Nowcasting the COVID-19 pandemic in Bavaria.
Nowcasting the COVID-19 pandemic in Bavaria.
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DOI：
10.1002/bimj.202000112
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发表时间：
2021-03
期刊：
影响因子：
--
通讯作者：
Höhle M
中科院分区：
文献类型：
--
作者：
Günther F;Bender A;Katz K;Küchenhoff H;Höhle M
为了评估一种流行病的当前动态，收集关于每日新发病例数量的信息至关重要。这在真实的实时监控中尤为重要，其目的是获得态势感知，例如，如果病例当前正在增加或减少。疾病发病和病例报告之间的报告延迟妨碍了我们在仅查看每日报告病例数时了解目前流行病动态的能力。Nowcasting可用于调整已发生但尚未报告的事件的每日病例计数。在这里，我们提出了一种新的即时预报应用于巴伐利亚州当前COVID-19大流行的数据。它是基于一个分层贝叶斯模型，考虑随着时间的推移，报告延迟分布的变化，并与报告的工作日。此外，我们提出了一种方法来估计有效的随时间变化的情况下再生数的预测的基础上的nowcast。这些方法是基于以前发表的工作，我们大大扩展和调整，以适应当前的任务，即时预报COVID-19病例。我们提供了所开发方法的方法细节，说明了基于当前疫情数据的结果，并根据巴伐利亚COVID-19的综合和回顾性数据评估了模型。我们的临近预报结果会报告给巴伐利亚州卫生当局，并每天在网页上发布（https：//corona.stat.uni-muenchen.de/）。用于分析的代码和合成数据可从https://github.com/FelixGuenther/nc_covid19_bavaria获得，并且可用于使我们的方法适应不同的数据。
To assess the current dynamics of an epidemic, it is central to collect information on the daily number of newly diseased cases. This is especially important in real‐time surveillance, where the aim is to gain situational awareness, for example, if cases are currently increasing or decreasing. Reporting delays between disease onset and case reporting hamper our ability to understand the dynamics of an epidemic close to now when looking at the number of daily reported cases only. Nowcasting can be used to adjust daily case counts for occurred‐but‐not‐yet‐reported events. Here, we present a novel application of nowcasting to data on the current COVID‐19 pandemic in Bavaria. It is based on a hierarchical Bayesian model that considers changes in the reporting delay distribution over time and associated with the weekday of reporting. Furthermore, we present a way to estimate the effective time‐varying case reproduction number based on predictions of the nowcast. The approaches are based on previously published work, that we considerably extended and adapted to the current task of nowcasting COVID‐19 cases. We provide methodological details of the developed approach, illustrate results based on data of the current pandemic, and evaluate the model based on synthetic and retrospective data on COVID‐19 in Bavaria. Results of our nowcasting are reported to the Bavarian health authority and published on a webpage on a daily basis (https://corona.stat.uni-muenchen.de/). Code and synthetic data for the analysis are available from https://github.com/FelixGuenther/nc_covid19_bavaria and can be used for adaption of our approach to different data.
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