Bayesian Spatio-Temporal Modeling of the Dynamics of COVID-19 Deaths in Peru
Amid the COVID-19 pandemic, understanding the spatial and temporal dynamics of the disease is crucial for effective public health interventions. This study aims to analyze COVID-19 data in Peru using a Bayesian spatio-temporal generalized linear model to elucidate mortality patterns and assess the i...
Guardado en:
| Autores principales: | , , , , , |
|---|---|
| Formato: | Artículo |
| Lenguaje: | inglés |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | Ver en el sistema de origen Ver en el sistema de origen Enlace permanente (DOI o Handle) Enlace permanente (DOI o Handle) |
| Etiquetas: |
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1881508988436086784 |
|---|---|
| author | Castro Galarza, César Raúl Díaz Sánchez, Omar Nolberto Pimentel, Jonatha Sousa Bulhões, Rodrigo López Gonzales, Javier Linkolk Rodrigues, Paulo Canas |
| author_browse | Bulhões, Rodrigo Castro Galarza, César Raúl Díaz Sánchez, Omar Nolberto López Gonzales, Javier Linkolk Pimentel, Jonatha Sousa Rodrigues, Paulo Canas |
| author_facet | Castro Galarza, César Raúl Díaz Sánchez, Omar Nolberto Pimentel, Jonatha Sousa Bulhões, Rodrigo López Gonzales, Javier Linkolk Rodrigues, Paulo Canas |
| author_sort | Castro Galarza, César Raúl |
| collection | Producción científica |
| description | Amid the COVID-19 pandemic, understanding the spatial and temporal dynamics of the disease is crucial for effective public health interventions. This study aims to analyze COVID-19 data in Peru using a Bayesian spatio-temporal generalized linear model to elucidate mortality patterns and assess the impact of vaccination efforts. Leveraging data from 194 provinces over 651 days, our analysis reveals heterogeneous spatial and temporal patterns in COVID-19 mortality rates. Higher vaccination coverage is associated with reduced mortality rates, emphasizing the importance of vaccination in mitigating the pandemic's impact. The findings underscore the value of spatio-temporal data analysis in understanding disease dynamics and guiding targeted public health interventions. |
| format | Article |
| id | oai:cris.upeu.edu.pe:20.500.15037/417 |
| institution | UPeU |
| language | English |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| record_format | dspace |
| spelling | oai:cris.upeu.edu.pe:20.500.15037/4172026-10-30T16:14:37ZBayesian Spatio-Temporal Modeling of the Dynamics of COVID-19 Deaths in PeruCastro Galarza, César RaúlDíaz Sánchez, Omar NolbertoPimentel, Jonatha SousaBulhões, RodrigoLópez Gonzales, Javier LinkolkRodrigues, Paulo CanasBayesian StatisticsSpatio-temporal ModelingCovid-19Areal Unit DataSpatio-temporal Generalized Linear ModelAmid the COVID-19 pandemic, understanding the spatial and temporal dynamics of the disease is crucial for effective public health interventions. This study aims to analyze COVID-19 data in Peru using a Bayesian spatio-temporal generalized linear model to elucidate mortality patterns and assess the impact of vaccination efforts. Leveraging data from 194 provinces over 651 days, our analysis reveals heterogeneous spatial and temporal patterns in COVID-19 mortality rates. Higher vaccination coverage is associated with reduced mortality rates, emphasizing the importance of vaccination in mitigating the pandemic's impact. The findings underscore the value of spatio-temporal data analysis in understanding disease dynamics and guiding targeted public health interventions.Articlehttps://pubmed.ncbi.nlm.nih.gov/38920483https://www.mdpi.com/1099-4300/26/6/474/pdf?version=1717058501https://doi.org/10.3390/e26060474PMC1120242010.3390/e26060474https://hdl.handle.net/20.500.15037/41738920483W4399157280enEntropy1099-43002024-05-302026-06-13T08:13:07Z2026-06-13T08:13:07Z |
| spellingShingle | Bayesian Statistics Spatio-temporal Modeling Covid-19 Areal Unit Data Spatio-temporal Generalized Linear Model Castro Galarza, César Raúl Díaz Sánchez, Omar Nolberto Pimentel, Jonatha Sousa Bulhões, Rodrigo López Gonzales, Javier Linkolk Rodrigues, Paulo Canas Bayesian Spatio-Temporal Modeling of the Dynamics of COVID-19 Deaths in Peru |
| title | Bayesian Spatio-Temporal Modeling of the Dynamics of COVID-19 Deaths in Peru |
| title_full | Bayesian Spatio-Temporal Modeling of the Dynamics of COVID-19 Deaths in Peru |
| title_fullStr | Bayesian Spatio-Temporal Modeling of the Dynamics of COVID-19 Deaths in Peru |
| title_full_unstemmed | Bayesian Spatio-Temporal Modeling of the Dynamics of COVID-19 Deaths in Peru |
| title_short | Bayesian Spatio-Temporal Modeling of the Dynamics of COVID-19 Deaths in Peru |
| title_sort | bayesian spatio temporal modeling of the dynamics of covid 19 deaths in peru |
| topic | Bayesian Statistics Spatio-temporal Modeling Covid-19 Areal Unit Data Spatio-temporal Generalized Linear Model |
| topic_facet | Bayesian Statistics Spatio-temporal Modeling Covid-19 Areal Unit Data Spatio-temporal Generalized Linear Model |
| url | https://pubmed.ncbi.nlm.nih.gov/38920483 https://www.mdpi.com/1099-4300/26/6/474/pdf?version=1717058501 https://doi.org/10.3390/e26060474 https://hdl.handle.net/20.500.15037/417 |
| work_keys_str_mv | AT castrogalarzacesarraul bayesianspatiotemporalmodelingofthedynamicsofcovid19deathsinperu AT diazsanchezomarnolberto bayesianspatiotemporalmodelingofthedynamicsofcovid19deathsinperu AT pimenteljonathasousa bayesianspatiotemporalmodelingofthedynamicsofcovid19deathsinperu AT bulhoesrodrigo bayesianspatiotemporalmodelingofthedynamicsofcovid19deathsinperu AT lopezgonzalesjavierlinkolk bayesianspatiotemporalmodelingofthedynamicsofcovid19deathsinperu AT rodriguespaulocanas bayesianspatiotemporalmodelingofthedynamicsofcovid19deathsinperu |