Whilst searching through a pile of papers recently I came across one I recalled as being refreshingly open about its message. The authors, advocates of traditional approaches for the control of Foot and Mouth Disease (FMD), were suggesting that, as useful as models may be, they were not necessary in the control of the FMD outbreak in the UK in 2001. Indeed, it was speculated that the implementation of models may have exacerbated the problems.
Traditional FMD control has and continues to revolve around a stamping-out approach, supplemented by increased biosecurity, surveillance and the implementation of control zones. If an animal on a farm is found to have FMD, the farm becomes an ‘infected premises’ (IP) and all FMD-susceptible species on the farm are slaughtered. Other premises with epidemiological links to the IP are then classed as ‘dangerous contacts’ (DC) and also have susceptible stock removed.
The controversial aspect - the contiguous cull - in the 2001 outbreak was that, rather than having identified epidemiological links, a farm was classed as a DC simply by having land contiguous to an IP. The contiguous cull was deeply unpopular and was largely supported by modelling. It appears to be this point which irked the authors most; their view was that FMD policy during the epidemic was now being influenced by “self-styled ‘experts’” sat behind computers producing models generated using data from previous outbreaks with different strains of virus, inaccurate livestock census data, and ‘inaccurate biological assumptions’.
Is this fair enough? Hindsight is a wonderful thing and models can easily be criticised for being unable to capture the complexity of an outbreak situation. Historically models were reductionist by their nature, but science is not static. The emergence of novel modelling approaches, along with the technological advances allowing the collation of more detailed quantitative and spatial datasets, as well as increasingly powerful computers, results in models of ever more sophistication and precision. The power of models to unveil patterns of spread and illuminate the most effective ways in which to employ control measures cannot, and will not, be ignored. Is this not the best way forward?
This is not a new debate; for every paper extolling the virtues of traditional approaches (if it ain’t broken....) there will be another detailing the benefits which can be reaped from models. An amalgamation of the two would appear to be the way forward. It would appear that models are here to stay, with the H1N1 pandemic influenza outbreak a classic example. So now there are new questions to ponder; ultimately, who should have the final say?
So if an outbreak happens tomorrow what should happen? I leave that for you to decide.