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改善大流行应对措施:利用数学模型应对 2019 年冠状病毒病。

Improving Pandemic Response: Employing Mathematical Modeling to Confront Coronavirus Disease 2019.

机构信息

COVID-19 Response, US Centers for Disease Control and Prevention, Atlanta, Georgia, USA.

Office of the Deputy Director for Infectious Diseases, US Centers for Disease Control and Prevention, Atlanta, Georgia, USA.

出版信息

Clin Infect Dis. 2022 Mar 9;74(5):913-917. doi: 10.1093/cid/ciab673.

Abstract

Modeling complements surveillance data to inform coronavirus disease 2019 (COVID-19) public health decision making and policy development. This includes the use of modeling to improve situational awareness, assess epidemiological characteristics, and inform the evidence base for prevention strategies. To enhance modeling utility in future public health emergencies, the Centers for Disease Control and Prevention (CDC) launched the Infectious Disease Modeling and Analytics Initiative. The initiative objectives are to: (1) strengthen leadership in infectious disease modeling, epidemic forecasting, and advanced analytic work; (2) build and cultivate a community of skilled modeling and analytics practitioners and consumers across CDC; (3) strengthen and support internal and external applied modeling and analytic work; and (4) working with partners, coordinate government-wide advanced data modeling and analytics for infectious diseases. These efforts are critical to help prepare the CDC, the country, and the world to respond effectively to present and future infectious disease threats.

摘要

建模补充监测数据,为 2019 冠状病毒病(COVID-19)公共卫生决策和政策制定提供信息。这包括利用建模来提高对疫情的认识,评估流行病学特征,并为预防策略提供证据基础。为了提高建模在未来公共卫生突发事件中的实用性,疾病预防控制中心(CDC)启动了传染病建模和分析倡议。该倡议的目标是:(1)加强传染病建模、疫情预测和高级分析工作的领导力;(2)在 CDC 内部建立和培养一个熟练的建模和分析从业者和使用者社区;(3)加强和支持内部和外部的应用建模和分析工作;(4)与合作伙伴合作,协调政府范围内传染病的高级数据建模和分析。这些努力对于帮助 CDC、国家和世界有效应对当前和未来的传染病威胁至关重要。

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