| Literature DB >> 34775298 |
Emma E Glennon1, Marjolein Bruijning2, Justin Lessler3, Ian F Miller4, Benjamin L Rice5, Robin N Thompson6, Konstans Wells7, C Jessica E Metcalf8.
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.Entities:
Keywords: Big data; Data integration; Fundamental theory; Genotype to phenotype map; Health system functioning; Immune landscape
Mesh:
Year: 2021 PMID: 34775298 DOI: 10.1016/j.epidem.2021.100516
Source DB: PubMed Journal: Epidemics ISSN: 1878-0067 Impact factor: 4.396