Geo-environmental and Ecological Determinants for Japanese Encephalitis (JE) Transmission in Meghalaya, Northeast India
Palaniyandi Masimalai *
Department of Geography and Disaster Management, Tripura University (A Central University), Suryamaninagar, Tripura (W), PIN- 799022, India.
Aman Kumar Choudhary
Department of Geography and Disaster Management, Tripura University (A Central University), Suryamaninagar, Tripura (W), PIN- 799022, India.
Probhu Boro
Department of Geography and Disaster Management, Tripura University (A Central University), Suryamaninagar, Tripura (W), PIN- 799022, India.
*Author to whom correspondence should be addressed.
Abstract
Japanese Encephalitis (JE) is a mosquito-borne viral disease and a persistent public health concern in Meghalaya, Northeast India. Remote Sensing and GIS, was integrated and fuzzy logic analysis was performed to assess the JE transmission dynamics, mosquito breeding habitats, and delineate transmission risk zones in Meghalaya. Land Use/Land Cover (LULC) changes were analysed and mapped at the 5 years interval (2010, 2015, 2020, and 2025), which indicated a growing anthropogenic influence could be increasing the mosquito breeding areas. A clustered distribution of JE epidemic cases was observed with JE vector mosquitoes breeding habitats suitability, and map topology was performed using LULC categories and Land Surface Temperature (LST), and JE hotspots risk areas were identified in the central and South-Eastern regions. A fuzzy model was applied to prepare the risk of JE transmission zone map, and was validated, and has a strong spatial association between the observed patients' household site locations and a model based predicted hotspots risk zones. The habitat suitability and human exposure layers through fuzzy overlay produced the final transmission risk map showing 21.89% of Meghalaya emerged as very high transmission risk territory, while 62.48% was classified as very low risk. JE transmission in Meghalaya is shaped by the combined influence of ecological and environmental determinants. The study provides a fuzzy Logic membership gamma index for predicting the JE transmission risk zones, offering a reliable framework for disease surveillance, vector control, and targeted public health intervention to control JE epidemics in the high risk zones.
Keywords: Japanese Encephalitis (JE), fuzzy logic membership, land use /land cover, culex genus mosquitoes breeding habitats, vector ecology, geo-environmental determinants, spatial epidemiology, environmental risk assessment, disease risk mapping