No Cover Image

Journal article 1038 views 119 downloads

Challenges in modeling the emergence of novel pathogens

Emma E. Glennon, Marjolein Bruijning, Justin Lessler, Ian F. Miller, Benjamin L. Rice, Robin N. Thompson, Konstans Wells Orcid Logo, C. Jessica E. Metcalf

Epidemics, Volume: 37, Start page: 100516

Swansea University Author: Konstans Wells Orcid Logo

  • 58490.pdf

    PDF | Version of Record

    © 2021 The Authors. This is an open access article under the CC BY license

    Download (487.37KB)

Check full text

DOI (Published version): 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...

Full description

Published in: Epidemics
ISSN: 1755-4365
Published: Elsevier BV 2021
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa58490
Tags: Add Tag
No Tags, Be the first to tag this record!
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.
Keywords: Immune landscape; Genotype to phenotype map; Big data; Data integration; Fundamental theory; Health system functioning
College: Faculty of Science and Engineering
Funders: EPSRC
Start Page: 100516

Similar Items