Modeling and Dynamics of Infectious Disease: Big Data Analytics

The rapid increase in population creates an issue in handling and analyzing the population data for the traditional data base management system. So Big data came into figure to solve the issue. The main components of Big data are Hadoop and Map-Reduce. Big data is more efficient in comparison to the traditional data base system due to some of its basic features like Velocity, Veracity, Volume, Verity and Value. Infectious disease is the illness resulting from infection. This is caused by infectious agents including Viruses, Prions, Bacteria, Nematodes etc. Population dynamics is a branch of life science which includes the study of population size and age composition of dynamic system and the biological and environmental process managing them. This proposed paper consider the Dengue Fever as an infectious disease and divides the population dynamic into three parts i.e. High Vulnerable, Mid vulnerable, Low vulnerable to Dengue. And also suggest the preventive measure respectively like Forced preventive for high vulnerable, Efficient preventive measure for mid vulnerable and delayed preventive measure for low vulnerable areas by utilizing the benefits of big data.