Digitalization, income inequality, and public health: Evidence from developing countries
1College of Economics and Management, Northeast Agricultural University, Harbin, PR China.
Abstract:
The COVID-19 pandemic has amplified the awareness and demand of public health worldwide. Based on the panel data of 81 developing countries from 2002 to 2019, this study probes into the effect of digitalization on public health and explores the mechanism through which digitalization affects public health from the perspective of income inequality. The results show that digitalization significantly enhances public health in developing countries, and this conclusion still holds after the robustness test. The heterogeneity analysis based on geographic location and income level indicates that the enhancing effect of digitalization on public health is most evident in Africa and middle-income countries. A further mechanism analysis suggests that digitalization can positively impact public health through the intermediary channel of suppressing income inequality. This study enriches the research on digitalization and public health and provides insights for comprehending public health needs and the powerful empowering effects of digitalization.
Related Concept Videos
Issues And Trends In Healthcare Delivery System
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Methods Of Healthcare Delivery System
Managed Care System:
The managed care system is designed to control the cost while maintaining the quality of care. The patient's care from admission to discharge is planned by the primary care provider or the case manager, also known as the gatekeeper. In a managed care system, the number of care providers is...
Current Trends in Nursing II
Principles of Disease Surveillance
Primary Healthcare Services
In 1978, international leaders convened in Alma-Ata, Kazakhstan, for what would be a pivotal event in global health. The Alma-Ata Declaration was the first to call...
Bias in Epidemiological Studies


