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Background & objectives: The presence of efficient malaria vectors namely Anopeles culicifacies, An. fluviatilis and An. annularis (Diptera: Culicidae), rapid industrialization causing large influx of population and poor health infrastructure are some of the factors that make malaria an important public health problem in Ranchi, the capital of Jharkhand State, India. A geographical information system (GIS) based retrospective study using spatial statistical tools was initiated in 328 subcentres of 14 primary health centres (PHCs) of the district using malaria epidemiological data of three years (2007-2009) to identify spatial distribution pattern of Plasmodium vivax (Pv) and Plasmodium falciparum (Pf) occurrence, delineation of hot spots and to map directional distribution trend of Pf spread to help formulate evidence-based policy and to prioritize control during 2011. Methods: Spatial statistics tools like Global Moran's I index, Getis-Ord Gi* and Standard Deviational Ellipse were used in GIS domain for analysis. Results: Spatial distribution pattern of Pv occurrence was found random while Pf distribution was significantly clustered. During 2007-2009, the number of subcentres under Pf hot spot category exhibited downward trend while high Pf risk subcentres exhibited upward trend. One consistent Pf hot spot consisting of five subcentres was identified in Silli PHC. During 2009, one Pf hot spot consisting of 20 subcentres and 18 subcentres under high Pf risk category were identified in Angara, Silli, Burmu and Kanke PHCs. A shifting trend in Pf spread was noticed from north-west to western direction from 2008 onwards. Interpretation & conclusions: The study recommended priority control in 20 Pf hot spot and 18 high Pf risk reporting subcentres including five consistent Pf hot spot subcentres in Angara, Silli, Burmu and Kanke PHCs during 2011 to address grave malaria situation in the district in a cost-effective manner.

Background & objectives: Ranchi, the capital of Jharkhand state is endemic for malaria, particularly the Bundu Primary Health Centre (PHC) is the worst affected. Therefore, a study was initiated during 2009 using remote sensing (RS) and geographical information system (GIS) to identify risk factors responsible for high endemicity in this PHC. Methods: Bundu and Angara in Ranchi district were identified as high and low malaria endemic PHCs based on epidemiological data of three years (2007–09). The habitation, streams, other water body, landform, PHC and village boundary thematic maps were prepared using IRS-P6/LISS III-IV imageries and macro level breeding sites were identified. Digital elevation model (DEM) of the PHCs was generated using Cartosat Stereo Pair images and from DEM, slope map was derived to calculate flat area. From slope, aspect map was derived to indicate direction of water flow. Length of perennial streams, area under rocky terrain and buffer zones of 250, 500 and 750 m were constructed around streams. High resolution remote sensing imageries were used to identify micro level breeding sites. Based on macro-micro breeding sites, six villages from each PHC were selected randomly having combination of different parameters representing all ecotypes. Entomological data were collected during 2010–11 in pre- and post-monsoon seasons following standard techniques and analyzed statistically. Differential analysis was attempted to comprehend socioeconomic and other determinants associated with malaria transmission. Results: The study identified eight risk factors responsible for higher malaria endemicity in Bundu in comparison to Angara PHC based on ecological, entomological, socioeconomic and other local parameters. Conclusion: Focused interventions in integrated vector management (IVM) mode are required to be carried out in the district for better management and control of disease.