Cargando…

Bayesian Spatial Survival Models for Hospitalisation of Dengue: A Case Study of Wahidin Hospital in Makassar, Indonesia

Spatial models are becoming more popular in time-to-event data analysis. Commonly, the intrinsic conditional autoregressive prior is placed on an area level frailty term to allow for correlation between areas. We considered a range of Bayesian Weibull and Cox semiparametric spatial models to describ...

Descripción completa

Detalles Bibliográficos
Autores principales: Aswi, Aswi, Cramb, Susanna, Duncan, Earl, Hu, Wenbiao, White, Gentry, Mengersen, Kerrie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7037865/
https://www.ncbi.nlm.nih.gov/pubmed/32019262
http://dx.doi.org/10.3390/ijerph17030878
_version_ 1783500521506603008
author Aswi, Aswi
Cramb, Susanna
Duncan, Earl
Hu, Wenbiao
White, Gentry
Mengersen, Kerrie
author_facet Aswi, Aswi
Cramb, Susanna
Duncan, Earl
Hu, Wenbiao
White, Gentry
Mengersen, Kerrie
author_sort Aswi, Aswi
collection PubMed
description Spatial models are becoming more popular in time-to-event data analysis. Commonly, the intrinsic conditional autoregressive prior is placed on an area level frailty term to allow for correlation between areas. We considered a range of Bayesian Weibull and Cox semiparametric spatial models to describe a dataset on hospitalisation of dengue. This paper aimed to extend these two models, to evaluate the suitability of these models for estimation and prediction of the length of stay, compare different spatial priors, and determine factors that significantly affect the duration of hospital stay for dengue fever patients in the case study location, namely Wahidin hospital in Makassar, Indonesia. We compared two different models with three different spatial priors with respect to goodness of fit and generalisability. For all models considered, the Leroux prior was preferred over the intrinsic conditional autoregressive and independent priors, but Cox and Weibull versions had similar predictive performance, model fit, and results. Age and platelet count were negatively associated with the length of stay, while red blood cell count was positively associated with the length of stay of dengue patients at this hospital. Using appropriate Bayesian spatial survival models enables identification of factors that substantively affect the length of stay.
format Online
Article
Text
id pubmed-7037865
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-70378652020-03-10 Bayesian Spatial Survival Models for Hospitalisation of Dengue: A Case Study of Wahidin Hospital in Makassar, Indonesia Aswi, Aswi Cramb, Susanna Duncan, Earl Hu, Wenbiao White, Gentry Mengersen, Kerrie Int J Environ Res Public Health Article Spatial models are becoming more popular in time-to-event data analysis. Commonly, the intrinsic conditional autoregressive prior is placed on an area level frailty term to allow for correlation between areas. We considered a range of Bayesian Weibull and Cox semiparametric spatial models to describe a dataset on hospitalisation of dengue. This paper aimed to extend these two models, to evaluate the suitability of these models for estimation and prediction of the length of stay, compare different spatial priors, and determine factors that significantly affect the duration of hospital stay for dengue fever patients in the case study location, namely Wahidin hospital in Makassar, Indonesia. We compared two different models with three different spatial priors with respect to goodness of fit and generalisability. For all models considered, the Leroux prior was preferred over the intrinsic conditional autoregressive and independent priors, but Cox and Weibull versions had similar predictive performance, model fit, and results. Age and platelet count were negatively associated with the length of stay, while red blood cell count was positively associated with the length of stay of dengue patients at this hospital. Using appropriate Bayesian spatial survival models enables identification of factors that substantively affect the length of stay. MDPI 2020-01-30 2020-02 /pmc/articles/PMC7037865/ /pubmed/32019262 http://dx.doi.org/10.3390/ijerph17030878 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Aswi, Aswi
Cramb, Susanna
Duncan, Earl
Hu, Wenbiao
White, Gentry
Mengersen, Kerrie
Bayesian Spatial Survival Models for Hospitalisation of Dengue: A Case Study of Wahidin Hospital in Makassar, Indonesia
title Bayesian Spatial Survival Models for Hospitalisation of Dengue: A Case Study of Wahidin Hospital in Makassar, Indonesia
title_full Bayesian Spatial Survival Models for Hospitalisation of Dengue: A Case Study of Wahidin Hospital in Makassar, Indonesia
title_fullStr Bayesian Spatial Survival Models for Hospitalisation of Dengue: A Case Study of Wahidin Hospital in Makassar, Indonesia
title_full_unstemmed Bayesian Spatial Survival Models for Hospitalisation of Dengue: A Case Study of Wahidin Hospital in Makassar, Indonesia
title_short Bayesian Spatial Survival Models for Hospitalisation of Dengue: A Case Study of Wahidin Hospital in Makassar, Indonesia
title_sort bayesian spatial survival models for hospitalisation of dengue: a case study of wahidin hospital in makassar, indonesia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7037865/
https://www.ncbi.nlm.nih.gov/pubmed/32019262
http://dx.doi.org/10.3390/ijerph17030878
work_keys_str_mv AT aswiaswi bayesianspatialsurvivalmodelsforhospitalisationofdengueacasestudyofwahidinhospitalinmakassarindonesia
AT crambsusanna bayesianspatialsurvivalmodelsforhospitalisationofdengueacasestudyofwahidinhospitalinmakassarindonesia
AT duncanearl bayesianspatialsurvivalmodelsforhospitalisationofdengueacasestudyofwahidinhospitalinmakassarindonesia
AT huwenbiao bayesianspatialsurvivalmodelsforhospitalisationofdengueacasestudyofwahidinhospitalinmakassarindonesia
AT whitegentry bayesianspatialsurvivalmodelsforhospitalisationofdengueacasestudyofwahidinhospitalinmakassarindonesia
AT mengersenkerrie bayesianspatialsurvivalmodelsforhospitalisationofdengueacasestudyofwahidinhospitalinmakassarindonesia