Maps showing the vaccination rate for every suburb* in the country, updated weekly. Built by the Spinoff’s head of data, Harkanwal Singh.
These maps display the most recent available data, released on Wednesday October 20.
These maps are made using Ministry of Health data on the vaccination uptake across the country. In the maps below, the first and second dose uptake rate is shown as a percentage of that area’s population. This data uses eligible population for proportion, and so excludes children aged 0 to 11. The population denominator we use is based on Health Service User numbers provided by the Ministry of Health.
This map is updated every Wednesday with every vaccine data release, and is now displaying the data released on October 20, along with the percentage change since last week.
All of The Spinoff’s data visualisations are made possible thanks to donations from Spinoff Members; join here so we can continue this work.
In areas with particularly low populations, the results are suppressed for privacy reasons (displayed on the maps below as “null”). In a few areas, you might get a vaccination count over 100%, owing to population movements. You can zoom into specific areas and hover or click to see vaccination proportion for all population groups. See all the details for an area by hovering, or clicking on it.
This page now includes a searchable table for better accessibility and a trend chart for every suburb. Both are available below the maps.
This area doesn’t look like a suburb. What is it?
The geography is called Statistical Area 2. The SA2 geography aims to reflect communities that interact together socially and economically. In populated areas, SA2s generally contain similar sized populations.
Why are you not calling it Statistical Area 2 in the headline?
It makes for a really long headline and no one knows what they are.
Where can I learn more about these strange geographies?
Note: the original map included Māori and Pacific vaccination rates by suburb/area. We have made the decision to remove this data due to the potential for misuse, particularly in regards to areas with lower populations.
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