Why were some countries more successful than others in curbing early COVID-19 mortality impact? A cross-country configurational analysis

Abstract

Why was there considerable variation in initial COVID-19 mortality impact across countries? Through a configurational lens, this paper examines which configurations of five conditions—a delayed public-health response, past epidemic experience, proportion of elderly in population, population density, and national income per capita—influence early COVID-19 mortality impact measured by years of life lost (YLL). A fuzzy-set qualitative comparative analysis (fsQCA) of 80 countries identifies four distinctive pathways associated with high YLL rate and four other different pathways leading to low YLL rate. Results suggest that there is no singular “playbook”—a set of policies that countries can follow. Some countries failed differently, whereas others succeeded differently. Countries should take into account their situational contexts to adopt a holistic response strategy to combat any future public-health crisis. Regardless of the country’s past epidemic experience and national income levels, a speedy public-health response always works well. For high-income countries with high population density or past epidemic experience, they need to take extra care to protect elderly populations who may otherwise overstretch healthcare capacity.

COVID-19 impact on life expectancy in Mexico. An analysis based on the Global Burden of Disease 2021 study

“…However, to better understand its drop, it is essential to consider other indicators such as the timely response of authorities, past epidemic experience, the proportion of older adults in the population, population density and national per capita income, which have been reported as the main factors that influence LEB drop. 26 In this study, mortality was analyzed considering different periods, comparisons between nations and between Mexican states, according to their degree of economic development. That is, if a state had a satisfactory performance, its actual result would be expected to be higher than projected.…”

High Income But Poor COVID-19 Outcomes: The Contrasting Results of The Pre-COVID 19 Joint External Evaluation Assessment Tool in Measuring Countries’ Global Health Security Preparedness and Response Capacities

“…JEE tools are primarily focused on measurable capacities based on predefined criteria. While the JEE exercise may find a country scoring "developed" or "sustainable" capacity based on the JEE assessment criteria, the respective country may not be able to demonstrate the same level of capacities and achieve expected outcomes in a real-life emergency due to many factors including delayed response [19,20], investment priority in critical sectors [21], demographic factors such as relative younger or older populations [22] Nevertheless, JEE tools must be reliable and action-oriented.…”

Impacto de COVID-19 en la esperanza de vida en México. Un análisis basado en el estudio <i>Global Burden of Disease</i> 2021

“…Sin embargo, para entender mejor su caída es esencial considerar otros indicadores como la respuesta oportuna de las autoridades, la experiencia epidémica pasada, la proporción de adultos mayores en la población, la densidad de la población y el ingreso nacional per cápita, que se han reportado como los principales factores que influyen en la caída de la EVN. 26 En este estudio, se analizó la mortalidad considerando distintos períodos, comparaciones entre naciones y entre los estados mexicanos, de acuerdo con su grado de desarrollo económico. Es decir, si un estado presentaba un desempeño adecuado, se esperaría que su resultado real fuera superior al proyectado.…”