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Bringing COVID-19 home for Christmas: a need for enhanced testing in healthcare institutions after the holidays
David RM Smith; Audrey Duval; Jean Ralph Zahar; Lulla Opatowski; Laura Temime.
Affiliation
  • David RM Smith; Institut Pasteur / Inserm / UVSQ
  • Audrey Duval; Institut Pasteur / Inserm / UVSQ
  • Jean Ralph Zahar; Sorbonne Paris Cite
  • Lulla Opatowski; Institut Pasteur / Inserm / UVSQ
  • Laura Temime; Conservatoire National des Arts et Metiers
Preprint in En | PREPRINT-MEDRXIV | ID: ppmedrxiv-20248460
ABSTRACT
Festive gatherings this 2020 holiday season threaten to cause a surge in new cases of novel coronavirus disease 2019 (COVID-19). Hospitals and long-term care facilities are key hotspots for COVID-19 outbreaks, and may be at elevated risk as patients and staff return from holiday celebrations in the community. Some settings and institutions have proposed fortified post-holiday testing regimes to mitigate this risk. We use an existing model to assess whether implementing a single round of post-holiday screening is sufficient to detect and manage holiday-associated spikes in COVID-19 introductions to the long-term care setting. We show that while testing early helps to detect cases prior to potential onward transmission, it likely to miss a substantial share of introductions owing to false negative test results, which are more probable early in infection. We propose a two-stage post-holiday testing regime as a means to maximize case detection and mitigate the risk of nosocomial COVID-19 outbreaks into the start of the new year. Whether all patients and staff should be screened, or only community-exposed patients, depends on available testing capacity the former will be more effective, but also more resource-intensive.
License
cc_by_nc
Full text: 1 Collection: 09-preprints Database: PREPRINT-MEDRXIV Type of study: Diagnostic_studies / Prognostic_studies Language: En Year: 2020 Document type: Preprint
Full text: 1 Collection: 09-preprints Database: PREPRINT-MEDRXIV Type of study: Diagnostic_studies / Prognostic_studies Language: En Year: 2020 Document type: Preprint