Classification of four ovine breeds of southern peninsular zone of India: Morphometric study using classical discriminant function analysis

Six morphometric traits (height at withers, body length, chest girth, ear length, tail length and body weight) were analyzed to characterize from a breed point of view 1981 sheep from four ovine breeds (Bellary, Kenguri, Hassan and Mandya) of southern peninsular zone of India. Discriminant Function Analysis was used to distinguish between four breeds by morphometric traits. The population variability showed Kenguri ewes were the largest and heaviest followed by Bellary, Hassan and Mandya whereas Kenguri rams were followed by Bellary, Mandya and Hassan. Overall sexual dimorphism (m/f) was 1.13, with Kenguri males being 47% heavier than females. The coefficient of variation of all traits in four breeds ranged from 4.06% to 30.28%. The flocks and age effects showed a high heterogeneity among females of different flocks. Height at withers was most discriminating trait in separating the four sheep breeds. The Mahalanobis distance of the morphological traits between Kenguri and Mandya sheep was most while the least differentiation was observed between Kenguri and Bellary sheep. Nearest neighbour discriminant analysis showed that most Kenguri sheep were classified into their source population followed by Mandya. However, varied percentages of misclassification between different breeds were observed showing the level of genetic exchange that has taken place between the breeds overtime. UPGMA based dendrogram showed formation of two separate groups; Mandya and Hassan clustered together while Bellary and Kenguri formed other group

Contact tracing for COVID-19 in a healthcare institution: Our experience and lessons learned

During the initial phases of the COVID-19 pandemic contact tracing was used to control spread of the disease. It played a key role in health care institute which continued to work even during lockdown. In this piece of work, we share the lessons learnt from the contact tracing activity done in the health care institution during April to July 2020. The training needs of persons involved in contact tracing, the follow of activities, use of technology, methods to fill the missing gaps were the key lessons learnt. Its documentation supports in setting up contact tracing activity for any emerging infectious disease outbreaks in future