Mapping malaria risk using environmental and anthropic variables

Revista Brasileira de Epidemiologia

Mauricio Edilberto Rincón-romero²  Julián Esteban Londoño¹ 

[1] ,Universidad del Valle,Colombia

关键词: Malaria;    GIS;    Spatial modeling;    Environmental modeling;    Malaria risk zoning;    Malaria;    SIG;    Modelación espacial;    Modelación ambiental;    Zonificación del riesgo de malaria;   

DOI  :  10.1590/S1415-790X2009000300005

来源: SciELO

【 摘 要 】

Despite much research in the identification of areas with malaria, it is urgent to further investigate mapping techniques to achieve better approaches in strategies to prevent, mitigate, and eradicate the mosquito and the illness eventually. By using spatial distributed modeling techniques with Geographical Information Systems (GIS), the study proposes methodology to map malaria risk zoning for the municipality of Buenaventura in Colombia. The model proposed by Craig et al.¹ using climatic information was adapted to the conditions of the study area regarding scale and spatial resolution. Geomorphologic and anthropic variables were added to improve spatial allocation of areas with higher risk of contracting the illness, refining zoning. Then, they were contrasted with the locations reported by health entities², taking into account spatial distribution. The comparison of results shows a decrease in the area obtained initially using the Craig et al. model¹ (1999), from 5,422.4 km² (89.1% of the municipality's territory) to 624.3km² (approximately 10% of the municipality's area), yielding a total reduction of 78.8% when environmental and anthropic variables were included in the model. Data show that of the 9,863 cases reported during 2001 to 2005 for 20 selected towns as basis for the amount of surveyed malaria cases², 1,132 were located in the very high-risk areas, 7,662 were in the areas of moderate risk, and 1,066 cases in low-risk areas, showing that 89% of the cases reported fell into the areas with higher risk for malaria.

【 授权许可】

CC BY   
 All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License