eprintid: 10327
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/03/27
datestamp: 2023-11-09 16:36:57
lastmod: 2023-11-09 16:36:57
status_changed: 2023-11-09 16:31:08
type: article
metadata_visibility: show
creators_name: Thiruchelvam, L.
creators_name: Dass, S.C.
creators_name: Zaki, R.
creators_name: Yahya, A.
creators_name: Asirvadam, V.S.
title: Correlation analysis of air pollutant index levels and dengue cases across five different zones in Selangor, Malaysia
ispublished: pub
keywords: air pollutant; analysis; Bayes theorem; dengue; Malaysia; spatial analysis; statistical model, Air Pollutants; Bayes Theorem; Dengue; Malaysia; Models, Statistical; Spatial Analysis
note: cited By 8
abstract: This study investigated the potential relationship between dengue cases and air quality � as measured by the Air Pollution Index (API) for five zones in the state of Selangor, Malaysia. Dengue case patterns can be learned using prediction models based on feedback (lagged terms). However, the question whether air quality affects dengue cases is still not thoroughly investigated based on such feedback models. This work developed dengue prediction models using the autoregressive integrated moving average (ARIMA) and ARIMA with an exogeneous variable (ARIMAX) time series methodologies with API as the exogeneous variable. The Box Jenkins (BJ) approach based on maximum likelihood was used for analysis as it gives effective model estimates and prediction. Three stages of model comparison were carried out for each zone: first with ARIMA models without API, then ARIMAX models with API data from the API station for that zone and finally, ARIMAX models with API data from the zone and spatially neighbouring zones. Bayesian Information Criterion (BIC) gives goodness-of-fit versus parsimony comparisons between all elicited models. Our study found that ARIMA models, with the lowest BIC value, outperformed the rest in all five zones. The BIC values for the zone of Kuala Selangor were �800.66, � 796.22, and �790.5229, respectively, for ARIMA only, ARIMAX with single API component and ARIMAX with API components from its zone and spatially neighbouring zones. Therefore, we concluded that API levels, either temporally for each zone or spatio-temporally based on neighbouring zones, do not have a significant effect on dengue cases. © L. Thiruchelvam et al.
date: 2018
publisher: Page Press Publications
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046792597&doi=10.4081%2fgh.2018.613&partnerID=40&md5=edc40df3bbca66ce09f265fa98434186
id_number: 10.4081/gh.2018.613
full_text_status: none
publication: Geospatial Health
volume: 13
number: 1
pagerange: 102-109
refereed: TRUE
issn: 18271987
citation:   Thiruchelvam, L. and Dass, S.C. and Zaki, R. and Yahya, A. and Asirvadam, V.S.  (2018) Correlation analysis of air pollutant index levels and dengue cases across five different zones in Selangor, Malaysia.  Geospatial Health, 13 (1).  pp. 102-109.  ISSN 18271987