Epidemiological Study of COVID-19 Fatalities and Vaccine Uptake: Insight From a Public Health Database in Ontario, Canada
Notice bibliographique
Résumé
Coronavirus disease (COVID-19) has reached millions of people worldwide and is responsible for millions of deaths around the world. Research on fatalities in rural communities remains limited. In addition, the scientific literature has not yet reported on the distribution of vaccines in Canada and compared the findings to the age distribution of COVID-19 fatalities in Canada to see whether the vaccines have been distributed to the highest age category populations. This research article used data from the Government of Ontario and Statistics Canada to analyze the number of cases, fatalities, case fatality rates (CFRs) by demographic factors, such as age, gender, urban-rural status, and compared the findings to national vaccination rates by age. As of June 11, 2021, this study found that among the 528,819 cases among 14.8 million people. Among this population, there were 8875 fatalities in Ontario with 82.208% (n=7296) of fatalities occurred in people over 70 years, and 93.183% in people over 60 years (n=8,270). Additionally, the odds ratio of a fatal event was 9,652 times higher in people over 90 years (95% CI: 4418, 31124, p<0.001) as compared with less than 20 years. Men had a higher number of fatalities (n=4,490, CFR=1.721%) compared with women (n=4,385, CFR=1.692%), and a higher odd of fatal events only when adjusted for age and gender (OR=1.66, 95% CI: 1.57, 1.74, p<0.001). Urban areas had 92.034% of fatalities (n=8,168) and had a CFR of 1.632%. In contrast, rural areas comprised 4.451% of total fatalities (n=395) and had the highest CFR (2.267%). The unadjusted odds of a fatality were 1.41 (95% CI: 1.27, 1.56) in rural areas compared with urban areas. Across Canada as of May 29, 2021, people over 80 years old received 1,530,318 vaccines with 91.98% of this population age group receiving at least one and 457,664 being fully vaccinated (27.51%). In Ontario, as the number of people with at least one vaccine increased for people over 90 years, the number of fatalities was reduced from about 8 per day prior to vaccines to approximately two per day. Furthermore, once the vaccination rates exceeded 75% in ages 60 years and over 50% in the younger age groups, the number of fatalities per day among all age groups was approximately one per day. In summary, age was found to be a significant factor for COVID-19 mortality in Ontario and vaccine uptake in Ontario was followed by decreases in COVID-19 mortality.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,014 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 source (Gemma direct ou Codex distillé), 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 ».