Excess Deaths
- References
- Deaths: Data Notes
- Population: Centers for Disease Control and Prevention, National Center for Health Statistics
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- There were a total of 173,938 deaths in New York in 2022
- 99,610 of all deaths were among females
- 47,643 of all deaths were among those aged 40-44
- 955 of all deaths were among women aged 40-44
- 31,047 of all deaths were from Unknown Causes
- 14,836 of female deaths were from Unknown Causes
- 500 deaths from Unknown Causes were among those aged 40-44
500 deaths from Unknown Causes were among women aged 40-44
2022 vs New Normal™ for women aged 40-44 in New York
- 500 of 955 total deaths were from Unknown Causes
- 52.36% of all deaths were from Unknown Causes
- This is up 7% compared to Old Normal rates.
- 462 of 872 total deaths would have been expected under Old Normal conditions.
- 38 excess deaths from Unknown Causes in 2022.
- 83 excess All Cause deaths in 2022.
- 58 excess deaths from Unknown Causes (2015-2022)
- 429 fewer than expected All Cause deaths over the first 8 years of New York’s New Normal™.
- To show this year’s deaths from Unknown Causes are up 7% compared to Old Normal rates, we need to calculate the rates for both 2022 and for the Old Normal.
Remember, death rates are calculated to answer these questions:
- “How many women aged 40-44 were there?” and
- “How many of them died from Unknown Causes?”
The following 2 charts provide this information:
Deaths – Unknown Causes – Female – Aged 40-44 | New York, United-states
Population – Female – Aged 40-44 – [2000-2022] | New York, United-states
From the charts, we can see that in 2022, 500 of 612,670 women aged 40-44 living in New York died from Unknown Causes.
500 ÷ 612,670 = 0.00082 (2022 CDR)
The table shows there were a total of 8,239 deaths from Unknown Causes among 10,930,257 women aged 40-44 living in New York in the 15 years immediately prior to the New Normal™.
8,239 ÷ 10,930,257 = 0.00075 (Old Normal CDR)
We can use the Old Normal rate to predict this year’s deaths:
2022 pop X Old Normal CDR = expected deaths
612,670 X 0.00075 = 462 expected deaths
The difference between actual and expected deaths shows lives saved or lost:
500 – 462 = 38
Dividing the actual deaths by the expected deaths gives us the comparative rates:
500 ÷ 462 = 1.0685
This reveals 38 lives lost and is 106.85% of what we expected (an increase of 7%) in deaths from Unknown Causes among women aged 40-44 living in New York in 2022, as compared to the Old Normal.
This is the same method used by Public Health to calculate the 5-yr CDR (Cumulative Death Rate):
3,206 ÷ 4,226,360 = 0.00076 (5-yr CDR)
612,670(2022 pop) X 0.00076 = 465 expected deaths
The difference between actual and expected deaths:
500 – 465 = 35 or 35 lives lost
Divide actual deaths by expected deaths:
500 ÷ 465 = 1.0618 or an increase of 6%
for deaths from Unknown Causes among women aged 40-44 living in New York in 2022, as compared to the previous 5 years.
Compare our Old Normal to the 5yr CDR. Does it tell the same story your TV does?
Finally, the same method can also be used to compare our Old Normal rate to the New Normal™ rate:
New Normal™ population X Old Normal rate = expected deaths
4,839,030 X 0.00075 = 3,648 expected deaths
The difference between actual and expected deaths:
3706 – 3,648 = 58 or 58 lives lost
Dividing the actual deaths by the expected deaths:
3,706 ÷ 3,648 = 1.0027 or an increase of 0%
in deaths from Unknown Causes among women aged 40-44 living in New York in the New Normal™, as compared to the Old Normal.
The world has been led to believe that a deadly pandemic swept the globe beginning in 2020, causing an increase in death rates, especially among the elderly
The data show that death rates began to increase in 2015, immediately upon implementation of the UN’s 2030 Agenda for Sustainable Development, that young adults have experienced ever-increasing death rates since, and that death rates among the elderly have remained relatively stable.
Return to the top of the page to select another age category.
Deaths/100,000 female 40-44 from Unknown Causes
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