{'fraction_non_alphanumeric': 0.009687034277198211, 'fraction_numerical': 0.0, 'mean_word_length': 5.8520408163265305, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Uncertainty and Sensitivity Analyses of a Decision Analytic Model for Posteradication Polio Risk Management

Decision analytic modeling of polio risk management policies after eradication may help inform decisionmakers about the quantitative tradeoffs implied by various options. Given the significant dynamic complexity and uncertainty involving posteradication decisions, this article aims to clarify the structure of a decision analytic model developed to help characterize the risks, costs, and benefits of various options for polio risk management after eradication of wild polioviruses and analyze the implications of different sources of uncertainty. We provide an influence diagram of the model with a description of each component, explore the impact of different assumptions about model inputs, and present probability distributions of model outputs. The results show that choices made about surveillance, response, and containment for different income groups and immunization policies play a major role in the expected final costs and polio cases. While the overall policy implications of the model remain robust to the variations of assumptions and input uncertainty we considered, the analyses suggest the need for policymakers to carefully consider tradeoffs and for further studies to address the most important knowledge gaps.