Accounting for Global COVID-19 Diffusion Patterns, January-April 2020

Abstract

Key factors in modeling a pandemic and guiding policy-making include mortality rates associated with infections; the ability of government policies, medical systems, and society to adapt to the changing dynamics of a pandemic; and institutional and demographic characteristics affecting citizens' perceptions and behavioral responses to stringent policies. This paper traces the cross-country associations between COVID-19 mortality, policy interventions aimed at limiting social contact, and their interactions with institutional and demographic characteristics. We document that, with a lag, more stringent pandemic policies were associated with lower mortality growth rates. The association between stricter pandemic policies and lower future mortality growth is more pronounced in countries with a greater proportion of the elderly population and urban population, greater democratic freedoms, and larger international travel flows. Countries with greater policy stringency in place prior to the first death realized lower peak mortality rates and exhibited lower durations to the first mortality peak. In contrast, countries with higher initial mobility saw higher peak mortality rates in the first phase of the pandemic, and countries with a larger elderly population, a greater share of employees in vulnerable occupations, and a higher level of democracy took longer to reach their peak mortalities. Our results suggest that policy interventions are effective at slowing the geometric pattern of mortality growth, reducing the peak mortality, and shortening the duration to the first peak. We also shed light on the importance of institutional and demographic characteristics in guiding policy-making for future waves of the pandemic.

Keywords: Covid-19; Cross-country estimates; Flattening the mortality curve; Government intervention; Lock-down; Pandemic; Policy stringency; Socioeconomic indicators.

Fig. 1

COVID-19 mortality rate curves, by country. LHS (a): Cumulative logged mortality rate. RHS (b): New Mortality Rate. 7-day rolling averages. Series starts from the 5th COVID-assigned death

Fig. 2

Sample Countries and New Mortality Curves, 1/23/20–4/28/20. Note: 7-Day rolling average new mortality rate by country. Y-axis normalized to have all countries fit the same scale. Period: January 23 – April 28, 2020. Special case countries we omit from the above plots: China (a discrete large spike in mortality in mid-April to account for past reporting delays and omissions), Singapore (highly fluctuating case curves associated to immigrant workers), and Vietnam (a flat line)

Fig. 3

Daily New COVID-19 Global Mortalities. Note: Cumulated daily deaths across all countries in the sample

Fig. 4

Peak-related dependent variables in country case of Czechia

Fig. 5

Daily new mortality curves of selected countries

Fig. 6

The mortality rate is negatively associated with the intensity of government response. Note: Pooled estimates from local projections are represented as gray circles. Error bars reflect 95% confidence intervals based on HAC-robust standard errors clustered by country

Fig. 7

Mortality impacts: government response, demographics, geography, and development level. Note: Red squares (blue circles) represent the local projection impact from a 10-unit higher stringency index on mortality growth for countries in the 75th percentile (25th percentile) of the country characteristic

Fig. 8

Time-to-peak duration analysis of mortality rates. Note: Y-axis indicates the probability the peak mortality/case is ‘yet to come’. The higher y-axis implies a lower probability of peaking. X-axis reflects the number of days since the first mortality/case was realized. Shaded areas represent 95% confidence intervals

Fig. 9

The cumulative mortality growth rate is negatively associated with the intensity of government response. Note: Results of panel analysis on cumulative mortality growth rates. Pooled estimates from local projections are represented as gray circles. Error bars reflect 95% confidence intervals based on HAC-robust standard errors clustered by country

Fig. 10

Cumulative mortality growth impacts: government response, demographics, geography, and development level. Note: Results of panel analysis on cumulative mortality growth rates. Red squares (blue circles) represent the local projection impact from a 10-unit higher stringency index on mortality growth for countries in the 75th percentile (25th percentile) of the country characteristic

Fig. 11

Global Distribution of Residuals of Cross-Country Analysis - Peak Mortality Rate. Note: Residuals are calculated from cross-country regression specified in Column [1] of Table 2, with the omission of the “Early Mobility” for a greater country coverage

Fig. 12

Global Distribution of Residuals of Cross-Country Analysis - Peak Mortality Rate-to-PD Ratio. Note: Residuals are calculated from cross-country regression specified in Column [1] of Table 2, with the omission of the “Early Mobility” for a greater country coverage