A spatial-temporal study of dengue in Peninsular Malaysia for the year 2017 in two different space-time model

© 2019 Informa UK Limited, trading as Taylor & Francis Group.

Bibliographische Detailangaben
Veröffentlicht in:Journal of applied statistics. - 1991. - 47(2020), 4 vom: 09., Seite 739-756
1. Verfasser: Abd Naeeim, Nurul Syafiah (VerfasserIn)
Weitere Verfasser: Abdul Rahman, Nuzlinda, Muhammad Fahimi, Fatin Afiqah
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2020
Zugriff auf das übergeordnete Werk:Journal of applied statistics
Schlagworte:Journal Article Bayesian estimation Disease mapping INLA SPDE dengue
LEADER 01000naa a22002652 4500
001 NLM342288806
003 DE-627
005 20231226013746.0
007 cr uuu---uuuuu
008 231226s2020 xx |||||o 00| ||eng c
024 7 |a 10.1080/02664763.2019.1648391  |2 doi 
028 5 2 |a pubmed24n1140.xml 
035 |a (DE-627)NLM342288806 
035 |a (NLM)35707492 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Abd Naeeim, Nurul Syafiah  |e verfasserin  |4 aut 
245 1 2 |a A spatial-temporal study of dengue in Peninsular Malaysia for the year 2017 in two different space-time model 
264 1 |c 2020 
336 |a Text  |b txt  |2 rdacontent 
337 |a ƒaComputermedien  |b c  |2 rdamedia 
338 |a ƒa Online-Ressource  |b cr  |2 rdacarrier 
500 |a Date Revised 16.07.2022 
500 |a published: Electronic-eCollection 
500 |a Citation Status PubMed-not-MEDLINE 
520 |a © 2019 Informa UK Limited, trading as Taylor & Francis Group. 
520 |a Spatio-temporal disease mapping models give a great worth in epidemiology, especially in describing the pattern of disease incidence across geographical space and time. This paper analyses the spatial and temporal variability of dengue disease rates based on generalized linear mixed models. For spatio-temporal study, the models incorporate spatially correlated random effects as well as temporal effects. In this study, two different spatial random effects are applied and compared. The first model is based on Leroux spatial model, while the second model is based on the stochastic partial differential equation approach. For the temporal effects, both models follow an autoregressive model of first-order model. The models are fitted within a hierarchical Bayesian framework with integrated nested Laplace approximation methodology. The main objective of this study is to compare both spatio-temporal models in terms of their ability in representing the disease phenomenon. The models are applied to weekly dengue fever data in Peninsular Malaysia reported to the Ministry of Health Malaysia in the year 2017 according to the district level 
650 4 |a Journal Article 
650 4 |a Bayesian estimation 
650 4 |a Disease mapping 
650 4 |a INLA 
650 4 |a SPDE 
650 4 |a dengue 
700 1 |a Abdul Rahman, Nuzlinda  |e verfasserin  |4 aut 
700 1 |a Muhammad Fahimi, Fatin Afiqah  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t Journal of applied statistics  |d 1991  |g 47(2020), 4 vom: 09., Seite 739-756  |w (DE-627)NLM098188178  |x 0266-4763  |7 nnns 
773 1 8 |g volume:47  |g year:2020  |g number:4  |g day:09  |g pages:739-756 
856 4 0 |u http://dx.doi.org/10.1080/02664763.2019.1648391  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 47  |j 2020  |e 4  |b 09  |h 739-756