Max Planck Institute for the Physics of Complex Systems (MPIPKS), Dresden, Germany.
Institute of Science and Technology Austria (IST Austria), Klosterneuburg, Austria.
PLoS One. 2022 Jul 18;17(7):e0269975. doi: 10.1371/journal.pone.0269975. eCollection 2022.
In Fall 2020, several European countries reported rapid increases in COVID-19 cases along with growing estimates of the effective reproduction rates. Such an acceleration in epidemic spread is usually attributed to time-dependent effects, e.g. human travel, seasonal behavioral changes, mutations of the pathogen etc. In this case however the acceleration occurred when counter measures such as testing and contact tracing exceeded their capacity limit. Considering Austria as an example, here we show that this dynamics can be captured by a time-independent, i.e. autonomous, compartmental model that incorporates these capacity limits. In this model, the epidemic acceleration coincides with the exhaustion of mitigation efforts, resulting in an increasing fraction of undetected cases that drive the effective reproduction rate progressively higher. We demonstrate that standard models which does not include this effect necessarily result in a systematic underestimation of the effective reproduction rate.
2020 年秋季，一些欧洲国家报告 COVID-19 病例迅速增加，同时有效繁殖率的估计值也在不断上升。这种疫情传播的加速通常归因于时间相关的影响，例如人类旅行、季节性行为变化、病原体突变等。然而，在这种情况下，加速发生在检测和接触者追踪等措施超过其能力极限时。以奥地利为例，我们在这里表明，这种动态可以通过纳入这些能力限制的独立的、即自治的、分区模型来捕捉。在该模型中，疫情加速与缓解措施的枯竭同时发生，导致未被发现的病例比例增加，从而使有效繁殖率逐渐升高。我们证明，不包括这一效应的标准模型必然会导致对有效繁殖率的系统低估。
