Literature DB >> 31056051

Detection, forecasting and control of infectious disease epidemics: modelling outbreaks in humans, animals and plants.

Robin N Thompson1,2,3, Ellen Brooks-Pollock4,5.   

Abstract

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'.

Entities:  

Keywords:  animal disease; human disease; mathematical modelling; one health; plant disease; public health

Mesh:

Year:  2019        PMID: 31056051      PMCID: PMC6553600          DOI: 10.1098/rstb.2019.0038

Source DB:  PubMed          Journal:  Philos Trans R Soc Lond B Biol Sci        ISSN: 0962-8436            Impact factor:   6.237


  83 in total

1.  Applying optimal control theory to complex epidemiological models to inform real-world disease management.

Authors:  E H Bussell; C E Dangerfield; C A Gilligan; N J Cunniffe
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-07-08       Impact factor: 6.237

2.  Strategies for containing Ebola in West Africa.

Authors:  Abhishek Pandey; Katherine E Atkins; Jan Medlock; Natasha Wenzel; Jeffrey P Townsend; James E Childs; Tolbert G Nyenswah; Martial L Ndeffo-Mbah; Alison P Galvani
Journal:  Science       Date:  2014-10-30       Impact factor: 47.728

3.  Virus epidemics, plant-controlled population bottlenecks and the durability of plant resistance.

Authors:  Elsa Rousseau; Mélanie Bonneault; Frédéric Fabre; Benoît Moury; Ludovic Mailleret; Frédéric Grognard
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-06-24       Impact factor: 6.237

4.  Critical transitions in malaria transmission models are consistently generated by superinfection.

Authors:  David Alonso; Andy Dobson; Mercedes Pascual
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-06-24       Impact factor: 6.237

5.  A simple approach to measure transmissibility and forecast incidence.

Authors:  Pierre Nouvellet; Anne Cori; Tini Garske; Isobel M Blake; Ilaria Dorigatti; Wes Hinsley; Thibaut Jombart; Harriet L Mills; Gemma Nedjati-Gilani; Maria D Van Kerkhove; Christophe Fraser; Christl A Donnelly; Neil M Ferguson; Steven Riley
Journal:  Epidemics       Date:  2017-02-24       Impact factor: 4.396

6.  Risk-based management of invading plant disease.

Authors:  Samuel R Hyatt-Twynam; Stephen Parnell; Richard O J H Stutt; Tim R Gottwald; Christopher A Gilligan; Nik J Cunniffe
Journal:  New Phytol       Date:  2017-03-28       Impact factor: 10.151

7.  A probabilistic census-travel model to predict introduction sites of exotic plant, animal and human pathogens.

Authors:  Tim Gottwald; Weiqi Luo; Drew Posny; Tim Riley; Frank Louws
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-07-08       Impact factor: 6.237

Review 8.  Outbreak analytics: a developing data science for informing the response to emerging pathogens.

Authors:  Jonathan A Polonsky; Amrish Baidjoe; Zhian N Kamvar; Anne Cori; Kara Durski; W John Edmunds; Rosalind M Eggo; Sebastian Funk; Laurent Kaiser; Patrick Keating; Olivier le Polain de Waroux; Michael Marks; Paula Moraga; Oliver Morgan; Pierre Nouvellet; Ruwan Ratnayake; Chrissy H Roberts; Jimmy Whitworth; Thibaut Jombart
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-07-08       Impact factor: 6.237

Review 9.  Unifying the epidemiological and evolutionary dynamics of pathogens.

Authors:  Bryan T Grenfell; Oliver G Pybus; Julia R Gog; James L N Wood; Janet M Daly; Jenny A Mumford; Edward C Holmes
Journal:  Science       Date:  2004-01-16       Impact factor: 47.728

10.  Management of invading pathogens should be informed by epidemiology rather than administrative boundaries.

Authors:  Robin N Thompson; Richard C Cobb; Christopher A Gilligan; Nik J Cunniffe
Journal:  Ecol Modell       Date:  2016-03-24       Impact factor: 2.974

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  9 in total

1.  The persistent threat of emerging plant disease pandemics to global food security.

Authors:  Jean B Ristaino; Pamela K Anderson; Daniel P Bebber; Kate A Brauman; Nik J Cunniffe; Nina V Fedoroff; Cambria Finegold; Karen A Garrett; Christopher A Gilligan; Christopher M Jones; Michael D Martin; Graham K MacDonald; Patricia Neenan; Angela Records; David G Schmale; Laura Tateosian; Qingshan Wei
Journal:  Proc Natl Acad Sci U S A       Date:  2021-06-08       Impact factor: 11.205

2.  A theoretical framework for transitioning from patient-level to population-scale epidemiological dynamics: influenza A as a case study.

Authors:  W S Hart; P K Maini; C A Yates; R N Thompson
Journal:  J R Soc Interface       Date:  2020-05-13       Impact factor: 4.118

3.  Interventions targeting non-symptomatic cases can be important to prevent local outbreaks: SARS-CoV-2 as a case study.

Authors:  Francesca A Lovell-Read; Sebastian Funk; Uri Obolski; Christl A Donnelly; Robin N Thompson
Journal:  J R Soc Interface       Date:  2021-05-19       Impact factor: 4.118

4.  Multiscale model for forecasting Sabin 2 vaccine virus household and community transmission.

Authors:  Michael Famulare; Wesley Wong; Rashidul Haque; James A Platts-Mills; Parimalendu Saha; Asma B Aziz; Tahmina Ahmed; Md Ohedul Islam; Md Jashim Uddin; Ananda S Bandyopadhyay; Mohammed Yunus; Khalequ Zaman; Mami Taniuchi
Journal:  PLoS Comput Biol       Date:  2021-12-21       Impact factor: 4.475

5.  An HLD Model for Tomato Bacterial Canker Focusing on Epidemics of the Pathogen Due to Cutting by Infected Scissors.

Authors:  Akira Kawaguchi; Shoya Kitabayashi; Koji Inoue; Koji Tanina
Journal:  Plants (Basel)       Date:  2022-08-30

6.  Improved inference of time-varying reproduction numbers during infectious disease outbreaks.

Authors:  R N Thompson; J E Stockwin; R D van Gaalen; J A Polonsky; Z N Kamvar; P A Demarsh; E Dahlqwist; S Li; E Miguel; T Jombart; J Lessler; S Cauchemez; A Cori
Journal:  Epidemics       Date:  2019-08-26       Impact factor: 4.396

7.  Outbreak response intervention models of vaccine-preventable diseases in humans and foot-and-mouth disease in livestock: a protocol for a systematic review.

Authors:  James M Azam; Elisha B Are; Xiaoxi Pang; Matthew J Ferrari; Juliet R C Pulliam
Journal:  BMJ Open       Date:  2020-10-05       Impact factor: 2.692

8.  Will an outbreak exceed available resources for control? Estimating the risk from invading pathogens using practical definitions of a severe epidemic.

Authors:  R N Thompson; C A Gilligan; N J Cunniffe
Journal:  J R Soc Interface       Date:  2020-11-11       Impact factor: 4.118

9.  Exploring the growth of COVID-19 cases using exponential modelling across 42 countries and predicting signs of early containment using machine learning.

Authors:  Dharun Kasilingam; Sakthivel Puvaneswaran Sathiya Prabhakaran; Dinesh Kumar Rajendran; Varthini Rajagopal; Thangaraj Santhosh Kumar; Ajitha Soundararaj
Journal:  Transbound Emerg Dis       Date:  2020-09-17       Impact factor: 4.521

  9 in total

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