Abstract

Background: Risk maps have proven to be important tools for public health decision-making and priority setting for vector-borne diseases because they assist with the targeting of prevention and control efforts. The spatial information obtained from mapping malaria hazard and risk will provide a guideline for control programs and preparing health facilities based on the requirement of each area. Geographic information system (GIS) has been continuously used for the analysis of spatial health-related data. It can be a useful tool for analyzing the spread of diseases. Aim and
Objective: This study attempts to identify malaria risk zones at macrolevel based on annual parasite index (API).
Materials and Methods: Spatiotemporal API data (2006–2011) are integrated into GIS and weighted overlay analysis is performed to delineate risk zones in Vadodara district.
Results: On the basis of API as recorded during 2006–2011 from the villages of the Vadodara district, it was figured out that 50% region of Chhota Udaipur Taluka has recorded continuously very high incidence of malaria and followed by part of Sankheda and then Dabhoi Taluka. Conclusion: API has declined, but still a considerable region is more than above the desirable limit of the API and several vulnerable regions are there with low API and there is the prospect of elimination of this disease in this region.