Modeling Spatio-temporal Malaria Risk Using Remote Sensing and Environmental Factors
Background: Remote sensing have been intensively used across many disciplines, however, such information was limited in spatial epidemiology. Methods: Two years (2009 & 2010) Landsat TM satellite data was used to develop vegetation, water bodies, air temperature and humidity criterion maps to...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Tehran University of Medical Sciences
2018-08-01
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| Series: | Iranian Journal of Public Health |
| Subjects: | |
| Online Access: | https://ijph.tums.ac.ir/index.php/ijph/article/view/14580 |
| _version_ | 1811189465081708544 |
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| author | Muhammad Haris MAZHER Javed IQBAL Muhammad Ahsan MAHBOOB Iqra ATIF |
| author_facet | Muhammad Haris MAZHER Javed IQBAL Muhammad Ahsan MAHBOOB Iqra ATIF |
| author_sort | Muhammad Haris MAZHER |
| collection | DOAJ |
| description | Background: Remote sensing have been intensively used across many disciplines, however, such information was limited in spatial epidemiology.
Methods: Two years (2009 & 2010) Landsat TM satellite data was used to develop vegetation, water bodies, air temperature and humidity criterion maps to model malaria risk and its spatiotemporal seasonal variation. The criterion maps were used in weighted overlay analysis to generate final categorized malaria risk map.
Results: Overall, 25%, 68%, 18% and 16% of the total area of Rawalpindi region was categorized as danger zone for Jun 2009, Oct 2009, Jan 2010 and Jun 2010, respectively. The malaria risk reached at its peak during the monsoon season whereas air temperature and relative humidity were the main contributing factors in seasonal variation.
Conclusion: Malaria risk maps could be used for prioritizing areas for malaria control measures. |
| first_indexed | 2024-04-11T14:36:20Z |
| format | Article |
| id | doaj.art-7b4001a8db944802a2676cb60ade24f6 |
| institution | Directory Open Access Journal |
| issn | 2251-6085 2251-6093 |
| language | English |
| last_indexed | 2024-04-11T14:36:20Z |
| publishDate | 2018-08-01 |
| publisher | Tehran University of Medical Sciences |
| record_format | Article |
| series | Iranian Journal of Public Health |
| spelling | doaj.art-7b4001a8db944802a2676cb60ade24f62022-12-22T04:18:19ZengTehran University of Medical SciencesIranian Journal of Public Health2251-60852251-60932018-08-01479Modeling Spatio-temporal Malaria Risk Using Remote Sensing and Environmental FactorsMuhammad Haris MAZHER0Javed IQBAL1Muhammad Ahsan MAHBOOB2Iqra ATIF3Institute of Geographic Information Systems, School of Civil and Environmental Engineering, National University of Sciences and Technology, Islamabad, PakistanInstitute of Geographic Information Systems, School of Civil and Environmental Engineering, National University of Sciences and Technology, Islamabad, PakistanInstitute of Geographic Information Systems, School of Civil and Environmental Engineering, National University of Sciences and Technology, Islamabad, PakistanInstitute of Geographic Information Systems, School of Civil and Environmental Engineering, National University of Sciences and Technology, Islamabad, PakistanBackground: Remote sensing have been intensively used across many disciplines, however, such information was limited in spatial epidemiology. Methods: Two years (2009 & 2010) Landsat TM satellite data was used to develop vegetation, water bodies, air temperature and humidity criterion maps to model malaria risk and its spatiotemporal seasonal variation. The criterion maps were used in weighted overlay analysis to generate final categorized malaria risk map. Results: Overall, 25%, 68%, 18% and 16% of the total area of Rawalpindi region was categorized as danger zone for Jun 2009, Oct 2009, Jan 2010 and Jun 2010, respectively. The malaria risk reached at its peak during the monsoon season whereas air temperature and relative humidity were the main contributing factors in seasonal variation. Conclusion: Malaria risk maps could be used for prioritizing areas for malaria control measures.https://ijph.tums.ac.ir/index.php/ijph/article/view/14580MalariaClimatic and environmental variablesRemote sensingMalaria risk modelingPakistan |
| spellingShingle | Muhammad Haris MAZHER Javed IQBAL Muhammad Ahsan MAHBOOB Iqra ATIF Modeling Spatio-temporal Malaria Risk Using Remote Sensing and Environmental Factors Iranian Journal of Public Health Malaria Climatic and environmental variables Remote sensing Malaria risk modeling Pakistan |
| title | Modeling Spatio-temporal Malaria Risk Using Remote Sensing and Environmental Factors |
| title_full | Modeling Spatio-temporal Malaria Risk Using Remote Sensing and Environmental Factors |
| title_fullStr | Modeling Spatio-temporal Malaria Risk Using Remote Sensing and Environmental Factors |
| title_full_unstemmed | Modeling Spatio-temporal Malaria Risk Using Remote Sensing and Environmental Factors |
| title_short | Modeling Spatio-temporal Malaria Risk Using Remote Sensing and Environmental Factors |
| title_sort | modeling spatio temporal malaria risk using remote sensing and environmental factors |
| topic | Malaria Climatic and environmental variables Remote sensing Malaria risk modeling Pakistan |
| url | https://ijph.tums.ac.ir/index.php/ijph/article/view/14580 |
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