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Stage 1 registered report: spatiotemporal patterns of the COVID-19 epidemic in Mexico at the municipality level

In this stage 1 registered report, we propose an analysis of the spatio-temporal patterns of the COVID-19 epidemic in Mexico using the georeferenced confirmed cases aggregated at the municipality level. We will compute weekly Moran index to assess spatial autocorrelation over time and identify clust...

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Autor principal: Mas, Jean-François
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7869664/
https://www.ncbi.nlm.nih.gov/pubmed/33604169
http://dx.doi.org/10.7717/peerj.10622
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author Mas, Jean-François
author_facet Mas, Jean-François
author_sort Mas, Jean-François
collection PubMed
description In this stage 1 registered report, we propose an analysis of the spatio-temporal patterns of the COVID-19 epidemic in Mexico using the georeferenced confirmed cases aggregated at the municipality level. We will compute weekly Moran index to assess spatial autocorrelation over time and identify clusters of the disease using the “flexibly shaped spatial scan” approach. Finally, different distance models will be compared to select the best suited to predict inter-municipality contagion. This study will help us understand the spread of the epidemic over the Mexican territory and give insights to model and predict the epidemic behavior.
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spelling pubmed-78696642021-02-17 Stage 1 registered report: spatiotemporal patterns of the COVID-19 epidemic in Mexico at the municipality level Mas, Jean-François PeerJ Epidemiology In this stage 1 registered report, we propose an analysis of the spatio-temporal patterns of the COVID-19 epidemic in Mexico using the georeferenced confirmed cases aggregated at the municipality level. We will compute weekly Moran index to assess spatial autocorrelation over time and identify clusters of the disease using the “flexibly shaped spatial scan” approach. Finally, different distance models will be compared to select the best suited to predict inter-municipality contagion. This study will help us understand the spread of the epidemic over the Mexican territory and give insights to model and predict the epidemic behavior. PeerJ Inc. 2021-02-05 /pmc/articles/PMC7869664/ /pubmed/33604169 http://dx.doi.org/10.7717/peerj.10622 Text en © 2021 Mas https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Epidemiology
Mas, Jean-François
Stage 1 registered report: spatiotemporal patterns of the COVID-19 epidemic in Mexico at the municipality level
title Stage 1 registered report: spatiotemporal patterns of the COVID-19 epidemic in Mexico at the municipality level
title_full Stage 1 registered report: spatiotemporal patterns of the COVID-19 epidemic in Mexico at the municipality level
title_fullStr Stage 1 registered report: spatiotemporal patterns of the COVID-19 epidemic in Mexico at the municipality level
title_full_unstemmed Stage 1 registered report: spatiotemporal patterns of the COVID-19 epidemic in Mexico at the municipality level
title_short Stage 1 registered report: spatiotemporal patterns of the COVID-19 epidemic in Mexico at the municipality level
title_sort stage 1 registered report: spatiotemporal patterns of the covid-19 epidemic in mexico at the municipality level
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7869664/
https://www.ncbi.nlm.nih.gov/pubmed/33604169
http://dx.doi.org/10.7717/peerj.10622
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