Responsiveness to Risk Explains Large Variation in COVID-19 Mortality across Countries
35 Pages Posted: 15 Dec 2020 Last revised: 8 Mar 2022
Date Written: March 7, 2022
Background: Health outcomes from the COVID-19 pandemic vary widely across countries – by 2022 New Zealand suffered ~10 total deaths per million people, whereas the U.K. and U.S. have had over 2000. Differences in infection fatality rates are insufficient to explain such vastly divergent outcomes. We propose that endogenous behavioral responses to risk shape countries’ epidemic trajectories, and that differences in responsiveness to risk are a primary driver of variation in epidemic scale and resultant mortality.
Methods: We develop several testable predictions based on the proposed endogenous risk response mechanism. We test these using a simple modified SEIR model incorporating this mechanism, which we estimate for 131 countries (5.96 billion people) using data on daily reported SARS-CoV-2 infections and COVID-19 deaths. We further examine associations between COVID-19 deaths and several observed and model-estimated country characteristics using linear regression.
Findings: We find empirical support for all predictions tested: 1) endogenous risk response substantially improves an SEIR model’s fit to data (mean absolute errors normalized by mean=66% across countries, vs. 551% without endogenous risk response); 2) Re converges to ~1 across countries in both empirical data and model estimates with endogenous risk response (but not without it); 3) most cross-country variation in death rates cannot be explained by intuitively important factors like hospital capacity or policy response stringency; and 4) responsiveness to risk, which governs the sensitivity of the endogenous risk response, correlates strongly with death rates (R2=0.75) and is the strongest explanatory factor for cross-country variation therein.
Interpretation: Countries converge to policy measures consistent with Re~1 (or exponentially growing outbreaks will compel them to increase restrictions). Responsiveness to risk, i.e. how readily a country adopts the required measures, shapes long-term cases and deaths. With greater responsiveness, many countries could considerably improve pandemic outcomes without imposing more restrictive control policies.
Keywords: epidemiology, COVID-19, SARS-CoV-2, epidemics, simulation, Bayesian estimation, economic tradeoff, mathematical model
JEL Classification: I12, I1, I18
Suggested Citation: Suggested Citation