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; C Jessica E Metcalf

doi:10.1016/j.epidem.2021.100516

Challenges in modeling the emergence of novel pathogens

Epidemics. 2021 Dec:37:100516. doi: 10.1016/j.epidem.2021.100516. Epub 2021 Oct 25.

Authors

Emma E Glennon¹, Marjolein Bruijning², Justin Lessler³, Ian F Miller⁴, Benjamin L Rice⁵, Robin N Thompson⁶, Konstans Wells⁷, C Jessica E Metcalf⁸

Affiliations

¹ Disease Dynamics Unit, Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, UK. Electronic address: eeg31@cam.ac.uk.
² Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA.
³ Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
⁴ Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA; Rocky Mountain Biological Laboratory, Crested Butte, CO 81224, USA.
⁵ Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA; Madagascar Health and Environmental Research (MAHERY), Maroantsetra, Madagascar.
⁶ Mathematics Institute, University of Warwick, Warwick CV4 7AL, UK; The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Warwick CV4 7AL, UK.
⁷ Department of Biosciences, Swansea University, Swansea SA28PP, UK.
⁸ Disease Dynamics Unit, Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, UK; Princeton School of Public and International Affairs, Princeton University, Princeton, NJ, USA.

PMID: 34775298
DOI: 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.

Keywords: Big data; Data integration; Fundamental theory; Genotype to phenotype map; Health system functioning; Immune landscape.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Disease Outbreaks*
Forecasting
Models, Theoretical*
Pandemics

Grants and funding

220463/Z/20/Z/WT_/Wellcome Trust/United Kingdom