September 2023
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Go to Quarterly Analysis.
Go to Weekly Analysis.
Go to Excess Deaths Page.
The data is based upon weekly deaths data from the US CDC spanning from 2015 to 2022.
Country: US
Source for Weekly Deaths (CDC): Weekly Counts of Death by Jurisdiction and Select Causes of Death.
Source for Vaccination data (CDC): COVID-19 Vaccinations in the United States.
Source for Population Estimates (UN - Population division): UN table: Population estimates.
Comment on the available data and its limitations.
The CDC data on excess deaths and vaccination has several limitations that one should be aware of when analysing the charts below. Unlike the data from Eurostat (for European countries), the data for weekly deaths in the US is only available in broad age groups, namely (0-24, 25-44, 45-64, 65-74, 75-84, 85+ and Total). Any analysis of the data does not allow us to observe the excess mortality on younger age groups with sufficient detail.
The CDC data on vaccination for the US as a whole is classified in different age groups from the age groups for weekly deaths. This poses a problem of how to show excess deaths versus vaccination rates for different age groups. The available vaccination age groups provided by the CDC are such that after some manipulation of the data, we can obtain vaccination rates for the following age groups: (0-5, 6-12, 13-18, 19-65, 65+ and Total).
To solve this problem, in the charts below we decided to match the excess deaths and vaccination age groups in the following way:
| Excess Deaths Age Group | Vaccination Age Group |
|---|---|
| 0-25 | 0-18 |
| 25-44 | 19-65 |
| 45-64 | 19-65 |
| 65-74 | 65+ |
| 75-84 | 65+ |
| 85+ | 65+ |
| Total | Total |
We show the analysis of excess mortality using the different methodologies described in our methodology papers.These papers illustrate the pitfalls and advantages of using the different calculation methods for excess mortality.
In summary, using method 1, excess deaths for 2020, 2021, 2022 and 2023 are computed by subtracting the N-year pre-pandemic average deaths (typically 3 to 5 years) from actual deaths in the Covid-19 pandemic years. This method is the one most widely used for estimating excess deaths, including by countries' statistical offices. However, this method has obvious pitfalls as the measurement of excess deaths is highly sensitive to the baseline for estimating "normal" deaths. By using a prior average of the number of deaths as a baseline, biases are easily introduced due to increasing or decreasing population over time. When the population is increasing, excess deaths are over-estimated while when populations are decreasing they tend to be under-estimated.
Method 2 solves some of these problems by computing changes in death rates relative to a given baseline and, as shown in our methodology papers, are much more reliable for estimating excess mortality.
The chart below shows the actual deaths (or death rate) versus the projected estimates when using the different methodologies described in our methodology papers.
The user can select the calculation method, age group and country. 2023 deaths or deaths rates are annualised estimates using a linear model.
The chart below shows the excess mortality for 2020, 2021, 2022 and 2023 (either excess deaths or excess death rates) for a given age group. Please be aware that we matched the age groups as described in the data section above.
The plot allows the user to select the desired methodology, country and age group. 2023 deaths or deaths rates are annualised estimates using a linear model.
The following chart shows the analysis of excess mortality for 2020, 2021, 2022 and 2023 for different age groups. The user can specify the method for estimating excess mortality.
Please be aware that for the US, the vaccination age groups do not match perfectly the excess deaths age groups as mentioned before. We matched the age groups as described in the data section above.
PHINANCE TECHNOLOGIES