November 2023
The data is based upon weekly deaths data from the Australian Bureau of Statistics spanning from 2015 to June of 2023. The data is only available for certain selected age groups.
Country: AU (Australia)
Source for Weekly Deaths (Australian Bureau of Statistics): ABS table: Deaths by week of occurrence.
Source for Vaccination data (Australian Government DHAC): Australian Department of Health and Aged Care.
Alternate Source for Vaccination data (Our World in Data): Our World in Data.
Source for Population Estimates (UN): UN table: Total Population, as of 1 July.
Comment on the available data and its limitations.
The 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 the majority of European countries, the data for weekly deaths in the Australia is only available limited age groups, namely (0-44, 45-64, 65-74, 75-84, 85+ and Total). Any analysis of the data does not allow us to observe the excess mortality in younger age groups with sufficient detail.
Additionally, the Australian DHAC data on vaccination that is available on the public website is of limited use as the data format is not user friendly and the time series are only available from September 2021. This poses a problem as we are unable to show excess deaths versus vaccination rates for different age groups using the official source.
For this reason, we decided to use the vaccination data for Australia from Our World in Data. The time series provided goes back to the start of the vaccination rollout, but is limited to the Total population and no age group granularity is available.
In the charts below, we show the excess deaths age groups compared to total vaccinations administered, in the following way:
Excess Deaths Age Group | Vaccination Age Group |
---|---|
0-44 | Total |
45-64 | Total |
65-74 | Total |
75-84 | Total |
85+ | Total |
Total | Total |
In order to estimate weekly excess mortality we perform a 2-step approach to estimate the baseline deaths. The first step is by estimating the trend in death rates using annual data as described in our methodology papers, while using method 2C.
The second step is to estimate weekly excess deaths by comparing deaths or death rates in a given week with the average death rate, which is computed using the average weekly frequency of deaths over a period of N-years (typically 5 to 10 years depending on the data availability). By using both methods in conjunction we obtain a trend adjusted and week of year adjusted estimate for excess mortality.
Our analysis computes both excess death rates and excess deaths, which are obtained by multiplying the excess death rates with population estimates for the given year.
Weekly data provides a granularity that allows us to investigate the impact of immediate vaccination deaths, lockdowns, or other effects, on excess mortality.
The following chart shows the analysis of excess mortality for 2020, 2021, 2022 and 2023, for different age groups. The Covid-19 vaccinations data (right hand scale) refers to the total accumulated doses for 2021 and 2022, as a percentage of the total population.
Please be aware that for Germany, the vaccination data is not broken down by age group as mentioned before.
The user can specify the method for estimating excess mortality.
The following chart allows the user to compare the trends in excess mortality during 2020, 2021, 2022 and 2023, for the different age groups.
This chart is particularly interesting for investigating excess mortality for older versus younger individuals as the pandemic evolved. In Australia, Covid-19 vaccination started to be rolled out in early 2021 and accelerated in April 2021. Vaccine penetration rates achieved high penetration in the population by July, with 3rd doses starting in the autumn.
The interactive chart allows the user can specify the year for evaluating the excess deaths.