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This interactive charts the new {{selectedData.toLowerCase()}} of COVID-19 in the past {{lookbackTime}} days vs. the total {{selectedData.toLowerCase()}} to date. When plotted in this way, exponential growth is represented as a straight line that slopes upwards. Notice that almost all countries follow a very similar path of exponential growth. We're all in this together. Learn more.
General background to the COVID-19 trends work and the rationale (See notes at the bottom of this section for adaptation of this work to the New Zealand setting)
To learn more about this graph, watch this video created by Minute Physics.
Note: The x-axis of this graph is not time, but is instead the total number of cases or deaths.
Tips: Press Space (or the play button) to Play/Pause. Press +/- keys (or drag the slider) to see daily changes. Hover over the graph data points / lines for more information. The top right of the graph shows additional controls when hovering over this area with a mouse. e.g. Select "Pan" and drag your mouse to move the graph, Use the + and - to zoom in and back out, Click on "Reset axes" to reset the view of the graph. Note: not all functionality works across all platforms. And don't forget to wash your hands and stay in your bubble!
Notes on the adaptation of the COVID Trends project to show trajectory of COVID-19 in New Zealand.
The Covid Trends code was adapted to also show New Zealand Ministry of Health COVID-19 data. The New Zealand interactive chart plots new cases of COVID-19 against total cases to date. The settings may be altered by the user to examine the path of the disease by case definition, averaging period, source of infection, age and location in New Zealand. Note: the NZ DHB visualisation will update later in each day and will show NZ data to 11.59 the previous night. The rationale for this is that complete days of data are used for analyses and visualisation. Constructed by Nick Young and Mark Gahegan from the Centre for e-Research, University of Auckland; Graeme Lindsay, Alistair Woodward, from the School of Population Health, University of Auckland.