Despite a long and stringent lockdown, cases in India continue to surge. Is poor testing a reason?
How to read the charts?
The graphs show the no. of daily cases (represented by the grey bars, left axis) and the cumulative no. of tests conducted per confirmed case (represented by the blue line, right axis) for select countries with more than 50,000 cases. The reference lines indicate how stringent a nation’s lockdown was on a particular date. The red line indicates when peak lockdown stringency was reached; the orange line indicates when it was relaxed (the govt. was preparing to unlock) and the green line indicates when the lowest stringency was recorded after the peak (further lifting of curbs). Stringency is calculated by the Oxford University based on 17 indicators such as school closures and restrictions in movement.
In all the charts, K indicates '000. For instance, 10K refers to 10,000.
Countries which were relatively worse-off
In these countries, cases were higher during and after unlock than at the start of the lockdown, indicating poor implementation of the lockdown. These nations did not test enough relative to the the size of their outbreak (indicated by a dipping blue line).
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ÂOnly India reached a stringency level of 100 (highest possible) in the list. But due to poor testing, the gains were minimal.
Also read: Data | Why is it necessary to test more to reduce the impact of COVID-19?
Countries which were relatively bad
In the U.S., Mexico and Chile, cases continue to rise but they did not choose to bring down the stringency (no yellow or green line observed). In Iran, a second wave increased the cases again, but it continued to test enough.
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ÂCountries which were relatively good
Cases were lower during and after unlock than at the start of the lockdown, indicating better lockdown implementation. All of them continue to test enough relative to their outbreak sizes (indicated by a rising blue line)
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