Browsing by Author "Hofman, Jan"

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    Making Waves: Collaboration in the time of SARS-CoV-2 - rapid development of an international co-operation and wastewater surveillance database to support public health decision-making
    (Elsevier, 2021-04-22) Lundy, Lian; Kassinos, Despo Fatta; Slobodnik, Jaroslav; Karaolia, Popi; Cirka, Lubos; Kreuzinger, Norbert; Castiglioni, Sara; Bijlsma, Lubertus; Dulio, Valeria; Deviller, Geneviève; Lai, Foon Yin; Barneo, Manuela; Baz-Lomba, Jose Antonio; Béen, Frederic; Cíchová, Marianna; Conde, Kelly; Covaci, Adrian; Donner, Erica; Ficek, Andrej; Hassard, Francis; Hedström, Annelie; Hernandez, Félix; Janská, Veronika; Hofman, Jan; Hill, Kelly
    The presence of SARS-CoV-2 RNA in wastewater was first reported in March 2020. Over the subsequent months, the potential for wastewater surveillance to contribute to COVID-19 mitigation programmes has been the focus of intense national and international research activities, gaining the attention of policy makers and the public. As a new application of an established methodology, focused collaboration between public health practitioners and wastewater researchers is essential to developing a common understanding on how, when and where the outputs of this non-invasive community-level approach can deliver actionable outcomes for public health authorities. Within this context, the NORMAN SCORE “SARS-CoV-2 in sewage” database provides a platform for rapid, open access data sharing, validated by the uploading of 276 data sets from nine countries to-date. Through offering direct access to underpinning meta-data sets (and describing its use in data interpretation), the NORMAN SCORE database is a resource for the development of recommendations on minimum data requirements for wastewater pathogen surveillance. It is also a tool to engage public health practitioners in discussions on use of the approach, providing an opportunity to build mutual understanding of the demand and supply for data and facilitate the translation of this promising research application into public health practice.
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    Monitoring occurrence of SARS-CoV-2 in school populations: a wastewater-based approach
    (PLOS (Public Library of Science), 2022-06-17) Castro-Gutierrez, Victor; Hassard, Francis; Vu, Milan; Leitao, Rodrigo; Burczynska, Beata; Wildeboer, Dirk; Stanton, Isobel; Rahimzadeh, Shadi; Baio, Gianluca; Garelick, Hemda; Hofman, Jan; Kasprzyk-Hordern, Barbara; Kwiatkowska, Rachel; Majeed, Azeem; Priest, Sally; Grimsley, Jasmine; Lundy, Lian; Singer, Andrew C.; Di Cesare, Mariachiara
    Clinical testing of children in schools is challenging, with economic implications limiting its frequent use as a monitoring tool of the risks assumed by children and staff during the COVID-19 pandemic. Here, a wastewater-based epidemiology approach has been used to monitor 16 schools (10 primary, 5 secondary and 1 post-16 and further education) in England. A total of 296 samples over 9 weeks have been analysed for N1 and E genes using qPCR methods. Of the samples returned, 47.3% were positive for one or both genes with a detection frequency in line with the respective local community. WBE offers a low cost, non-invasive approach for supplementing clinical testing and can provide longitudinal insights that are impractical with traditional clinical testing.
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    Wastewater monitoring for detection of public health markers during the COVID-19 pandemic: near-source monitoring of schools in England over an academic year
    (PLOS (Public Library of Science), 2023-05-30) Hassard, Francis; Vu, Milan; Rahimzadeh, Shadi; Castro-Gutierrez, Victor; Stanton, Isobel; Burczynska, Beata; Wildeboer, Dirk; Baio, Gianluca; Brown, Mathew R.; Garelick, Hemda; Hofman, Jan; Kasprzyk-Hordern, Barbara; Majeed, Azeem; Priest, Sally; Denise, Hubert; Khalifa, Mohammad; Bassano, Irene; Wade, Matthew J.; Grimsley, Jasmine; Lundy, Lian; Singer, Andrew C.; Di Cesare, Mariachiara
    Background: Schools are high-risk settings for infectious disease transmission. Wastewater monitoring for infectious diseases has been used to identify and mitigate outbreaks in many near-source settings during the COVID-19 pandemic, including universities and hospitals but less is known about the technology when applied for school health protection. This study aimed to implement a wastewater surveillance system to detect SARS-CoV-2 and other public health markers from wastewater in schools in England. Methods: A total of 855 wastewater samples were collected from 16 schools (10 primary, 5 secondary and 1 post-16 and further education) over 10 months of school term time. Wastewater was analysed for SARS-CoV-2 genomic copies of N1 and E genes by RT-qPCR. A subset of wastewater samples was sent for genomic sequencing, enabling determination of the presence of SARS-CoV-2 and emergence of variant(s) contributing to COVID-19 infections within schools. In total, >280 microbial pathogens and >1200 AMR genes were screened using RT-qPCR and metagenomics to consider the utility of these additional targets to further inform on health threats within the schools. Results: We report on wastewater-based surveillance for COVID-19 within English primary, secondary and further education schools over a full academic year (October 2020 to July 2021). The highest positivity rate (80.4%) was observed in the week commencing 30th November 2020 during the emergence of the Alpha variant, indicating most schools contained people who were shedding the virus. There was high SARS-CoV-2 amplicon concentration (up to 9.2x106 GC/L) detected over the summer term (8th June - 6th July 2021) during Delta variant prevalence. The summer increase of SARS-CoV-2 in school wastewater was reflected in age-specific clinical COVID-19 cases. Alpha variant and Delta variant were identified in the wastewater by sequencing of samples collected from December to March and June to July, respectively. Lead/lag analysis between SARS-CoV-2 concentrations in school and WWTP data sets show a maximum correlation between the two-time series when school data are lagged by two weeks. Furthermore, wastewater sample enrichment coupled with metagenomic sequencing and rapid informatics enabled the detection of other clinically relevant viral and bacterial pathogens and AMR. Conclusions: Passive wastewater monitoring surveillance in schools can identify cases of COVID-19. Samples can be sequenced to monitor for emerging and current variants of concern at the resolution of school catchments. Wastewater based monitoring for SARS-CoV-2 is a useful tool for SARS-CoV-2 passive surveillance and could be applied for case identification and containment, and mitigation in schools and other congregate settings with high risks of transmission. Wastewater monitoring enables public health authorities to develop targeted prevention and education programmes for hygiene measures within undertested communities across a broad range of use cases.