Epidemic Decision

Epidemic decision-making research focuses on developing and improving models that aid in effective and equitable responses to outbreaks. Current efforts concentrate on integrating diverse data sources (including social media and street-view imagery) with machine learning techniques like reinforcement learning (e.g., A2C, PPO) and adversarial/contrastive learning to optimize policy recommendations while mitigating biases and ensuring fairness across populations. These advancements aim to enhance the speed, accuracy, and ethical considerations of public health interventions, ultimately improving pandemic preparedness and response.