{"id":6674301,"date":"2020-03-28T14:55:53","date_gmt":"2020-03-28T14:55:53","guid":{"rendered":"http:\/\/cfe.econ.jhu.edu\/?p=6674301"},"modified":"2021-01-12T16:46:25","modified_gmt":"2021-01-12T16:46:25","slug":"covid-19-data-signal-versus-noise","status":"publish","type":"post","link":"https:\/\/krieger.jhu.edu\/financial-economics\/2020\/03\/28\/covid-19-data-signal-versus-noise\/","title":{"rendered":"COVID-19 Data: Signal versus Noise"},"content":{"rendered":"

Two burning questions confront all of us:
\nHow big is our public health problem?
\nHow sharp is our economic retrenchment?<\/p>\n

We think that the toolkit of economic forecasters has something to offer on the scale of the public health problem. Ignore the frantic quotes focused on reported COVID-19 cases\u2014the numbers are all but meaningless. Instead, keep your eye on reported deaths and the growth rate for total deaths. These data are likely close to correct, and they will provide signal if the pandemic curve is flattening. And that is the signal we all are hoping to see. <\/p>\n

Nearly everyone recognizes that in much of the world there is a dramatic shortage of test kits. Thus, nearly all agree that reported incidences of COVID-19 likely meaningfully understate the actual level of infection. We think we can use reported deaths to infer a likely range of infection. When we do so, the divergence between reported cases and likely actual cases is breathtaking. <\/p>\n

Let\u2019s do some arithmetic aimed at divining an estimate of total global infections as of 10 days back. <\/p>\n

1.\tWe start with JHU\u2019s 3\/27 tally of reported worldwide COVID-19 deaths, 27,333.
\n2.\tWe assume that deaths are much less likely to be missed than infections. That said, we acknowledge that some COVID-19 deaths no doubt have been attributed to other causes.
\n3.\tWe assume that actual total COVID-19 deaths run 10% higher than reported deaths.
\n4.\tWe assume that death takes at least 10 days from initial infection.
\n5.\tWe, therefore, conclude that the total death tally, as of 3\/27, identifies those who succumbed to COVID-19, from the total global pool of infected people, as of 10 days earlier, 3\/17.<\/p>\n

What do we learn? There were 215,000 reported cases, on March 17th. To believe that number is true, with nearly 30,000 deaths attributed to that group, you need to accept the notion that the COVID-19 mortality rate is 14%, something that seems impossible based on Chinese studies.<\/p>\n

So what is a better estimate? We can use our upwardly adjusted figure for total deaths, and work backward. We divide it by a range of possible mortality rates, to estimate what the actual total pool of infected individuals was, 10 days ago.<\/p>\n

The table below does so. The results are quite eye opening. To assert that COVID-19 has the same mortality rate as the flu, you need to believe that on March 17th the actual case level, worldwide, was over 30 million. Again, the reported case total for March 17th is 215,000. If you suspect the death rate is closer to 1%, then total cases, 10 days back were around 3 million. Even the notion of a draconian death rate, 2.5%, requires you to believe that actual worldwide cases are 7 times the reported tally.
\n\"Table\n<\/p>\n

This phenomenon is in place in most nations. The table below calculates mortality rates for a host of nations, based on death totals 10 days forward. Only Germany and South Korea might be roughly plausible. The other nations, including the U.S.A., must have a much higher incidence of infection.
\n\"Table\n<\/p>\n

Which leads us to a simple conclusion. The tally of global confirmed infections is completely compromised by the dearth of test equipment. In stark contrast, the cumulative death tally and its growth rate, are powerful measures of the state of the pandemic. <\/p>\n

Does current radical social distancing in the U.S. make sense? Over the past week, in the USA, reported deaths have grown, on average, at a 31% per day rate. We all appreciate the rapidly explosive nature of exponential growth rates. Nonetheless, we tend to be surprised when we do the math. What happens to total deaths if they continue to grow, through mid-April, at the pace of the last week? Some 280,000 deaths would be recorded on April 15th.. And, clearly, no one wants to calculate the lost souls in place if that pace extends to the end of May. <\/p>\n

Radical social distancing is the only way to flatten the curve. Even if we succeed, however, the long awaited surge of test kits could generate a leap for reported cases, preordained by recent death rate tallies. So, grimly, watch the death tallies. Divide by your guess for the mortality rate, to get a handle on infection incidence 10 days back. Most importantly, pray for a quick and dramatic slide for deaths\u2019 daily climb. <\/p>\n","protected":false},"excerpt":{"rendered":"

Two burning questions confront all of us: How big is our public health problem? How sharp is our economic retrenchment? We think that the toolkit of economic forecasters has something to offer on the scale of the public health problem. Ignore the frantic quotes focused on reported COVID-19 cases\u2014the numbers are all but meaningless. Instead, […]<\/p>\n","protected":false},"author":470,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[111,112,141],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/krieger.jhu.edu\/financial-economics\/wp-json\/wp\/v2\/posts\/6674301"}],"collection":[{"href":"https:\/\/krieger.jhu.edu\/financial-economics\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/krieger.jhu.edu\/financial-economics\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/krieger.jhu.edu\/financial-economics\/wp-json\/wp\/v2\/users\/470"}],"replies":[{"embeddable":true,"href":"https:\/\/krieger.jhu.edu\/financial-economics\/wp-json\/wp\/v2\/comments?post=6674301"}],"version-history":[{"count":7,"href":"https:\/\/krieger.jhu.edu\/financial-economics\/wp-json\/wp\/v2\/posts\/6674301\/revisions"}],"predecessor-version":[{"id":6674315,"href":"https:\/\/krieger.jhu.edu\/financial-economics\/wp-json\/wp\/v2\/posts\/6674301\/revisions\/6674315"}],"wp:attachment":[{"href":"https:\/\/krieger.jhu.edu\/financial-economics\/wp-json\/wp\/v2\/media?parent=6674301"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/krieger.jhu.edu\/financial-economics\/wp-json\/wp\/v2\/categories?post=6674301"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/krieger.jhu.edu\/financial-economics\/wp-json\/wp\/v2\/tags?post=6674301"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}