Early days of the pandemic—The association of economic and socio-political country characteristics with the development of the COVID-19 death toll

Abstract

This article examines cross-national differences in growth of deaths by COVID-19 over time in the first phase of the pandemic, during the time period of 31st December 2019 to 2nd April 2020. We seek to understand and explain country level reaction in the initial period of the pandemic. We explore socio-economic and socio-political country characteristics as determinants of deaths per day and we examine whether country characteristics act as moderating factors for different growth patterns of deaths per day over time. The country characteristics include variables about economy, globalization, health care and demography. We examine data published by the European Center of Disease Prevention and Control (ECDC) in combination with World Bank data and a webscraping approach. Using a conditional growth model specified as a multilevel regression model with deaths by COVID-19 per day as the outcome variable, we show that economic variables are not significantly associated with decrease or increase of deaths by COVID-19. In contrast, variables about national health care mitigate the impact of the pandemic. Demography shows expected effects with an increase of growth of deaths in countries with a higher percentage of people older than 65 years. Globalization predicts the death toll as well: Social interaction between people is deadly on a short-term scale (in the form of tourism). Our results mirror frequent demands for global investment in national health systems.

Association of government effectiveness, logistics performance, IT systems and income with COVID-19 mortality

“…They are also vulnerable to COVID-19 and the resultant mortality as they are less health-conscious than people from developed countries. COVID-19 has a greater toll in more developed nations [ 54 , 67 ] and economic variables are not significantly associated with a decrease or increase in deaths by COVID-19 [ 68 ].…”

The trade-off between health system resiliency and efficiency: evidence from COVID-19 in European regions

“…Income levels have been related to health outcomes, so all those studies use some indicator related to the income level (such as Gross Domestic Product per capita at purchasing power parities or Household income) or some variable related to material deprivation, such as the poverty rate, the unemployment rate, or a measure of inequality (Gini coefficient). The other economic factor found to be related to COVID-19 deaths is some measure of the economic structure of the region, since some workers are at higher risk of COVID-19 than others, because they work in physical proximity to other people (such as in manufacturing), or because they are more exposed to international contacts (in the tourism sector), or are at lower risk of COVID-19 because they are more able to work remotely (as it is the case for some services); the share of employees in the industry sector [ 35 ] or in the service sector [ 32 ], and the number of inbound tourists [ 38 ] have been used as measures of the exposure to COVID-19 due to the economic structure of the region.…”

“…The explanatory variables vector X includes the health system efficiency index computed as described above, and other variables that have been identified as significant determinants of COVID-19 deaths in previous literature (namely in [14,32,[35][36][37][38]), that can be classified in four groups.…”

The complexity of examining laboratory-based biological markers associated with mortality in hospitalized patients during early phase of the COVID-19 pandemic: A systematic review and evidence map

“…The original search for COVID-19 literature was conducted from December 2019-March 2020 in OVID MEDLINE In-Process, EMBASE, and Web of Science and an updated search extended the period to March 9, 2021 to maximize the inclusion of studies published during the early phase of the pandemic (late 2019 to early 2021) [13]. Additional studies were identified by checking abstracts and reference lists of included articles and systematic reviews; we did not contact study authors.…”