Country-level determinants of the severity of the first global wave of the COVID-19 pandemic: an ecological study

Abstract

Objective: We aimed to identify the country-level determinants of the severity of the first wave of the COVID-19 pandemic.

Design: Ecological study of publicly available data. Countries reporting >25 COVID-19 related deaths until 8 June 2020 were included. The outcome was log mean mortality rate from COVID-19, an estimate of the country-level daily increase in reported deaths during the ascending phase of the epidemic curve. Potential determinants assessed were most recently published demographic parameters (population and population density, percentage population living in urban areas, population >65 years, average body mass index and smoking prevalence); economic parameters (gross domestic product per capita); environmental parameters (pollution levels and mean temperature (January-May); comorbidities (prevalence of diabetes, hypertension and cancer); health system parameters (WHO Health Index and hospital beds per 10 000 population); international arrivals; the stringency index, as a measure of country-level response to COVID-19; BCG vaccination coverage; UV radiation exposure; and testing capacity. Multivariable linear regression was used to analyse the data.

Primary outcome: Country-level mean mortality rate: the mean slope of the COVID-19 mortality curve during its ascending phase.

Participants: Thirty-seven countries were included: Algeria, Argentina, Austria, Belgium, Brazil, Canada, Chile, Colombia, the Dominican Republic, Ecuador, Egypt, Finland, France, Germany, Hungary, India, Indonesia, Ireland, Italy, Japan, Mexico, the Netherlands, Peru, the Philippines, Poland, Portugal, Romania, the Russian Federation, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, Ukraine, the UK and the USA.

Results: Of all country-level determinants included in the multivariable model, total number of international arrivals (beta 0.033 (95% CI 0.012 to 0.054)) and BCG vaccination coverage (-0.018 (95% CI -0.034 to -0.002)), were significantly associated with the natural logarithm of the mean death rate.

Conclusions: International travel was directly associated with the mortality slope and thus potentially the spread of COVID-19. Very early restrictions on international travel should be considered to control COVID-19 outbreaks and prevent related deaths.

Keywords: epidemiology; infectious diseases; public health.

Figure 1

Graphical representation of the smoothed* number of daily deaths of each country (before reaching mortality peak, if applicable) as a function of the number of days passed since the first day when an excess of three deaths were reported. Countries with higher mean mortality rates are depicted in blue, while those with lower mean mortality rates are depicted in red. *Smoothed using a local regression (Lowess) function with a bandwidth of 0.4.

Figure 2

Predicted (based on the results of the multivariable linear regression) and observed country-level mortality rate (mean daily increase in deaths until the peak in mortality) as a function of the recorded country-level number of international arrivals in 2018 (millions). The solid red line represents the point estimate of the predicted log daily increase in deaths, while the blue-grey area represents the corresponding 95% CI. The crosses represent the observed values of the log daily increase in deaths.

Figure 3

Predicted (based on the results of the multivariable linear regression) and observed country-level mortality rate (mean daily increase in deaths until the peak in mortality) as a function of each country-level determinant included in the multivariable model. The solid red lines represent the point estimates of the predicted log daily increase in deaths, while the blue-grey areas represent the corresponding 95% CI. The crosses represent the observed values of the log daily increase in deaths.