Excess Deaths during COVID-19 pandemic in Alberta, Canada
Notice bibliographique
Résumé
PURPOSE: To determine if there was excess mortality in Alberta, Canada during the pandemic. We sought to confirm if excess mortality affected all age groups equally and determine what proportion of excess deaths is directly related to COVID-19. METHODS & MATERIALS: Excess mortality was calculated by comparing observed to expected number of deaths. Monthly Crude death rates (CDR) for 2015 to 2019 was calculated by dividing monthly deaths by the mid-year population. Expected deaths was calculated by multiplying mean monthly CDR by the mid-year population in 2020 and the projected mid-year population in 2021 to calculate expected deaths. Age-adjusted monthly mortality rates for January 2020 to March 2021 was compared to the previous 5 years. RESULTS: From January 2020 to May 2021 there was a 11% excess mortality corresponding to an average of 248 monthly excess deaths with a minimum of 49 deaths in January 2020 (no COVID-19-related deaths) and a maximum of 781 excess deaths in December 2020. COVID-19 related deaths (n=2266) account for 53.8 % of the total excess deaths (n=4214) that occurred in the 17 months. Increase in all cause -excess deaths was proportionately higher, and in significantly greater numbers, in the younger age groups. Deaths directly linked to COVID-19 were: 8 (20-29 years), 12 (30-39 years), 32 (40-49 years), 74 (50-59 years), 225 (60-69 years), 409 (70-79 years), and 1274 (>80 years) Statistically significant increases in monthly drug poisoning deaths from March 2020 to April 2021 with a total of 1819 deaths. Excess 731 drug poisoning deaths representing 18.2 % of total all-cause excess mortality affected mostly those age 25-60. 53.9 % of all excess deaths is directly related to COVID-19 and 18.2% are drug poisoning related excess deaths. The remaining 27.9 % of excess deaths are likely due other factors such as limited access to urgent medical care. CONCLUSION: There was statistically significant increase in all-cause mortality. Although older adults are more likely to die of COVID-19, there was massive increase in non-COVID-19 related mortality among the youth. These should be factored in public policy decisions on epidemic/pandemic management.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».