What should the best practices be for modeling zoonotic disease risks, e.g. to anticipate the next pandemic, when background assumptions are unsettled or evolving rapidly? This challenge runs deeper than one might expect, all the way into how we model the robustness of contemporary phylogenetic inference and taxonomic classifications. Different and legitimate taxonomic assumptions can destabilize the putative objectivity of zoonotic risk assessments, thus potentially supporting inconsistent and overconfident policy decisions.

中文翻译：

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蝙蝠、客观性和病毒溢出风险

当背景假设不稳定或迅速发展时，对人畜共患疾病风险进行建模（例如预测下一次大流行）的最佳实践应该是什么？这一挑战比人们想象的要深入，一直到我们如何模拟当代系统发育推理和分类学分类的稳健性。不同且合理的分类学假设可能会破坏人畜共患病风险评估的假定客观性，从而可能支持不一致和过度自信的政策决策。