Guzzi Pietro H, Tradigo Giuseppe, Veltri Pierangelo
Department of Surgical and Medical Sciences, University of Catanzaro, CZ, Italy.
Ecampus University, Novedrate, Italy.
JMIR Med Inform. 2021 Mar 9;9(3):e18933. doi: 10.2196/18933.
COVID-19 has been declared a worldwide emergency and a pandemic by the World Health Organization. It started in China in December 2019, and it rapidly spread throughout Italy, which was the most affected country after China. The pandemic affected all countries with similarly negative effects on the population and health care structures.
The evolution of the COVID-19 infections and the way such a phenomenon can be characterized in terms of resources and planning has to be considered. One of the most critical resources has been intensive care units (ICUs) with respect to the infection trend and critical hospitalization.
We propose a model to estimate the needed number of places in ICUs during the most acute phase of the infection. We also define a scalable geographic model to plan emergency and future management of patients with COVID-19 by planning their reallocation in health structures of other regions.
We applied and assessed the prediction method both at the national and regional levels. ICU bed prediction was tested with respect to real data provided by the Italian government. We showed that our model is able to predict, with a reliable error in terms of resource complexity, estimation parameters used in health care structures. In addition, the proposed method is scalable at different geographic levels. This is relevant for pandemics such as COVID-19, which has shown different case incidences even among northern and southern Italian regions.
Our contribution can be useful for decision makers to plan resources to guarantee patient management, but it can also be considered as a reference model for potential upcoming waves of COVID-19 and similar emergency situations.
世界卫生组织已宣布新型冠状病毒肺炎(COVID-19)为全球紧急情况和大流行病。它于2019年12月在中国开始,并迅速蔓延至意大利,意大利是继中国之后受影响最严重的国家。这场大流行病影响了所有国家,对人口和医疗保健结构产生了类似的负面影响。
必须考虑COVID-19感染的演变情况以及如何根据资源和规划来描述这一现象。就感染趋势和危重症住院情况而言,最关键的资源之一是重症监护病房(ICU)。
我们提出了一个模型,用于估计感染最急性期所需的ICU床位数量。我们还定义了一个可扩展的地理模型,通过规划将COVID-19患者重新分配到其他地区的卫生机构,来规划对COVID-19患者的应急和未来管理。
我们在国家和地区层面应用并评估了该预测方法。根据意大利政府提供的实际数据对ICU床位预测进行了测试。我们表明,我们的模型能够在资源复杂性、医疗保健机构使用的估计参数方面以可靠的误差进行预测。此外,所提出的方法在不同地理层面上是可扩展的。这对于像COVID-19这样的大流行病很重要,因为即使在意大利北部和南部地区,其病例发生率也有所不同。
我们的贡献对决策者规划资源以保障患者管理可能有用,但它也可被视为应对未来可能出现的COVID-19浪潮及类似紧急情况的参考模型。