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“Crunch Time” arrives and… was everyone wrong about the Coronavirus?

One week ago, when looking at the growing divergence between the number of new coronavirus cases in the US and shrinking number of fatalities, we referred to Nordea’s strategist Andreas Steno Larsen, who observed that “we are entering “crunch time” on fatalities since they should start to rise in early July given the lead/lag structure versus new cases.”

As Larsen further predicted, “if fatalities don’t spike early in July, then people will conclude that it’s probably spreading amongst a part of the population that is not as sensitive, or that it is a resulted of increased testing or that the virus has become less deadly as we move into the summer months. Governors in Texas, California and Florida seem to have concluded that the below correlation holds, but the jury is still out.”

His conclusion was that “the next 6-10 days will be crucial.”

Well, one week later, we decided to follow up on the current status and… there is still no spike in fatalities at either the federal level…

… or even state level as can be seen in the Florida cases vs deaths chart below:

Meanwhile, as cases appear to be plateauing in several states, not only are deaths not inflecting higher but are at the lowest level since March.

So were most experts wrong that the surge in cases would also lead to a spike in deaths?

While we are debating that question, here’s another one: back in late March and early April, consensus emerged that unless the first coronavirus wave is contained, it would result in an even more acute and deadly second wave.

Why? Because both professional and armchair epidemiologists were using the Spanish flu as a case study as shown in the following chart from JPMorgan.

Now, according to Deutsche Bank, it appears that this comparison to the 1918 Spanish Flu may have also been terribly wrong.

As DB’s Jim Reid writes, one paper that influenced market thinking in the early days of the Covid-19 pandemic looked at the effect of non-pharmaceutical interventions like social distancing and school closures during the Spanish flu (link here). The paper found that the US cities that implemented these measures tended to have better economic outcomes over the medium term. This offered historical support to the argument that there wasn’t such a big trade-off between economic activity and public health, because you needed to suppress the virus to enable consumers to be more confident and for businesses to operate as normal.

However, a major difference between Spanish flu and Covid-19 is the age distribution of fatalities, as shown in the chart below.

For Covid-19, the elderly have been overwhelmingly the worst hit. For the Spanish flu of 1918, the young working-age population were severely affected too. In fact, the death rate from pneumonia and influenza that year among 25-34 year olds in the United States was more than 50% higher than that for 65-74 year olds, “a remarkable difference to Covid-19.”

This, as the strategist then notes, therefore begs the question of how history will judge the lockdown response to Covid-19, given its much more limited impact on workers in the economy.

In short, we have an interesting situation at the moment, where rapidly rising cases in the US are slowing reopenings (negative) but the death rate is falling (positive).

Here are some further observations conducted by another DB strategist, Francis Yared, which suggest that the second wave is far less serious than the media is making it out to be.

Conclusion:

The overall mortality rate as measured by weekly deaths/ weekly new cases (2 weeks lead) is about 1/3rd of the level observed in the second half of April.

Analysis:

We calculate (1) the hospitalization rate as currently hospitalized (weekly average) / new cases (weekly sum, 1 week lead) and (2) the hospitalization mortality rate as Deaths (weekly sum) /currently hospitalized (weekly average, 1 week lead). The latter is a normalization of last week’s calculation from daily deaths to weekly deaths. We focus on weekly averages and weekly lags as the time spent in hospital is about 1 week and to smooth the volatility due to week-end effects.

Results:

The hospitalization rate has declined to ~20% by 10-15pp since the second half of April. This may be due to (a) increased testing and better quality of the tests capturing milder cases and (b) self-selection of the population taking risks (e.g. average age of new cases declining)

The hospitalization mortality rate halved to ~10% (last week’s results scaled from daily to weekly deaths) since the second half of April.

The overall mortality rate (deaths over lagged new cases) is the product of the previous two calculations. Since the second half of April, it has declined by about 2/3rd from 6.5% to 2%.

For the three largest states with hospitalization data CA/NY/TX, the respective current levels are as follows. Hospitalization rate: 18.1%, 18.7%, 19.4%. Hospitalization mortality rate: 7.8%, 6.9%, 5.2%. Overall mortality rate: 1.7%, 1.5%, 1.0%.

Meanwhile daily tests in the US hit a new all time high every single day.

As DB concludes, “this may eventually give us more faith that we are now better at living with the virus.”

Source: ZERO HEDGE