The 1918 influenza pandemic is one of the most devastating infectious disease epidemics on record, having caused approximately 50 million deaths worldwide. Control measures, including prohibiting non-essential gatherings as well as closing cinemas and music halls, were applied with varying success and limited knowledge of transmission dynamics. One hundred years later, following developments in the field of mathematical epidemiology, models are increasingly used to guide decision-making and devise appropriate interventions that mitigate the impacts of epidemics. Epidemiological models have been used as decision-making tools during outbreaks in human, animal and plant populations. However, as the subject has developed, human, animal and plant disease modelling have diverged. Approaches have been developed independently for pathogens of each host type, often despite similarities between the models used in these complementary fields. With the increased importance of a One Health approach that unifies human, animal and plant health, we argue that more inter-disciplinary collaboration would enhance each of the related disciplines. This pair of theme issues presents research articles written by human, animal and plant disease modellers. In this introductory article, we compare the questions pertinent to, and approaches used by, epidemiological modellers of human, animal and plant pathogens, and summarize the articles in these theme issues. We encourage future collaboration that transcends disciplinary boundaries and links the closely related areas of human, animal and plant disease epidemic modelling. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.
|Journal||Philosophical Transactions of the Royal Society B: Biological Sciences|
|Publication status||Published - 2019|
Bibliographical noteFunding Information:
The dominance of human disease modelling is driven by several factors. First, the availability of funding (figure 1b). In the UK in 2017/8, the Medical Research Council (MRC) received more than one and half times more funding (£594 million) than either the Biotechnology and Biological Sciences Research Council (BBSRC) or the Natural Environment Research Council (NERC), both of which fund animal and plant disease modelling. Human disease modelling is also funded by a number of charitable foundations including the Wellcome Trust. Charities such as the Bill and Melinda Gates Foundation provide funding for animal and plant disease modelling (e.g. the project on West African Virus Epidemiology for Root and Tuber Crops), however they fund epidemiological studies of human pathogens to a higher extent.
Data accessibility. This article does not contain any additional data. Competing interests. We declare we have no competing interests. Funding. R.N.T. was funded by a Junior Research Fellowship from Christ Church, Oxford. E.B.-P. was supported by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Evaluation of Interventions. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. The NIHR had no role in writing the manuscript or the decision to publish. Acknowledgements. This pair of theme issues is dedicated to Michael Thompson, who died at the age of 59 on 15 October 2018. He had the original idea to compile a special issue of a journal to coincide (approximately!) with the centenary of the 1918 ‘Spanish flu’ pandemic, and so these theme issues would not exist without his encouragement. Thanks also to Helen Eaton for commissioning these theme issues and being available to answer our (many!) questions, Sunetra Gupta for discussions about the theme issues while they were compiled, and Nik Cunniffe for discussions about this introductory article.
© 2019 The Author(s) Published by the Royal Society. All rights reserved.
- Animal disease
- Human disease
- Mathematical modelling
- One health
- Plant disease
- Public health