Population surveillance approach to detect and respond to new clusters of COVID-19
- DOI
- Language of the publication
- English
- Date
- 2021-06
- Type
- Article
- Author(s)
- Rees, Erin E.
- Rodin, Rachel
- Ogden, Nicholas H.
- Publisher
- Public Health Agency of Canada
Abstract
BACKGROUND: To maintain control of the coronavirus disease 2019 (COVID-19) epidemic as lockdowns are lifted, it will be crucial to enhance alternative public health measures. For surveillance, it will be necessary to detect a high proportion of any new cases quickly so that they can be isolated, and people who have been exposed to them traced and quarantined. Here we introduce a mathematical approach that can be used to determine how many samples need to be collected per unit area and unit time to detect new clusters of COVID-19 cases at a stage early enough to control an outbreak. METHODS: We present a sample size determination method that uses a relative weighted approach. Given the contribution of COVID-19 test results from sub-populations to detect the disease at a threshold prevalence level to control the outbreak to 1) determine if the expected number of weekly samples provided from current healthcare-based surveillance for respiratory virus infections may provide a sample size that is already adequate to detect new clusters of COVID-19 and, if not, 2) to determine how many additional weekly samples were needed from volunteer sampling. RESULTS: In a demonstration of our method at the weekly and Canadian provincial and territorial (P/T) levels, we found that only the more populous P/T have sufficient testing numbers from healthcare visits for respiratory illness to detect COVID-19 at our target prevalence level—assumed to be high enough to identify and control new clusters. Furthermore, detection of COVID-19 is most efficient (fewer samples required) when surveillance focuses on healthcare symptomatic testing demand. In the volunteer populations: the higher the contact rates; the higher the expected prevalence level; and the fewer the samples were needed to detect COVID-19 at a predetermined threshold level. CONCLUSION: This study introduces a targeted surveillance strategy, combining both passive and active surveillance samples, to determine how many samples to collect per unit area and unit time to detect new clusters of COVID-19 cases. The goal of this strategy is to allow for early enough detection to control an outbreak.
Subject
- Health
Keywords
- Surveillance,
- Detection,
- COVID-19,
- Mathematical approach
Rights
Pagination
243-250
Peer review
Yes
Identifiers
- PubMed ID
- 34220348
- ISSN
- 1481-8531
Article
- Journal title
- Canada Communicable Disease Report
- Journal volume
- 47
- Journal issue
- 5-6
Relation
- Is translation of:
- https://open-science.canada.ca/handle/123456789/2997
Citation(s)
Rees EE, Rodin R, Ogden NH. Population surveillance approach to detect and respond to new clusters of COVID-19. Can Commun Dis Rep. 2021 Jun 9;47(56):243-250. doi: 10.14745/ccdr.v47i56a01.