Cargando…
Applying Spatio-temporal Scan Statistics and Spatial Autocorrelation Statistics to identify Covid-19 clusters in the world - A Vaccination Strategy?
With the whole world being affected by the pandemic, it is a matter of great importance that studies about spatial and spatio-temporal aspects of the COVID-19 (Sars-Cov-2) pandemic should be conducted, therefore the main goal of this paper is to present the Global Moran's I and the Local Moran&...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545727/ https://www.ncbi.nlm.nih.gov/pubmed/34774258 http://dx.doi.org/10.1016/j.sste.2021.100461 |
_version_ | 1784590058820468736 |
---|---|
author | Morais, Lucas Rabelo de Araújo Gomes, Gecynalda Soares da Silva |
author_facet | Morais, Lucas Rabelo de Araújo Gomes, Gecynalda Soares da Silva |
author_sort | Morais, Lucas Rabelo de Araújo |
collection | PubMed |
description | With the whole world being affected by the pandemic, it is a matter of great importance that studies about spatial and spatio-temporal aspects of the COVID-19 (Sars-Cov-2) pandemic should be conducted, therefore the main goal of this paper is to present the Global Moran's I and the Local Moran's I used to evaluate spatial association in the number of deaths and infections by COVID-19, and a spatio-temporal Poisson scan statistic used to identify emerging or “alive” clusters of infections by Sars-Cov-2 in space and time. As of January 2021 vaccination against COVID-19 already started, since the use of spatial clustering methods to identify non-vaccinated populations is not new among studies on vaccination coverage strategies, this paper also aims to discuss the implementation of spatial and spatio-temporal clustering methods in early vaccination. |
format | Online Article Text |
id | pubmed-8545727 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85457272021-10-26 Applying Spatio-temporal Scan Statistics and Spatial Autocorrelation Statistics to identify Covid-19 clusters in the world - A Vaccination Strategy? Morais, Lucas Rabelo de Araújo Gomes, Gecynalda Soares da Silva Spat Spatiotemporal Epidemiol Article With the whole world being affected by the pandemic, it is a matter of great importance that studies about spatial and spatio-temporal aspects of the COVID-19 (Sars-Cov-2) pandemic should be conducted, therefore the main goal of this paper is to present the Global Moran's I and the Local Moran's I used to evaluate spatial association in the number of deaths and infections by COVID-19, and a spatio-temporal Poisson scan statistic used to identify emerging or “alive” clusters of infections by Sars-Cov-2 in space and time. As of January 2021 vaccination against COVID-19 already started, since the use of spatial clustering methods to identify non-vaccinated populations is not new among studies on vaccination coverage strategies, this paper also aims to discuss the implementation of spatial and spatio-temporal clustering methods in early vaccination. Elsevier Ltd. 2021-11 2021-10-25 /pmc/articles/PMC8545727/ /pubmed/34774258 http://dx.doi.org/10.1016/j.sste.2021.100461 Text en © 2021 Elsevier Ltd. All rights reserved. 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 Morais, Lucas Rabelo de Araújo Gomes, Gecynalda Soares da Silva Applying Spatio-temporal Scan Statistics and Spatial Autocorrelation Statistics to identify Covid-19 clusters in the world - A Vaccination Strategy? |
title | Applying Spatio-temporal Scan Statistics and Spatial Autocorrelation Statistics to identify Covid-19 clusters in the world - A Vaccination Strategy? |
title_full | Applying Spatio-temporal Scan Statistics and Spatial Autocorrelation Statistics to identify Covid-19 clusters in the world - A Vaccination Strategy? |
title_fullStr | Applying Spatio-temporal Scan Statistics and Spatial Autocorrelation Statistics to identify Covid-19 clusters in the world - A Vaccination Strategy? |
title_full_unstemmed | Applying Spatio-temporal Scan Statistics and Spatial Autocorrelation Statistics to identify Covid-19 clusters in the world - A Vaccination Strategy? |
title_short | Applying Spatio-temporal Scan Statistics and Spatial Autocorrelation Statistics to identify Covid-19 clusters in the world - A Vaccination Strategy? |
title_sort | applying spatio-temporal scan statistics and spatial autocorrelation statistics to identify covid-19 clusters in the world - a vaccination strategy? |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545727/ https://www.ncbi.nlm.nih.gov/pubmed/34774258 http://dx.doi.org/10.1016/j.sste.2021.100461 |
work_keys_str_mv | AT moraislucasrabelodearaujo applyingspatiotemporalscanstatisticsandspatialautocorrelationstatisticstoidentifycovid19clustersintheworldavaccinationstrategy AT gomesgecynaldasoaresdasilva applyingspatiotemporalscanstatisticsandspatialautocorrelationstatisticstoidentifycovid19clustersintheworldavaccinationstrategy |