Early adoption of non-pharmaceutical interventions and COVID-19 mortality

Abstract

To contain the spread of the COVID-19 pandemic, many countries around the globe have adopted social distancing measures. Yet, establishing the causal effect of non-pharmaceutical interventions (NPIs) is difficult because they do not occur arbitrarily. We exploit a quasi-random source of variation for identification purposes -namely, regional differences in the placement on the pandemic curve following an unexpected and nationwide lockdown. Our results reveal that regions where the outbreak had just started when the lockdown was implemented had 1.62 fewer daily deaths per 100,000 inhabitants when compared to regions for which the lockdown arrived 10+ days after the pandemic's outbreak. As a result, a total of 4,642 total deaths (232 deaths/daily) could have been avoided by the end of our period of study -a figure representing 23% of registered deaths in Spain at the time. We rule out differential pre-COVID mortality trends and self-distancing behaviors across the compared regions prior to the swift lockdown, which was also uniformly observed nationwide. In addition, we provide supporting evidence for contagion deceleration as the main mechanism behind the effectiveness of the early adoption of NPIs in lowering the death rate, rather than an increased healthcare capacity.

Keywords: COVID-19; Coronavirus; Lockdown; Mortality; Pandemic; Spain.

Fig. 1

Daily COVID-19 Deaths per 100,000 Inhabitants. Notes:Early-on-the-curve refers to regions for which the lockdown occurred 2 days or less after the pandemic outbreak [i.e. Andalucía (1), Baleares (0), Canarias (2), Cantabria (2), Comunidad Valenciana (0), Extremadura (2), Castilla-León (3), Cataluña (2), Galicia (2) and Murcia (1)]. Late-on-the-curve refers to regions for which the lockdown took place 3+ days after the outbreak [i.e. Aragón (4), Asturias (4), Madrid (9), País Vasco (7), Castilla La Mancha (4), Navarra (4) and La Rioja (10)].

Fig. 2

Predicted Daily COVID-19 Deaths per 100,000 Inhabitants by Days Elapsed from Outbreak to Lockdown. Notes: Raw data are average regional daily death rates. Simulation shows predictions from the model in Eq. (1) when the variable $S_j$ is set equal to 0.

Fig. 3

Changes in Mobility Patterns. Notes:Early-on-the-curve refers to regions for which the lockdown occurred 2 days or less after the pandemic outbreak [i.e. Andalucía (1), Baleares (0), Canarias (2), Cantabria (2), Comunidad Valenciana (0), Extremadura (2), Castilla-León (2), Cataluña (2), Galicia (2) and Murcia (2)]. Late-on-the-curve refers to regions for which the lockdown took place 3+ days after the outbreak [i.e. Aragón (4), Asturias (4), Madrid (6), País Vasco (7), Castilla La Mancha (4), Navarra (4) and La Rioja (10)].

Fig. A1

The Impact of Accelerating the Lockdown Implementation on Daily COVID-19 Mortality Removing One Region at a Time. Note: The horizontal red line represents the impact of accelerating the lockdown implementation on daily COVID-19 mortality when using all regions, and the dotted lines the corresponding confidence intervals. Each one of the thicker dots represents the effect of accelerating the implementation of the lockdown on daily COVID-19 mortality when we exclude one region at a time.

Fig. A2

Daily 2019 Deaths per 100,000 Inhabitants. Notes:Early-on-the-curve refers to regions for which the lockdown occurred 2 days or less after the pandemic outbreak [i.e. Andalucía (1), Baleares (0), Canarias (2), Cantabria (2), Comunidad Valenciana (0), Extremadura (2), Castilla-León (3), Cataluña (2), Galicia (2) and Murcia (1)]. Late-on-the-curve refers to regions for which the lockdown took place 3+ days after the outbreak [i.e. Aragón (4), Asturias (4), Madrid (9), País Vasco (7), Castilla La Mancha (4), Navarra (4) and La Rioja (10)].

Fig. A3

Retail and Recreation Mobility.

Fig. A4

Grocery and Pharmacy Mobility.

Fig. A5

Parks Mobility.

Fig. A6

Transit Stations Mobility.

Fig. A7

Workplaces Mobility.

Fig. A8

Residential Mobility.