Sains Malaysiana 40(8)(2011): 937–943

 

Evaluation of the Spatial Risk Factors for High Incidence of Dengue Fever and Dengue Hemorrhagic Fever Using GIS Application

(Penilaian Faktor-faktor Risiko Ruangan Bagi Kejadian Penyakit Demam Denggi dan Demam Denggi Berdarah Menggunakan Aplikasi GIS)

 

Aziz Shafie*

Department of Geography , Faculty of Arts and Social Sciences, University of Malaya

50603 Kuala Lumpur, Malaysia

 

Received: 25 May 2010 / Accepted: 29 November 2010

 

ABSTRACT

 

In Malaysia, the incidence of Dengue Fever (DF) and Dengue Hemorrhagic Fever (DHF) have risen dramatically in the last twenty years. With the use of Geographical Information System an explanation for the spread and control of these diseases can be obtained. This study aims to develop a spatial modeling that can predict the risks for DF and DHF based on environmental factors such as physical surroundings, land use, rainfall, temperature and GIS application using logistic regression. A total of 16 variables were used in the process of spatial modeling development. At the significant level of 0.05, the results of logistic regression showed that only 10 out of 16 significant variables in the modeling process. The accuracy of the resulting model is 70.3%. A crucial feature of this study is a risk area map for incidence of DF and DHF in the study area. This study also highlights the application of spatial analysis in planning and implementing the process for the prevention and control activities of DF and DHF in Malaysia.

 

Keywords: Dengue fever; dengue hemorrhagic fever; geographic information system (GIS); risk mapping; spatial modeling

 

ABSTRAK

 

Di Malaysia, kejadian kes Demam Denggi (DD) dan Demam Denggi Berdarah (DBD) telah meningkat secara dramatik dalam dua puluh tahun terakhir. Dengan penggunaan Sistem Maklumat Geografi (GIS), penjelasan tentang penyebaran dan pengawalan penyakit ini boleh dilakukan. Kajian ini bertujuan untuk membangunkan model ruangan yang dapat meramalkan risiko kejadian penyakit DF dan DBD berdasarkan faktor-faktor persekitaran seperti persekitaran fizikal, guna tanah, hujan, suhu dan aplikasi GIS menggunakan kaedah regreasi logistik. Sebanyak 16 pemboleh telah digunakan dalam proses pembentukan model ruangan. Pada aras signifikan 0.05, keputusan regrasi logistik mendapati hanya 10 daripada 16 pembolehubah signifikan dalam proses pembentukan model. Ketepatan model yang dihasilkan ialah sebanyak 70.3%. Hasil penting kajian ini adalah peta risiko kejadian DF dan DBD di kawasan kajian. Kajian ini juga menyoroti penggunaan analisis ruangan dalam proses perancangan dan pelaksanaan aktiviti untuk pencegahan dan kawalan penyakit DD dan DDB di Malyasia.

 

Kata kunci: Demam denggi; demam denggi berdarah; pemetaan risiko; permodelan ruangan: sistem maklumat geografi (GIS)

REFERENCES

 

Aziz, S. 2008. Geographic Information System (GIS) Application to Identify High Risk Area of Dengue and Dengue Hemorrhagic Fever In Georgetown, Penang. PhD Thesis. Universiti Sains Malaysia, Geography Section. (Unpublished)

Barbazan, P., Yoksun, S. & Gonzalez, J.P. 2002. Dengue hemorrhagic fever epidemiology in Thailand. Description and forecasting of epidemics. Microbes and Infectors 4:669-705.

Beaty, J & Marquardt, C. 996. The Biology of Disease Vectors. Colorado: University Press of Colorado.

Benjamin, G.J., Joel, A.M., Erick, C., Daniel, A.G. & Robert, J.N. 2010. Geomapping generalize deigenvalue frequency distributions for predicting prolific Aedes albopictus and Culex quinquefasciatus habitats based on spatiotemporal field. ActaTropica doi:10.1016/j.actatropica.2010.10.002.

Bohra, A. & Andrianasolo, H. 2001. Application of GIS in Modeling of Dengue Risk Based On Sociocultural Data: Case of Jalore, Rajasthan, India. Dengue Bulletin 25: 92-102.

Chan, K.L. 1985. Singapore’s Dengue Hemorrhagic Fever Control Programme A case Study Of The Successful Control Of Aedes Aegypti And Aedesm Alboppictus Using Mainly Environmental Measures As A Part Of Integrated Vector Control. Tokyo: Southeast Asian Medical Information Centre (SEAMIC).

Cheong, W.H. 1986. Dengue Hemorrhagic Fevers in Malaysia. In Dengue Fever Studies in Malaysia. In Dengue Fever Studies in Malaysia. Edited by Rudnick & Lim. Kuala Lumpur: Institute for Medical Research.

Field, A. 2005. Discovering Statistics Using SPSS. London: Sage Publication.

Gubler, D.J. & Kuno, G. 1997. Dengue and Dengue Hemorrhagic Fever. Cambridge: CAB International.

Haliza, M.R. 2001. Perception, Knowledge and Behavioral Aspects of Dengue Control in Urban Communities in Kuala Lumpur. Proceedings of the Behavioral Interventions in Dengue Control in Malaysia, Universiti Sains Malaysia, Pulau Pinang: 125-140.

Kolivras, K.N. 2006. Mosquito habitat and dengue risk potential in Hawaii: a conceptual framework and GIS application. Professional Geographer 58: 139-154.

Manguin, S., Bangs, M.J., Pothikasikorn, J. & Chareonviriyaphap, T. 2010. Review on global co-transmission of human Plasmodium species and Wuchereria bancrofti by Anopheles mosquitoes. Infection, Genetics and Evolution 10: 159-177.

Ministry of Health (MOH). 2009. Current Situation of Dengue and Dengue Hemorrhagic Fever. Kuala Lumpur: Ministry of Health.

Mohammad, A., Wagatsuma, Y., Emch, M. & Breiman, R. 2003. Use of A Geographic Information System For Defining Spatial Risk For Dengue Transmission in Bangladesh: Role For Aedes albopictus in An Urban Outbreak. American Journal of Tropical Medicine and Hygiene 69: 634-640.

Mondini, A. & Chiaravalloti-Neto, F. 2008. Spatial correlation of incidence of dengue with socioeconomic, demographic and environmental variables in a Brazilian city. Science of the Total Environment 393: 241-248.

Pang, T., Hamimah, H. & Shivaji, R. 1998. Dengue and Dengue Hemorrhagic Fever. Kuala Lumpur: Dewan Bahasa dan Pustaka.

Pedigo, L. 1999. Entomology And Pest Management. Upper Saddle River: Prentice Hall.

Pei-Chih Wua, Jinn-Guey Layb, How-Ran Guoc, Chuan-Yao Lind, Shih-Chun Lung & Huey-Jen Su 2009. Higher temperature and urbanization affect the spatial patterns of dengue fever transmission in subtropical Taiwan. Science of the Total Environment 407: 2224-2233.

Peterson, A.T., Campos, C.M., Yoshinori Nakazawac & Meyerd, E.M. 2005. Time-specific ecological niche modeling predicts spatial dynamics of vector insects and human dengue cases. Transactions of the Royal Society of Tropical Medicine and Hygiene 99: 647-655.

Richards, E.E., Masuoka, P., Major, D.B., Smith, M., Klein, T.A., Kim, H.C., Anyamba, A. & Grieco, J. (2010). The relationship between mosquito abundance and rice field density in the Republic of Korea. International Journal of Health Geographic 9: 32-42.

Rotela, C., Fouque, F., Lamfri, M., Sabatier, P., Introini, V., Zaidenberg, M. & Scavuzzo, C. 2007. Space–time analysis of the dengue spreading dynamics in the 2004 Tartagal outbreak, Northern Argentina. Acta Tropica 103: 1-13.

Schroder, W. 2006. GIS, geostatistics, metadata banking, and tree-based models for data analysis and mapping in environmental monitoring and epidemiology. International Journal of Medical Microbiology 296 (S1): 23-36

Tan, B.T. & Teo, B.T. 1986. Modus Operandi in Aedes Surveillance and Control in Singapore. Singapore: Institute of Environmental Epidemiology, Ministry of Environment.

Tham, A.S. 2001. Issues and Challenges in Aedes Surveillance and Control. Proceedings of the Behavioral Interventions

in Dengue Control in Malaysia. Universiti Sains Malaysia, Penang: 15-26.

Thomson, M.C. & Connor, S.J. 2000. Environmental information systems for the control of arthropod vectors of disease. Medical and Veterinary Entomology 14: 227-244.

Troyo, A., Fuller, D.O., Arguedas, O.C., Solano, M.E. & Beier, J.C. 2009. Urban structure and dengue fever in Puntarenas, Costa Rica. Singapore Journal of Tropical Geography 30(2): 265-282.

Tzai, H.W., Neal, H.L., Chun, H.L., Chwan, C.K. & Ming, D.S. 2006. Spatial mapping of temporal risk characteristics to improve environmental health risk identification: A case study of a dengue epidemic in Taiwan. Science of the Total Environment 367: 631-640.

Tzai-Hung Wen, Neal, H.L., Day-Yu Chao, Kao-Pin Hwang, Chih-Chun Kan, Katherine Chun-Min Lin, Joseph Tsung-Shu Wu, Scott Yan-Jang Huang, I-Chun Fan & Chwan-Chuen King. (2010). Spatial–temporal patterns of dengue in areas at risk of dengue hemorrhagic fever in Kaohsiung, Taiwan, 2002. International Journal of Infectious Diseases 14: 334-343.

Wegbreit, K.C. & Reisen, W.K. 2000. Relationship Among Weather, Mosquito Abundance, and Encephalitis Virus Activity in California: Kern County 1990-1998. Journal of the American Mosquito Control Association 16: 22-27.

Wellmer, H. 1983. Dengue Haemorrhagic Fever in Thailand. Geomedical Observations on Developments Over the Period 1970-1979. Berlin: Springer-Verlag; 1983.

 

*Corresponding author; email: azizs@um.edu.my

 

 

previous