Detection of Covid-19 Outbreaks Using Built Environment Testing for SARS-CoV-2 Article Swipe
Michael Fralick
,
Caroline Nott
,
Jason Moggridge
,
Lucas Castellani
,
Ashley Raudanskis
,
David S. Guttman
,
Aaron Hinz
,
Nisha Thampi
,
Alex Wong
,
Douglas G. Manuel
,
Allison McGeer
,
Evgueni Doukhanine
,
Hebah Mejbel
,
Veronica Zanichelli
,
Madison Burella
,
Sylva L. Donaldson
,
Pauline W. Wang
,
Rees Kassen
,
Derek R. MacFadden
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1056/evidoa2200203
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1056/evidoa2200203
BACKGROUND: Environmental surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through wastewater has become a useful tool for population-level surveillance. Built environment sampling may provide a more spatially refined approach for surveillance in congregate living settings. METHODS: We conducted a prospective study in 10 long-term care homes (LTCHs) between September 2021 and November 2022. Floor surfaces were sampled weekly at multiple locations within each building and analyzed for the presence of SARS-CoV-2 using quantitative reverse transcriptase polymerase chain reaction. The primary outcome was the presence of a coronavirus disease 2019 (Covid-19) outbreak in the week that floor sampling was performed. RESULTS: Over the 14-month study period, we collected 4895 swabs at 10 LTCHs. During the study period, 23 Covid-19 outbreaks occurred with 119 cumulative weeks under outbreak. During outbreak periods, the proportion of floor swabs that were positive for SARS-CoV-2 was 54.3% (95% confidence interval [CI], 52 to 56.6), and during non-outbreak periods it was 22.3% (95% CI, 20.9 to 23.8). Using the proportion of floor swabs positive for SARS-CoV-2 to predict Covid-19 outbreak status in a given week, the area under the receiver-operating characteristic curve was 0.84 (95% CI, 0.78 to 0.9). Among 10 LTCHs with an outbreak and swabs performed in the prior week, eight had positive floor swabs exceeding 10% at least 5 days before outbreak identification. For seven of these eight LTCHs, positivity of floor swabs exceeded 10% more than 10 days before the outbreak was identified. CONCLUSIONS: Detection of SARS-CoV-2 on floors is strongly associated with Covid-19 outbreaks in LTCHs. These data suggest a potential role for floor sampling in improving early outbreak identification.
Related Topics
Concepts
Outbreak
Medicine
Coronavirus disease 2019 (COVID-19)
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
Confidence interval
Population
Coronavirus
Veterinary medicine
Emergency medicine
Virology
Internal medicine
Environmental health
Disease
Infectious disease (medical specialty)
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1056/evidoa2200203
- https://evidence.nejm.org/doi/pdf/10.1056/EVIDoa2200203
- OA Status
- bronze
- Cited By
- 11
- References
- 21
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4321203127
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4321203127Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1056/evidoa2200203Digital Object Identifier
- Title
-
Detection of Covid-19 Outbreaks Using Built Environment Testing for SARS-CoV-2Work title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-02-17Full publication date if available
- Authors
-
Michael Fralick, Caroline Nott, Jason Moggridge, Lucas Castellani, Ashley Raudanskis, David S. Guttman, Aaron Hinz, Nisha Thampi, Alex Wong, Douglas G. Manuel, Allison McGeer, Evgueni Doukhanine, Hebah Mejbel, Veronica Zanichelli, Madison Burella, Sylva L. Donaldson, Pauline W. Wang, Rees Kassen, Derek R. MacFaddenList of authors in order
- Landing page
-
https://doi.org/10.1056/evidoa2200203Publisher landing page
- PDF URL
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https://evidence.nejm.org/doi/pdf/10.1056/EVIDoa2200203Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://evidence.nejm.org/doi/pdf/10.1056/EVIDoa2200203Direct OA link when available
- Concepts
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Outbreak, Medicine, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Confidence interval, Population, Coronavirus, Veterinary medicine, Emergency medicine, Virology, Internal medicine, Environmental health, Disease, Infectious disease (medical specialty)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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11Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3, 2024: 6, 2023: 2Per-year citation counts (last 5 years)
- References (count)
-
21Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| publication_year | 2023 |
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| abstract_inverted_index.52 | 147 |
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| abstract_inverted_index.10% | 213, 232 |
| abstract_inverted_index.119 | 123 |
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| abstract_inverted_index.and | 52, 66, 150, 200 |
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| abstract_inverted_index.with | 122, 197, 251 |
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| abstract_inverted_index.2022. | 54 |
| abstract_inverted_index.22.3% | 156 |
| abstract_inverted_index.54.3% | 142 |
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| abstract_inverted_index.Floor | 55 |
| abstract_inverted_index.LTCHs | 196 |
| abstract_inverted_index.These | 256 |
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| abstract_inverted_index.LTCHs, | 226 |
| abstract_inverted_index.LTCHs. | 113, 255 |
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| abstract_inverted_index.disease | 89 |
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| abstract_inverted_index.period, | 106, 117 |
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| abstract_inverted_index.reverse | 75 |
| abstract_inverted_index.sampled | 58 |
| abstract_inverted_index.suggest | 258 |
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| abstract_inverted_index.14-month | 104 |
| abstract_inverted_index.Covid-19 | 119, 173, 252 |
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| abstract_inverted_index.periods, | 130 |
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| abstract_inverted_index.presence | 70, 85 |
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| abstract_inverted_index.exceeding | 212 |
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| abstract_inverted_index.outbreaks | 120, 253 |
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| abstract_inverted_index.potential | 260 |
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| abstract_inverted_index.settings. | 36 |
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| abstract_inverted_index.(Covid-19) | 91 |
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| abstract_inverted_index.wastewater | 12 |
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| countries_distinct_count | 2 |
| institutions_distinct_count | 19 |
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