GIS-aided planning of insecticide spraying to control dengue transmission

International Journal of Health Geographics

Fang-Ju Jao¹  Ta-Chien Chan²  Hone-Jay Chu¹ 

[1] Department of Geomatics, National Cheng Kung University, No. 1, University Road, 701 Tainan City, Taiwan;Research Center for Humanities and Social Sciences, Academia Sinica, 128 Academia Road, Section 2, 115 Nankang, Taipei, Taiwan

关键词: Multi-objective;    GIS;    Epidemic risk;    Insecticide spraying planning;    Dengue fever;    Integer programming;   

Others  :  810050
DOI  :  10.1186/1476-072X-12-42

 received in 2013-08-22, accepted in 2013-09-24,  发布年份 2013

【 摘 要 】

Background

The purpose of this paper is to integrate a multi-objective integer programming formulation and geographic information system (GIS) into dynamically planning the insecticide spraying area for preventing the transmission of dengue fever.

Methods

The optimal spraying area to combat dengue infections is calculated by the multi-objective integer programming model using the dengue epidemic in 2007 in Tainan City of southern Taiwan and is compared with the areas actually sprayed by the local health department. The dynamic epidemic indicators (i.e. frequency, intensity and duration) that identify major temporal characteristics of the dynamic process of an epidemic are all incorporated into the model.

Results

The results indicate that the model can design the spraying area effectively when the trade-off between the coverage of dengue epidemics risk and area compactness is considered.

Conclusions

The model provides an alternative way to obtain a cost-effective spraying area in controlling future dengue epidemics. The proposed model in this study will be beneficial for strategically allocating dengue control resources.

【 授权许可】

   
2013 Chu et al.; licensee BioMed Central Ltd.

【 图 表 】

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【 参考文献 】

• [1]Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, Drake JM, Brownstein JS, Hoen AG, Sankoh O, et al.: The global distribution and burden of dengue. Nature 2013, 496(7446):504-507.
• [2]Konishi E: Issues related to recent dengue vaccine development. Trop Med Health 2011, 39(4 Suppl):63-71.
• [3]Seidahmed OM, Siam HA, Soghaier MA, Abubakr M, Osman HA, Abd Elrhman LS, Elmagbol B, Velayudhan R: Dengue vector control and surveillance during a major outbreak in a coastal Red Sea area in Sudan. East Mediterr Health J 2012, 18(12):1217-1224.
• [4]Sarfraz MS, Tripathi NK, Tipdecho T, Thongbu T, Kerdthong P, Souris M: Analyzing the spatio-temporal relationship between dengue vector larval density and land-use using factor analysis and spatial ring mapping. BMC Public Health 2012, 12:853. BioMed Central Full Text
• [5]Wang C-Y, Lin C, Ge Y-F, Chien H-F, Lin C-S, Wang C-S, Jian S-W, Chen Y-H, Wang Y-Z, Teng H-J: Survey of dengue fever vector density before and after insecticide spraying. Taiwan Epidemiol Bull 2011, 27(19):323-330.
• [6]Wen TH, Lin NH, Lin CH, King CC, Su MD: Spatial mapping of temporal risk characteristics to improve environmental health risk identification: a case study of a dengue epidemic in Taiwan. Sci Total Environ 2006, 367(2–3):631-640.
• [7]Aziz S, Ngui R, Lim YAL, Sholehah I, Farhana JN, Azizan AS, Yusoff WWS: Spatial pattern of 2009 dengue distribution in Kuala Lumpur using GIS application. Trop Biomed 2012, 29(1):113-120.
• [8]Chang AY, Parrales ME, Jimenez J, Sobieszczyk ME, Hammer SM, Copenhaver DJ, Kulkarni RP: Combining Google Earth and GIS mapping technologies in a dengue surveillance system for developing countries. Int J Health Geogr 2009, 8:49. doi: 10.1186/1476-072X-8-49 BioMed Central Full Text
• [9]Wright J, Revelle C, Cohon J: A multiobjective integer programming-model for the land acquisition problem. Reg Sci Urban Econ 1983, 13(1):31-53.
• [10]Armstrong MP, Rushton G, Zimmerman DL: Geographically masking health data to preserve confidentiality. Stat Med 1999, 18(5):497-525.
• [11]Nazri Che D, Zulkiflee Abd L, Abu Hassan A, Rodziah I, Pradhan B: Manifestation of GIS tools for spatial pattern distribution analysis of dengue fever epidemic in the City of Subang Jaya, Malaysia. EnvironmentAsia 2012, 5(2):82-92.
• [12]Taiwan CDC: Guidelines for Dengue Control. Taipei, Taiwan: CDC, Department of Health; 2010.
• [13]Esu E, Lenhart A, Smith L, Horstick O: Effectiveness of peridomestic space spraying with insecticide on dengue transmission; systematic review. Trop Med Int Health 2010, 15(5):619-631.
• [14]Teng HJ, Chen TJ, Tsai SF, Lin CP, Chiou HY, Lin MC, Yang SY, Lee YW, Kang CC, Hsu HC, et al.: Emergency vector control in a DENV-2 outbreak in 2002 in Pingtung City, Pingtung County, Taiwan. Jpn J Infect Dis 2007, 60(5):271-279.
• [15]World Health Organization: Handbook for integrated vector management. Geneva, Switzerland: WHO Press; 2012.
• [16]Oki M, Sunahara T, Hashizume M, Yamamoto T: Optimal timing of insecticide fogging to minimize dengue cases: modeling dengue transmission among various seasonalities and transmission intensities. PLoS Negl Trop Dis 2011, 5(10):e1367.
• [17]Kroeger A, Lenhart A, Ochoa M, Villegas E, Levy M, Alexander N, McCall PJ: Effective control of dengue vectors with curtains and water container covers treated with insecticide in Mexico and Venezuela: cluster randomised trials. BMJ 2006, 332(7552):1247-1252.
• [18]Rizzo N, Gramajo R, Escobar MC, Arana B, Kroeger A, Manrique-Saide P, Petzold M: Dengue vector management using insecticide treated materials and targeted interventions on productive breeding-sites in Guatemala. BMC Public Health 2012, 12:931. doi: 10.1186/1471-2458-12-931 BioMed Central Full Text