Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.
PLoS Comput Biol. 2022 May 23;18(5):e1008800. doi: 10.1371/journal.pcbi.1008800. eCollection 2022 May.
The fraction of cases reported, known as 'reporting', is a key performance indicator in an outbreak response, and an essential factor to consider when modelling epidemics and assessing their impact on populations. Unfortunately, its estimation is inherently difficult, as it relates to the part of an epidemic which is, by definition, not observed. We introduce a simple statistical method for estimating reporting, initially developed for the response to Ebola in Eastern Democratic Republic of the Congo (DRC), 2018-2020. This approach uses transmission chain data typically gathered through case investigation and contact tracing, and uses the proportion of investigated cases with a known, reported infector as a proxy for reporting. Using simulated epidemics, we study how this method performs for different outbreak sizes and reporting levels. Results suggest that our method has low bias, reasonable precision, and despite sub-optimal coverage, usually provides estimates within close range (5-10%) of the true value. Being fast and simple, this method could be useful for estimating reporting in real-time in settings where person-to-person transmission is the main driver of the epidemic, and where case investigation is routinely performed as part of surveillance and contact tracing activities.
报告病例的比例，即“报告率”，是疫情应对中的一个关键绩效指标，也是在进行传染病建模和评估其对人群影响时需要考虑的一个重要因素。不幸的是，由于它与疫情中未被观察到的部分有关，因此其估计具有内在的难度。我们引入了一种简单的统计方法来估计报告率，该方法最初是为应对 2018-2020 年刚果民主共和国（DRC）东部的埃博拉疫情而开发的。该方法使用通过病例调查和接触者追踪通常收集的传播链数据，并使用已知报告感染者的调查病例比例作为报告率的代理。通过模拟疫情，我们研究了该方法在不同疫情规模和报告水平下的表现。结果表明，我们的方法具有较低的偏差、合理的精度，并且尽管覆盖范围不理想，但通常能够提供与真实值相差 5-10%的估计值。该方法快速简单，在人际传播是疫情主要驱动因素的情况下，以及在病例调查作为监测和接触者追踪活动的一部分常规进行的情况下，该方法可用于实时估计报告率。
