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Forewarning of Livestock Diseases July-2024

ANDHRA PRADESH AND TAMIL NADU for likely occurrence of Anthrax in September-2024

UTTAR PRADESH are predicted for likely occurrence of Babesiosis in September-2024

ANDHRA PRADESH,ASSAM,BIHAR,CHHATTISGARH,JAMMU & KASHMIR,JHARKHAND,KARNATAKA,MADHYA PRADESH,MAHARASHTRA,MEGHALAYA,ODISHA,RAJASTHAN,TAMIL NADU,TRIPURA,UTTAR PRADESH,WEST BENGAL,DAMAN & DIU AND TELANGANA are predicted for likely occurrence of Black quarter in September-2024

KARNATAKA AND WEST BENGAL are predicted for likely occurrence of Bluetongue in September-2024

MANIPUR,MEGHALAYA AND PUDUCHERRY are predicted for likely occurrence of Classical Swine fever in September-2024

JHARKHAND AND KARNATAKA are predicted for likely occurrence of Enterotoxaemia in September-2024

ARUNACHAL PRADESH,ASSAM,JHARKHAND,KERALA,MANIPUR,ODISHA,TRIPURA,WEST BENGAL,ANDAMAN & NICOBAR AND PUDUCHERRY are predicted for likely occurrence of Fascioliasis in September-2024

KERALA,MANIPUR,ODISHA,ANDAMAN & NICOBAR,DAMAN & DIU AND LAKSHADWEEP are predicted for likely occurrence of Foot and mouth disease in September-2024

ARUNACHAL PRADESH,BIHAR,GUJARAT,HARYANA,JAMMU & KASHMIR,JHARKHAND,KERALA,MADHYA PRADESH,MAHARASHTRA,MIZORAM,RAJASTHAN,TAMIL NADU,UTTAR PRADESH,WEST BENGAL AND ANDAMAN & NICOBAR are predicted for likely occurrence of Haemorrhagic septicaemia in September-2024

ASSAM,BIHAR,GUJARAT,HARYANA,JAMMU & KASHMIR,JHARKHAND,KARNATAKA,KERALA,MADHYA PRADESH,MAHARASHTRA,ODISHA,TAMIL NADU,TRIPURA,UTTAR PRADESH,UTTARAKHAND AND WEST BENGAL are predicted for likely occurrence of PPR in September-2024

ASSAM,GOA,KERALA,MADHYA PRADESH,MAHARASHTRA,MIZORAM AND UTTARAKHAND are predicted for likely occurrence of African Swine Fever in September-2024 TAMIL NADU AND UTTARAKHAND are predicted for likely occurrence of S & G Pox in September-2024

ANDHRA PRADESH,ASSAM,BIHAR,GOA,HARYANA,JHARKHAND,KERALA,PUNJAB,SIKKIM,TRIPURA,UTTAR PRADESH AND WEST BENGAL are predicted for likely occurrence of Theileriosis in September-2024

BIHAR,GUJARAT,JAMMU & KASHMIR,MADHYA PRADESH,MAHARASHTRA,RAJASTHAN AND WEST BENGAL are predicted for likely occurrence of Trypanosomiasis in August-2024

ASSAM,BIHAR,CHHATTISGARH,GUJARAT,KARNATAKA,MADHYA PRADESH,RAJASTHAN,SIKKIM,TAMIL NADU,TRIPURA,LAKSHADWEEP are predicted for likely occurrence of Lumpy Skin Disease in September-2024

Risk Prediction September-2024

African swine fever - 26 Risk districts, with Accuracy of 100%

Anthrax - 20 Risk districts, with Accuracy of 99.44%

Babesiosis - 76 Risk districts, with Accuracy of 98.34%

Black quarter - 71 Risk districts, with Accuracy of 94.36%

Bluetoungue- 08 Risk district, with Accuracy of 98.89%

Classical Swine Fever - 43 Risk districts, with Accuracy of 98.76%

Enterotoxaemia- 31 Risk districts, with Accuracy of 98.62%

Fasciolosis - 60 Risk districts, with Accuracy of 97.66%

FMD - 99 Risk districts, with Accuracy of 96.97%

HS - 284 Risk districts, with Accuracy of 66.57%

LSD - 43 Risk districts, with Accuracy of 99.86%

PPR - 54 Risk districts, with Accuracy of 99.03%

S&G Pox - 22 Risk districts, with Accuracy of 99.44%

Theileriosis - 72 Risk districts, with Accuracy of 97.24%

Trypanosomiasis - 67 Risk districts, with Accuracy of 97.93%

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Total of 18,62,586 SMS alerts on disease forecasts have been issued to farmers through FRUITS, NIC, Govt of Karnataka, for the month of July-2024.

ಸಂದೇಶ: ನೆರಡಿ ರೋಗದ ಒಟ್ಟು 3,12,938 ಸಂದೇಶಗಳುನ್ನು ರೈತಾ ಮಿತ್ರುಗಳಿಗೆ ಜಂಗಮ ವಾಣಿ (ಮೊಬೈಲ್) ಮುಲಕಾ ರವಾನಿಸಲಾಗಿದೆ.

ಬಾಗಲಕೋಟೆ, ಬಳ್ಳಾರಿ, ಚಿಕ್ಕಬಳ್ಳಾಪುರ, ಚಿತ್ರದುರ್ಗ, ದಾವಣಗೆರೆ, ಹಾವೇರಿ, ಕೊಪ್ಪಳ, ರಾಯಚೂರು, ತುಮಕೂರು ಮತ್ತು ಸುತ್ತಮುತ್ತಲಿನ ಗ್ರಾಮದಲ್ಲಿ ಮುಂಬರುವ ಸೆಪ್ಟಂಬರ ತಿಂಗಳಲ್ಲಿ ರಾಸುಗಳಿಗೆ ನೆರಡಿ ರೋಗ ರೋಗ ಕಂಡುಬರುವ ಮುನ್ಸೂಚನೆ ಇರುವುದರಿಂದ ಹತ್ತಿರದ ಪಶುಚಿಕಿತ್ಸಾಲಯವನ್ನು ಸಂಪರ್ಕಿಸಿ. ಹೆಚ್ಚಿನ ಮಾಹಿತಿಗಾಗಿ https://fruits.karnataka.gov.in/AnimalDiseaseDetails.aspx?AId=1&DId=1&Type=F ಕ್ಲಿಕ್ ಮಾಡಿ. From: FRUITS

ಸಂದೇಶ: ಚಪ್ಪೆ ರೋಗದ ಒಟ್ಟು 5,50,829 ಸಂದೇಶಗಳುನ್ನು ರೈತಾ ಮಿತ್ರುಗಳಿಗೆ ಜಂಗಮ ವಾಣಿ (ಮೊಬೈಲ್) ಮುಲಕಾ ರವಾನಿಸಲಾಗಿದೆ.

ಬೆಳಗಾವಿ, ಚಿಕ್ಕಮಗಳೂರು, ಚಿತ್ರದುರ್ಗ, ದಾವಣಗೆರೆ, ಧಾರವಾಡ, ಹಾಸನ, ಹಾವೇರಿ, ಕೊಪ್ಪಳ, ಮೈಸೂರು, ರಾಯಚೂರು, ಶಿವಮೊಗ್ಗ, ಉಡುಪಿ ಮತ್ತು ಸುತ್ತಮುತ್ತಲಿನ ಗ್ರಾಮದಲ್ಲಿ ಮುಂಬರುವ ಸೆಪ್ಟಂಬರ ತಿಂಗಳಲ್ಲಿ ರಾಸುಗಳಿಗೆ ಚಪ್ಪೆ ರೋಗ ರೋಗ ಕಂಡುಬರುವ ಮುನ್ಸೂಚನೆ ಇರುವುದರಿಂದ ಹತ್ತಿರದ ಪಶುಚಿಕಿತ್ಸಾಲಯವನ್ನು ಸಂಪರ್ಕಿಸಿ. ಹೆಚ್ಚಿನ ಮಾಹಿತಿಗಾಗಿ https://fruits.karnataka.gov.in/AnimalDiseaseDetails.aspx?AId=1&DId=3&Type=F ಕ್ಲಿಕ್ ಮಾಡಿ. From: FRUITS.

ಸಂದೇಶ: ಕಾಲು ಬಾಯಿ ರೋಗದ ಒಟ್ಟು 9,98,819 ಸಂದೇಶಗಳುನ್ನು ರೈತಾ ಮಿತ್ರುಗಳಿಗೆ ಜಂಗಮ ವಾಣಿ ಮುಲಕಾ (ಮೊಬೈಲ್) ರವಾನಿಸಲಾಗಿದೆ.

ಬೆಂಗಳೂರು ನಗರ, ಬೆಂಗಳೂರು ಗ್ರಾಮಾಂತರ, ಬಳ್ಳಾರಿ, ಚಾಮರಾಜನಗರ, ಚಿಕ್ಕಬಳ್ಳಾಪುರ, ಚಿಕ್ಕಮಗಳೂರು, ಚಿತ್ರದುರ್ಗ, ದಕ್ಷಿಣ ಕನ್ನಡ, ದಾವಣಗೆರೆ, ಗದಗ, ಹಾಸನ, ಹಾವೇರಿ, ಕೊಪ್ಪಳ, ಮಂಡ್ಯ, ಮೈಸೂರು, ರಾಮನಗರ, ಶಿವಮೊಗ್ಗ, ತುಮಕೂರು, ಉಡುಪಿ, ಉತ್ತರ ಕನ್ನಡ ಮತ್ತು ಸುತ್ತಮುತ್ತಲಿನ ಗ್ರಾಮದಲ್ಲಿ ಮುಂಬರುವ ಸೆಪ್ಟಂಬರ ತಿಂಗಳಲ್ಲಿ ರಾಸುಗಳಿಗೆ ಕಾಲು ಬಾಯಿ ರೋಗ ರೋಗ ಕಂಡುಬರುವ ಮುನ್ಸೂಚನೆ ಇರುವುದರಿಂದ ಹತ್ತಿರದ ಪಶುಚಿಕಿತ್ಸಾಲಯವನ್ನು ಸಂಪರ್ಕಿಸಿ. ಹೆಚ್ಚಿನ ಮಾಹಿತಿಗಾಗಿ https://fruits.karnataka.gov.in/AnimalDiseaseDetails.aspx?AId=1&DId=7&Type=F ಕ್ಲಿಕ್ ಮಾಡಿ. From: FRUITS.
Govt Schemes for farmers

Risk Maps

The basic reproduction number (R0) is the number of cases directly caused by an infected individual throughout its infectious period and is an indicator of the infectiousness or transmissibility of infectious pathogen. R0 is used to determine the ability of a disease to spread within a given population and has been described as being one of the fundamental and most often used metrics for study of infectious disease dynamics.
Geographical maps indicating the value of basic reproduction number(R0), can be used to identify the areas of higher risk of probability for major outbreak/incidence of livestock in India. This is a first step towards an integrative method to predict the risk of establishment of disease based on mathematical modelling combined with a geographic information system that may comprise climate variables including satellite data, landscape, host parameters and other relevant factors determining risk of establishment for livestock diseases. Geographical maps indicating the value of basic reproduction number(R0), can be used to identify the areas of higher risk of probability for major outbreak/Incidence. This is a first step towards an integrative method to predict the risk of establishment of disease based on mathematical modelling combined with a geographic information system that may comprise climate variables including satellite data, landscape, host parameters and other relevant factors determining risk of establishment for livestock diseases.


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