A wastewater-based epidemic model for SARS-CoV-2 with application to three Canadian cities

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creativework.keywords - en
COVID-19* / epidemiology
Canada / epidemiology
Cities / epidemiology
Humans
Pandemics
RNA, Viral
SARS-CoV-2*
Wastewater
dc.contributor.author
Nourbakhsh, Shokoofeh
Fazil, Aamir
Li, Michael
Mangat, Chand S.
Peterson, Shelley W.
Daigle, Jade
Langner, Stacie
Shurgold, Jayson
D'Aoust, Patrick
Delatolla, Robert
Mercier, Elizabeth
Pang, Xiaoli
Lee, Bonita E.
Stuart, Rebecca
Wijayasri, Shinthuja
Champredon, David
dc.date.accessioned
2024-03-08T19:55:05Z
dc.date.available
2024-03-08T19:55:05Z
dc.date.issued
2022-04-08
dc.description.abstract - en
The COVID-19 pandemic has stimulated wastewater-based surveillance, allowing public health to track the epidemic by monitoring the concentration of the genetic fingerprints of SARS-CoV-2 shed in wastewater by infected individuals. Wastewater-based surveillance for COVID-19 is still in its infancy. In particular, the quantitative link between clinical cases observed through traditional surveillance and the signals from viral concentrations in wastewater is still developing and hampers interpretation of the data and actionable public-health decisions. We present a modelling framework that includes both SARS-CoV-2 transmission at the population level and the fate of SARS-CoV-2 RNA particles in the sewage system after faecal shedding by infected persons in the population. Using our mechanistic representation of the combined clinical/wastewater system, we perform exploratory simulations to quantify the effect of surveillance effectiveness, public-health interventions and vaccination on the discordance between clinical and wastewater signals. We also apply our model to surveillance data from three Canadian cities to provide wastewater-informed estimates for the actual prevalence, the effective reproduction number and incidence forecasts. We find that wastewater-based surveillance, paired with this model, can complement clinical surveillance by supporting the estimation of key epidemiological metrics and hence better triangulate the state of an epidemic using this alternative data source.
dc.identifier.citation
Nourbakhsh S, Fazil A, Li M, et al. A wastewater-based epidemic model for SARS-CoV-2 with application to three Canadian cities. Epidemics. 2022;39:100560. doi:https://doi.org/10.1016/j.epidem.2022.100560
dc.identifier.doi
https://doi.org/10.1016/j.epidem.2022.100560
dc.identifier.uri
https://open-science.canada.ca/handle/123456789/2041
dc.language.iso
en
dc.publisher
Elsevier
dc.rights - en
Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.rights - fr
Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.rights.openaccesslevel - en
Gold
dc.rights.openaccesslevel - fr
Or
dc.rights.uri - en
https://creativecommons.org/licenses/by/4.0/
dc.rights.uri - fr
https://creativecommons.org/licenses/by/4.0/deed.fr
dc.subject - en
Health
dc.subject - fr
Santé
dc.subject.en - en
Health
dc.subject.fr - fr
Santé
dc.title - en
A wastewater-based epidemic model for SARS-CoV-2 with application to three Canadian cities
dc.type - en
Article
dc.type - fr
Article
local.acceptedmanuscript.articlenum
100560
local.article.journaltitle
Epidemics
local.article.journalvolume
39 (2022)
local.peerreview - en
Yes
local.peerreview - fr
Oui
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