Modeling and Designing Non-Pharmaceutical Interventions in Epidemics: A Submodular Approach

Fuente: arXiv
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Autori principali: Cheng, Shiyu, Niu, Luyao, Ramasubramanian, Bhaskar, Clark, Andrew, Poovendran, Radha
Natura: Preprint
Pubblicazione: 2024
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author Cheng, Shiyu
Niu, Luyao
Ramasubramanian, Bhaskar
Clark, Andrew
Poovendran, Radha
author_facet Cheng, Shiyu
Niu, Luyao
Ramasubramanian, Bhaskar
Clark, Andrew
Poovendran, Radha
contents This paper considers the problem of designing non-pharmaceutical intervention (NPI) strategies, such as masking and social distancing, to slow the spread of a viral epidemic. We formulate the problem of jointly minimizing the infection probabilities of a population and the cost of NPIs based on a Susceptible-Infected-Susceptible (SIS) propagation model. To mitigate the complexity of the problem, we consider a steady-state approximation based on the quasi-stationary (endemic) distribution of the epidemic, and prove that the problem of selecting a minimum-cost strategy to satisfy a given bound on the quasi-stationary infection probabilities can be cast as a submodular optimization problem, which can be solved in polynomial time using the greedy algorithm. We carry out experiments to examine effects of implementing our NPI strategy on propagation and control of epidemics on a Watts-Strogatz small-world graph network. We find the NPI strategy reduces the steady state of infection probabilities of members of the population below a desired threshold value.
format Preprint
id arxiv_https___arxiv_org_abs_2411_18982
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Modeling and Designing Non-Pharmaceutical Interventions in Epidemics: A Submodular Approach
Cheng, Shiyu
Niu, Luyao
Ramasubramanian, Bhaskar
Clark, Andrew
Poovendran, Radha
Systems and Control
This paper considers the problem of designing non-pharmaceutical intervention (NPI) strategies, such as masking and social distancing, to slow the spread of a viral epidemic. We formulate the problem of jointly minimizing the infection probabilities of a population and the cost of NPIs based on a Susceptible-Infected-Susceptible (SIS) propagation model. To mitigate the complexity of the problem, we consider a steady-state approximation based on the quasi-stationary (endemic) distribution of the epidemic, and prove that the problem of selecting a minimum-cost strategy to satisfy a given bound on the quasi-stationary infection probabilities can be cast as a submodular optimization problem, which can be solved in polynomial time using the greedy algorithm. We carry out experiments to examine effects of implementing our NPI strategy on propagation and control of epidemics on a Watts-Strogatz small-world graph network. We find the NPI strategy reduces the steady state of infection probabilities of members of the population below a desired threshold value.
title Modeling and Designing Non-Pharmaceutical Interventions in Epidemics: A Submodular Approach
topic Systems and Control
url https://arxiv.org/abs/2411.18982