Keller Niklas, Jenny Mirjam A
Simply Rational-The Decision Institute, Berlin, Germany.
Science Communication Unit, Robert Koch-Institute, Berlin, Germany.
MDM Policy Pract. 2020 Nov 5;5(2):2381468320963068. doi: 10.1177/2381468320963068. eCollection 2020 Jul-Dec.
Extensive testing lies at the heart of any strategy to effectively combat the SARS-COV-2 pandemic. In recent months, the use of enzyme-linked immunosorbent assay-based antibody tests has gained a lot of attention. These tests can potentially be used to assess SARS-COV-2 immunity status in individuals (e.g., essential health care personnel). They can also be used as a screening tool to identify people that had COVID-19 asymptomatically, thus getting a better estimate of the true spread of the disease, gain important insights on disease severity, and to better evaluate the effectiveness of policy measures implemented to combat the pandemic. But the usefulness of these tests depends not only on the quality of the test but also, critically, on how far disease has already spread in the population. For example, when only very few people in a population are infected, a positive test result has a high chance of being a false positive. As a consequence, the spread of the disease in a population as well as individuals' immunity status may be systematically misinterpreted. SARS-COV-2 infection rates vary greatly across both time and space. In many places, the infection rates are very low but can quickly skyrocket when the virus spreads unchecked. Here, we present two tools, natural frequency trees and positive and negative predictive value graphs, that allow one to assess the usefulness of antibody testing for a specific context at a glance. These tools should be used to support individual doctor-patient consultation for assessing individual immunity status as well as to inform policy discussions on testing initiatives.
广泛检测是有效抗击新冠疫情的任何策略的核心。近几个月来,基于酶联免疫吸附测定的抗体检测受到了广泛关注。这些检测有可能用于评估个体(如基本医疗保健人员)的新冠病毒免疫状态。它们还可作为一种筛查工具,以识别无症状感染新冠病毒的人群,从而更好地估计疾病的实际传播情况,深入了解疾病严重程度,并更好地评估为抗击疫情而实施的政策措施的有效性。但这些检测的有用性不仅取决于检测质量,关键还取决于疾病在人群中已经传播的程度。例如,当人群中只有极少数人感染时,检测呈阳性很可能是假阳性。因此,疾病在人群中的传播情况以及个体的免疫状态可能会被系统性地误判。新冠病毒的感染率在时间和空间上差异很大。在许多地方,感染率很低,但如果病毒不受控制地传播,感染率可能会迅速飙升。在此,我们介绍两种工具,自然频率树以及阳性和阴性预测值图,它们能让人一眼评估抗体检测在特定情况下的有用性。这些工具应用于支持医生与患者的个体咨询,以评估个体免疫状态,并为有关检测举措的政策讨论提供参考。