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Expanded SEIRCQ Model Applied to COVID-19 Epidemic Control Strategy Design and Medical Infrastructure Planning
Mathematical Problems in Engineering Pub Date : 2020-08-08 , DOI: 10.1155/2020/8198563
J. M. V. Grzybowski 1 , R. V. da Silva 1 , M. Rafikov 2
Affiliation  

The rapid spread of COVID-19 has demanded a quick response from governments in terms of planning contingency efforts that include the imposition of social isolation measures and an unprecedented increase in the availability of medical services. Both courses of action have been shown to be critical to the success of epidemic control. Under this scenario, the timely adoption of effective strategies allows the outbreak to be decelerated at early stages. The objective of this study is to present an epidemic model specially tailored for the study of the COVID-19 epidemics, and the model is aimed at allowing the integrated study of epidemic control strategies and dimensioning of the required medical infrastructure. Along with the theoretical model, a case study with three prognostic scenarios is presented for the first wave of the epidemic in the city of Manaus, the capital city of Amazonas state, Brazil. Although the temporary collapse of the medical infrastructure is hardly avoidable in the state-of-affairs at this time (April 2020), the results show that there are feasible control strategies that could substantially reduce the overload within reasonable time. Furthermore, this study delivers and presents an intuitive, straightforward, free, and open-source online platform that allows the direct application of the model. The platform can hopefully provide better response time and clarity to the planning of contingency measures.

中文翻译:

扩展的SEIRCQ模型应用于COVID-19流行控制策略设计和医疗基础设施规划

COVID-19的迅速传播要求政府在计划应急工作方面做出快速反应,包括采取社会隔离措施和医疗服务空前增加。两种行动方案都已证明对流行病控制的成功至关重要。在这种情况下,及时采用有效的策略可以使爆发在早期阶段减速。这项研究的目的是提供一个专门为研究COVID-19流行病而设计的流行病模型,该模型旨在允许对流行病控制策略和所需医疗基础设施的规模进行综合研究。连同理论模型 在巴西玛瑙斯州首府马瑙斯市,针对第一波流行病,提出了具有三种预后情况的案例研究。尽管在此时(2020年4月)很难避免医疗基础设施的暂时崩溃,但结果表明,存在可行的控制策略,可以在合理的时间内显着减少过载。此外,本研究提供并提出了一个直观,直接,免费和开放源代码的在线平台,该平台可直接应用模型。该平台有望为应急措施的规划提供更好的响应时间和清晰度。尽管在此时(2020年4月)很难避免医疗基础设施的暂时崩溃,但结果表明,存在可行的控制策略,可以在合理的时间内显着减少过载。此外,本研究提供并提出了一个直观,直接,免费和开放源代码的在线平台,该平台可直接应用模型。该平台有望为应急措施的规划提供更好的响应时间和清晰度。尽管在此时(2020年4月)很难避免医疗基础设施的暂时崩溃,但结果表明,存在可行的控制策略,可以在合理的时间内显着减少过载。此外,本研究提供并提出了一个直观,直接,免费和开放源代码的在线平台,该平台可直接应用模型。该平台有望为应急措施的规划提供更好的响应时间和清晰度。
更新日期:2020-08-08
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