Data for modelling policy decisions to mitigate risk of emerging arboviral diseases under ecological change in Uganda

In this study, we applied Bayesian Decision Modelling to evaluate how different policy interventions may reduce arboviral disease risk in Uganda. This dataset comprises the results of the policy analysis we conducted to identify and compare the potential Ugandan policy options that could reduce the risk of arboviral disease emergence. During workshops, multidisciplinary experts reviewed these policies and identified disease preventive interventions. Experts also assessed the influence of 29 preventive actions on disease risk under four policy options and made decisions on their probability of implementation under the policy options. We present the experts' conditional probabilities that were subsequently used in Bayesian Decision Modelling.