SARS-CoV-2 Surveillance System in Canada: Longitudinal Trend Analysis.

Alberta British Columbia COVID 7-day lag COVID transmission deceleration COVID transmission jerk COVID-19 COVID-21 Canada Public Health Surveillance Canada SARS-CoV-2 Canadian COVID transmission acceleration Canadian COVID transmission speed Canadian COVID-19 Canadian COVID-19 surveillance system Canadian econometrics Great COVID Shutdown Manitoba New Brunswick Newfoundland and Labrador Northwest Territories Nova Scotia Nunavut Ontario Prince Edward Island Quebec Saskatchewan Yukon dynamic panel data generalized method of the moments global COVID surveillance new COVID strains surveillance metrics wave 2 Canada COVID-19

Journal

JMIR public health and surveillance
ISSN: 2369-2960
Titre abrégé: JMIR Public Health Surveill
Pays: Canada
ID NLM: 101669345

Informations de publication

Date de publication:
10 05 2021
Historique:
received: 13 11 2020
accepted: 09 04 2021
revised: 25 02 2021
pubmed: 15 4 2021
medline: 15 5 2021
entrez: 14 4 2021
Statut: epublish

Résumé

The COVID-19 global pandemic has disrupted structures and communities across the globe. Numerous regions of the world have had varying responses in their attempts to contain the spread of the virus. Factors such as public health policies, governance, and sociopolitical climate have led to differential levels of success at controlling the spread of SARS-CoV-2. Ultimately, a more advanced surveillance metric for COVID-19 transmission is necessary to help government systems and national leaders understand which responses have been effective and gauge where outbreaks occur. The goal of this study is to provide advanced COVID-19 surveillance metrics for Canada at the country, province, and territory level that account for shifts in the pandemic including speed, acceleration, jerk, and persistence. Enhanced surveillance identifies risks for explosive growth and regions that have controlled outbreaks successfully. Using a longitudinal trend analysis study design, we extracted 62 days of COVID-19 data from Canadian public health registries for 13 provinces and territories. We used an empirical difference equation to measure the daily number of cases in Canada as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. We compare the week of February 7-13, 2021, with the week of February 14-20, 2021. Canada, as a whole, had a decrease in speed from 8.4 daily new cases per 100,000 population to 7.5 daily new cases per 100,000 population. The persistence of new cases during the week of February 14-20 reported 7.5 cases that are a result of COVID-19 transmissions 7 days earlier. The two most populous provinces of Ontario and Quebec both experienced decreases in speed from 7.9 and 11.5 daily new cases per 100,000 population for the week of February 7-13 to speeds of 6.9 and 9.3 for the week of February 14-20, respectively. Nunavut experienced a significant increase in speed during this time, from 3.3 daily new cases per 100,000 population to 10.9 daily new cases per 100,000 population. Canada excelled at COVID-19 control early on in the pandemic, especially during the first COVID-19 shutdown. The second wave at the end of 2020 resulted in a resurgence of the outbreak, which has since been controlled. Enhanced surveillance identifies outbreaks and where there is the potential for explosive growth, which informs proactive health policy.

Sections du résumé

BACKGROUND
The COVID-19 global pandemic has disrupted structures and communities across the globe. Numerous regions of the world have had varying responses in their attempts to contain the spread of the virus. Factors such as public health policies, governance, and sociopolitical climate have led to differential levels of success at controlling the spread of SARS-CoV-2. Ultimately, a more advanced surveillance metric for COVID-19 transmission is necessary to help government systems and national leaders understand which responses have been effective and gauge where outbreaks occur.
OBJECTIVE
The goal of this study is to provide advanced COVID-19 surveillance metrics for Canada at the country, province, and territory level that account for shifts in the pandemic including speed, acceleration, jerk, and persistence. Enhanced surveillance identifies risks for explosive growth and regions that have controlled outbreaks successfully.
METHODS
Using a longitudinal trend analysis study design, we extracted 62 days of COVID-19 data from Canadian public health registries for 13 provinces and territories. We used an empirical difference equation to measure the daily number of cases in Canada as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R.
RESULTS
We compare the week of February 7-13, 2021, with the week of February 14-20, 2021. Canada, as a whole, had a decrease in speed from 8.4 daily new cases per 100,000 population to 7.5 daily new cases per 100,000 population. The persistence of new cases during the week of February 14-20 reported 7.5 cases that are a result of COVID-19 transmissions 7 days earlier. The two most populous provinces of Ontario and Quebec both experienced decreases in speed from 7.9 and 11.5 daily new cases per 100,000 population for the week of February 7-13 to speeds of 6.9 and 9.3 for the week of February 14-20, respectively. Nunavut experienced a significant increase in speed during this time, from 3.3 daily new cases per 100,000 population to 10.9 daily new cases per 100,000 population.
CONCLUSIONS
Canada excelled at COVID-19 control early on in the pandemic, especially during the first COVID-19 shutdown. The second wave at the end of 2020 resulted in a resurgence of the outbreak, which has since been controlled. Enhanced surveillance identifies outbreaks and where there is the potential for explosive growth, which informs proactive health policy.

Identifiants

pubmed: 33852410
pii: v7i5e25753
doi: 10.2196/25753
pmc: PMC8112542
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e25753

Informations de copyright

©Lori Post, Michael J Boctor, Tariq Z Issa, Charles B Moss, Robert Leo Murphy, Chad J Achenbach, Michael G Ison, Danielle Resnick, Lauren Singh, Janine White, Sarah B Welch, James F Oehmke. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 10.05.2021.

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Auteurs

Lori Post (L)

Buehler Center for Health Policy and Economics, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.

Michael J Boctor (MJ)

Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.

Tariq Z Issa (TZ)

Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.

Charles B Moss (CB)

Institute of Food and Agricultural Sciences, University of Florida, Gainsville, FL, United States.

Robert Leo Murphy (RL)

Institute of Global Health, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.

Chad J Achenbach (CJ)

Divison of Infectious Disease, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.

Michael G Ison (MG)

Divison of Infectious Disease, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.

Danielle Resnick (D)

International Food Policy Research Institute, Washington, DC, United States.

Lauren Singh (L)

Buehler Center for Health Policy and Economics, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.

Janine White (J)

Buehler Center for Health Policy and Economics, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.

Sarah B Welch (SB)

Buehler Center for Health Policy and Economics, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.

James F Oehmke (JF)

Buehler Center for Health Policy and Economics, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.

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