Robot Dance: A mathematical optimization platform for intervention against COVID-19 in a complex network

IF 2.6 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

EURO Journal on Computational Optimization Pub Date : 2022-01-01 DOI:10.1016/j.ejco.2022.100025

Luis Gustavo Nonato , Pedro Peixoto , Tiago Pereira , Claudia Sagastizábal , Paulo J.S. Silva

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引用次数: 1048

Abstract

Robot Dance is a computational optimization platform developed in response to the COVID-19 outbreak, to support the decision-making on public policies at a regional level. The tool is suitable for understanding and suggesting levels of intervention needed to contain the spread of infectious diseases when the mobility of inhabitants through a regional network is a concern. Such is the case for the SARS-CoV-2 virus that is highly contagious and, therefore, makes it crucial to incorporate the circulation of people in the epidemiological compartmental models. Robot Dance anticipates the spread of an epidemic in a complex regional network, helping to identify fragile links where applying differentiated measures of containment, testing, and vaccination is important. Based on stochastic optimization, the model determines efficient strategies on the basis of commuting of individuals and the situation of hospitals in each district. Uncertainty in the capacity of intensive care beds is handled by a chance-constraint approach. Some functionalities of Robot Dance are illustrated in the state of São Paulo in Brazil, using real data for a region with more than forty million inhabitants.

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机器人舞蹈：在复杂网络中干预新冠肺炎的数学优化平台

“机器人之舞”是为应对新冠肺炎疫情而开发的计算优化平台，旨在支持区域层面的公共政策决策。当居民通过区域网络流动成为一个问题时，该工具适用于了解和建议控制传染病传播所需的干预水平。SARS-CoV-2病毒就是这种情况，它具有高度传染性，因此将人员流动纳入流行病学分区模型至关重要。“机器人之舞”预测流行病在复杂的区域网络中的传播，帮助识别脆弱环节，在这些环节中应用差异化的遏制、检测和疫苗接种措施很重要。该模型基于随机优化，根据个体通勤情况和各区医院情况确定有效策略。重症监护病床容量的不确定性由机会约束方法处理。Robot Dance的一些功能在巴西圣保罗州进行了演示，使用了一个拥有4000多万居民的地区的真实数据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

EURO Journal on Computational Optimization OPERATIONS RESEARCH & MANAGEMENT SCIENCE-

CiteScore

3.50

自引率

0.00%

发文量

审稿时长

60 days

期刊介绍： The aim of this journal is to contribute to the many areas in which Operations Research and Computer Science are tightly connected with each other. More precisely, the common element in all contributions to this journal is the use of computers for the solution of optimization problems. Both methodological contributions and innovative applications are considered, but validation through convincing computational experiments is desirable. The journal publishes three types of articles (i) research articles, (ii) tutorials, and (iii) surveys. A research article presents original methodological contributions. A tutorial provides an introduction to an advanced topic designed to ease the use of the relevant methodology. A survey provides a wide overview of a given subject by summarizing and organizing research results.