the big story

The alarming spike in India numbers

The TLDR: The Covid count in India is currently 198,370. We added a record 8,392 new cases on Monday—and are now the seventh-worst hit nation in the world, having overtaken both France and Spain. This surge is alarming, yes. But it also disguises serious problems with the data—which is outdated and filled with holes.

First, the surge

• The greatest numbers are located in Maharashtra, Tamil Nadu, Delhi and Gujarat—which contribute almost 70% of all new cases. 
• But the fastest-growing tallies belong to Bihar, Assam, Haryana and Kerala—all of whom are witnessing a resurgence due to the return of migrants and easing of travel restrictions. 
• Also in trouble: Delhi, which has reported 1,000-plus cases for five days in a row. Its tally jumped by 6,000 last week, and is now 19,844. 
• It’s why CM Kejriwal has sealed the city’s borders—worried that patients from neighbouring states will overwhelm the capital’s hospitals.
• The worst hit: Maharashtra with 67,655 cases and 2,236 deaths.

But these numbers are old!

Every virus tally typically states that these are “recorded” cases. This implies that there may be more infections that have not been detected. But the word also indicates that the numbers are at least two weeks old. And that’s because of how the virus behaves:

“The available evidence suggests that it usually takes about five days for an infected person to go from transmission to symptoms, but it can take as long as 14 days, and the person infected will be contagious for much of that time. The flu, by comparison, goes from transmission to symptoms in an average of two days and a maximum of four, according to the Centers for Disease Control and Prevention, and most people are infectious for only about a day before becoming ill.”

Now add the fact that people who fall sick often fail to seek help—staying home for days, hoping they will get better. Added disincentive: there’s a severe shortage of beds (which we explained here) and the crap arrangements for quarantine. The reality is that many of us will not get tested or head for the hospital in a hurry.

Point to note: Contrary to what many headlines claim, India did not surge during Lockdown 4.0. The numbers we are seeing now reflect what happened during the phase before.

Next: India’s slo-mo testing

Last week, Huffington Post put together an excellent deep dive that explained why Covid numbers put out by the government are meaningless. The big reason: there are huge bottlenecks within the testing process. The article offers this example of Ashok Nagar in Madhya Pradesh—which is considered a green district:

"In the first day of May, Ashok Nagar had collected a total of 330 samples and received reports of 248 patients; the results of 82 samples were pending from April. By the 13th of May, the district had sent 940 samples, but a bottleneck in analysing these samples meant the number of pending samples had ballooned to 345 — more than four times the number of pending samples from a fortnight ago."

Plus: India’s slo-mo data collection

If it takes time to get test results, it sometimes takes even more time to record them in the database. Take, for example, the high recovery rate being tomtommed by authorities. Last Friday marked the first day that the number of recoveries were higher than the number of new cases. Yay, right? Not so fast, and Indian Express explains why:

"Maharashtra had bunched together hundreds of previously unreported recoveries from its districts in the last several days, and reported it all together on Friday. The state usually reports between 700 and 1400 recoveries every day. On Friday, it reported 8,381 recoveries in a single day. That was more than double the usual number of recoveries that are reported from the entire country."

This is also true for numbers put out for the number of deaths. Last week, Delhi reported a single day jump of 82 fatalities in a single day. The reason: 13 deaths did indeed occur on Friday, but the remaining 69 were recorded in the past 34 days and were reported late!

Finally: huge data gaps

On Saturday, the government put out its data analysis of the over one million tests conducted between 22 January and 30 April. What did it reveal? According to an expert analysis in The Print:

"Unknown to most people, but now revealed by the Indian Council of Medical Research (ICMR) data, India’s contact tracing faltered a long time ago. Of the 10 lakh plus people tested until April 30l, the mode of Covid-19 transmission is not known for 57% of them. And of the 40,184 people who tested positive, the Narendra Modi government does not know how 44% of them got infected, the ICMR has revealed. Worryingly, this number has only grown over time." 

And yet authorities insist that there is no “community transmission”—i.e. the stage when the virus is spreading freely in the population. 

What the data does tell us: home quarantine is a bust. Entire families are testing positive, and households are the most at-risk group. And many are asymptomatic, suggesting it is time to randomly test the population to identify such cases.

The bottomline: We are throwing open the doors with very little information and, sadly, very little choice. The four lockdowns haven’t helped—at least not as much as widely claimed. And they certainly hurt the most vulnerable Indians. As for the consequences of Unlock 1.0, we won’t know for weeks—may be not until it is too late.

The Reading List

• The Atlantic explains the horror of the coronavirus data lag.
• Huffington Post offers the best analysis of India-specific delays in testing and reporting. Indian Express explains why the recovery numbers are misleading. 
• The Print has the data gaps—including the low testing rates for Indian women.
• Indian Express also has a state-by-state breakdown of the latest numbers—and explains why Delhi is in better shape than Mumbai. 
• Mint has decoded the data to flag a serious health worker crunch on the horizon.
• Goa, OTOH, is worried about all those rich Delhiwalas fleeing to their second homes.
• Now we are in Unlock 1.0, we recommend this handy NPR guide that assesses the risk of various activities.