Systematic Determinants of Global COVID-19 Burden: Longitudinal Time-Series Analysis Using Big Data-Driven Artificial Intelligence.

ABSTRACT:

Background

The COVID-19 pandemic has transitioned into an endemic phase with heterogeneous resurgences. Despite widespread vaccination and public health measures, the interplay of viral evolution, population immunity, and environmental factors drives diverse global patterns of COVID-19 burden. However, how these systematic factors dynamically shape disease transmission and severity across populations remains incompletely understood.

Objective

This study aims to determine the relative contributions and temporal dynamics of viral variants, population immunity (natural infection and vaccination), environmental conditions, and public health measures in determining COVID-19 disease burden.

Methods

This retrospective longitudinal time-series study used a big data-driven int

SUBMITTER: Cao Z 

PROVIDER: S-EPMC12796881 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature