Most new human infections are of animal origin, but there is rarely sufficient evidence to make a risk assessment of the zoonotic potential of emerging animal diseases. An algorithm for early qualitative public health risk assessment has been developed to guide risk management Most newly emerging human infections of global importance are of animal origin, 1 w1 but early accurate predictions of zoonotic risk of emerging animal diseases are difficult, as shown by the epidemic of bovine spongiform encephalopathy and variant Creutzfeldt-Jakob disease in the United Kingdom. w2 Miscalculation, delays, or poor risk communication can result in failure to protect the public's health and undermine public trust, 2 but overreaction can waste resources and even harm the economy of countries, as in the case of suspected plague in India. 3 The public are increasingly anxious to understand the basis on which a government's decisions on risk management are taken, w3 but scientists and government may be reluctant to engage with the public at an early stage because of the fear of provoking a public scare. However, since the BSE epidemic, it has been accepted that the criteria used and the evidence considered in risk assessments should be open and explicit. 4 w4 w5 In this article we describe and illustrate such an approach, one that explicitly distinguishes evidence of lack of zoonotic potential from lack of evidence. The algorithm, endorsed by the UK government's Zoonoses Group w6 and by the National Expert Panel on New and Emerging Infection, w7 is being used by the Human and Animal Infections and Risk Surveillance Group of the Health Protection Agency. 5
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Palmer et al. (2005) studied this question.
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