Artificial intelligence for modelling infectious disease epidemics

Area of Science:

• Epidemiology
• Infectious Diseases
• Artificial Intelligence

Background:

• Infectious disease threats are diverse and unpredictable.
• Artificial intelligence (AI) is increasingly used in decision-making across various fields.
• AI has the potential to significantly advance infectious disease epidemiology.

Purpose of the Study:

• To explore the application of AI in infectious disease modeling.
• To discuss how AI can address key epidemiological questions.
• To examine the social context and limitations of AI in this domain.

Main Methods:

• Review of AI systems combining machine learning, computational statistics, information retrieval, and data science.
• Application of AI methods to infectious disease surveillance data.
• Analysis of social aspects including explainability, safety, accountability, and ethics.

Main Results:

• AI can accelerate breakthroughs in epidemiological research.
• Specific AI methods can be applied to routinely collected surveillance data.
• The social context of AI implementation requires careful consideration.

Conclusions:

• AI offers transformative potential for infectious disease epidemiology.
• Effective harnessing of AI requires addressing ethical and practical challenges.
• Recommendations are provided for maximizing AI's impact on public health.