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Analysis of bluetongue disease epizootics in sheep of Andhra Pradesh, India using spatial and temporal autocorrelation

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Title Analysis of bluetongue disease epizootics in sheep of Andhra Pradesh, India using spatial and temporal autocorrelation
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Creator Ravichandran Karthikeyan, Ramkumar N Rupner, Shiva Reddy Koti, Nagaraj Jaganathasamy, Michael V. Lalrinzuala, Sachin Sharma, Shikha Tamta, Rotluangkimi, Sukdeb Nandi, Yashpal Singh Malik, Zunjar Baburao Dubal, Dharmendra Kumar Sinha, Bhoj R. Singh & Obli Rajendran Vinodhkumar
 
Subject Analysis of bluetongue disease epizootics in sheep of Andhra Pradesh, India using spatial and temporal autocorrelation
 
Description Not Available
Bluetongue (BT) disease poses a constant risk to the livestock population around the world. A better understanding of the risk factors will enable a more accurate prediction of the place and time of high-risk events. Mapping the disease epizootics over a period in a particular geographic area will identify the spatial distribution of disease occurrence. A Geographical Information System (GIS) based methodology to analyze the relationship between bluetongue epizootics and spatial–temporal patterns was used for the years 2000 to 2015 in sheep of Andhra Pradesh, India. Autocorrelation (ACF), partial autocorrelation (PACF), and cross-correlation (CCF) analyses were carried out to find the self-dependency between BT epizootics and their dependencies on environmental factors and livestock population. The association with climatic or remote sensing variables at different months lag, including wind speed, temperature, rainfall, relative humidity, normalized difference vegetation index (NDVI), normalized difference water index (NDWI), land surface temperature (LST), was also examined. The ACF & PACF of BT epizootics with its lag showed a significant positive autocorrelation with a month’s lag (r = 0.41). Cross-correlations between the environmental variables and BT epizootics indicated the significant positive correlations at 0, 1, and 2 month’s lag of rainfall, relative humidity, normalized difference water index (NDWI), and normalized difference vegetation index (NDVI). Spatial autocorrelation analysis estimated the univariate global Moran’s I value of 0.21. Meanwhile, the local Moran’s I value for the year 2000 (r = 0.32) showed a high degree of spatial autocorrelation. The spatial autocorrelation analysis revealed that the BT epizootics in sheep are having considerable spatial association among the outbreaks in nearby districts, and have to be taken care of while making any forecasting or disease prediction with other risk factors.
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Date 2023-06-07T03:45:14Z
2023-06-07T03:45:14Z
2022-02-01
 
Type Article
 
Identifier Not Available
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http://krishi.icar.gov.in/jspui/handle/123456789/78067
 
Language English
 
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Publisher Not Available