This paper studies cohorting in public transit systems and its usefulness in mitigating disease transmission. The Mumbai suburban railway system is used as a case study.

Cohorting to Isolate Asymptomatic Spreaders: An Agent-Based Simulation Study on the Mumbai Suburban Railway

In many community health settings, it is crucial to have a systematic monitoring and intervention process to ensure that the patients adhere to healthcare programs, such as periodic health checks or taking medications. When these interventions are expensive, they can be provided to only a fixed small fraction of the patients at any period of time. Hence, it is important to carefully choose the beneficiaries who should be provided with interventions and when. We model this scenario as a restless multi-armed bandit (RMAB) problem, where each beneficiary is assumed to transition from one state to another depending on the intervention provided to them. In practice, the transition probabilities are unknown a priori, and hence, we propose a mechanism for the problem of balancing the explore-exploit trade-off. Empirically, we find that our proposed mechanism outperforms the baseline intervention scheme maternal healthcare dataset.

Learning Index Policies for Restless Bandits with Application to Maternal Healthcare

Poster/Demo Session 4 

poster

AAMAS is the largest and most influential conference in the area of agents and multiagent systems, bringing together researchers and practitioners in all areas of agent technology and providing and internationally renowned high-profile forum for publishing and finding out about the latest developments in the field. AAMAS is the flagship conference of the non-profit International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).  

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Gaurav Aggarwal

2

Presentations

Cohorting to Isolate Asymptomatic Spreaders: An Agent-Based Simulation Study on the Mumbai Suburban Railway

Learning Index Policies for Restless Bandits with Application to Maternal Healthcare

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