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...
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doaj-de17068f85d14507a7f7dcbccfa54d592020-11-25T03:49:14ZengElsevierEpidemics1755-43652020-09-0132100395Tooling-up for infectious disease transmission modellingMarc Baguelin0Graham F. Medley1Emily S. Nightingale2Kathleen M. O’Reilly3Eleanor M. Rees4Naomi R. Waterlow5Moritz Wagner6School of Public Health, Infectious Disease Epidemiology, Imperial College London, United Kingdom; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UKCentre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UKCentre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UKCentre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK; Corresponding author.Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UKCentre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UKCentre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UKIn 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.http://www.sciencedirect.com/science/article/pii/S1755436520300220Mathematical modellingPerspectiveMethodology |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Marc Baguelin Graham F. Medley Emily S. Nightingale Kathleen M. O’Reilly Eleanor M. Rees Naomi R. Waterlow Moritz Wagner |
spellingShingle |
Marc Baguelin Graham F. Medley Emily S. Nightingale Kathleen M. O’Reilly Eleanor M. Rees Naomi R. Waterlow Moritz Wagner Tooling-up for infectious disease transmission modelling Epidemics Mathematical modelling Perspective Methodology |
author_facet |
Marc Baguelin Graham F. Medley Emily S. Nightingale Kathleen M. O’Reilly Eleanor M. Rees Naomi R. Waterlow Moritz Wagner |
author_sort |
Marc Baguelin |
title |
Tooling-up for infectious disease transmission modelling |
title_short |
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_sort |
tooling-up for infectious disease transmission modelling |
publisher |
Elsevier |
series |
Epidemics |
issn |
1755-4365 |
publishDate |
2020-09-01 |
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. |
topic |
Mathematical modelling Perspective Methodology |
url |
http://www.sciencedirect.com/science/article/pii/S1755436520300220 |
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