A new hybrid model of dengue incidence rate using negative binomial generalised additive model and fuzzy c-means model: a case study in Selangor

Dengue is one of the top reason for illness and mortality in the world with beyond onethird of the world's population living in the risk areas of dengue infection. In this study, there are five stages to achieve the research objectives. Firstly, the verification of predetem1ined variables. Sec...

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Main Author:	Mohamad, Nazeera
Format:	Thesis
Language:	English English English
Published:	2018
Subjects:	RC Internal medicine RC109-216 Infectious and parasitic diseases
Online Access:	http://eprints.uthm.edu.my/7517/2/24p%20NAZEERA%20MOHAMAD.pdf http://eprints.uthm.edu.my/7517/1/NAZEERA%20MOHAMAD%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/7517/3/NAZEERA%20MOHAMAD%20WATERMARK.pdf
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spelling	my-uthm-ep.75172022-08-15T03:07:53Z A new hybrid model of dengue incidence rate using negative binomial generalised additive model and fuzzy c-means model: a case study in Selangor 2018-08 Mohamad, Nazeera RC Internal medicine RC109-216 Infectious and parasitic diseases Dengue is one of the top reason for illness and mortality in the world with beyond onethird of the world's population living in the risk areas of dengue infection. In this study, there are five stages to achieve the research objectives. Firstly, the verification of predetem1ined variables. Secondly, the identification of new datasets after clustered by district and Fuzzy C-Means Model (FCM). Thirdly, the development of models using the existing dataset and the new datasets which clustered by the two different clustering categories. Then, to assess the models developed by using three measurement methods which are deviance (D), Akaike Jnfonnation Criteria (AIC) and Bayesian Infonnation Criteria (BIC} Lastly, the validation of model developed by comparing the value of D, AIC and BIC between the existing model and the new models developed which used the new datasets. There are two different clustering techniques applied which are clustering the data by district and by FCM. This study proposed a new modelling hybrid framework by using two statistical models which are FCM and negative binomial Generalised Additive Model (GAM). This study successfully presents the significant difference in the climatic and non-climatic factors that influenced dengue incidence rate (DIR) in Selangor, Malaysia. Results show that the climatic factors such as rainfall with current month up to 3 months and number of rainy days with current month up to lag 3 months are significant to DIR. Besides, the interaction between rainfall and number of rainy days also shows strong positive relationship to DIR. Meanwhile, non-climatic vaiiables such as population density, number of locality and lag DIR from I month until 3 months also show significant relationship towards DIR For both clustering techniques, there are two clusters fonned and there are four new models developed in this study. After comparing the values of D, AIC ai1d BIC between the existing model and the new models, this study concluded that four new models recorded lower values compared to the existing model. Therefore, the four new models are selected to present the dengue incidence in Selangor. 2018-08 Thesis http://eprints.uthm.edu.my/7517/ http://eprints.uthm.edu.my/7517/2/24p%20NAZEERA%20MOHAMAD.pdf text en public http://eprints.uthm.edu.my/7517/1/NAZEERA%20MOHAMAD%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/7517/3/NAZEERA%20MOHAMAD%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Fakulti Sains Gunaan dan Teknologi
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	RC Internal medicine RC109-216 Infectious and parasitic diseases
spellingShingle	RC Internal medicine RC109-216 Infectious and parasitic diseases Mohamad, Nazeera A new hybrid model of dengue incidence rate using negative binomial generalised additive model and fuzzy c-means model: a case study in Selangor
description	Dengue is one of the top reason for illness and mortality in the world with beyond onethird of the world's population living in the risk areas of dengue infection. In this study, there are five stages to achieve the research objectives. Firstly, the verification of predetem1ined variables. Secondly, the identification of new datasets after clustered by district and Fuzzy C-Means Model (FCM). Thirdly, the development of models using the existing dataset and the new datasets which clustered by the two different clustering categories. Then, to assess the models developed by using three measurement methods which are deviance (D), Akaike Jnfonnation Criteria (AIC) and Bayesian Infonnation Criteria (BIC} Lastly, the validation of model developed by comparing the value of D, AIC and BIC between the existing model and the new models developed which used the new datasets. There are two different clustering techniques applied which are clustering the data by district and by FCM. This study proposed a new modelling hybrid framework by using two statistical models which are FCM and negative binomial Generalised Additive Model (GAM). This study successfully presents the significant difference in the climatic and non-climatic factors that influenced dengue incidence rate (DIR) in Selangor, Malaysia. Results show that the climatic factors such as rainfall with current month up to 3 months and number of rainy days with current month up to lag 3 months are significant to DIR. Besides, the interaction between rainfall and number of rainy days also shows strong positive relationship to DIR. Meanwhile, non-climatic vaiiables such as population density, number of locality and lag DIR from I month until 3 months also show significant relationship towards DIR For both clustering techniques, there are two clusters fonned and there are four new models developed in this study. After comparing the values of D, AIC ai1d BIC between the existing model and the new models, this study concluded that four new models recorded lower values compared to the existing model. Therefore, the four new models are selected to present the dengue incidence in Selangor.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Mohamad, Nazeera
author_facet	Mohamad, Nazeera
author_sort	Mohamad, Nazeera
title	A new hybrid model of dengue incidence rate using negative binomial generalised additive model and fuzzy c-means model: a case study in Selangor
title_short	A new hybrid model of dengue incidence rate using negative binomial generalised additive model and fuzzy c-means model: a case study in Selangor
title_full	A new hybrid model of dengue incidence rate using negative binomial generalised additive model and fuzzy c-means model: a case study in Selangor
title_fullStr	A new hybrid model of dengue incidence rate using negative binomial generalised additive model and fuzzy c-means model: a case study in Selangor
title_full_unstemmed	A new hybrid model of dengue incidence rate using negative binomial generalised additive model and fuzzy c-means model: a case study in Selangor
title_sort	new hybrid model of dengue incidence rate using negative binomial generalised additive model and fuzzy c-means model: a case study in selangor
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Sains Gunaan dan Teknologi
publishDate	2018
url	http://eprints.uthm.edu.my/7517/2/24p%20NAZEERA%20MOHAMAD.pdf http://eprints.uthm.edu.my/7517/1/NAZEERA%20MOHAMAD%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/7517/3/NAZEERA%20MOHAMAD%20WATERMARK.pdf
_version_	1747831162432126976

A new hybrid model of dengue incidence rate using negative binomial generalised additive model and fuzzy c-means model: a case study in Selangor

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