Abstract
Abstract. Visceral Leishmaniasis (VL) commonly known as Kala-azar is one of the most neglected tropical disease affecting approximately 200 million poorest populations 'at risk in 109 districts of three endemic countries namely Bangladesh, India and Nepal at different levels. This tropical disease is caused by the protozoan parasite Leishmania donovani and transmitted by female Phlebotomus argentipes sand flies. The analysis of disease dynamics indicate the periodicity at seasonal and inter-annual temporal scale which forms the basis for development of advanced early warning system. Study area of highly endemic Vaishali district, Bihar, India has been taken for model development. A Systematic study of geo-environmental parameters derived from satellite data in conjunction with ground intelligence enabled modelling of infectious disease and risk villages. High resolution Indian satellites data of IRS LISS IV (multi-spectral) and Cartosat-1 (Pan) have been used for studying environmentally risk parameters viz. peri-domestic vegetation, dwelling condition, wetland ecosystem, cropping pattern, Normalised Difference Vegetation Index (NDVI), detailed land use etc towards risk assessment. Univariate analysis of the relationship between vector density and various land cover categories and climatic variables suggested that all the variables are significantly correlated. Using the significantly correlated variables with vector density, a seasonal multivariate regression model has been carried out incorporating geo-environmental parameters, climate variables and seasonal time series disease parameters. Linear and non-linear models have been applied for periodicity and interannual temporal scale to predict Man-hour-density (MHD) and 'out-of-fit' data set used for validating the model with reasonable accuracy. To improve the MHD predictive approach, fuzzy model has also been incorporated in GIS environment combining spatial geo-environmental and climatic variables using fuzzy membership logic. Based on the perceived importance of the geoenvironmental parameters assigned by epidemiology expert, combined fuzzy membership has been calculated. The combined fuzzy membership indicate the predictive measure of vector density in each village. A γ factor has been introduced to have increasing effect in the higher side and decreasing effect in the lower side which facilitated for prioritisation of the villages. This approach is not only to predict vector density but also to prioritise the villages for effective control measures. A software package for modelling the risk villages integrating multivariate regression and fuzzy membership analysis models have been developed to estimate MHD (vector density) as part of the early warning system.
Highlights
India has 52 kala-azar endemic districts in four states of India Bihar (31 districts with 62.3 million population), Uttar Pradesh (11 districts with 50.0 million population), West Bengal (6 districts with 11.0 million population), and Jharkhand (4 districts with 6.7 million population)
A study in a predefined endemic focus revealed that an optimal of 8 Man-Hour-Density (MHD) which is critical vector density was essential for P.argentipes enabling it to transmit infection from one infected host to a new host
The overall methodology is divided into four different steps namely satellite data processing, collateral data analysis, statistical analysis and GIS model development for early warning system
Summary
India has 52 kala-azar endemic districts in four states of India Bihar (31 districts with 62.3 million population), Uttar Pradesh (11 districts with 50.0 million population), West Bengal (6 districts with 11.0 million population), and Jharkhand (4 districts with 6.7 million population). Bihar alone contributes 70-80 % of the kala-azar cases. In 1992, the highest number of cases were reported (77170) after which the incidence has declined gradually. From 2003 to 2007 there has been a steady increase in the annual number of reported cases. A study in a predefined endemic focus revealed that an optimal of 8 Man-Hour-Density (MHD) which is critical vector density was essential for P.argentipes enabling it to transmit infection from one infected host to a new host. The transmission cycle of Kala-azar vector is shown in fig. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012 XXII ISPRS Congress, 25 August – 01 September 2012, Melbourne, Australia that the preponderance of vector (except winter months) was 2 to 3 times higher than the critical density in summer and rainy months (from March – October) thereby suggesting probability of successful transmission subject to presence of host and conducive environmental situation.[2, 4, 6, 8, 11]
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