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Challenges in modeling the emergence of novel pathogens
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Glennon, Emma E., Bruijning, Marjolein, Lessler, Justin, Miller, Ian F., Rice, Benjamin L., Thompson, Robin N., Wells, Konstans and Metcalf, C. Jessica E. (2021) Challenges in modeling the emergence of novel pathogens. Epidemics, 37 . 100516. doi:10.1016/j.epidem.2021.100516
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WRAP-challenges-modeling-emergence-novel-pathogens-Thompson-2021.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (472Kb) | Preview |
Official URL: http://dx.doi.org/10.1016/j.epidem.2021.100516
Abstract
The emergence of infectious agents with pandemic potential present scientific challenges from detection to data interpretation to understanding determinants of risk and forecasts. Mathematical models could play an essential role in how we prepare for future emergent pathogens. Here, we describe core directions for expansion of the existing tools and knowledge base, including: using mathematical models to identify critical directions and paths for strengthening data collection to detect and respond to outbreaks of novel pathogens; expanding basic theory to identify infectious agents and contexts that present the greatest risks, over both the short and longer term; by strengthening estimation tools that make the most use of the likely range and uncertainties in existing data; and by ensuring modelling applications are carefully communicated and developed within diverse and equitable collaborations for increased public health benefit.
| Item Type: | Journal Article | |||||||||||||||
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| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software Q Science > QH Natural history |
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| Divisions: | Faculty of Science > Mathematics | |||||||||||||||
| Library of Congress Subject Headings (LCSH): | Pathogenic microorganisms, Pathogenic microorganisms -- Detection -- Mathematic models, Genotype-environment interaction , Genotype-environment interaction -- Mathematic models, Big data | |||||||||||||||
| Journal or Publication Title: | Epidemics | |||||||||||||||
| Publisher: | Elsevier BV | |||||||||||||||
| ISSN: | 1755-4365 | |||||||||||||||
| Official Date: | December 2021 | |||||||||||||||
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| Volume: | 37 | |||||||||||||||
| Article Number: | 100516 | |||||||||||||||
| DOI: | 10.1016/j.epidem.2021.100516 | |||||||||||||||
| Status: | Peer Reviewed | |||||||||||||||
| Publication Status: | Published | |||||||||||||||
| Access rights to Published version: | Open Access | |||||||||||||||
| RIOXX Funder/Project Grant: |
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