Department of Statistics, Computer Science, Applications G. Parenti, University of Florence, Florence (Italy).
Regional Health Agency of Tuscany, Florence (Italy);
Epidemiol Prev. 2020 Sep-Dec;44(5-6 Suppl 2):184-192. doi: 10.19191/EP20.5-6.S2.117.
since the beginning of the COVID-19 pandemic, the importance of developing a serological test has emerged and a debate on test accuracy and reliability become an issue widely discussed in the media. The importance of communication during this pandemic has been strongly underlined by public health experts, epidemiologists, media expert, psychologists, sociologists. In the case of serological tests, there are several aspects that have to be considered: why we perform the test, what population is tested, which are the parameters conditioning the results and their interpretation.
to show how to quantify the uncertainty related to the validity of the serological test with respect to its predictive value and in particular the positive predictive value.
the evaluation of a qualitative diagnostic test includes four distinct assessments: accuracy, empirical evidence, practical importance, and prevalence of the pathology. Accuracy is measured by the sensitivity and specificity of the test; empirical evidence is quantified by the likelihood ratio, respectively for a positive and negative test result; the practical importance of the result of a diagnostic test is assessed by the positive or negative predictive value. Prevalence of COVID-19 is substantial uncertainty and it is possible to estimate the apparent prevalence starting from the results obtained with a diagnostic test.
at the moment, the knowledge about the accuracy of serological tests is limited and little attention is paid to confidence interval on point estimates. In terms of practical importance of testing at individual level, while negative predictive values are high whatever the level of sensitivity of the test, the interpretation of a positive results is very cumbersome. Positive predictive values above 90% can be reached only by tests with specificity above 99% at the expected prevalence rate of 5%. There is a linear relationship between apparent - testing positive - prevalence and real prevalence. The apparent prevalence in the context of serological test for COVID-19 is always larger than real prevalence. The level of specificity is crucial.
the main applications of the serological test in the epidemic contest are: to study the seroprevalence of the virus antibodies in the general population; to screen the healthcare workers for the early identification of contagious subjects' health care settings and to screen the general population in order to identify new incident cases. In the first two cases, seroprevalence study and screening of a high-risk population, the consequences of the uncertainty associated to the statistics are already accounted for in the first situation, or are overcome by repeating the screening on the healthcare workers, and using the molecular test to verify the presence of the virus in those tested positive. The case of screening of general population is more complex and of major interest for the implication it may have on individual behaviours and on the implementation of public health interventions by the political decision makers. A positive result has, per se, no practical value for individuals since the probability of being really infected by the virus is low. The uncertainty associated with the different estimates (sensitivity, specificity and disease prevalence) play a double role: it is a key factor in defining the informative content of the test result and it might guide the individual actions and the public policy decisions.
自 COVID-19 大流行开始以来，开发血清学检测的重要性已经显现出来，检测准确性和可靠性的争论也成为媒体广泛讨论的问题。公共卫生专家、流行病学家、媒体专家、心理学家和社会学家都强烈强调了在大流行期间进行沟通的重要性。在血清学检测的情况下，有几个方面需要考虑：为什么要进行检测、检测哪些人群、影响结果及其解释的参数有哪些。
展示如何量化与血清学检测的预测值相关的不确定性，特别是其阳性预测值。
对定性诊断检测的评估包括四个不同的评估：准确性、经验证据、实际重要性和疾病的流行率。准确性通过检测的敏感性和特异性来衡量；经验证据由阳性和阴性检测结果的似然比来量化；诊断检测结果的实际重要性通过阳性或阴性预测值来评估。COVID-19 的流行率存在很大的不确定性，可以根据诊断性检测的结果来估计表观流行率。
目前，血清学检测的准确性知识有限，很少关注点估计的置信区间。就个体水平检测的实际重要性而言，无论检测的敏感性如何，阴性预测值都很高，而阳性结果的解释非常麻烦。只有在预期流行率为 5%时，特异性高于 99%的检测才能达到阳性预测值高于 90%。表观流行率（检测呈阳性）与真实流行率之间存在线性关系。在 COVID-19 的血清学检测中，表观流行率总是大于真实流行率。特异性水平至关重要。
血清学检测在疫情中的主要应用有：研究病毒抗体在人群中的血清流行率；筛选医护人员以早期发现有传染性的医护人员；筛选一般人群，以发现新的感染病例。在前两种情况下，即血清流行率研究和高危人群筛查，与统计学相关的不确定性的后果已经在第一种情况下得到考虑，或者通过对医护人员重复筛查，并使用分子检测来验证检测呈阳性者是否存在病毒，从而得到克服。筛查一般人群的情况则更为复杂，并且对个人行为和政治决策者实施公共卫生干预措施可能产生重大影响。阳性结果本身对个人没有实际价值，因为个体感染病毒的概率很低。与不同估计值（敏感性、特异性和疾病流行率）相关的不确定性起着双重作用：它是定义检测结果信息含量的关键因素，并且可能指导个体行动和公共政策决策。
