Assessing the impact of varying levels of case detection and contact tracing on COVID-19 transmission in Canada during lifting of restrictive closures using a dynamic compartmental mode

Ludwig, Antoinette; Berthiaume, Philippe; Orpana, Heather; Nadeau, Claude; Diasparra, Maikol; Barnes, Joel; Hennessy, Deirdre; Otten, Ainsley; Ogden, Nicholas

doi:https://open-science.canada.ca/handle/123456789/2513

Assessing the impact of varying levels of case detection and contact tracing on COVID-19 transmission in Canada during lifting of restrictive closures using a dynamic compartmental mode

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creativework.keywords - en: Covid-19; case detection; contact tracing; dynamic compartmental model; Canada
dc.contributor.author: Ludwig, Antoinette; Berthiaume, Philippe; Orpana, Heather; Nadeau, Claude; Diasparra, Maikol; Barnes, Joel; Hennessy, Deirdre; Otten, Ainsley; Ogden, Nicholas
dc.date.accessioned: 2024-05-24T17:25:08Z
dc.date.available: 2024-05-24T17:25:08Z
dc.date.issued: 2020-11-05
dc.description - en: The objectives of this paper are to present an aged-stratified dynamic compartmental model developed by the Public Health Agency of Canada in collaboration with Statistics Canada and to model the impact of non-pharmaceutical interventions on the attack rate of COVID-19 infection in Canada. This model simulates the impact of different levels of non-pharmaceutical interventions, including case detection/isolation, contact tracing/quarantine and changes in the level of physical distancing in Canada, as restrictive closures began to be lifted in May 2020. This model allows us to highlight the importance of a relatively high level of detection and isolation of cases, as well as tracing and quarantine of individuals in contact with those cases, in order to avoid a resurgence of the epidemic in Canada as restrictive closures are lifted. Some level of physical distancing by the public will also likely need to be maintained. This study underlines the importance of a cautious approach to lifting restrictive closures in this second phase of the epidemic. This approach includes efforts by public health to identify cases and trace contacts, and to encourage Canadians to get tested if they are at risk of having been infected and to maintain physical distancing in public areas.
dc.description.abstract - en: BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic began with a detected cluster of pneumonia cases in Wuhan, China in December 2019. Endemic transmission was recognized in Canada in early February 2020, making it urgent for public health stakeholders to have access to robust and reliable tools to support decision-making for epidemic management. The objectives of this paper are to present one of these tools—an aged-stratified dynamic compartmental model developed by the Public Health Agency of Canada in collaboration with Statistics Canada—and to model the impact of non-pharmaceutical interventions on the attack rate of COVID-19 infection in Canada. METHODS: This model simulates the impact of different levels of non-pharmaceutical interventions, including case detection/isolation, contact tracing/quarantine and changes in the level of physical distancing in Canada, as restrictive closures began to be lifted in May 2020. RESULTS: This model allows us to highlight the importance of a relatively high level of detection and isolation of cases, as well as tracing and quarantine of individuals in contact with those cases, in order to avoid a resurgence of the epidemic in Canada as restrictive closures are lifted. Some level of physical distancing by the public will also likely need to be maintained. CONCLUSION: This study underlines the importance of a cautious approach to lifting restrictive closures in this second phase of the epidemic. This approach includes efforts by public health to identify cases and trace contacts, and to encourage Canadians to get tested if they are at risk of having been infected and to maintain physical distancing in public areas.
dc.description.abstract-fosrctranslation - fr: CONTEXTE : La pandémie de coronavirus de 2019 (COVID-19) a commencé avec un agrégat de cas de pneumonie détectés à Wuhan, en Chine, en décembre 2019. La transmission endémique a été reconnue au Canada au début de février 2020. Il était donc urgent que les intervenants en santé publique aient accès à des outils robustes et fiables pour soutenir la prise de décisions en matière de gestion des épidémies. Le présent document vise à présenter l’un de ces outils – un modèle compartimental dynamique stratifié en fonction de l’âge élaboré par l’Agence de la santé publique du Canada en collaboration avec Statistique Canada – et à modéliser l’impact des interventions non pharmaceutiques sur le taux d’attaque des infections à la COVID-19 au Canada. MÉTHODES : Ce modèle simule l’impact de niveaux variés d’interventions non pharmaceutiques, incluant la détection et l’isolement des cas, la recherche des contacts et la quarantaine ainsi que les changements de niveau de distanciation physique au Canada, alors que les fermetures imposées ont commencé à être levées en mai 2020. RÉSULTATS : Ce modèle nous permet de souligner l’importance d’un niveau relativement élevé de détection et d’isolement des cas, ainsi que de la recherche et de la mise en quarantaine des personnes en contact avec ces cas, afin d’éviter une résurgence de l’épidémie au Canada à mesure que les fermetures imposées sont levées. Il faudra probablement aussi qu’un certain niveau de distanciation physique soit maintenu par le public. CONCLUSION : Cette étude souligne l’importance d’appliquer une approche prudente lors de la levée des fermetures imposées dans cette deuxième phase de l’épidémie. Cette approche comprend des efforts de la santé publique pour recenser les cas et rechercher les contacts, ainsi que pour encourager les Canadiens à passer un test de dépistage s’ils risquent d’être infectés et à maintenir une distance physique dans les zones publiques.
dc.identifier.citation: Ludwig A, Berthiaume P, Orpana H, et al. Assessing the impact of varying levels of case detection and contact tracing on COVID-19 transmission in Canada during lifting of restrictive closures using a dynamic compartmental model. Canada communicable disease report. 2020;46(11-12):409-421. doi:https://doi.org/10.14745/ccdr.v46i1112a08
dc.identifier.doi: 10.14745/ccdr.v46i1112a08
dc.identifier.uri: https://open-science.canada.ca/handle/123456789/2513
dc.language.iso: en
dc.publisher: CCDR
dc.relation.istranslationof: https://open-science.canada.ca/handle/123456789/2514
dc.rights - en: Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.rights - fr: Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.rights.openaccesslevel - en: Gold
dc.rights.openaccesslevel - fr: Or
dc.rights.uri - en: https://creativecommons.org/licenses/by/4.0/
dc.rights.uri - fr: https://creativecommons.org/licenses/by/4.0/deed.fr
dc.subject - en: Health
dc.subject - fr: Santé
dc.subject.en - en: Health
dc.subject.fr - fr: Santé
dc.title - en: Assessing the impact of varying levels of case detection and contact tracing on COVID-19 transmission in Canada during lifting of restrictive closures using a dynamic compartmental mode
dc.type - en: Article
dc.type - fr: Article
local.article.journalissue: 11/12
local.article.journaltitle: Canada Communicable Disease Report
local.article.journalvolume: 46
local.peerreview - en: Yes
local.peerreview - fr: Oui

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