TITLE:
Integrating GBD-Based Burden Assessment with AI-Driven Surveillance: A Comprehensive Framework for Multiple Infectious Disease Control and Policy Optimization
AUTHORS:
Ruiqi Huo
KEYWORDS:
Global Burden of Disease, Multiple Infectious Diseases, Artificial Intelligence, Climate and Health, Digital Surveillance, Health Equity, Precision Public Health, Pandemic Preparedness
JOURNAL NAME:
Journal of Biosciences and Medicines,
Vol.13 No.11,
November
28,
2025
ABSTRACT: Background: The post-pandemic era has highlighted critical gaps in traditional single-disease surveillance systems, particularly regarding multiple infectious disease co-circulation and syndemic interactions. The complex interplay between COVID-19 and other infectious diseases, coupled with evolving climate change impacts and digital health transformation, demands innovative approaches to disease burden assessment and control strategy optimization. Methods: This comprehensive review employs a multidisciplinary framework integrating bibliometric analysis, mathematical modeling, and health economic evaluation. We systematically analyzed Global Burden of Disease (GBD) 2021 data and synthesized evidence from 125 recent studies (2018-2024) on infectious disease dynamics modeling, AI-based surveillance systems, and intervention effectiveness across multiple disease domains. Key Findings: Our analysis reveals three critical insights: First, integrated surveillance systems combining wastewater-based epidemiology, multiplex serological assays, and climate-informed prediction models improved outbreak detection accuracy by 42% compared to conventional systems. Second, the COVID-19 pandemic induced significant disease burden redistribution, with mental health disorders (depression and anxiety) showing DALY increases of 83.0 and 73.8 per 100,000 respectively, while disrupting essential health services for malaria, HIV, and tuberculosis in low-income regions. Third, AI-driven early warning systems reduced response times to 6 - 9 minutes with 97.06% prediction accuracy, demonstrating potential for real-time public health decision-making. Conclusion: The convergence of GBD analytics, AI technologies, and interdisciplinary methodologies presents unprecedented opportunities for transforming multiple infectious disease control. Future strategies must prioritize equity-sensitive approaches, climate adaptation measures, and sustainable digital solutions to build resilient health systems capable of addressing complex syndemic challenges.