Mapping ex ante risks of COVID‐19 in Indonesia using a Bayesian geostatistical model on airport network data

A rapid response to global infectious disease outbreaks is crucial to protect public health. Ex ante information on the spatial probability distribution of early infections can guide governments to better target protection efforts. We propose a two‐stage statistical approach to spatially map the ex...

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Detalles Bibliográficos
Autores principales: Seufert, Jacqueline D., Python, Andre, Weisser, Christoph, Cisneros, Elías, Kis‐Katos, Krisztina, Kneib, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9350309/
https://www.ncbi.nlm.nih.gov/pubmed/35942194
http://dx.doi.org/10.1111/rssa.12866

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9350309/
https://www.ncbi.nlm.nih.gov/pubmed/35942194
http://dx.doi.org/10.1111/rssa.12866

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