Abstract
Abstract. Malaria epidemic is one of the complex spatial problems around the world. According to WHO, an estimated 6, 27, 000 deaths occurred due to malaria in 2012. In many developing nations with diverse ecological regions, it is still a large cause of human mortality. Owing to the incompleteness of epidemiological data and their spatial origin, the quantification of disease incidence burdening basic public health planning is a major constrain especially in developing countries. The present study focuses on the integrated Geospatial and Multi-Criteria Evaluation (AHP) technique to determine malaria risk zones. The study is conducted in Vadodara district, including 12 Taluka among which 4 Taluka are predominantly tribal. The influence of climatic and physical environmental factors viz., rainfall, hydro geomorphology; drainage, elevation, and land cover are used to score their share in the evaluation of malariogenic condition. This was synthesized on the basis of preference over each factor and the total weights of each data and data layer were computed and visualized. The district was divided into three viz., high, moderate and low risk zones .It was observed that a geographical area of 1885.2sq.km comprising 30.3% fall in high risk zone. The risk zones identified on the basis of these parameters and assigned weights shows a close resemblance with ground condition. As the API distribution for 2011overlaid corresponds to the risk zones identified. The study demonstrates the significance and prospect of integrating Geospatial tools and Analytical Hierarchy Process for malaria risk zones and dynamics of malaria transmission.
Highlights
The threats to human health from vector bore diseases especially mosquito borne diseases like malaria, dengue, elephantiasis etc. continue to be a global problem
The district was divided into three viz., high, moderate and low risk zones
It was observed that a geographical area of 1885.2 sq.km comprising 30.3% fall in high risk zone
Summary
The threats to human health from vector bore diseases especially mosquito borne diseases like malaria, dengue, elephantiasis etc. continue to be a global problem. MCE based approaches begin with an intelligence phase where the problem definition, decision constraints and evaluation criteria are defined.(Malczewski J:1999) This study can help identifying risk areas adding to the efficiency of prevention efforts and will contribute as means of targeting high risk areas, which help to organize efforts towards the fight against malaria efficiently.
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