from 25 cases for larger plants to a single case in smaller plants. SARS-CoV-2 viral RNA load can be used to predict the number of cases detected in the WWTP catchment area, with a clear statistically significant relationship observed above site-specific case thresholds.
| S-EPMC8577191 | biostudies-literature
Project description:BackgroundBronchiolitis is considered one of the earliest and most common causes of hospitalisation in young children. Development of molecular technologies allowed a better understanding of bronchiolitis aetiology. Results from cohort studies evaluating the association between single, multiple viral infections and clinical outcomes are conflicting. Data on viral bronchiolitis in children were found to be limited in Qatar. This study aimed to determine frequency and seasonal trends of viral pathogens causing acute bronchiolitis, and to explore association between viral pathogens, disease severity and length of stay (LOS).MethodsThis is a retrospective descriptive study, including children admitted in 2010 and 2011 with acute bronchiolitis. Presenting history, physical examination and respiratory viral co-infections as detected by molecular assays were analysed.ResultsAt least one virus was detected in 315/369 (85.4%) of included children with single and multiple viruses in 67 and 33% of cases respectively. Respiratory syncytial virus (RSV) was the most detected virus, accounting for 51.2% followed by rhinovirus (RV) in 25.5% of cases. Fall and summer admissions were associated with longer LOS. On multivariate logistic regression analysis, retraction (OR 3.96; 95% CI 1.64,9.59) and age group 1-3 months (OR 3.09; 95% CI 1.06,9.05) were associated with longer LOS. Crepitation (OR 9.15; 95% CI 1.58,53.13), retraction (OR 4.10; 95% CI 1.05,16.12) and respiratory rate (OR 1.46; 95% CI 1.28,1.66) were associated with moderate to severe bronchiolitis. Identifying the viral agent did not influence disease severity or LOS.ConclusionClinical presentation is of more relevance to LOS and disease severity than the detected viruses. Future studies should investigate the interplay between climate characteristics, population's factors and the most detectable circulating viruses.
| S-EPMC5307797 | biostudies-literature
Project description:Raw municipal wastewater from five wastewater treatment plants representing the vast majority of the Qatar population was sampled between the third week of June 2020 and the end of August 2020, during the period of declining cases after the peak of the first wave of infection in May 2020. The N1 region of the SARS-CoV-2 genome was used to quantify the viral load in the wastewater using RT-qPCR. The trend in Ct values in the wastewater samples mirrored the number of new daily positive cases officially reported for the country, confirmed by RT-qPCR testing of naso-pharyngeal swabs. SARS-CoV-2 RNA was detected in 100% of the influent wastewater samples (7889 ± 1421 copy/L - 542,056 ± 25,775 copy/L, based on the N1 assay). A mathematical model for wastewater-based epidemiology was developed and used to estimate the number of people in the population infected with COVID-19 from the N1 Ct values in the wastewater samples. The estimated number of infected population on any given day using the wastewater-based epidemiology approach declined from 542,313 ± 51,159 to 31,181 ± 3081 over the course of the sampling period, which was significantly higher than the officially reported numbers. However, seroprevalence data from Qatar indicates that diagnosed infections represented only about 10% of actual cases. The model estimates were lower than the corrected numbers based on application of a static diagnosis ratio of 10% to the RT-qPCR identified cases, which is assumed to be due to the difficulty in quantifying RNA losses as a model term. However, these results indicate that the presented WBE modeling approach allows for a realistic assessment of incidence trend in a given population, with a more reliable estimation of the number of infected people at any given point in time than can be achieved using human biomonitoring alone.
| S-EPMC7870436 | biostudies-literature