Artificial Intelligence (AI) has emerged as a transformative instrument in epidemiology, markedly enhancing the capacity of health professionals to predict, monitor, and manage the dissemination of diseases. A comprehensive review indicates that AI has achieved notable success in forecasting disease outbreaks, identifying transmission patterns, and optimizing the allocation of healthcare resources. AI-driven surveillance systems, such as BlueDot and HealthMap, have demonstrated their efficacy in providing early warnings of disease outbreaks, as evidenced during the COVID-19 pandemic. Nevertheless, the deployment of AI in epidemiology encounters challenges, including data privacy concerns, resource limitations in low-income countries, and the necessity for explicit ethical guidelines. This report examines the diverse applications of AI in epidemiology, its advantages over traditional methodologies, and the challenges and future directions for advancing this technology to bolster global disease control and prevention efforts.
Ilmaskal et al. (Wed,) studied this question.
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