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Applying Artificial Intelligence to Improve Early Detection and Containment of Infectious Disease Outbreaks, Supporting National Public Health Preparedness
Abstract
The swift transmission of infectious diseases constitutes a serious global public health problem and therefore there is a need for sophisticated tools to improve early detection and containment measures. Artificial Intelligence (AI) has become a powerful tool in the transformation of public health preparedness as a means of providing real-time intelligence, predictive modeling and data-driven interventions. This article explores the application of AI in the improvement of early detection of infectious diseases outbreaks and improved containment efforts. We go over some use cases that are important in recent studies, including AI-driven surveillance systems, predictive modeling in disease spreading, and big data analytics that works to optimize response strategies. Notably, AI has been instrumental in the face of the current pandemic, known as the Coronavirus or Covid-19, with its role in diagnostics, tracking and developing preventative measures. However, challenges, such as data privacy, cross-sector data integration and algorithmic biases, have to be addressed in order to leverage the full potential of AI. The article also speaks of incorporating AI with other technologies, like telehealth and digital health systems, in creating resilient public health infrastructures. Overall, AI is set to make a significant impact on the preparedness of a country by improving its early warning systems, decision-making, and response coordination efforts which will ultimately reduce the impact of future outbreaks.
Article information
Journal
Journal of Medical and Health Studies
Volume (Issue)
4 (3)
Pages
82-93
Published
Copyright
Open access

This work is licensed under a Creative Commons Attribution 4.0 International License.

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