statnews | The current coronavirus disease, Covid-19, has been called a once-in-a-century pandemic. But it may also be a once-in-a-century evidence fiasco.
At a time when everyone needs better information, from disease
modelers and governments to people quarantined or just social
distancing, we lack reliable evidence on how many people have been
infected with SARS-CoV-2 or who continue to become infected. Better
information is needed to guide decisions and actions of monumental
significance and to monitor their impact.
Draconian countermeasures have been adopted in many countries. If the
pandemic dissipates — either on its own or because of these measures —
short-term extreme social distancing and lockdowns may be bearable. How
long, though, should measures like these be continued if the pandemic
churns across the globe unabated? How can policymakers tell if they are
doing more good than harm?
Vaccines or affordable treatments take many months (or even years) to
develop and test properly. Given such timelines, the consequences of
long-term lockdowns are entirely unknown.
The data collected so far on how many people are infected and how the
epidemic is evolving are utterly unreliable. Given the limited testing
to date, some deaths and probably the vast majority of infections due to
SARS-CoV-2 are being missed. We don’t know if we are failing to capture
infections by a factor of three or 300. 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.
This evidence fiasco creates tremendous uncertainty about the risk of
dying from Covid-19. Reported case fatality rates, like the official
3.4% rate from the World Health Organization, cause horror — and are
meaningless. Patients who have been tested for SARS-CoV-2 are
disproportionately those with severe symptoms and bad outcomes. As most
health systems have limited testing capacity, selection bias may even
worsen in the near future.
