Predicting COVID-19 Incidence Using Wastewater Surveillance Data, Denmark, October 2021–June 2022

Details

• Alternative Title:
  Emerg Infect Dis
• Personal Author:
  McManus, Oliver ; Christiansen, Lasse Engbo ; Nauta, Maarten ; Krogsgaard, Lene Wulff ; Bahrenscheer, Naja Stolberg ; von Kappelgaard, Lene ; Christiansen, Tobias ; Hansen, Mikkel ; Hansen, Nicco Claudio ; Kähler, Jonas ; Rasmussen, Anders ; Richter, Stine Raith ; Rasmussen, Lasse Dam ; Franck, Kristina Træholt ; Ethelberg, Steen
• Description:
  Analysis of wastewater is used in many settings for surveillance of SARS-CoV-2, but it remains unclear how well wastewater testing results reflect incidence. Denmark has had an extensive wastewater analysis system that conducts 3 weekly tests in ≈200 sites and has 85% population coverage; the country also offers free SARS-CoV-2 PCR tests to all residents. Using time series analysis for modeling, we found that wastewater data, combined with information on circulating variants and the number of human tests performed, closely fitted the incidence curve of persons testing positive. The results were consistent at a regional level and among a subpopulation of frequently tested healthcare personnel. We used wastewater analysis data to estimate incidence after testing was reduced to a minimum after March 2022. These results imply that data from a large-scale wastewater surveillance system can serve as a good proxy for COVID-19 incidence and for epidemic control.
• Subjects:
  Coronavirus Disease COVID-19 Denmark Epidemiological Methods Epidemiological Models Epidemiological Monitoring Epidemiology Humans Incidence Predicting COVID-19 Incidence Using Wastewater Surveillance Data, Denmark, October 2021–June 2022 Research Respiratory Infections RNA, Viral SARS-CoV-2 Severe Acute Respiratory Syndrome Coronavirus 2 Time Series Viruses Wastewater Wastewater-Based Epidemiological Monitoring Wastewater Surveillance Zoonoses

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• Source:
  Emerg Infect Dis. 2023; 29(8):1589-1597
• Pubmed ID:
  37486168
• Pubmed Central ID:
  PMC10370843
• Document Type:
  Journal Article
• Volume:
  29
• Issue:
  8
• Collection(s):
  Emerging Infectious Diseases
• Main Document Checksum:
  urn:sha256:c36534362c7130fb6a11f456703cf0021d232a027cc312b2fe00b8665163b43b
• Download URL:
  https://stacks.cdc.gov/view/cdc/132601/cdc_132601_DS1.pdf
• File Type:
  [PDF - 1.40 MB ]