Case Study: University of Tokyo improves BSE (mad cow) detection and optimizes surveillance strategy with Palisade’s @RISK

University of Tokyo - Customer Case Study

The University of Tokyo brought Palisade’s @RISK to bear on a difficult food‑safety problem: improving bovine spongiform encephalopathy (BSE, “mad cow disease”) surveillance in Japan. Faculty in the Graduate School of Agriculture and Life Sciences needed to account for long, variable incubation periods and limits of diagnostic tests to decide optimal ages for testing slaughtered and fallen cattle without extensive new programming — a challenge Palisade’s Monte Carlo–based tool could address directly within Excel.

Using Palisade’s @RISK, researchers built stochastic models to simulate surveillance strategies with different minimum testing ages (0, 21, 31, 41 months for slaughter; 24, 31, 41 months for fallen stock). The simulations showed that increasing minimum test age from 0 to 21 months had little effect on the probability of detecting infected animals, and further increases mainly reduced the number of animals tested while leaving detection probability essentially unchanged; detection rates for some cattle types remained very low across all strategies. Palisade’s @RISK therefore enabled the team to quantify tradeoffs, eliminate testing age as a primary driver of detection, and refocus resources on more effective control measures — all within familiar Excel workflows.

University of Tokyo

Katsuaki Sugiura

Professor