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Spatio-temporal small area surveillance of the COVID-19 pandemic
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 curr...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier B.V.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8574159/ https://www.ncbi.nlm.nih.gov/pubmed/34782854 http://dx.doi.org/10.1016/j.spasta.2021.100551 |
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author | Martinez-Beneito, Miguel A. Mateu, Jorge Botella-Rocamora, Paloma |
author_facet | Martinez-Beneito, Miguel A. Mateu, Jorge Botella-Rocamora, Paloma |
author_sort | Martinez-Beneito, Miguel A. |
collection | PubMed |
description | 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 [Formula: see text] , 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 [Formula: see text] 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. |
format | Online Article Text |
id | pubmed-8574159 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Author(s). Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85741592021-11-08 Spatio-temporal small area surveillance of the COVID-19 pandemic Martinez-Beneito, Miguel A. Mateu, Jorge Botella-Rocamora, Paloma Spat Stat Article 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 [Formula: see text] , 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 [Formula: see text] 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. The Author(s). Published by Elsevier B.V. 2022-06 2021-11-08 /pmc/articles/PMC8574159/ /pubmed/34782854 http://dx.doi.org/10.1016/j.spasta.2021.100551 Text en © 2021 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Martinez-Beneito, Miguel A. Mateu, Jorge Botella-Rocamora, Paloma Spatio-temporal small area surveillance of the COVID-19 pandemic |
title | Spatio-temporal small area surveillance of the COVID-19 pandemic |
title_full | Spatio-temporal small area surveillance of the COVID-19 pandemic |
title_fullStr | Spatio-temporal small area surveillance of the COVID-19 pandemic |
title_full_unstemmed | Spatio-temporal small area surveillance of the COVID-19 pandemic |
title_short | Spatio-temporal small area surveillance of the COVID-19 pandemic |
title_sort | spatio-temporal small area surveillance of the covid-19 pandemic |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8574159/ https://www.ncbi.nlm.nih.gov/pubmed/34782854 http://dx.doi.org/10.1016/j.spasta.2021.100551 |
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