When Dallas County Judge Clay Jenkins issued the shelter-in-place order on Sunday, he showed a graph and cited a model from COVID ACT NOW to justify his decision. At the time the order was enacted on March 23, there were two deaths and 131 confirmed cases of COVID-19 in Dallas County, which has a population of over 2.7 million.
The COVID ACT NOW graph was showing at the time that a shelter-in-place order must be enacted before March 31 to avoid a scenario of overrunning hospital capacity. However, now the graph has been updated to show that the shelter-in-place order must be enacted by April 21, three weeks later.
Some doctors, like the Texas Chapter of the Association of American Physicians & Surgeons (AAPS), are questioning whether Jenkins acted prematurely or whether the projections are accurate.
COVID ACT NOW bases much of its model on the paper put out by Imperial College of London, which assumes a 7.3 percent hospitalization rate of serious cases. It updates the model every four days, based on some inputs of actual hospitalizations.
According to the World Health Organization, roughly 80 percent of known COVID-19 patients experience mild symptoms, about 14 percent require hospitalization, and five percent will be treated in the intensive care unit.
For comparison, the CDC’s preliminary data shows that last year’s seasonal flu in the United States had a hospitalization rate of one percent. It will be some time before the actual overall hospitalization rate of coronavirus in the U.S. can be assessed.
Texas currently has 794 reported cases according to Texas Health and Human Services, but it does not list how many are hospitalized. The first reported case of COVID-19 in Texas was on March 4.
Regarding the COVID ACT NOW model, the Texas Chapter of the Association of American Physicians & Surgeons said, “The model presented has a number of limitations and is likely to be an exaggerated estimate of deaths for the state of Texas. It does not take into account the limitations of the available data, which include selection bias due to limited number of tests, high false positives and false negatives of the test widely used, differences in social structure, population density, population health and risk factors such as smoking among the nations reporting data.”
Smoking creates a higher risk for those who acquire COVID-19, according to the TxAAPS, but the percentage of smokers in the United States is at least 10 percent lower than that of China and Italy.
Another factor, population density, could be of particular significance in the United States. “China’s population density is 397 people per square mile. Italy’s is 532 people per square mile, and South Korea’s is 1,366. The United States, by contrast, has only 94 people per square mile. That’s got to be a fact in our favor,” TxAAPS wrote in their statement.
COVID ACT NOW was started by some information technology executives and a member of the Alaska legislature. The medical advisor is Nirav Shah, an adjunct professor of medicine in primary care and population health at Stanford. He is not an epidemiologist or specialist in public health responses. His biographical profile says, “He is a leader in patient safety and quality, innovation and digital health, and the strategies required to transition to lower-cost, patient-centered health care.”
Another Stanford medical professor, John Ioannidis, a professor in disease prevention in the school of medicine and professor of health research and policy (epidemiology), sees issues with the current models being used for policy decisions.
In an article published a week ago by Stat News, Ioannidis points out what he sees as flaws in many of the projections. “We lack reliable evidence on how many people have been infected with SARS-CoV-2 [COVID-19] or who continue to become infected. Better information is needed to guide decisions and actions of monumental significance and to monitor their impact.”
AAPS also sees issues with only focusing on a high death rate projection and not considering the whole picture. “It is easy to see that by projecting a high number of COVID 19 related deaths while disregarding the increase in deaths that will result from the rapid economic decline, the necessary delay of treatment for people with other medical needs such as cancer, and the inevitable worsening of mental illness related to severe isolation measures and media-driven fear, a hollow victory may be claimed for implementing restrictions that edge closer to those used by communist dictatorships.”
One of the recommendations by Ioannidis and others is better testing of the population. “Three months after the outbreak emerged, most countries, including the U.S., lack the ability to test a large number of people and no countries have reliable data on the prevalence of the virus in a representative random sample of the general population.”
In other words, if we don’t know how many people actually have the virus, the death rate could be inflated and policies based on that could be an overreaction. “If that is the true rate [0.05%], locking down the world with potentially tremendous social and financial consequences may be totally irrational,” Ioannidis writes.
Two other Stanford professors, Dr. Jay Bhattacharya and Dr. Eran Bendavid, published an editorial in the Wall Street Journal calling for better testing in the United States.
Bhattacharya, a professor of medicine and researcher into the effect of government policies on vulnerable populations, and Bendavid, a professor of medicine who has a clinical focus on infectious diseases, are concerned with decisions being made based on misleading fatality rates.
They believe the number of actual infections is much larger than currently being considered because they believe the virus started here as early as January 1.
“An epidemic seed on Jan. 1 implies that by March 9 about six million people in the U.S. would have been infected. As of March 23, according to the Centers for Disease Control and Prevention, there were 499 Covid-19 deaths in the U.S. If our surmise of six million cases is accurate, that’s a mortality rate of 0.01%, assuming a two week lag between infection and death. This is one-tenth of the flu mortality rate of 0.1%. Such a low death rate would be cause for optimism.”
According to the March 25 data from the Centers for Disease Control, the U.S. now has nearly 60,000 confirmed cases and 737 deaths with New York becoming the epicenter at nearly 30,000 cases.
With better testing, however, it is possible that vulnerable populations could be isolated for their protection, and other citizens might be able to get back to work. This is the model that seemed to be successful in South Korea.
The good news amid debate over models and questions over how widespread the disease has become is that private companies such as Abbott Laboratories and Roche Diagnostics are ramping up test productions. Abbott plans to ship out 1,000,000 tests per week by the end of March and Roche sent out 400,000 this week.
This means more data collection is on the way. And with it, hopefully, better information for those tasked with making the critical decisions balancing public health with economic activity.
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Kim Roberts is a reporter for the Texan in the DFW metroplex area where she has lived for over twenty years. She has a Juris Doctor from Baylor University Law School and a Bachelor's in government from Angelo State University. In her free time, Kim home schools her daughter and coaches high school extemporaneous speaking and apologetics. She has been happily married to her husband for 23 years, has three wonderful children, and two dogs.