Spatial mapping and analysis of anaemia cases in Gadag district, Karnataka: a GIS-based study

Background: Anaemia is one of the chronic public health problems in India and it is associated with inequities in healthcare service, nutrition status and socioeconomic status. Knowledge of geographic distribution of anemia can help for the identification of high-risk areas, where focused interventions can be implemented. This study aimed to map and analyse the spatial distribution, clustering patterns and hotspots of laboratory confirmed anaemia cases in the Gadag District. Methods: A retrospective cross-sectional study on 4,040 cases of laboratory-confirmed anaemia has been carried out using secondary data. Spatial clustering was analysed using the average nearest neighbour (ANN) test; Global and Local Moran's I tested for spatial autocorrelation along with hotspots and cold areas of anaemia patients. Results: Significant clustering was detected by the ANN test (p<0.001). Different hotspots were identified by using Local Moran's I and Getis-Ord Gi tools mainly in the Shirahatti, Laxmeshwar and Mundargi taluks, whereas Global Moran's I did not detect any significant autocorrelation. Conclusions: The spatial distribution of anaemia in the Gadag District is non-random, spatially heterogeneous, with well-defined hotspot zones. The use of GIS based surveillance at district level planning will help in early detection and targeted management of anemia.