This study was aimed to understand the temporal and spatial epidemiology of peste des petits ruminants (PPR) in India using national surveillance data available in the National Animal Diseases Referral Expert System (NADRES) along with its control plan undertaken. On analysis of the outbreaks/cases reports in sheep and goats in NADRES database from 1995 to 2019, it was observed that PPR features among the top ten diseases and stands first among viral diseases, and among reported deaths, PPR accounts for 36% of mortality in sheep and goats. PPR outbreaks occur round the year in all the seasons but are encountered most frequently during the lean period especially, in the winter season (January to February) in different regions/zones. The reported outbreaks have been progressively declined in most of the states in India due to the implementation of a mass vaccination strategic program since 2011. On state-wise analysis, the PPR risk-areas showed wide variations with different levels of endemicity. Andhra Pradesh, West Bengal, and Karnataka were the top three outbreaks reported states during 1995–2010, whereas Jharkhand and West Bengal states reported more outbreaks during 2011–2015 and 2016–2019 periods. The temporal and spatial distribution of PPR in India provides valuable information on the hotspot areas/zones to take appropriate policy decisions towards its prevention and control in different regions/zones of India. The study also identifies when and where intensive surveillance and vaccination along with biosecurity measures need to be implemented for the control and eradication of the disease from India in consonance with the PPR Global Control and Eradication Strategy.

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Aim:Somatic cell count (SCC) is the most widely used single reliable indicator of udder health. The present study was carried out with an objective to find the exact threshold of SCC.Materials and Methods:Milk samples collected from a total of 214 Holstein Friesian crossbred dairy animals were subjected to bacterial DNA extraction and SCC estimation by digital PortaCheck. California Mastitis Test and polymerase chain reaction based on amplification of organism using reported primers were performed to diagnose subclinical mastitis. Receiver’s operating characteristic (ROC) curve analysis and discriminate function analyses were performed using SPSS 18 software.Results:ROC curve analysis represented that the area under the curve was 0.930 with the standard error of 0.02. Results indicated that 93% of the case could be correctly predicted as mastitis infected using SCC as a marker (p<0.001). At cut score level of 282 000 cells/ml, 285,000 cells/ml and 288,000 cells/ml, sensitivity remained 92.6% and specificity augmented as 86.3%, 87.2%, and 88%, respectively. At SCC value of 310,000 cells/ml of milk, sensitivity and specificity were optimal, namely, 92.6% and 91.5%, respectively. The function fitted demonstrated 89.2% accuracy with p<0.001. The functions at group centroids were −0.982 and 1.209, respectively, for normal and mastitis-infected animals and log_SCC value was the most important factor contributing 38.30% of the total distance measured.Conclusion:Our study supports that the threshold value to delineate subclinical mastitis case from the normal is 310,000 somatic cells/ml of milk and a model so fitted using the variable SCC can be successfully used in field for the diagnosis of subclinical cases of mastitis which otherwise would be difficult to differentiate based on clinical signs.