An Eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in Khyber-Pakhtunkhwa, Pakistan

Identifying the abnormally high-risk regions in a spatiotemporal space that contains an unexpected disease count is helpful to conduct surveillance and implement control strategies. The EigenSpot algorithm has been recently proposed for detecting space-time disease clusters of arbitrary shapes with...

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Detalles Bibliográficos
Autores principales: Ullah, Sami, Daud, Hanita, Dass, Sarat C., Fanaee-T, Hadi, Khalil, Alamgir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6007829/
https://www.ncbi.nlm.nih.gov/pubmed/29920540
http://dx.doi.org/10.1371/journal.pone.0199176

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6007829/
https://www.ncbi.nlm.nih.gov/pubmed/29920540
http://dx.doi.org/10.1371/journal.pone.0199176

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