GIS-aided planning of insecticide spraying to control dengue transmission

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 i...

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Veröffentlicht in:International journal of health geographics Jg. 12; H. 1; S. 42
Hauptverfasser: Chu, Hone-Jay, Chan, Ta-Chien, Jao, Fang-Ju
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London BioMed Central 25.09.2013
BioMed Central Ltd
Springer Nature B.V
Schlagworte:
Aedes - drug effects
Animals
Comparative analysis
Control
Dengue
Dengue - epidemiology
Dengue - prevention & control
Dengue - transmission
Dengue fever
Disease transmission
Disease Transmission, Infectious - prevention & control
Epidemics
Epidemiology
Geographic information systems
Geographic Information Systems - trends
Health Informatics
Health Promotion and Disease Prevention
Human Geography
Humans
Infections
Insecticides
Insecticides - administration & dosage
Integer programming
Integrated approach
Mathematical models
Medical Geography
Medicine
Medicine & Public Health
Mosquito Control - methods
Mosquito Control - trends
Mosquitoes
Planning
Planning Techniques
Prevention
Public Health
Remote sensing
Spraying
Studies
Taiwan - epidemiology
Vector-borne diseases
Taiwan
ISEW, Taiwan
Integer programming
GIS
Insecticide spraying planning
Epidemic risk
Multi-objective
Dengue fever
ISSN:1476-072X, 1476-072X
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Zusammenfassung: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.
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ISSN:1476-072X
1476-072X
DOI:10.1186/1476-072X-12-42