Challenges in modeling the emergence of novel pathogens

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...

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Autores principales:	Emma E. Glennon, Marjolein Bruijning, Justin Lessler, Ian F. Miller, Benjamin L. Rice, Robin N. Thompson, Konstans Wells, C. Jessica E. Metcalf
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Immune landscape Genotype to phenotype map Big data Data integration Fundamental theory Health system functioning Infectious and parasitic diseases RC109-216
Acceso en línea:	https://doaj.org/article/e271154330bd4de4b7066d0c42321336
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spelling	oai:doaj.org-article:e271154330bd4de4b7066d0c423213362021-11-12T04:28:33ZChallenges in modeling the emergence of novel pathogens1755-436510.1016/j.epidem.2021.100516https://doaj.org/article/e271154330bd4de4b7066d0c423213362021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1755436521000621https://doaj.org/toc/1755-4365The 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.Emma E. GlennonMarjolein BruijningJustin LesslerIan F. MillerBenjamin L. RiceRobin N. ThompsonKonstans WellsC. Jessica E. MetcalfElsevierarticleImmune landscapeGenotype to phenotype mapBig dataData integrationFundamental theoryHealth system functioningInfectious and parasitic diseasesRC109-216ENEpidemics, Vol 37, Iss , Pp 100516- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Immune landscape Genotype to phenotype map Big data Data integration Fundamental theory Health system functioning Infectious and parasitic diseases RC109-216
spellingShingle	Immune landscape Genotype to phenotype map Big data Data integration Fundamental theory Health system functioning Infectious and parasitic diseases RC109-216 Emma E. Glennon Marjolein Bruijning Justin Lessler Ian F. Miller Benjamin L. Rice Robin N. Thompson Konstans Wells C. Jessica E. Metcalf Challenges in modeling the emergence of novel pathogens
description	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.
format	article
author	Emma E. Glennon Marjolein Bruijning Justin Lessler Ian F. Miller Benjamin L. Rice Robin N. Thompson Konstans Wells C. Jessica E. Metcalf
author_facet	Emma E. Glennon Marjolein Bruijning Justin Lessler Ian F. Miller Benjamin L. Rice Robin N. Thompson Konstans Wells C. Jessica E. Metcalf
author_sort	Emma E. Glennon
title	Challenges in modeling the emergence of novel pathogens
title_short	Challenges in modeling the emergence of novel pathogens
title_full	Challenges in modeling the emergence of novel pathogens
title_fullStr	Challenges in modeling the emergence of novel pathogens
title_full_unstemmed	Challenges in modeling the emergence of novel pathogens
title_sort	challenges in modeling the emergence of novel pathogens
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/e271154330bd4de4b7066d0c42321336
work_keys_str_mv	AT emmaeglennon challengesinmodelingtheemergenceofnovelpathogens AT marjoleinbruijning challengesinmodelingtheemergenceofnovelpathogens AT justinlessler challengesinmodelingtheemergenceofnovelpathogens AT ianfmiller challengesinmodelingtheemergenceofnovelpathogens AT benjaminlrice challengesinmodelingtheemergenceofnovelpathogens AT robinnthompson challengesinmodelingtheemergenceofnovelpathogens AT konstanswells challengesinmodelingtheemergenceofnovelpathogens AT cjessicaemetcalf challengesinmodelingtheemergenceofnovelpathogens
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Challenges in modeling the emergence of novel pathogens

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