From COVID-19 to the Future: Lessons Learned in Global Pandemic Preparedness Using AI and Predictive Analytics

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@article{1707481,
      author = {Samuel Mari Twum},
      title = {From COVID-19 to the Future: Lessons Learned in Global Pandemic Preparedness Using AI and Predictive Analytics},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {8},
      number = {9},
      pages = {803-817},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1707481.pdf},
      abstract = {The COVID-19 pandemic revealed the vulnerabilities of global health systems and the transformative potential of artificial intelligence (AI) and predictive analytics in managing public health crises. From early outbreak detection and epidemiological modeling to healthcare resource optimization and vaccine development, AI-driven technologies played a critical role in managing the impact of the pandemic. Predictive analytics enabled data-driven decision-making, allowing policymakers and healthcare providers to allocate resources efficiently and respond proactively to evolving threats. However, despite these advancements, challenges such as algorithmic bias, data privacy concerns, and global disparities in AI accessibility highlighted the need for ethical governance and inclusive AI deployment. This study examines the effectiveness of AI and predictive analytics in pandemic response, identifying key successes and limitations while proposing strategies to enhance future preparedness. Findings suggest that while AI improves disease tracking and public health communication, gaps in transparency, regulatory oversight, and equitable AI adoption must be addressed. Strengthening AI integration into global health policies, ensuring ethical data governance, and ensuring public-private partnerships will be crucial in leveraging AI for pandemic resilience. As the world prepares for possible future health crises, investments in next-generation AI applications, prioritizing inclusivity and fairness, will be essential in safeguarding global health security.},
      keywords = {AI, Predictive Analytics, Pandemic Preparedness, Global Health Security, Disease Modeling, Machine Learning, Big Data Analytics, Telemedicine, Health Policy, Disease Surveillance},
      month = {March},
  }