Abstract 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.

中文翻译：

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意大利地区 COVID-19 重症监护入住率短期预测的整体方法

摘要：在 COVID-19 流行期间，重症监护病床的可用性对于保证对受严重影响的患者进行最佳治疗至关重要。在这项工作中，我们展示了一种用于短期预测 COVID-19 重症监护病房 (ICU) 床位的简单策略，该策略在 2020 年 2 月至 2020 年 5 月的意大利爆发期间被证明非常有效。我们的方法基于两个的最佳集合简单方法：广义线性混合回归模型，汇集不同区域的信息，以及特定区域的非平稳整数自回归方法。最佳权重是使用留出原理估计的。该方法已在意大利的第一波流行病中建立并得到验证。包括其在区域层面预测 ICU 入住率的性能报告。