Analysing water-borne diseases susceptibility in Kolkata Municipal Corporation using WQI and GIS based Kriging interpolation

The varieties of water-borne disease are caused by pathogens transmitted and spread by different routes. The spread of such infection increases while the water quality affected by external sources. Changes in the quality of water can influence the dynamics of microbial pathogens which can also influ...

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Bibliographic Details
Published in:GeoJournal 2020-08, Vol.85 (4), p.1151-1174
Main Authors: Ali, Sk Ajim, Ahmad, Ateeque
Format: Article
Language:English
Subjects:
Autocorrelation
Chemicals
Disease transmission
Diseases
Dynamics
Environmental Management
Error analysis
Geographic information systems
Geographical information systems
Geography
Geostatistics
Groundwater
Groundwater quality
Human Geography
Information systems
Justification
Kriging interpolation
Mapping
Microorganisms
Organic chemistry
Parameter identification
Parameters
Pathogens
Satellite navigation systems
Social Sciences
Statistical methods
Susceptibility
Water
Water quality
Waterborne diseases
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Summary:The varieties of water-borne disease are caused by pathogens transmitted and spread by different routes. The spread of such infection increases while the water quality affected by external sources. Changes in the quality of water can influence the dynamics of microbial pathogens which can also influence the prevalence and transmission dynamics of water-borne diseases. The present study highlighted on selected chemical parameters of ground water to signify the water quality index and mapping of water-borne diseases susceptibility areas in Kolkata Municipal Corporation, India. The main objective of present study was to demonstrate the significance of geographical information system based Geostatistical technique for identifying water-borne diseases susceptibility by taking different ground water parameters, water quality index and reported water-borne diseases into consideration. Using Kriging interpolation, the spatial map of water parameters, water quality index and reported disease cases were prepared and reclassified by putting risk rank to generate susceptibility map of water-borne diseases. The accuracy of the result was assessed through error estimation and spatial autocorrelation. The result from error estimation, it was found that the root mean square error between diseases susceptibility and selected chemical parameters, water quality index and reported water-borne diseases are 0.0847, 0.1182 and 0.0640 respectively which is always 
ISSN:0343-2521
1572-9893
DOI:10.1007/s10708-019-10015-3