Evidence map›Paper›PMID 34622758›Full record

ArticleEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin2021

Long time frames to detect the impact of changing COVID-19 measures, Canada, March to July 2020.

Jessica E Stockdale, Renny Doig, Joosung Min, Nicola Mulberry, Liangliang Wang, Lloyd T Elliott, Caroline Colijn

Open access · diamondAbstract read
In one paragraph

Article in Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.1field-weighted citation impact, top 60% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Jessica E StockdaleDepartment of Mathematics, Simon Fraser University, Burnaby BC, Canada.
Renny DoigDepartment of Statistics and Actuarial Science, Simon Fraser University, Burnaby BC, Canada.
Joosung MinDepartment of Statistics and Actuarial Science, Simon Fraser University, Burnaby BC, Canada.
Nicola MulberryDepartment of Mathematics, Simon Fraser University, Burnaby BC, Canada.
Liangliang WangDepartment of Statistics and Actuarial Science, Simon Fraser University, Burnaby BC, Canada.
Lloyd T ElliottDepartment of Statistics and Actuarial Science, Simon Fraser University, Burnaby BC, Canada.
Caroline ColijnDepartment of Mathematics, Simon Fraser University, Burnaby BC, Canada.
Simon Fraser University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BackgroundMany countries have implemented population-wide interventions to control COVID-19, with varying extent and success. Many jurisdictions have moved to relax measures, while others have intensified efforts to reduce transmission.AimWe aimed to determine the time frame between a population-level change in COVID-19 measures and its impact on the number of cases.MethodsWe examined how long it takes for there to be a substantial difference between the number of cases that occur following a change in COVID-19 physical distancing measures and those that would have occurred at baseline. We then examined how long it takes to observe this difference, given delays and noise in reported cases. We used a susceptible-exposed-infectious-removed (SEIR)-type model and publicly available data from British Columbia, Canada, collected between March and July 2020.ResultsIt takes 10 days or more before we expect a substantial difference in the number of cases following a change in COVID-19 control measures, but 20-26 days to detect the impact of the change in reported data. The time frames are longer for smaller changes in control measures and are impacted by testing and reporting processes, with delays reaching ≥ 30 days.ConclusionThe time until a change in control measures has an observed impact is longer than the mean incubation period of COVID-19 and the commonly used 14-day time period. Policymakers and practitioners should consider this when assessing the impact of policy changes. Rapid, consistent and real-time COVID-19 surveillance is important to minimise these time frames.

Indexed as

COVID-19CanadaHumansSARS-CoV-2CanadacontrolCOVID-19modellingphysical distancingSARS-CoV-2

Identifiers

PMID34622758
PMCPMC8511756
OpenAlexW3204504037

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.