This column has often mentioned the similarities between the spread of coronavirus disease in the US and India, both in geographically large and populated countries. The United States is bigger than India; and India is more populous than the United States. But there is a big difference, one that points to a mystery in the Indian numbers.
In every state in the US, there is significant similarity in terms of the number of cases per 100,000 people. The large difference between the absolute number of cases in the US and India makes comparisons difficult, but it is possible to look for similarities within countries.
The difference (per 100,000 people; and from now on, whenever this column refers to cases, it is per 100,000 people) between the state ranked first (Louisiana) and the state ranked 20 is one third of the number of cases in the first. And many of the states in the top 10 (excluding Louisiana) are grouped within the 20% of cases in the state with the second highest number of cases, Florida. The difference between Louisiana and the state that ranks 40 is 43% of the number of cases in the first.
In India, Delhi is the city-state with the highest number of cases per 100,000 inhabitants (875; this analysis has excluded smaller states and Union territories). They are followed by Andhra Pradesh (813), Maharashtra (640), Tamil Nadu (557), Karnataka (510) and Telangana (330). The difference per 100,000 cases between Delhi and Telangana is about 62% of the number of cases in the former. The numbers drop dramatically after that.
In fact, some of the most populous states in India are at the bottom of the list: West Bengal, with 165 cases per 100,000; Bihar with 113; and Uttar Pradesh (100). Nationally, India has 271 cases per 100,000 inhabitants. All numbers are from HT’s panel on Sunday night.
The tests explain some of this. For example, India had tested 31,741 people per million of its population as of Sunday night. But Uttar Pradesh, Bihar, and West Bengal had only analyzed 24,404, 25,913, and 19,043 people per million, respectively. In a country that lags behind when it comes to testing, these states are in the bottom quartile in terms of tests per million. Among the 10 countries ranked with the highest number of cases in the world, only Mexico tests less per million than India. In the 20 countries classified according to the most cases, only four (Mexico, Argentina, Bangladesh and Pakistan) evaluate fewer people per million.
But the tests don’t explain everything. On Sunday, for example, Uttar Pradesh carried out most of the tests, but its positivity rate was among the lowest: 4.42%. Bihar’s was even lower (1.92%) and performed the highest number of tests after Uttar Pradesh. Even that of West Bengal, on a much lower evidence base, was around 7%. In contrast, Tamil Nadu, which carried out the third-highest number of tests after Uttar Pradesh and Bihar on Sunday, recorded a 7.8% positivity rate. And Maharashtra, which conducted the fourth highest number of tests, had a 22% positivity rate. Delhi saw a positivity rate of 9.9%.
Among these states, Delhi has seen its positivity rate drop (from highs in the early 1930s to lows in the 5-7% range) before starting to rise again. Tamil Nadu was one of the first to adapt to the merits of aggressive testing, but while the positivity rate has dropped from its peaks, the state is clearly on a long plateau. As for the rest, their positivity rates aren’t, for the most part, seeing the kind of trend that should be seen with more evidence: a rise, a long plateau, and a drop.
Part of the disparity between states in India can be explained because the first wave of infections was largely confined to large urban centers. But this newspaper has written about how that is changing with 55.3% of cases in the third million (India ended Monday with 3.68 million cases) coming from rural districts. The mystery, then, is that large states like Uttar Pradesh, Bihar, and West Bengal aren’t seeing the kind of numbers they should.
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