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了解流行病程以改进疫情预测。

Understanding the Epidemic Course in Order to Improve Epidemic Forecasting.

作者信息

Jia Peng

机构信息

Department of Land Surveying and Geo-Informatics The Hong Kong Polytechnic University Hong Kong China.

International Institute of Spatial Lifecourse Epidemiology (ISLE) Hong Kong China.

出版信息

Geohealth. 2020 Oct 1;4(10):e2020GH000303. doi: 10.1029/2020GH000303. eCollection 2020 Oct.

Abstract

The epidemic course of the severe acute respiratory syndrome (SARS) has been differently divided according to its transmission pattern and the infection and mortality status. Unfortunately, such efforts for the coronavirus disease 2019 (COVID-19) have been lacking. Does every epidemic have a unique epidemic course? Can we coordinate two arbitrary courses into an integrated course, which could better reflect a common real-world progression pattern of the epidemics? To what degree can such arbitrary divisions help predict future trends of the COVID-19 pandemic and future epidemics? Spatial lifecourse epidemiology provides a new perspective to understand the course of epidemics, especially pandemics, and a new toolkit to predict the course of future epidemics on the basis of big data. In the present data-driven era, data should be integrated to inform us how the epidemic is transmitting at the present moment, how it will transmit at the next moment, and which interventions would be most cost-effective to curb the epidemic. Both national and international legislations are needed to facilitate the integration of relevant policies of data sharing and confidentiality protection into the current pandemic preparedness guidelines.

摘要

严重急性呼吸综合征(SARS)的流行过程根据其传播模式以及感染和死亡情况有不同的划分方式。遗憾的是,针对2019冠状病毒病(COVID-19)尚未有此类研究。每种流行病都有其独特的流行过程吗?我们能否将任意两种病程整合为一个综合病程,以更好地反映流行病在现实世界中的共同发展模式?这种任意划分在多大程度上有助于预测COVID-19大流行及未来流行病的发展趋势?空间生命历程流行病学为理解流行病尤其是大流行的过程提供了新视角,并基于大数据提供了预测未来流行病病程的新工具。在当前数据驱动的时代,应整合数据,以便告知我们流行病当前的传播方式、下一阶段的传播方式以及哪种干预措施在控制疫情方面最具成本效益。需要国家和国际立法,以促进将数据共享和保密保护的相关政策纳入当前的大流行防范指南。

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