A hybrid model for forecasting communicable diseases in Maldives

The Maldives is an island nation and the islands are scattered over 26 atolls. The government of Maldives is trying to improve health services in the country and improve the accessibility of services throughout the country at the peripheral levels. The healthcare industry collects a large amount of...

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Main Authors: Rad, Babak Bashari, Shareef, Ali Aseel, Thiruchelvam, Vinesh, Afshar, Andia, Bamiah, Mervat Adib
Format: Article
Published: Taylor's University 2018
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Online Access:http://eprints.um.edu.my/20999/
http://jestec.taylors.edu.my/Special%20Issue%20ICCSIT%202018/ICCSIT18_01.pdf
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Institution: Universiti Malaya
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spelling my.um.eprints.209992019-04-18T03:18:38Z http://eprints.um.edu.my/20999/ A hybrid model for forecasting communicable diseases in Maldives Rad, Babak Bashari Shareef, Ali Aseel Thiruchelvam, Vinesh Afshar, Andia Bamiah, Mervat Adib R Medicine The Maldives is an island nation and the islands are scattered over 26 atolls. The government of Maldives is trying to improve health services in the country and improve the accessibility of services throughout the country at the peripheral levels. The healthcare industry collects a large amount of healthcare information, which contains several patterns, such as outbreaks of diseases. However, this data frequently goes unexploited. Accurate forecasting using this past data could help healthcare managers in taking appropriate decisions especially in implementing preventing measures. Due to the geographical nature of Maldives, it is difficult to implement preventive measures in case of an outbreak. There is no single approach to be used for health forecasting; thus, various methods have been used to specific health conditions or healthcare resources. Healthcare comprises of both complex linear and nonlinear patterns, which can affect the forecasting accuracy if only linear models or neural networks are used. In this research, a hybrid of the ARIMA model and Neural Network has been proposed to forecast healthcare data. A dataset comprising of 10 diseases including unique cases reported for each disease, between the years 2012 and 2016 have been used in this research. It was found that the proposed model performed well on 7 out of the 10 diseases. Taylor's University 2018 Article PeerReviewed Rad, Babak Bashari and Shareef, Ali Aseel and Thiruchelvam, Vinesh and Afshar, Andia and Bamiah, Mervat Adib (2018) A hybrid model for forecasting communicable diseases in Maldives. Journal of Engineering Science and Technology, 13. pp. 1-13. ISSN 1823-4690 http://jestec.taylors.edu.my/Special%20Issue%20ICCSIT%202018/ICCSIT18_01.pdf
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic R Medicine
spellingShingle R Medicine
Rad, Babak Bashari
Shareef, Ali Aseel
Thiruchelvam, Vinesh
Afshar, Andia
Bamiah, Mervat Adib
A hybrid model for forecasting communicable diseases in Maldives
description The Maldives is an island nation and the islands are scattered over 26 atolls. The government of Maldives is trying to improve health services in the country and improve the accessibility of services throughout the country at the peripheral levels. The healthcare industry collects a large amount of healthcare information, which contains several patterns, such as outbreaks of diseases. However, this data frequently goes unexploited. Accurate forecasting using this past data could help healthcare managers in taking appropriate decisions especially in implementing preventing measures. Due to the geographical nature of Maldives, it is difficult to implement preventive measures in case of an outbreak. There is no single approach to be used for health forecasting; thus, various methods have been used to specific health conditions or healthcare resources. Healthcare comprises of both complex linear and nonlinear patterns, which can affect the forecasting accuracy if only linear models or neural networks are used. In this research, a hybrid of the ARIMA model and Neural Network has been proposed to forecast healthcare data. A dataset comprising of 10 diseases including unique cases reported for each disease, between the years 2012 and 2016 have been used in this research. It was found that the proposed model performed well on 7 out of the 10 diseases.
format Article
author Rad, Babak Bashari
Shareef, Ali Aseel
Thiruchelvam, Vinesh
Afshar, Andia
Bamiah, Mervat Adib
author_facet Rad, Babak Bashari
Shareef, Ali Aseel
Thiruchelvam, Vinesh
Afshar, Andia
Bamiah, Mervat Adib
author_sort Rad, Babak Bashari
title A hybrid model for forecasting communicable diseases in Maldives
title_short A hybrid model for forecasting communicable diseases in Maldives
title_full A hybrid model for forecasting communicable diseases in Maldives
title_fullStr A hybrid model for forecasting communicable diseases in Maldives
title_full_unstemmed A hybrid model for forecasting communicable diseases in Maldives
title_sort hybrid model for forecasting communicable diseases in maldives
publisher Taylor's University
publishDate 2018
url http://eprints.um.edu.my/20999/
http://jestec.taylors.edu.my/Special%20Issue%20ICCSIT%202018/ICCSIT18_01.pdf
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