With the United States gradually ramping up testing for the coronavirus, there has been a sharp, expected increase in the number of cases of COVID-19 disease. The individuals tested will learn whether they are infected, but, paradoxically, the public—and public health officials—will not know whether the total results are encouraging or discouraging. This is because the rates of the coronavirus infectivity and mortality will remain poorly understood. And without such information, it is impossible to predict, accurately, the percentage of Americans who have been or are likely to become infected, and of those infected how many will be asymptomatic, have a relatively mild, flu-like disease, become critically ill, or die.
Worst-case scenarios are, by definition, intended to depict extreme events before taking into account effective mitigation strategies, such as social distancing.
Also important, it will be hard to know when we can begin to reduce the restrictions on Americans’ activities.
New York Times investigative reporter James Glanz and his colleagues have reported that the driving force for growth in COVID-19 in the U.S are Americans with mild symptoms who are carrying and spreading the virus without being aware that they have it. Their March 20th article estimates the number of undetected cases at 11 times more than those officially reported, and Jane Qiu wrote on March 20th in the journal Nature, preliminary estimates of these covert cases suggest they might comprise 60 percent of all infections.
In February, the CDC considered various possible scenarios for how the outbreak would progress, based on characteristics of the virus, including crude estimates of infectiousness and severity of the illness. Its “worst case” was shocking, indeed, with the possibility of more than 200 million Americans infected, 2.4 million to 21 million potentially requiring hospitalization, and as many as 200, 000 to 1.7 million dying. This scenario was worse than the 1918 Spanish Flu pandemic, which globally infected 500 million people (one-third of the world’s population) and killed at least 50 million people worldwide and 675,000 in the United States alone. The CDC’s worst-case scenario would crush the nation’s medical system, which has only about 925,000 staffed hospital beds, with less than a tenth of those available for the critically ill.
Worst-case scenarios are, by definition, intended to depict extreme events before taking into account effective mitigation strategies, such as social distancing. But coronavirus testing of statistically appropriate population samples will be necessary for information essential to the management of the pandemic and offer critical information about important, disease-causing characteristics of this particular virus that are essential to formulating policies to control and predict the spread of COVID-19.
CRITICAL DATA FOR CRITICAL QUESTIONS
How many people of various ages, sex, ethnicities, and other demographic characteristics in the population became infected? How many remain asymptomatic, and how many have symptoms? Of those with symptoms, how many cases are mild, require hospitalization, or are fatal? How readily is it transmitted from person to person? How many people will an infected person subsequently infect? What is the length of the incubation period and the usual course of the disease? How long does post-infection immunity to infection persist?
The U.S. government has been slow and inept at developing and distributing coronavirus tests and obtaining timely test results, which has wasted valuable time and delayed effective disease prevention and treatment.
These are all questions that epidemiologists and legislators cannot answer right now—and they are the questions that should inform what the next 4-12 weeks look like for Americans.
The coronavirus test kits currently available in the U.S. can provide only part of the puzzle. They detect only certain coronavirus genetic fragments (RNA). Thus, in trying to ascertain what proportion of the population has had any degree of infection (asymptomatic, mild, or more serious), such post-recovery testing will yield “false negatives” because the body clears these genetic fragments after recovery. That distorts our understanding of infection and case fatality rates because accurate calculation of rates requires a true denominator. And the absence of knowledge of those rates blurs our understanding of how successful mitigation measures have been.
Answers to the missing part of the puzzle will need to come from so-called “serological tests” that measure anti-coronavirus antibodies in the blood and reveal whether a person has been infected with the coronavirus and recovered. (Antibodies arise approximately 10-14 days after infection.)
Serological tests are currently being used in Singapore and China, and are under development by the CDC. Their availability and application to a statistically appropriate sample of Americans will provide essential data on how widespread and pervasive in the U.S. COVID-19 infections have been. Understanding the percentage of the population that has been infected—and, subsequently, developed antibodies to the virus—is a critical factor in determining the likely course of the epidemic and the best approaches to managing it.
The U.S. government has been slow and inept at developing and distributing coronavirus tests and obtaining timely test results, which has wasted valuable time and delayed effective disease prevention and treatment. The federal government should avoid further missteps by aggressively conducting population studies with both coronavirus testing and serological assays for antibodies. Only then will a better understanding of the epidemiological characteristics of COVID-19 enable us to slow its spread, and ultimately, know when we can begin to roll back painful restrictions on Americans’ daily lives.