Identifying waterborne disease prone areas using geospatial approach along the right bank of Yamuna River in Delhi

Abstract

ABSTRACTThis paper presents a spatial risk analysis of waterborne diseases using analytical hierarchy process that rely on geographical information system (GIS)-automated techniques. We selected nine parameters for assessing waterborne diseases prone areas (WBDP). All the weighted parameter layers were integrated to obtain WBDP map. Of the total WBDP area, 42% area was found under medium category, 34% and 24% area under high and low category, respectively. We have also empirically analysed the factors influencing WBDP areas using regression model. Results revealed that explanatory variables like purification of water, washing hand before drinking and eating, and Surface Water Quality Index (SWQI) are the most influential and positively associated while dipping hand in the vessel is negatively associated with the WBD. Further, WBDP areas were validated by analysing their relationship with the actual incidences of WBD(s). Our study may prove to be beneficial for managing and formulating guidelines for the WBDP areas in similar geographical regions.Abbreviations: GIS: Geographical information system; WBDP: Water borne diseases prone areas; SWQI: Surface water quality index; WBD: Water borne Disease; MDG: Millennium Development Goal; AHP: Analytical hierarchical process; GPS: Global Positioning System; NCR: National Capital Region; IDW: Inverse distance weighted; pH: Potential of Hydrogen; TDS: Total dissolved solid; COD: Chemical Oxygen Demand; BOD: Biochemical Oxygen Demand; TA: Total alkalinity; TH: Total Hardness; Cl: Chlorination; SO4: Sulphate, NO3: Nitrate; FL: Floride; ICMR: Indian Council of Medical Research; ISB: Indian Standards Bureau; RW: Relative weights; WQI: Water Quality Index; DJB: Delhi Jal Board; MDG: Millennium Development Goals; GWQI: Ground Water Quality Index; MCD: Municipality Corporation of Delhi; CPCB: Central Pollution Control Board