This paper addresses pandemic statistics from a management perspective. Both input and output are easy to understand. Focus is on operations and cross border communication. To be able to work with simple available data some new missing data issues have to be solved from a mathematical statistical point of view. We illustrate our approach with data from France collected during the recent Covid-19 pandemic. Our new benchmark method also introduces a potential new division of labour while working with pandemic statistics allowing crucial input to be fed to the model via prior knowledge from external experts.

翻译：本文从管理视角探讨疫情统计数据。输入与输出均易于理解，重点聚焦于操作环节与跨境沟通。为能利用简单可得数据进行工作，需从数理统计角度解决若干新型数据缺失问题。我们以近期新冠疫情期间收集的法国数据为例阐释该方法。本文提出的新基准方法还引入了疫情统计工作中潜在的新型劳动分工，使外部专家的先验知识能够为模型提供关键输入。