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2019冠状病毒病大流行的时空小区域监测

Spatio-temporal small area surveillance of the COVID-19 pandemic.

作者信息

Martinez-Beneito Miguel A, Mateu Jorge, Botella-Rocamora Paloma

机构信息

Department of Statistics and Operations Research, University of Valencia, Burjassot (Valencia), Spain.

Unitat Mixta de recerca en mètodes estadístics per a dades biomédiques i sanitàries, UV-FISABIO, Spain.

出版信息

Spat Stat. 2022 Jun;49:100551. doi: 10.1016/j.spasta.2021.100551. Epub 2021 Nov 8.

Abstract

The emergence of COVID-19 requires new effective tools for epidemiological surveillance. Spatio-temporal disease mapping models, which allow dealing with small units of analysis, are a priority in this context. These models provide geographically detailed and temporally updated overviews of the current state of the pandemic, making public health interventions more effective. These models also allow estimating epidemiological indicators highly demanded for COVID-19 surveillance, such as the instantaneous reproduction number , even for small areas. In this paper, we propose a new spatio-temporal spline model particularly suited for COVID-19 surveillance, which allows estimating and monitoring for small areas. We illustrate our proposal on the study of the disease pandemic in two Spanish regions. As a result, we show how tourism flows have shaped the spatial distribution of the disease in these regions. In these case studies, we also develop new epidemiological tools to be used by regional public health services for small area surveillance.

摘要

新冠疫情的出现需要新的有效流行病学监测工具。时空疾病映射模型能够处理小分析单元,在此背景下是优先选择。这些模型提供了疫情当前状态的地理详细且随时间更新的概述,使公共卫生干预更有效。这些模型还能估计新冠疫情监测中迫切需要的流行病学指标,比如瞬时繁殖数,即使对于小区域也是如此。在本文中,我们提出一种特别适用于新冠疫情监测的新时空样条模型,它能对小区域估计和监测。我们在西班牙两个地区的疾病大流行研究中阐述了我们的提议。结果,我们展示了旅游流动如何塑造了这些地区疾病的空间分布。在这些案例研究中,我们还开发了新的流行病学工具供地区公共卫生服务机构用于小区域监测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c1c/8574159/16b43bbf8bd9/gr1_lrg.jpg

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