In tackling agricultural challenges, policy-makers in sub-Saharan Africa (SSA) have increasingly considered genetically modified (GM) crops as a potential tool to increase productivity and to improve product quality. Yet, as elsewhere in the world, the adoption of GM crops in SSA has been marked by controversy, encompassing not only the potential risks to animal and human health, and to the environment, but also other concerns such as ethical issues, public participation in decision-making, socio-economic factors and intellectual property rights. With these non-scientific factors complicating an already controversial situation, disseminating credible information to the public as well as facilitating stakeholder input into decision-making is essential. In SSA, there are various and innovative risk communication approaches and strategies being developed, yet a comprehensive analysis of such data is missing. This gap is addressed by giving an overview of current strategies, identifying similarities and differences between various country and institutional approaches and promoting a way forward, building on a recent workshop with risk communicators working in SSA.

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Rice yellow mottle virus (RYMV)

Internationally recognised guidelines for the assessment of risk posed by nonnative organisms generally suggest that the assessment is disaggregated into a series of components each being scored and then the scores added or averaged to give the final result. Assigning odds instead of scores allows a more rigorous probabilistic treatment of the data, which can offer more effective discrimination between organisms. For each component of the assessment, the odds express how likely is the evidence if the organism poses a risk as a quarantine pest. According to Bayesian theory, the odds for all components are multiplied together and the product divided by itself plus one to give the probability that the organism poses a risk as a quarantine pest given the evidence available (assuming that the prior probability is neutral). A general illustration of the different distributions of outcomes obtained from score averaging and probability is provided. The approach is then applied to a set of risk assessments for 256 potential quarantine pests compiled for Tanzania in 1997. The greater discrimination between cases may help improve communication between risk assessment scientists and regulatory decision makers.Quantitative risk assessment of quarantine pests and non-native organisms J. Holt et al.

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