Foodborne disease outbreaks are rare events that can be extremely costly in terms of public health as well as monetary losses for industry and government. These events can overwhelm the local public healthcare network and exceed the capacity of epidemiologists and local public health officials to investigate and manage the outbreak. Planning and allocation of sufficient resources requires an understanding of both the frequency and magnitude of large foodborne outbreaks. Describing these two characteristics is difficult because most statistical methods describe central tendencies of the phenomena under study. An exception is extreme value theory (EVT), which intends to estimate the size and frequency of adverse events as large as, or larger than, those previously observed. This study applies extreme value theory methods to foodborne disease outbreak data collected in the United States between 1973 and 2016. A brief summary of the data, including changes in the surveillance system and their effect on the outbreak data, is provided. Estimates of the outbreak size expected to be exceeded within time periods of 10, 20, 40 and 100 years, referred to as the return level, ranged from 2500 to 10,400. The estimated time period time between outbreaks (i.e., the return period) of at least 500, 5,000, 10,000 and 20,000 cases ranged from 1 to greater than 400 years.

食源性疾病暴发是罕见的事件，就公共卫生以及产业和政府的金钱损失而言，其代价可能非常高昂。这些事件会使当地的公共医疗网络不堪重负，超出了流行病学家和当地公共卫生官员调查和管理疫情的能力。计划和分配足够的资源需要了解大规模食源性疾病暴发的频率和程度。很难描述这两个特征，因为大多数统计方法都描述了所研究现象的集中趋势。极值理论（EVT）是一个例外，它旨在估计不良事件的大小和频率，其大小与先前观察到的一样大或更大。这项研究将极值理论方法应用于1973年至2016年间在美国收集的食源性疾病暴发数据。提供了该数据的简要摘要，包括监视系统的变化及其对暴发数据的影响。预计将在10年，20年，40年和100年的时间段内超过爆发规模的估计值，即返回水平，范围为2500至10400。两次暴发之间的估计时间间隔（即恢复期）至少为500、5,000、10,000和20,000，范围从1年到大于400年。20年，40年和100年，称为回报水平，范围从2500到10,400。两次暴发之间的估计时间间隔（即恢复期）至少为500、5,000、10,000和20,000，范围从1年到大于400年。20年，40年和100年，称为回报水平，范围从2500到10,400。两次暴发之间的估计时间间隔（即恢复期）至少为500、5,000、10,000和20,000，范围从1年到大于400年。