Covid-19: What you need to know today
Maharashtra has thus far tested 26,750 people per million of its population; Andhra Pradesh 56,713, and Karnataka 32,435. The national average is 23,815. Clearly, these are India’s primary Covid-19 hot spots at this point.
On Tuesday, India saw 65,141 new cases of the coronavirus disease. There were 60,433 recoveries. There has been a lot of focus on daily recoveries exceeding daily new cases — after it happened once over the past week (on August 17) — along with commentary of how this could mean things are getting better. This isn’t the first time the number of daily recoveries exceeded the number of new cases (it has happened a few times over the past two months), but it is definitely not a sign of a turnaround — at least, not yet. The seven-day average of daily new cases in the 15 Indian states and the Capital that accounted for the most new cases on Tuesday (92%) was 57,698, marginally higher than the 14-day average of 56,873, clearly indicating that the number of new cases has stayed at the same level.
This is a good time to revisit the status of the pandemic across these 16 places. There is no significant trend, up or down, between the seven-day and 14-day averages in 13 states and Delhi; in some, the number has increased marginally, and in others, it has decreased marginally. The other two, Odisha and Karnataka, have seen the most significant increases. But in isolation, this data doesn’t tell us anything.
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Which is why it is important to look at the positivity rate: the proportion of those testing positive to those tested. The average positivity rate for the past seven days was the highest in Maharashtra (18.9%), Andhra Pradesh (16.7%) and Karnataka (14.7%). These are worrying numbers in any context — a 7-12% range is considered acceptable (and safe) in a state that has begun testing adequately, and a 3-8% range in a state that has been testing adequately for some time. All three states have been testing more than the national average (which still doesn’t mean they are testing adequately).
Maharashtra has thus far tested 26,750 people per million of its population; Andhra Pradesh 56,713, and Karnataka 32,435. The national average is 23,815. Clearly, these are India’s primary Covid-19 hot spots at this point. Overall, till Tuesday night, Maharashtra has seen 615,477 cases, Andhra 306,261 cases, and Karnataka 240,948. They rank 1, 3, and 4 in the country in terms of number of cases (Tamil Nadu is 2), and account for 42% of all Covid cases recorded thus far in the country.
Between the week ended Tuesday, and the previous week, Maharashtra’s positivity rate actually saw an increase by 2.7 percentage points. This can be directly attributed to its lower testing over the past week — on average, around 8,500 fewer tests were conducted in the week ended Tuesday compared to the previous week. The same reason helped Odisha — by conducting roughly 28,000 tests a day more than it did in the previous week, the state was able to lower its positivity rate from 9.4% to 5%. Bihar, too, reduced its positivity rate by 1.9 percentage points on the strength of higher testing, as did West Bengal (by 1.7 percentage points).
How much testing is adequate? This is a moving target, and this writer’s own assessment has evolved with a deeper understanding of how the pandemic plays out across regions. There are two stages to this. One, states with a population in excess of 50 million should be testing at least 4-5% of its population; between 20 million and 50 million, 5-7%; and below 20 million, 7-10%. Two, states that meet the adequacy criteria listed above and continue to see rising positivity rates should keep increasing testing till these start plateauing (or dropping).
Based on this, only four of the 15 states and Delhi — Delhi itself, Assam, Andhra Pradesh, and Tamil Nadu — are testing adequately. Of the four, only Delhi and Assam are both testing adequately and have a safe positivity rate. Tamil Nadu has been testing adequately, but it is clearly on a long plateau of cases. And Andhra Pradesh actually needs to test even more till its positivity rate declines.