A Flexible Smoother Adapted to Censored Data With Outliers and Its Application to SARS-CoV-2 Monitoring in Wastewater Article Swipe
Marie Courbariaux
,
Nicolas Cluzel
,
Siyun Wang
,
Vincent Maréchal
,
Laurent Moulin
,
Sébastien Wurtzer
,
Jean‐Marie Mouchel
,
Yvon Maday
,
Grégory Nuel
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3389/fams.2022.836349
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3389/fams.2022.836349
A sentinel network, Obépine , has been designed to monitor SARS-CoV-2 viral load in wastewaters arriving at wastewater treatment plants (WWTPs) in France as an indirect macro-epidemiological parameter. The sources of uncertainty in such a monitoring system are numerous, and the concentration measurements it provides are left-censored and contain outliers, which biases the results of usual smoothing methods. Hence, the need for an adapted pre-processing in order to evaluate the real daily amount of viruses arriving at each WWTP. We propose a method based on an auto-regressive model adapted to censored data with outliers. Inference and prediction are produced via a discretized smoother which makes it a very flexible tool. This method is both validated on simulations and real data from Obépine . The resulting smoothed signal shows a good correlation with other epidemiological indicators and is currently used by Obépine to provide an estimate of virus circulation over the watersheds corresponding to about 200 WWTPs.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fams.2022.836349
- https://www.frontiersin.org/articles/10.3389/fams.2022.836349/pdf
- OA Status
- gold
- Cited By
- 16
- References
- 22
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4225598388
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4225598388Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3389/fams.2022.836349Digital Object Identifier
- Title
-
A Flexible Smoother Adapted to Censored Data With Outliers and Its Application to SARS-CoV-2 Monitoring in WastewaterWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-02-09Full publication date if available
- Authors
-
Marie Courbariaux, Nicolas Cluzel, Siyun Wang, Vincent Maréchal, Laurent Moulin, Sébastien Wurtzer, Jean‐Marie Mouchel, Yvon Maday, Grégory NuelList of authors in order
- Landing page
-
https://doi.org/10.3389/fams.2022.836349Publisher landing page
- PDF URL
-
https://www.frontiersin.org/articles/10.3389/fams.2022.836349/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.frontiersin.org/articles/10.3389/fams.2022.836349/pdfDirect OA link when available
- Concepts
-
Outlier, Smoothing, Inference, Computer science, Anomaly detection, Statistics, Environmental science, Data mining, Mathematics, Artificial intelligenceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
16Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 3, 2023: 4, 2022: 7Per-year citation counts (last 5 years)
- References (count)
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22Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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