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Identification of multiple potential viral diseases in a large urban center using wastewater surveillance.

ABSTRACT: 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.

SUBMITTER: McCall C

PROVIDER: S-EPMC7342010 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Identification of multiple potential viral diseases in a large urban center using wastewater surveillance.

McCall Camille C Wu Huiyun H Miyani Brijen B Xagoraraki Irene I

Water research 20200707

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 ...[more]

PMID: 32738707

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Project description:The early warning and tracking of COVID-19 prevalence in the community provided by wastewater surveillance has highlighted its potential for much broader viral disease surveillance. In this proof-of-concept study, 46 wastewater samples from four wastewater treatment plants (WWTPs) in Queensland, Australia, were analyzed for the presence and abundance of 13 respiratory viruses, and the results were compared with reported clinical cases. The viruses were concentrated using the adsorption-extraction (AE) method, and extracted nucleic acids were analyzed using qPCR and RT-qPCR. Among the viruses tested, bocavirus (BoV), parechovirus (PeV), rhinovirus A (RhV A) and rhinovirus B (RhV B) were detected in all wastewater samples. All the tested viruses except influenza B virus (IBV) were detected in wastewater sample from at least one WWTP. BoV was detected with the greatest concentration (4.96-7.22 log10 GC/L), followed by Epstein-Barr virus (EBV) (4.08-6.46 log10 GC/L), RhV A (3.95-5.63 log10 GC/L), RhV B (3.74-5.61 log10 GC/L), and PeV (3.17-5.32 log10 GC/L). Influenza viruses and respiratory syncytial virus (RSV) are notifiable conditions in Queensland, allowing the gene copy (GC) concentrations to be compared with reported clinical cases. Significant correlations (ρ = 0.60, p < 0.01 for IAV and ρ = 0.53, p < 0.01 for RSV) were observed when pooled wastewater influenza A virus (IAV) and RSV log10 GC/L concentrations were compared to log10 clinical cases among the four WWTP catchments. The positive predictive value for the presence of IAV and RSV in wastewater was 97 % for both IAV and RSV clinical cases within the four WWTP catchments. The overall accuracy of wastewater analysis for predicting clinical cases of IAV and RSV was 97 and 90 %, respectively. This paper lends credibility to the application of wastewater surveillance to monitor respiratory viruses of various genomic characteristics, with potential uses for increased surveillance capabilities and as a tool in understanding the dynamics of disease circulation in the communities.

Project description:BACKGROUND:The Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey is the first publicly reported nationwide survey to evaluate and compare hospitals. Increasing patient satisfaction is an important goal as it aims to achieve a more effective and efficient healthcare delivery system. In this study, we develop and apply an integrative, data-driven approach to identify clinical risk factors that associate with patient satisfaction outcomes. METHODS:We included 1,771 unique adult patients who completed the HCAHPS survey and were discharged from the inpatient Medicine service from 2010 to 2012. We collected 266 clinical features including patient demographics, lab measurements, medications, disease categories, and procedures. We developed and applied a data-driven approach to identify risk factors that associate with patient satisfaction outcomes. FINDINGS:We identify 102 significant risk factors associating with 18 surveyed questions. The most significantly recurrent clinical risk factors were: self-evaluation of health, education level, Asian, White, treatment in BMT oncology division, being prescribed a new medication. Patients who were prescribed pregabalin were less satisfied particularly in relation to communication with nurses and pain management. Explanation of medication usage was associated with communication with nurses (q = 0.001); however, explanation of medication side effects was associated with communication with doctors (q = 0.003). Overall hospital rating was associated with hospital environment, communication with doctors, and communication about medicines. However, patient likelihood to recommend hospital was associated with hospital environment, communication about medicines, pain management, and communication with nurse. CONCLUSIONS:Our study identified a number of putatively novel clinical risk factors for patient satisfaction that suggest new opportunities to better understand and manage patient satisfaction. Hospitals can use a data-driven approach to identify clinical risk factors for poor patient satisfaction to support development of specific interventions to improve patients' experience of care.

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Identification of multiple potential viral diseases in a large urban center using wastewater surveillance.

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Identification of multiple potential viral diseases in a large urban center using wastewater surveillance.

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