When the newest corona virus, COVID-19, was released into the world from China there was little known about it. Most of our information necessarily came from China, an authoritarian government not known for its transparency. Assumptions were necessary based on the Chinese experience and data was inserted into computer models to predict the possible outcomes of this new viral pandemic.
Some of those models predicted up to 500,000 deaths in the United Kingdom and up to 2.2 million deaths in the United States. With time, these models were adjusted and the number of predicted deaths plummeted to still frightening numbers of 100,000 to 240,000 deaths in the U.S. Eventually the models brought the numbers below 100,000. As I write these words, the number of deaths in the U.S. has reached 39,000. While that’s still a lot of people, it’s a long way from 2.2 million and actually represents fewer deaths thus far from COVID-19 than some years from influenza (2017 – 61,000 deaths from influenza).
The mortality rate of COVID-19 has been estimated by the World Health Organization (WHO) at 3.4%. The accuracy of this number depends entirely on knowing the number of people who got infected but did not die. That number forms the basis of the denominator in any calculation of the mortality rate. Therefore, accuracy must be based on testing, not only those with obvious disease, but also those without symptoms, which has been unavailable to date.
All of these predictions thus far have been based on unreliable data and speculation. But now we have the first scientific study to draw more accurate conclusions. A preliminary study from Stanford University has just been released that sharply differs with previous conclusions.
Andrew Bogan, a molecular biologist writing in The Wall Street Journal, reports a seroprevalence study of Santa Clara County, California. They sampled 3,300 residents to test them for the presence of antibodies in their blood that would show if they had previously been infected with the corona virus. The researchers found the percentage of infections in the population was indeed vastly larger than the roughly 1,000 known positive cases in the county at the time of the study. This is certainly consistent with expectations since only those with viral symptoms and fever were being tested.
The preliminary results show that between 2.5% and 4.2% of county residents are estimated to have antibodies against the virus. That translates into 48,000 to 81,000 infections, 50 to 85 times as high as the number of known cases. Rather than being frightening, this is great news. It means thousands of people are experiencing infection by the virus without ever knowing it – and that means the mortality rate is much, much lower than expected.
Based on this seroprevalence data, the authors estimate that in Santa Clara County the true infection fatality rate is somewhere in the range of 0.12% to 0.2%. This is much closer to the seasonal influenza rates than to the original, case-based estimates.
This is not to suggest that COVID-19 is not a serious viral disease nor to imply that precautions were unnecessary. There can be no doubt that it has taken a significant world-wide toll of human lives. At this writing the number of world-wide deaths has reached 161,904. Until there is an effective vaccine, there will continue to be a real and present danger especially to those who are elderly, immunosuppressed, or have significant other medical co-morbidities including heart disease, COPD, and diabetes.
However, given what we now know about the virus and its lethality, in the future we can make better policy decisions designed to protect the most vulnerable while maintaining some semblance of normalcy that does not destroy the economy. We certainly don’t take draconian steps to prevent the spread of influenza, which in some seasons has been even more lethal than COVID-19.
