Manifestation of GIS Tools for Spatial Pattern Distribution Analysis of Dengue Fever Epidemic in the City of Subang Jaya, Malaysia
Dengue has now emerged as one of the major public health problems in Malaysia. It was first reported in 1901 in Penang and since then the disease has become endemic concentrating mostly in urban areas. This study used the temporal-spatial model to determine high risk areas for dengue outbreak by mea...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Thai Society of Higher Eduction Institutes on Environment
2012-06-01
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| Series: | EnvironmentAsia |
| Subjects: | |
| Online Access: | http://www.tshe.org/ea/pdf/vol5%20no2%20p82-92.pdf |
| _version_ | 1828794874124566528 |
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| author | Nazri Che Dom Zulkiflee Abd Latif Abu Hassan Ahmad Rodziah Ismail Biswajeet Pradhan |
| author_facet | Nazri Che Dom Zulkiflee Abd Latif Abu Hassan Ahmad Rodziah Ismail Biswajeet Pradhan |
| author_sort | Nazri Che Dom |
| collection | DOAJ |
| description | Dengue has now emerged as one of the major public health problems in Malaysia. It was first reported in 1901 in Penang and since then the disease has become endemic concentrating mostly in urban areas. This study used the temporal-spatial model to determine high risk areas for dengue outbreak by measuring three temporal risk characteristics (i.e. frequency, duration and intensity) in order to define the severity and magnitude of outbreak transmission. This study examined a total of 4,651 confirmed dengue fever cases, geo-coded by address in the city of Subang Jaya between January 2006 and December 2009. The values of the three indices were considered high in a spatial unit when their standard values were positive. Measurement of the three temporal risk indices found that there were areas with significant high value for each of the temporal indices. This suggested that areas within Subang Jaya Municipality had different temporal characteristics for dengue occurrence. The utilization of three risk measures enabled to identify higher-risk areas for the occurrence of dengue fever. Even though case notification data are subjected to bias, this information is available in the health services and can lead to important conclusions, recommendations and hypotheses. As a recommendation, the temporal risk indices can be utilized by public health officials to characterize dengue rather than relying on the traditional case incidence data. |
| first_indexed | 2024-12-12T03:54:44Z |
| format | Article |
| id | doaj.art-25b5ed2ab7e5495db7a3ad98db513e14 |
| institution | Directory Open Access Journal |
| issn | 1906-1714 |
| language | English |
| last_indexed | 2024-12-12T03:54:44Z |
| publishDate | 2012-06-01 |
| publisher | Thai Society of Higher Eduction Institutes on Environment |
| record_format | Article |
| series | EnvironmentAsia |
| spelling | doaj.art-25b5ed2ab7e5495db7a3ad98db513e142022-12-22T00:39:17ZengThai Society of Higher Eduction Institutes on EnvironmentEnvironmentAsia1906-17142012-06-01528292Manifestation of GIS Tools for Spatial Pattern Distribution Analysis of Dengue Fever Epidemic in the City of Subang Jaya, MalaysiaNazri Che DomZulkiflee Abd LatifAbu Hassan AhmadRodziah IsmailBiswajeet PradhanDengue has now emerged as one of the major public health problems in Malaysia. It was first reported in 1901 in Penang and since then the disease has become endemic concentrating mostly in urban areas. This study used the temporal-spatial model to determine high risk areas for dengue outbreak by measuring three temporal risk characteristics (i.e. frequency, duration and intensity) in order to define the severity and magnitude of outbreak transmission. This study examined a total of 4,651 confirmed dengue fever cases, geo-coded by address in the city of Subang Jaya between January 2006 and December 2009. The values of the three indices were considered high in a spatial unit when their standard values were positive. Measurement of the three temporal risk indices found that there were areas with significant high value for each of the temporal indices. This suggested that areas within Subang Jaya Municipality had different temporal characteristics for dengue occurrence. The utilization of three risk measures enabled to identify higher-risk areas for the occurrence of dengue fever. Even though case notification data are subjected to bias, this information is available in the health services and can lead to important conclusions, recommendations and hypotheses. As a recommendation, the temporal risk indices can be utilized by public health officials to characterize dengue rather than relying on the traditional case incidence data.http://www.tshe.org/ea/pdf/vol5%20no2%20p82-92.pdfspatial pattern distributiondengue feverSubang JayaMalaysia |
| spellingShingle | Nazri Che Dom Zulkiflee Abd Latif Abu Hassan Ahmad Rodziah Ismail Biswajeet Pradhan Manifestation of GIS Tools for Spatial Pattern Distribution Analysis of Dengue Fever Epidemic in the City of Subang Jaya, Malaysia EnvironmentAsia spatial pattern distribution dengue fever Subang Jaya Malaysia |
| title | Manifestation of GIS Tools for Spatial Pattern Distribution Analysis of Dengue Fever Epidemic in the City of Subang Jaya, Malaysia |
| title_full | Manifestation of GIS Tools for Spatial Pattern Distribution Analysis of Dengue Fever Epidemic in the City of Subang Jaya, Malaysia |
| title_fullStr | Manifestation of GIS Tools for Spatial Pattern Distribution Analysis of Dengue Fever Epidemic in the City of Subang Jaya, Malaysia |
| title_full_unstemmed | Manifestation of GIS Tools for Spatial Pattern Distribution Analysis of Dengue Fever Epidemic in the City of Subang Jaya, Malaysia |
| title_short | Manifestation of GIS Tools for Spatial Pattern Distribution Analysis of Dengue Fever Epidemic in the City of Subang Jaya, Malaysia |
| title_sort | manifestation of gis tools for spatial pattern distribution analysis of dengue fever epidemic in the city of subang jaya malaysia |
| topic | spatial pattern distribution dengue fever Subang Jaya Malaysia |
| url | http://www.tshe.org/ea/pdf/vol5%20no2%20p82-92.pdf |
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