Stage 1 registered report: spatiotemporal patterns of the COVID-19 epidemic in Mexico at the municipality level.
COVID-19
Clusters
GIS
SARS-CoV-2 pandemic
Spatial analysis
Spatial autocorrelation
Spatial modeling
Spatial patterns
Journal
PeerJ
ISSN: 2167-8359
Titre abrégé: PeerJ
Pays: United States
ID NLM: 101603425
Informations de publication
Date de publication:
2021
2021
Historique:
received:
21
08
2020
accepted:
30
11
2020
entrez:
19
2
2021
pubmed:
20
2
2021
medline:
20
2
2021
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 33604169
doi: 10.7717/peerj.10622
pii: 10622
pmc: PMC7869664
doi:
Types de publication
Journal Article
Langues
eng
Pagination
e10622Informations de copyright
© 2021 Mas.
Déclaration de conflit d'intérêts
The author declares that they have no competing interests.
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