The Imperial Model is strongly based on traditional SIR-type differential equations. It treats the farm as the individual unit and classifies each farm by its infectious status. The initial model was formulated was formulated during the first few weeks of the 2001 FMD epidemic and was a crude approximation, ignoring farm differences and only differentiating between local and long-range transmission. This model also sacrifices many of the details present in more complex models for the ability rapidly and robustly to parameterize the equations from epidemic data. However, whereas standard SIR models ignore all spatial structure, the imperial model attempts to capture the clustering of infection (and hence the increased competition for susceptible farms) by assuming that all farms can weakly transmit infection at random over long distances but can only strongly have a limited number of local connections (estimated between 5.5 and 8.3). Therefore, this model not only considers the number of farms in each state, but also the number of pairs of locally connected farms through which the effects of clustering can be captured.