Map-Reduce based Modeling and Dynamics of Infectious Disease

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. 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. Day by day the disease are growing and becoming harmful to the society irrespective of treatments that are available. Infectious disease 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 an infectious disease i.e Dengue Fever and divides the population dynamic into three parts those are High Vulnerable, Mid vulnerable, Low vulnerable to Dengue. Then suggest the preventive measure 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.