Enhancing global preparedness during an ongoing pandemic from partial and noisy data

Author:

Klamser Pascal P12ORCID,d’Andrea Valeria3ORCID,Di Lauro Francesco4ORCID,Zachariae Adrian12ORCID,Bontorin Sebastiano35ORCID,Di Nardo Antonello6ORCID,Hall Matthew4,Maier Benjamin F12ORCID,Ferretti Luca4ORCID,Brockmann Dirk12ORCID,De Domenico Manlio78ORCID

Affiliation:

1. Robert Koch-Institute , Nordufer 20, 13353 Berlin , Germany

2. Department of Biology, Institute for Theoretical Biology, Humboldt-University of Berlin , Philippstr. 13, 10115 Berlin , Germany

3. Fondazione Bruno Kessler , Via Sommarive 18, 38123, Povo (TN) , Italy

4. Big Data Institute, University of Oxford , Old Road Campus, OX3 7LF Oxford , UK

5. Department of Physics, University of Trento , Via Sommarive 14, 38123 Povo (TN) , Italy

6. The Pirbright Institute , Ash Road, GU24 0NF Surrey , UK

7. Department of Physics and Astronomy, G. Galilei, University of Padua , Via Francesco Marzolo 8, 35131 Padua , Italy

8. Padua Center for Network Medicine, University of Padua , Via Francesco Marzolo 8, 35131 Padua , Italy

Abstract

Abstract As the coronavirus disease 2019 spread globally, emerging variants such as B.1.1.529 quickly became dominant worldwide. Sustained community transmission favors the proliferation of mutated sub-lineages with pandemic potential, due to cross-national mobility flows, which are responsible for consecutive cases surge worldwide. We show that, in the early stages of an emerging variant, integrating data from national genomic surveillance and global human mobility with large-scale epidemic modeling allows to quantify its pandemic potential, providing quantifiable indicators for pro-active policy interventions. We validate our framework on worldwide spreading variants and gain insights about the pandemic potential of BA.5, BA.2.75, and other sub- and lineages. We combine the different sources of information in a simple estimate of the pandemic delay and show that only in combination, the pandemic potentials of the lineages are correctly assessed relative to each other. Compared to a country-level epidemic intelligence, our scalable integrated approach, that is pandemic intelligence, permits to enhance global preparedness to contrast the pandemic of respiratory pathogens such as SARS-CoV-2.

Publisher

Oxford University Press (OUP)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3