Trading Health for Wealth: The Effect of COVID-19 Response Stringency

Abstract

International governments' COVID-19 responses must balance human and economic health. Beyond slowing viral transmission, strict lockdowns have severe economic consequences. This work investigated response stringency, quantified by the Oxford COVID-19 Government Response Tracker's Stringency Index, and examined how restrictive interventions affected infection rates and gross domestic product (GDP) in China and OECD countries. Accounting for response timing, China imposed the most stringent restrictions, while Sweden and Japan were the least stringent. Expected GDP declines range from -8% (Japan) to -15.4% (UK). While greater restrictions generally slowed viral transmission, they failed to reach statistical significance and reduced GDP (p = 0.006). Timing was fundamental: governments who responded to the pandemic faster saw greater reductions in viral transmission (p = 0.013), but worse decreases in GDP (p = 0.044). Thus, response stringency has a greater effect on GDP than infection rates, which are instead affected by the timing of COVID-19 interventions. Attempts to mitigate economic impacts by delaying restrictions or decreasing stringency may buoy GDP in the short term but increase infection rates, the longer-term economic consequences of which are not yet fully understood. As highly restrictive interventions were successful in some but not all countries, decision-makers must consider whether their strategies are appropriate for the country on health and economic grounds.

Keywords: COVID-19; GDP; infection rate; stringency index.

Figure 1

Stringency index and infection rates. The rate of new cases is shown in black for periods of one month before and one month after a period at maximum stringency index (SI) [10,12], which is highlighted in red. SI over the same period is overlaid in blue and scaled from 0 to 100 in all plots to enable comparisons.

Figure 2

The effect of COVID-19 responses on annual GDP growth rates. Annual GDP growth rates were estimated by the OECD.13 (a) Results of multilevel mixed-effect linear regression models of change in annual growth rate 2019–2020 per interquartile range (IQR) due to a double-hit scenario (38 countries; multivariate analyses adjusted for GDP). Error bars show 95% confidence intervals; * p < 0.05. The difference between the 2019 and 2020 growth rates is shown against (b) response stringency and duration (area under the curve; AUC) and (c) the time for each country to respond to the pandemic (stringency index > 0); this includes both preventative restrictions that may have preceded confirmed cases in those countries.