Dispelling Some Of The COVID-19 Unknowns
For anyone following the COVID-19 pandemic – and who isn’t? – it’s evident that we’re awash in punditry, speculation, and modeling. But we two are Massachusetts Institute of Technology graduates, and we’re looking past the noise to what critical data we don’t yet have that will affect the management of the outbreak – which will, in turn, affect both public health and our economic recovery.
On the medical front, let’s consider what we do know. First and foremost, the situation in the U.S. continues to worsen. The nation’s death toll is rising exponentially, and the steepness of New York’s curve is terrifying. So are the number of confirmed infections, but that statistic is of limited value, inasmuch as its accuracy depends on the (now finally increasing) numbers of tests conducted.
Second, it is certain that where health care delivery systems are overwhelmed – as appears to be imminent in New York, Chicago, San Francisco, Los Angeles, Atlanta, Detroit, and a few other places – there will be many potentially avoidable deaths. They may not be only in undertreated COVID-19 patients, but also in patients with other critical needs who are crowded out and delayed, such as a stroke victim or a teenager with a severe brain injury from a motorcycle accident. They may even be patients hospitalized with non-COVID-19 ailments who become infected because of a breakdown in isolation procedures due to overcrowding and shortages of personal protection equipment for medical staff.
Drug treatments currently being evaluated offer hope to reduce the pressure on hospitals, especially their intensive-care units. But the timing remains uncertain.
Finally, we do know that help from a vaccine, which would be the best solution, is, at best, years away. The current public health and regulatory standard for vaccines that would be universally administered to healthy people is randomized, controlled clinical trials in tens of thousands of subjects, to assure that it is both safe and effective. Safety requirements are obvious: If hundreds of millions potentially could receive a vaccine, a small incidence of serious side effects can become a major problem. Efficacy testing is essential because a failure should redirect effort to develop and test other candidate vaccines.
Beyond that, we are still largely in what soldiers call the “fog of war.” There is debate about the “true” death rate, which is an important determinant of policy, but we’re fuzzy on the denominator, in large part because many – perhaps, more than half – of infections are asymptomatic or mildly symptomatic and don’t come to medical attention. We need to know that number accurately, which would provide us critical information of several kinds:
- The degree of covert vs. symptomatic penetration of the virus in various demographic and other definable groups, which is important so that we can tailor policies accordingly if there are significant differences.
- An understanding of the full scope of the outbreak, including how the virus spreads.
- Knowledge of true case fatality rates, which can be known only with accurate determination of overall infections, not just those patients who presented disease symptoms and had infection confirmed by a test for viral genetic material. Only by having these data in hand do we know how COVID-19 really compares to the flu, SARS, or MERS.
The test kits in use in the U.S. up to now detect viral genetic material — RNA, in the case of coronaviruses — which can be infectious material or noninfectious fragments. Once the patient has recovered and the RNA has been cleared, the tests will become negative. Therefore, if we’re trying to ascertain what proportion of the population has been infected and experienced asymptomatic, mild or more serious infections, such post-infection testing yields “false negatives.”
Therefore, infection data will need to come from “serological tests” that measure antibodies in blood, which will tell us whether a person has been recently infected with SARS-CoV-2 and recovered. (Note that antibodies take about 10-14 days from exposure to the virus to appear.)
Henry Schein Inc. announced that the shipping of such serological tests began this week. These are reportedly point-of-care tests that are simple and inexpensive to administer, with the results available immediately. (The company did not provide information on the source of the tests, or their sensitivity and specificity.) We expect that others will follow soon.
Epidemiologists will now be able to design protocols to use serological tests to assess infection rates in the population. This is analogous to polling, where scientifically selected samples can be assessed, allowing extrapolations to the larger population.
Currently, in most places, government officials appear to be adopting measures that are appropriately conservative in order to protect public health. They include testing, quarantines of infected patients, and social distancing (a term that no longer connotes boys and girls congregating separately at school dances). A methodical, scientific, serological testing program will provide information that could facilitate the rolling back of the debilitating restrictions on Americans’ lives and livelihoods. We must get that underway as quickly as possible, so we can substitute data for assumptions-dependent modeling and begin to ramp up economic activity as soon as feasible.
Fillat spent his career in technology venture capital and information technology companies. He is also the co-inventor of relational databases. Miller, a physician and molecular biologist, is a senior fellow at the Pacific Research Institute. He was the co-discoverer of a critical enzyme in the influenza virion. They were undergraduates together at the Massachusetts Institute of Technology.