An ensemble approach to short-term forecast of COVID-19 intensive care occupancy in Italian regions
An ensemble approach to short-term forecast of COVID-19 intensive care occupancy in Italian regions
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DOI：
10.1002/bimj.202000189
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发表时间：
2020-11-30
影响因子：
1.7
通讯作者：
Lovison, Gianfranco
中科院分区：
文献类型：
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作者：
Farcomeni, Alessio;Maruotti, Antonello;Lovison, Gianfranco
在COVID-19疫情期间，重症监护病床的可用性对于保证严重受影响的患者获得最佳治疗至关重要。在这项工作中，我们展示了一种用于COVID-19重症监护病房（ICU）床位短期预测的简单策略，该策略在2020年2月至5月的意大利疫情期间被证明非常有效。我们的方法是基于两个简单的方法的最佳合奏：广义线性混合回归模型，它汇集了不同地区的信息，和特定区域的非平稳整数自回归方法。最佳权重估计使用留后的理由。该方法已在意大利第一波流行期间建立和验证。它的性能预测ICU占用率在区域一级的报告。
The availability of intensive care beds during the COVID-19 epidemic is crucial to guarantee the best possible treatment to severely affected patients. In this work we show a simple strategy for short-term prediction of COVID-19 intensive care unit (ICU) beds, that has proved very effective during the Italian outbreak in February to May 2020. Our approach is based on an optimal ensemble of two simple methods: a generalized linear mixed regression model, which pools information over different areas, and an area-specific nonstationary integer autoregressive methodology. Optimal weights are estimated using a leave-last-out rationale. The approach has been set up and validated during the first epidemic wave in Italy. A report of its performance for predicting ICU occupancy at regional level is included.