Use and abuse of mathematical models : an illustration from the 2001 foot and mouth disease epidemic in the United Kingdom

Abstract

Foot and mouth disease (FMD) is a major threat, not only to countries whose economies rely on agricultural exports, but also to industrialised countries that maintain a healthy domestic livestock industry by eliminating major infectious diseases from their livestock populations. Traditional methods of controlling diseases such as FMD require the rapid detection and slaughter of infected animals, and any susceptible animals with which they may have been in contact, either directly or indirectly. During the 2001 epidemic of FMD in the United Kingdom (UK), this approach was supplemented by a culling policy driven by unvalidated predictive models. The epidemic and its control resulted in the death of approximately ten million animals, public disgust with the magnitude of the slaughter, and political resolve to adopt alternative options, notably including vaccination, to control any future epidemics. The UK experience provides a salutary warning of how models can be abused in the interests of scientific opportunism.

A comparison of predictions made by three simulation models of foot-and-mouth disease

“…Although not included in some of the mathematical models used in the FMD epidemic in the United Kingdom in 2001 (Ferguson et al 2001;Keeling et al 2001), it was accepted that there was within-herd transmission of FMD (Hutber and Kitching 2000). Accordingly, it is likely that farm-level infectiousness would increase over time as the number of animals infected increased (Taylor 2003;Haydon et al 2004;Honhold et al 2004;Kitching et al 2006). Future comparisons should assess the impact of within-herd spread in more complex, realistic scenarios.…”

The rising impact of mathematical modelling in epidemiology: antibiotic resistance research as a case study

“…However, perception of these models by other scientists working on these public health problems remains divided. Although modelling approaches have gained growing acceptance in recent years, as illustrated by the number of articles published in high-profile journals [4][5][6], the use of mathematical models has also at times elicited scepticism or defiance [7,8]. To the best of our knowledge, no study quantifying the perceived growing impact of the modelling approach on the scientific community or providing in-depth information on the relationships between mathematical models and other relevant scientific fields has been published.…”

Uncertainties in the governance of animal disease: an interdisciplinary framework for analysis

“…These approaches provide contexts in which policy options for disease control and risk assessment can be built into system preparedness, though from experience they are often poor decision-making tools for disease alleviation (see below). Perhaps not surprisingly, the specification and parametrization of these models, and their accompanying evidence base, have often been identified as highly uncertain [30,31]. Parameter estimation, an essential part of model development, is frequently based on data considered to be comparable to the system under study, while clearly being different.…”