Detection of Covid-19 case clusters in Québec, May–October 2020
Bibliographic Data
| ID | 8900813 |
|---|---|
| Authors | Germain Lebel (Institut National de Santé Publique du Québec, corresponding author), Élise Fortin (0000-0001-6612-9091, Institut National de Santé Publique du Québec), Ernest Lo (0000-0001-6267-4674, McGill University), Marie-Claude Boivin (Institut National de Santé Publique du Québec), Matthieu Tandonnet (Institut National de Santé Publique du Québec), Nathalie Gravel (0000-0002-8942-0073, Institut National de Santé Publique du Québec) |
| Year | 2021 |
| Volume | 112 |
| Issue | 5 |
| Pages | 807-817 |
| Publication date | 2021-08-09 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Canadian Journal of Public Health (JOURNAL) |
| Journal identifiers | ISSN: 0008-4263 • E-ISSN: 1920-7476 |
| Publisher | Springer Science+Business Media (PUBLISHER • DE) |
| DOI | 10.17269/s41997-021-00560-1 |
| PMID | 34374036 |
| OpenAlex | W3189604282 |
| Language | EN |
| References cited | 12 |
Considering the objective of timely cluster detection, the use of near-real-time health surveillance data of varying quality over time and by region constitutes an acceptable compromise between timeliness and data quality. This tool serves to supplement the epidemiologic investigations carried out by regional public health authorities for purposes of COVID-19 management and prevention
2019-20 coronavirus outbreak · Cluster (spacecraft · Compromise · Coronavirus disease 2019 (COVID-19 · Environmental health · Geography · Poisson distribution · Political science · Public health · Public health interventions · Public health surveillance · Scan statistic · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 · Software deployment · Statistic · Statistics · Computer Science · COVID-19 epidemiological studies · Data-Driven Disease Surveillance · Medicine · Nursing · Public Health Policies and Education · Virology
| Highly cited | No |
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