Canadian death clock: Technical notes

On this page

• Data sources
• Assumptions and limitations
• Calculating estimated deaths in Canada

Data sources

Using Statistics Canada's Table 13-10-0394-01, we extracted data on the top causes of death among people living in Canada between 2014 and 2023, including stratifications by age and sex.

In order to estimate the number of deaths in 2025, we extracted the projected number of people living in Canada in the first quarter of 2025 (Q1 2025) from Statistics Canada's Table 17-10-0009-01.

Assumptions and limitations

In addition to the assumptions and limitations noted in the Statistics Canada data sources, this data tool makes its own assumptions and has its own limitations

• The apportioning method (assumption of an "assembly line") was used to estimate the number of deaths that have occurred throughout the day and throughout the year. This method assumes that deaths occur at a consistent pace, which is inaccurate to reality, wherein deaths occur sporadically. Additionally, the frequencies of deaths by many causes fluctuate depending on the time of day, the time of year, or both.
• Making future predictions via linear regression, and estimating values based on data which do not appear in a dataset (extrapolation), results in high levels of uncertainty in the estimated values. The estimated values included in this data tool are presented for illustrative purposes only, and their imprecision must be assumed.
• Using only population change to estimate the number of deaths by specific causes within specific population groups in a given year is simplistic and does not reflect the numerous factors which contribute to the number of deaths by different causes and among different population groups year-to-year.

Calculating estimated deaths in Canada

To calculate the estimated total number of deaths in Canada, we first computed a linear regression of the number of deaths in Canada as a function of the country's population over 10 years. This linear regression was calculated for each stratification and for each of the top 10 causes of death within each stratification in 2023. We used the resulting linear functions to estimate the projected number of people who would die in 2025 based on the latest population estimates.

For any time that a linear regression projected a negative number of deaths for a cause within a stratification (and for estimating the number of deaths by "All other causes"), we instead multiplied the number of deaths related to that cause by the population growth factor for the specific stratification between 2023 and 2025 (2025-estimate / 2023-estimate).

Finally, to calculate the estimated amount of time elapsed between deaths by each cause, we divided the number of seconds in a years (assuming days of precisely 24 hours, and a year of 365.2422 days) by the total numbers of deaths.

Estimates using linear regression

To find the line of best fit for the number of deaths as a function of population, we first calculated the average population and the average number of deaths between 2014 and 2023 for each of the top 10 causes of death for each population breakdown.

$Average\; population\; (<mi\; style="border-top:1px\; solid\; black;">x</mi>)=\frac{\sum _{i=1}^{n}xi}{n}$

With the average death and population values, we could then find the slope of the line of best fit using the least squares method, as follows:

$Slope\; (<mi>m</mi>)=\frac{\sum _{i=1}^n\left((xi-x)\right)\left((di-d)\right)}{\sum _{i=1}^n{\left((xi-x)\right)}^2}$

Note:

• i: individual observation (one year of death or population data)
• n: number of observations (total number of years of death or population data)

Next, we calculated the intercept for each line of best fit, using the following equation:

$Intercept\; (<mi>b</mi>)=d-mx$

Finally, we could predict the number of deaths in 2025 as a function of the population in 2025, using the calculated line of best fit, according to the following formula:

$Predicted\; deaths\; in\; 2025\; (<mi>d</mi><mi\; style="font-size:12px;\; position:relative;\; bottom:-2px;">2025</mi>)=mx\mathrm{2025}+b$

Estimations based on most recent death data and population growth

As noted previously, any time that the predicted number of deaths was negative (and for all instances of predicting the number of deaths by "All other causes"), we instead estimated the number of deaths in 2025 based on the number of deaths in 2023 and the change in population between 2023 and 2025. To do so, we used the following formula:

$Estimated\; deaths\; in\; 2025\; (<mi>d</mi><mi\; style="font-size:12px;\; position:relative;\; bottom:-2px;">2025</mi>)=d\mathrm{2023}\frac{x\mathrm{2025}}{x\mathrm{2023}}$

Calculating time between deaths by cause

Having calculated the estimated or predicted number of deaths for each cause for each population stratification, we calculated how the average amount of time that would elapse between deaths for each estimate by dividing the number of seconds in a years (according to a year of 365.2422 days) by the total numbers of deaths:

$Time\; between\; deaths=\frac{60\times 60\times 24\times 365.2422}{d\mathrm{2025}}$