Abstract

Animal disease outbreaks pose a significant threat in terms of potential economic losses, reduced productivity, and negative impacts on public health, food security and nutrition. This paper considers four issues in ex-post evaluation of animal disease interventions: firstly, a counterfactual involves simulating disease trajectories without the intervention. But some diseases can become endemic or become dormant after an outbreak, making it a challenge to know the true trajectory without the intervention. Secondly, without adequate design of controls and treatments, how can the estimated impacts be attributed to a given intervention? Thirdly, how do we assess costs saved by the intervention? Fourthly, given data uncertainty, would a stochastic simulation give better estimates than a deterministic one in solving for key variables? This paper addresses these issues and proposes solutions that bridge the gap between household level analysis and macro-level simulations in modelling the impact of animal diseases outbreaks.

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