Prevention of vector-borne disease by the identification and risk assessment of mosquito vector habitats using GIS and remote sensing: a case study of Gorakhpur, India

Abstract

Vector-borne diseases (VBD) constitute a major portion of diseases spread over the tropical and sub-tropical regions, considerably because of the highly conducive tropical climate. It is the leading cause of viral infections and outbreaks which affects thousands of people annually. It is mostly spread by mosquitoes. The northern part of India is severely affected by VBD. To identify the risk zones of VBD and to take precautionary measures to mitigate the risk of outbreaks in VBD prone area, comprehensive and analytical research involving geographical information system (GIS) and remote sensing is carried out. In this work, the Gorakhpur district of India is taken as the study area. The study area is scrutinized from the Landsat-7 images of the years 2014, 2015 and 2016. These multispectral temporal images have facilitated the identification and delineation of water logged areas and mosquito breeding sites. The VBD risk zones are marked by considering the various parameters that support mosquito breeding. These parameters are water, moisture, vegetation and temperature that are computed through normalized difference water index (NDWI), normalized difference moisture index (NDMI), normalized difference vegetation index (NDVI) and land surface temperature (LST), respectively. NDWI is calculated to identify the shallow and deep water. NDMI identifies the regions with low and high moisture. NDVI finds the sparse and dense vegetation. LST maps the surface temperature using the thermal band data of satellite image. All the layers are reclassified and overlaid that gives the mosquito habitat layer of each year. The ranking of risk zones is then given, and VBD risk layer is subsequently created. The area of 190.15 km2 comes under the risk out of which 39.00 km2 is at high risk, 96.02 km2 is at medium risk, and 55.13 km2 is at low risk. Finally, VBD risk pattern map is generated through spatial interpolation which gives the risk at each coordinate of the study area. This work shows the synergetic use of space-borne satellite images with the GIS for the prevention of VBD.