A Security Games Inspired Approach for Distributed Control Of Pandemic Spread
Ariel Alexi, Ariel Rosenfeld, Teddy Lazebnik
Abstract
Abstract Pandemics are a source of extensive mortality, economic impairment, and dramatic social fluctuation. Once a pandemic occurs, policymakers are faced with the highly challenging task of controlling it over time and space. In this article, a novel pandemic intervention policy that relies on the strategic deployment of inspection units (IUs) is proposed. These IUs are allocated in the environment, represented as a graph, and sample individuals who pass through the same node. If a sampled individual is identified as infected, she is extracted from the environment until she recovers (or dies). A realistic simulation‐based evaluation of the Influenza A pathogen using both synthetic and real‐world data is provided. The results demonstrate potential significant benefits of the proposed PIP in mitigating a pandemic spread which can complement other standard policies such as social distancing and mask‐wearing.