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Disease prediction model to assess the impact of changes in precipitation level on the risk of anthrax infectiousness among the livestock hosts in Karnataka, India

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Title Disease prediction model to assess the impact of changes in precipitation level on the risk of anthrax infectiousness among the livestock hosts in Karnataka, India
Not Available
 
Creator Bylaiah S
Shedole S
Suresh KP
Gowda L
Shivananda B
Shivamallu C
Patil SS
 
Subject Anthrax
Disease prediction
Karnataka
Livestock
Machine Learning
Outbreak
 
Description Not Available
Anthrax is a one of the zoonotic diseases existing in India. Early detection of anthrax outbreaks is crucial for minimizing anthrax morbidity and death, as well as the risk of anthrax transmission in the population. Objective of the present research is to develop a disease prediction model by employing Machine-Learning techniques to assess the risk of anthrax analogous to the impact of changes in precipitation level that can benefit as an early warning system for detecting future anthrax outbreaks among livestock across Karnataka. By considering the disease incidence data during 2000 to 2019, livestock population data and the ecological parameters, the machine learning model was successful in identifying the next outbreak susceptible areas and the parameters that contribute significantly to the disease outbreak. Machine learning model was developed by R statistical software version 3.1.3 using different data mining regression and classification models viz., GLM, GAM, MARS, FDA, CT, SVM, NB, ADA, RF, GBM and ANN. Disease incidence data was collected from Department of animal husbandry, Bengaluru, Karnataka. Disease incidence data was divided in two groups based on average annual precipitation above and below normal (1151mm) for the risk assessment and study the impact of changes in precipitation level. Data with average annual-precipitation above normal was predicted with high risk in the north, northern east and the state's southern region. Whereas data with average annual-precipitation below normal was predicted with high risk in south, northern east and the state's central region. Cohen's Kappa, ROC curve, True Skill Statistics (TSS), and ACCURACY was used to assess the models performance. Further, this model can be intensified and validated using the anthrax outbreak data available at national level which will be useful for policymakers to formulate control
strategies
Not Available
 
Date 2023-04-10T06:44:09Z
2023-04-10T06:44:09Z
2022-02-01
 
Type Research Paper
 
Identifier Bylaiah, Sushma & Shedole, Seema & Suresh, Kuralayanapalya & Gowda, Leena & Shivananda, Bindya & Shivamallu, Chandan & Patil, Sharanagouda. (2022). Disease Prediction Model to Assess the Impact of Changes in Precipitation Level on the Risk of Anthrax Infectiousness among the Livestock Hosts in Karnataka, India. International Journal of Special Education. 33. 711-727.
0827-3383
http://krishi.icar.gov.in/jspui/handle/123456789/76779
 
Language English
 
Relation Not Available;
 
Publisher Research Gate