Epidemiological Study of COVID-19 Fatalities and Vaccine Uptake: Insight From a Public Health Database in Ontario, Canada
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".