Factors that most expose countries to COVID-19: a composite indicators-based approach

Area of Science:

• Epidemiology
• Public Health
• Socioeconomics

Background:

• Previous studies correlated COVID-19 outcomes with various factors but didn't pinpoint country-specific exposure drivers.
• Understanding factors influencing a country's vulnerability to COVID-19 is crucial for targeted public health interventions.

Purpose of the Study:

• To identify key factors impacting COVID-19 cases and deaths globally.
• To measure and compare countries' exposure levels to COVID-19 using a composite indicator approach.

Main Methods:

• Development of three composite indicators for COVID-19 exposure using Principal Component Analysis, Simple Additive Weighting, and k-means clustering.
• Correlation analysis between composite indicator scores, country clusters, and COVID-19 case and death data.
• Comparative analysis of demographic and socioeconomic factors between high and low COVID-19 exposed countries.

Main Results:

• Strong correlations (r > 0.60) were found between composite indicator scores and COVID-19 cases/deaths.
• Population age emerged as a primary factor; more exposed countries had populations 12 years older on average.
• Higher Gross Domestic Product per capita and Human Development Index were associated with increased COVID-19 exposure.

Conclusions:

• Population age and factors enhancing life expectancy (e.g., GDP per capita, HDI) significantly increase a country's COVID-19 exposure.
• Improved living conditions paradoxically heighten vulnerability to COVID-19, necessitating tailored public health strategies.