Investigating the impact of adaptive control strategies on infectious disease outbreaks
Lead Research Organisation:
University of Warwick
Department Name: School of Life Sciences
Abstract
Endemic and epidemic infectious diseases have the potential to undermine livestock sustainability and food security in the UK and worldwide. In the event of an infectious disease outbreak, control strategies are used to try and minimise the impact of the epidemic. The aim of adaptive management is to gain information about an outbreak as it occurs in 'real-time', in order to implement the optimal control strategy for this unique outbreak.
Building from an existing meta-population model of an example infectious disease outbreak we will begin to investigate the impact of different infection control measures on the course of livestock infectious disease outbreaks. We plan to simulate the use of a number of potential control strategies at a variety of time-points throughout an epidemic to see what effect this has on a number management objectives of interest.
This framework will then be built upon existing livestock infectious disease models such as those for foot-and-mouth disease and avian influenza, in order to inform policymakers and decision makers about the optimal ways to deal with an infectious disease prior to an outbreak occurring.
Alongside the modelling of adaptive management strategies, we will also develop interactive computer applications that are designed to make infectious disease modelling results more accessible to decision makers.
This will take the form of applications that run simple and faster infectious disease models within them, where individuals can interact through various menus and selection boxes to change model parameters and explore how these results change model outputs or applications ready loaded with simulation data to allow individuals to interactively change certain criteria to automatically produce visualisations of results.
Building from an existing meta-population model of an example infectious disease outbreak we will begin to investigate the impact of different infection control measures on the course of livestock infectious disease outbreaks. We plan to simulate the use of a number of potential control strategies at a variety of time-points throughout an epidemic to see what effect this has on a number management objectives of interest.
This framework will then be built upon existing livestock infectious disease models such as those for foot-and-mouth disease and avian influenza, in order to inform policymakers and decision makers about the optimal ways to deal with an infectious disease prior to an outbreak occurring.
Alongside the modelling of adaptive management strategies, we will also develop interactive computer applications that are designed to make infectious disease modelling results more accessible to decision makers.
This will take the form of applications that run simple and faster infectious disease models within them, where individuals can interact through various menus and selection boxes to change model parameters and explore how these results change model outputs or applications ready loaded with simulation data to allow individuals to interactively change certain criteria to automatically produce visualisations of results.
Organisations
People |
ORCID iD |
Michael Tildesley (Primary Supervisor) | |
Naomi Marsden (Student) |
Publications

Bradbury N
(2018)
Clinicians' attitude towards a placebo-controlled randomised clinical trial investigating the effect of neuraminidase inhibitors in adults hospitalised with influenza.
in BMC health services research

Owen RK
(2019)
MetaInsight: An interactive web-based tool for analyzing, interrogating, and visualizing network meta-analyses using R-shiny and netmeta.
in Research synthesis methods

Tildesley MJ
(2019)
The Role of Movement Restrictions in Limiting the Economic Impact of Livestock Infections.
in Nature sustainability
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
BB/M01116X/1 | 30/09/2015 | 31/03/2024 | |||
1782645 | Studentship | BB/M01116X/1 | 02/10/2016 | 29/06/2021 | Naomi Marsden |
Title | MetaInsight |
Description | MetaInsight is a tool that is freely available and that conducts network meta-analysis (NMA) via the web requiring no specialist software for the user to install but leveraging established analysis routines (specifically the netmeta package in R). The tool is interactive and uses an intuitive 'point and click' interface and presents results in visually intuitive and appealing ways. It can also carry out sensitivity analysis on existing NMAs. |
Type Of Technology | Webtool/Application |
Year Produced | 2017 |
Impact | MetaInsight is freely available to assist those in conducting NMA who are not statistical experts, and, in turn, increase the relevance of published meta-analyses, and in the long term contribute to improved healthcare decision making as a result. It has been used by the National Institute for Health Research Complex Reviews Support Unit in workshops for systematic reviewers. |
URL | https://crsu.shinyapps.io/metainsightc/ |