Using Big Data For Computational Epidemiology In India

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Shweta Chaudhary

Abstract

The myriad epidemic data and factors contributing to epidemic outbreaks in India are scattered so unmanageably that it hardly leads to any conclusions or analysis for future predictions. In a developing country like India, the dual burden of communicable and chronic diseases hits a large population every year without sparing enough time to Government Bodies to issue any health advisories in time and develop adequate vaccinations/medications to control the epidemic. Big Data poses as a promising technology to help combat epidemics by making combined use of enormous sources of data like physical health data and trends on the open web. Computational epidemiology relies on the access and analysis of massive health data. When analyzed, these provide for possibilities of constructing flexible and dynamic systems with attractive real-time properties; such uses include early warnings, halting or mitigation of disease spread, simulations and scenario-based reasoning relating to health policies, and real-time decision support to first responders. Keywords: Big Data, Analytics, Public Data, Computational Epidemiology, Health advisory

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