传染病建模是否适用于全球:COVID-19的经验教训

IF 6.7 Q1 ENVIRONMENTAL SCIENCES
Dhammika N. Magana-Arachchi , Rasika P. Wanigatunge , Meththika S. Vithanage
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引用次数: 0

摘要

需要对传染病进行监测,以防止在社区内传播。及时的咨询和预测对于克服这些流行病的后果是必要的。目前,重点放在计算机建模上,以实现所需的预测,最好的例子是COVID-19大流行。科学家们使用各种模型来确定不同的社会人口因素如何相互关联并影响COVID-19的全球传播,并展示了计算机模型作为疾病管理工具的实用性。然而,由于建模是在设定规则的假设下完成的,因此在报告结果和可信地描述局限性时,计算不确定性量化在传染病建模中是必不可少的。本文以COVID-19大流行为重点,总结了传染病建模策略、挑战和全球适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Can infectious modeling be applicable globally: Lessons from COVID-19

Can infectious modeling be applicable globally: Lessons from COVID-19

Contagious diseases are needed to be monitored to prevent spreading within communities. Timely advice and predictions are necessary to overcome the consequences of those epidemics. Currently, emphasis has been placed on computer modeling to achieve the needed forecasts, the best example being the COVID-19 pandemic. Scientists used various models to determine how diverse sociodemographic factors correlated and influenced COVID-19 Global transmission and demonstrated the utility of computer models as tools in disease management. However, as modeling is done with assumptions with set rules, calculating uncertainty quantification is essential in infectious modelling when reporting the results and trustfully describing the limitations. This article summarizes the infectious disease modeling strategies, challenges, and global applicability by focusing on the COVID-19 pandemic.

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来源期刊
Current Opinion in Environmental Science and Health
Current Opinion in Environmental Science and Health Medicine-Public Health, Environmental and Occupational Health
CiteScore
14.90
自引率
0.00%
发文量
92
审稿时长
114 days
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