ArticleGates open research2024
Stakeholder Interviews to Inform Best Practice for Public Facing COVID-19 Wastewater Dashboards.
Article in Gates open research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Communicating wastewater-based surveillance data to drive action.Journal of water and health · 2025Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Wastewater (WW) -based epidemiology is the detection of pathogens and chemicals from wastewater, typically sewage systems. Its use gained popularity during the COVID-19 pandemic as a rapid and non-invasive way to assess infection prevalence in a population. Public facing dashboards for SARS-CoV-2 were developed in response to the discovery that RNA biomarkers were being shed in faeces before symptoms. However, there is not a standard template or guidance for countries to follow. The aim of this research is to reflect on how currently available dashboards evolved during the pandemic and identify suitable content and rationale from these experiences. Methods: Interviews were carried out with implementers and users of dashboards for SARS-CoV-2 WW data across Europe and North America. The interviews addressed commonalities and inconsistencies in displaying epidemiological data of SARS-CoV-2, clinical parameters of COVID-19, data on variants, and data transparency. Results: The thematic analysis identified WW dashboard elements that can facilitate standardization, or at least interoperability. These elements emphasise communication among developers under the same organization, open access for identified stakeholders, and data summarized with a time-intensive graphic analysis through normalizing at least by population. Simultaneous communication of clinical surveillance is recommended. More research is needed on flow and faecal indicators for normalization of WW data, and on the analysis and representation of variants. Discussion: WW dashboard development between 2020-2023 provided a 'real-time' iterative process of data representation, and several recommendations have been identified. Communication of data through dashboards has the potential to support early warning systems for infectious diseases.
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Registered trials
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