How Big Is the Risk of Epidemics, Really?
November 14 2023
The COVID-19 pandemic caused losses of lives and livelihoods on a scale that many of us had never seen in our lifetimes, shedding light on the ways that pandemics are a “neglected dimension” of global security. And yet, as we are already observing, proposals for increased, sustained support for surveillance and preparedness are having to contend with an entrenched panic-neglect cycle in health security.
This inertia is partially the result of a variety of cognitive biases that make it difficult to grapple with low frequency, high severity events. Policymakers tend to treat epidemics as both unpredictable and inevitable, for example, assuming that COVID-19 was a “once in a lifetime” or even “once in a century” threat. This assumption—which we systematically dismantle—reduces the urgency to invest in preparedness.
This is a mistake, and potentially an extremely costly one. We propose instead a risk-informed approach to design preparedness investments, using rigorous assessments of the frequency and severity—put simply, the risk—of future epidemics. This type of process is already used to guide preparedness efforts for other natural disasters, such hurricanes and earthquakes. The time has come to apply it to the large—and rising—challenge of infectious disease threats.
A new approach to understanding epidemic risk
We’ve published new estimates of the risk of future epidemics as a joint Center for Global Development and Disease Control Priorities (DCP-4) working paper. Our approach diverges from many existing approaches in that in addition to drawing upon historical data, which is particularly suited to estimating the risk from frequent or recurring epidemics, we use a computational epidemiology framework to generate simulated data that fills in the gaps, including the crucial and data-poor region of “tail risk”—that is, infrequent, high-consequence epidemics. These types of models are very uncommon in public health literature, but widely used in other areas of natural hazard modeling, such as for floods and earthquakes.
