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Setting a baseline for global urban virome surveillance in sewage.

ABSTRACT: The rapid development of megacities, and their growing connectedness across the world is becoming a distinct driver for emerging disease outbreaks. Early detection of unusual disease emergence and spread should therefore include such cities as part of risk-based surveillance. A catch-all metagenomic sequencing approach of urban sewage could potentially provide an unbiased insight into the dynamics of viral pathogens circulating in a community irrespective of access to care, a potential which already has been proven for the surveillance of poliovirus. Here, we present a detailed characterization of sewage viromes from a snapshot of 81 high density urban areas across the globe, including in-depth assessment of potential biases, as a proof of concept for catch-all viral pathogen surveillance. We show the ability to detect a wide range of viruses and geographical and seasonal differences for specific viral groups. Our findings offer a cross-sectional baseline for further research in viral surveillance from urban sewage samples and place previous studies in a global perspective.

SUBMITTER: Nieuwenhuijse DF

PROVIDER: S-EPMC7426863 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: Endemic and seasonally recurring respiratory viruses are a major cause of disease and death globally. The burden is particularly severe in developing countries. Improved understanding of the source of infection, pathways of spread and persistence in communities would be of benefit in devising intervention strategies. Methods: We report epidemiological data obtained through surveillance of respiratory viruses at nine outpatient health facilities within the Kilifi Health and Demographic Surveillance System, Kilifi County, coastal Kenya, between January and December 2016. Nasopharyngeal swabs were collected from individuals of all ages presenting with acute respiratory infection (ARI) symptoms (up to 15 swabs per week per facility) and screened for 15 respiratory viruses using real-time PCR. Paediatric inpatient surveillance at Kilifi County Hospital for respiratory viruses provided comparative data. Results: Over the year, 5,647 participants were sampled, of which 3,029 (53.7%) were aged <5 years. At least one target respiratory virus was detected in 2,380 (42.2%) of the samples; the most common being rhinovirus 18.6% (1,050), influenza virus 6.9% (390), coronavirus 6.8% (387), parainfluenza virus 6.6% (371), respiratory syncytial virus (RSV) 3.9% (219) and adenovirus 2.7% (155). Virus detections were higher among <5-year-olds compared to older children and adults (50.3% vs 32.7%, respectively; χ 2(1) =177.3, P=0.0001). Frequency of viruses did not differ significantly by facility (χ 2(8) =13.38, P=0.072). However, prevalence was significantly higher among inpatients than outpatients in <5-year-olds for RSV (22.1% vs 6.0%; χ 2(1) = 159.4, P=0.0001), and adenovirus (12.4% vs 4.4%, χ 2(1) =56.6, P=0.0001). Conclusions: Respiratory virus infections are common amongst ARI outpatients in this coastal Kenya setting, particularly in young children. Rhinovirus predominance warrants further studies on the health and socio-economic implications. RSV and adenovirus were more commonly associated with severe disease. Further analysis will explore epidemiological transmission patterns with the addition of virus sequence data.

Project description:Understanding disease burden and transmission dynamics in resource-limited, low-income countries like Nepal are often challenging due to inadequate surveillance systems. These issues are exacerbated by limited access to diagnostic and research facilities throughout the country. Nepal has one of the highest COVID-19 case rates (915 cases per 100,000 people) in South Asia, with densely-populated Kathmandu experiencing the highest number of cases. Swiftly identifying case clusters (hotspots) and introducing effective intervention programs is crucial to mounting an effective containment strategy. The rapid identification of circulating SARS-CoV-2 variants can also provide important information on viral evolution and epidemiology. Genomic-based environmental surveillance can help in the early detection of outbreaks before clinical cases are recognized and identify viral micro-diversity that can be used for designing real-time risk-based interventions. This research aimed to develop a genomic-based environmental surveillance system by detecting and characterizing SARS-CoV-2 in sewage samples of Kathmandu using portable next-generation DNA sequencing devices. Out of 22 sites in the Kathmandu Valley from June to August 2020, sewage samples from 16 (80%) sites had detectable SARS-CoV-2. A heatmap was created to visualize the presence of SARS-CoV-2 infection in the community based on viral load intensity and corresponding geospatial data. Further, 47 mutations were observed in the SARS-CoV-2 genome. Some detected mutations (n = 9, 22%) were novel at the time of data analysis and yet to be reported in the global database, with one indicating a frameshift deletion in the spike gene. SNP analysis revealed possibility of assessing circulating major/minor variant diversity on environmental samples based on key mutations. Our study demonstrated the feasibility of rapidly obtaining vital information on community transmission and disease dynamics of SARS-CoV-2 using genomic-based environmental surveillance.

Project description:In low prevalence settings the development of sensitive and specific quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR) tests to detect SARS-CoV-2 (the virus causing COVID-19) in sewage presents the possibility of using sewage sampling as a diagnostic test for the presence of infected people in the catchment of the sampled sewer. However, the usefulness of such surveillance has not been quantified. In this study in the Australian state of Victoria between August and October 2020 the location of each known SARS-CoV-2-infected person was determined on each day from two days before onset to 55 days after, in 46 metropolitan and rural sewer catchments sampled weekly – a total of 71 positive and 275 negative samples, and 354,155 person-days of location data. These were categorised by time since onset and distance from the sampling site. The odds of detection in sewage were between 5 and 20 times higher where known cases were present, with less effect of distance than time since onset. Using positive qRT-PCR in a sewage sample as a diagnostic test not just for viral RNA in the sample, but for the presence of known infected people in the catchment on the same day, the sensitivity was moderate (31% to 76%) and the specificity high (87% to 94%). The odds of detection were increased with increased numbers of known infected people but decreased with increased distance and time since onset. The probability of detection of the viral subgenome in sewage samples was about 10% when one known infected person was present, and this increased with higher numbers of known infected people and greater proximity to the sampling site. Sewage surveillance can be used to detect people infected with SARS-CoV-2 in the catchment, directing a search for infectious clinical cases and other public health actions. However, detection at least eight weeks after onset may be due to existing cases rather than new ones, and, although not zero, the probability of detecting a single case is low. Graphical abstract Unlabelled Image

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Setting a baseline for global urban virome surveillance in sewage.

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