Evidence map›Paper›PMID 35462206›Full record

ArticleEpidemics2022

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

Shokoofeh Nourbakhsh, Aamir Fazil, Michael Li, Chand S Mangat, Shelley W Peterson, Jade Daigle, Stacie Langner, Jayson Shurgold, Patrick D'Aoust, Robert Delatolla and 6 more

Open access · goldAbstract read
In one paragraph

Article in Epidemics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 2 pooled it
11.7field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

52 citing papers in PubMed, 2 syntheses or guidelines pooled it, 118 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Review
  6. Article
  7. Economic evaluation of wastewater surveillance in Ontario, Canada, using COVID-19 as a case study.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2026
    Article
  8. Comparing Wastewater-Based and Case-BasedEpidemiology and infection · 2026
    Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Mathematical modelling for pandemic preparedness in Canada: Learning from COVID-19.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2024
    Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 4 institutions in 1 country.

Shokoofeh NourbakhshPublic Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON, Canada.
Aamir FazilPublic Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON, Canada.
Michael LiPublic Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON, Canada.
Chand S MangatOne Health Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada.
Shelley W PetersonOne Health Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada.
Jade DaigleOne Health Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada.
Stacie LangnerOne Health Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada.
Jayson ShurgoldAntimicrobial Resistance Division, Infectious Diseases Prevention and Control Branch, Public Health Agency of Canada, Ottawa, ON, Canada.
Patrick D'AoustUniversity of Ottawa, Department of Civil Engineering, Ottawa, ON, Canada.
Robert DelatollaUniversity of Ottawa, Department of Civil Engineering, Ottawa, ON, Canada.
Elizabeth MercierUniversity of Ottawa, Department of Civil Engineering, Ottawa, ON, Canada.
Xiaoli PangPublic Health Laboratory, Alberta Precision Laboratory, Edmonton, AB, Canada; Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB, Canada.
Bonita E LeeDepartment of Pediatrics, University of Alberta, Edmonton, AB, Canada.
Rebecca StuartToronto Public Health, Toronto, ON, Canada.
Shinthuja WijayasriToronto Public Health, Toronto, ON, Canada; Canadian Field Epidemiology Program, Emergency Management, Public Health Agency of Canada, Canada.
David ChampredonPublic Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON, Canada. Electronic address: david.champredon@canada.ca.
Public Health Agency of Canada · CAUniversity of Ottawa · CAUniversity of Alberta · CAToronto Public Health · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

COVID-19SARS-CoV-2CanadaCitiesHumansPandemicsRNA, ViralWastewaterRNA, ViralWastewaterEnvironmental surveillanceEpidemic modelSARS-CoV-2/COVID-19Wastewater

Identifiers

PMID35462206
PMCPMC8993419
OpenAlexW4225310480

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.