How social indicators and healthcare systems shape pandemic outcomes: Lessons from COVID-19
Year: 2025
Type: article
Study design: Observational Study
Abstract: Introduction: The COVID-19 pandemic exposed structural weaknesses in healthcare and socioeconomic systems worldwide. This study examines how perceived corruption, health literacy, and communication with healthcare workers influenced COVID-19 cases and deaths across 79 countries. While earlier research considered various determinants, these socio-institutional factors remain underexplored in cross-country analyses. By integrating them into a single empirical framework, this study offers new insights into how trust and public awareness affect pandemic outcomes. Methods: Using cross-sectional data from 79 countries, we employed Ordinary Least Squares (OLS) regression to analyze two outcomes: reported COVID-19 cases and deaths. Key independent variables include perceived corruption, a composite health literacy index, and citizens’ ability to communicate with healthcare workers. Results: Perceived corruption is negatively associated with both cases and deaths, significant at the 1% level—a one-unit rise predicts a 76% drop in cases and 2.77-fold reduction in deaths. Perceived criminality increases death rates by 148% (5% significance). Health literacy shows a positive association with reported cases (2.28-fold increase, 5% significance), likely reflecting greater testing and awareness. Its relationship with deaths is positive but not statistically significant. Communication with healthcare workers is linked to a 119% increase in deaths (10% significance), possibly indicating late engagement with medical services. Discussion: The results highlight how institutional trust, public awareness, and healthcare access shape pandemic responses. Corruption may undermine public compliance, while health literacy enhances early detection. Increased mortality associated with delayed communication suggests gaps in timely care access.
DOI: 10.19204/2025/hwsc2
Authors: SM Asif EHSAN, KA Binte ARIF, Mostafizur RAHMAN
Institutions: North South University, BRAC, BRAC University
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7104431835
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