Cargando…

Tooling-up for infectious disease transmission modelling

In this introduction to the Special Issue on methods for modelling of infectious disease epidemiology we provide a commentary and overview of the field. We suggest that the field has been through three revolutions that have focussed on specific methodological developments; disease dynamics and heter...

Descripción completa

Detalles Bibliográficos
Autores principales: Baguelin, Marc, Medley, Graham F., Nightingale, Emily S., O’Reilly, Kathleen M., Rees, Eleanor M., Waterlow, Naomi R., Wagner, Moritz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Published by Elsevier B.V. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219405/
https://www.ncbi.nlm.nih.gov/pubmed/32405321
http://dx.doi.org/10.1016/j.epidem.2020.100395
_version_ 1783532990883692544
author Baguelin, Marc
Medley, Graham F.
Nightingale, Emily S.
O’Reilly, Kathleen M.
Rees, Eleanor M.
Waterlow, Naomi R.
Wagner, Moritz
author_facet Baguelin, Marc
Medley, Graham F.
Nightingale, Emily S.
O’Reilly, Kathleen M.
Rees, Eleanor M.
Waterlow, Naomi R.
Wagner, Moritz
author_sort Baguelin, Marc
collection PubMed
description In this introduction to the Special Issue on methods for modelling of infectious disease epidemiology we provide a commentary and overview of the field. We suggest that the field has been through three revolutions that have focussed on specific methodological developments; disease dynamics and heterogeneity, advanced computing and inference, and complexity and application to the real-world. Infectious disease dynamics and heterogeneity dominated until the 1980s where the use of analytical models illustrated fundamental concepts such as herd immunity. The second revolution embraced the integration of data with models and the increased use of computing. From the turn of the century an emergence of novel datasets enabled improved modelling of real-world complexity. The emergence of more complex data that reflect the real-world heterogeneities in transmission resulted in the development of improved inference methods such as particle filtering. Each of these three revolutions have always kept the understanding of infectious disease spread as its motivation but have been developed through the use of new techniques, tools and the availability of data. We conclude by providing a commentary on what the next revoluition in infectious disease modelling may be.
format Online
Article
Text
id pubmed-7219405
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Published by Elsevier B.V.
record_format MEDLINE/PubMed
spelling pubmed-72194052020-05-13 Tooling-up for infectious disease transmission modelling Baguelin, Marc Medley, Graham F. Nightingale, Emily S. O’Reilly, Kathleen M. Rees, Eleanor M. Waterlow, Naomi R. Wagner, Moritz Epidemics Article In this introduction to the Special Issue on methods for modelling of infectious disease epidemiology we provide a commentary and overview of the field. We suggest that the field has been through three revolutions that have focussed on specific methodological developments; disease dynamics and heterogeneity, advanced computing and inference, and complexity and application to the real-world. Infectious disease dynamics and heterogeneity dominated until the 1980s where the use of analytical models illustrated fundamental concepts such as herd immunity. The second revolution embraced the integration of data with models and the increased use of computing. From the turn of the century an emergence of novel datasets enabled improved modelling of real-world complexity. The emergence of more complex data that reflect the real-world heterogeneities in transmission resulted in the development of improved inference methods such as particle filtering. Each of these three revolutions have always kept the understanding of infectious disease spread as its motivation but have been developed through the use of new techniques, tools and the availability of data. We conclude by providing a commentary on what the next revoluition in infectious disease modelling may be. Published by Elsevier B.V. 2020-09 2020-05-13 /pmc/articles/PMC7219405/ /pubmed/32405321 http://dx.doi.org/10.1016/j.epidem.2020.100395 Text en © 2020 Published by Elsevier B.V. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Baguelin, Marc
Medley, Graham F.
Nightingale, Emily S.
O’Reilly, Kathleen M.
Rees, Eleanor M.
Waterlow, Naomi R.
Wagner, Moritz
Tooling-up for infectious disease transmission modelling
title Tooling-up for infectious disease transmission modelling
title_full Tooling-up for infectious disease transmission modelling
title_fullStr Tooling-up for infectious disease transmission modelling
title_full_unstemmed Tooling-up for infectious disease transmission modelling
title_short Tooling-up for infectious disease transmission modelling
title_sort tooling-up for infectious disease transmission modelling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219405/
https://www.ncbi.nlm.nih.gov/pubmed/32405321
http://dx.doi.org/10.1016/j.epidem.2020.100395
work_keys_str_mv AT baguelinmarc toolingupforinfectiousdiseasetransmissionmodelling
AT medleygrahamf toolingupforinfectiousdiseasetransmissionmodelling
AT nightingaleemilys toolingupforinfectiousdiseasetransmissionmodelling
AT oreillykathleenm toolingupforinfectiousdiseasetransmissionmodelling
AT reeseleanorm toolingupforinfectiousdiseasetransmissionmodelling
AT waterlownaomir toolingupforinfectiousdiseasetransmissionmodelling
AT wagnermoritz toolingupforinfectiousdiseasetransmissionmodelling