Seventeen classical swine fever virus (CSFV) isolates recovered during the period of 3 years (2006:2008) from India were subjected to nucleotide sequencing in the 50 untranslated region (UTR). For genetic typing, 150 nucleotides within this region were used. For better epizootiological understanding, 39 nucleotide sequences of the above region, including 13 Indian CSFV sequences, available either in the Genbank or published literature were also included in the study. Based on the phylogenetic analysis, the Indian isolates could be grouped in to two subgroups, viz., 1.1 and 2.2. The study also revealed predominance of subgroup 1.1 and involvement of viruses of more than one subgroup in an outbreak.
In our country the existing system of collection, management and reporting of animal health information is primitive and results in the loss of information and time without benefiting the end user or disease control process. As such there is an urgent need of dynamic relational database software, which can store, transmit and analyse retrospective / prospective disease and livestock related data. Accurate information about the health status of a nation's animal population is critical in the fight against livestock diseases and this forms the basis for initiating disease control strategies through optimal utilization of meager funds, veterinary resources and manpower.
The project on "Weather based animal disease forecast" (WB_ADF) launched during the year 2000 developed national livestock disease forecasting system for the first time in the country. In this process retrospective and secondary animal health and related data generated by passive surveillance program carried out by the state animal husbandry and other institutions or departments in the country were collected. The wide range of data collected is organized into relational database with GIS support. This has also facilitated the demarcation of disease specific eco-pathozones of the country based on the high, medium and low disease frequencies observed over the long period. The "Animal Health Information System through Disease Monitoring and Surveillance (AHIS_DMS)" generated the active surveillance data through village surveys carried out adopting stratified sampling techniques. The prevalence of the diseases was estimated with 95% confidence. The combined outcome of these two projects was the innovative National Animal Disease Referral Expert System (NADRES) developed as web based dynamic and interactive livestock disease relational database supported by Geographic Information System (GIS) that serves as an Epidemiology software. This software addresses the needs of data collection, transmission, retrieval, analysis of critical reporting of disease events as and when they occur and useful for field veterinarians, administrators, technocrats, research personnel, farmers, veterinary colleges and students.