Application of big data analytics for health care – A study on COVID-19.

The objective of the research is analyzed and help provide a prediction model for similar diseases by using MERS and SARS data. There are examples of companies like BlueDot which used AI analysis of data points from multiple resources and predicted the outbreak in December 2019 mid. Using big data will have its advantages because we can use data from multiple sources and merge them to understand the next COVID19 or similar disease outbreak and predict the possible occurrences in different regions. Contact tracing is essential to predict the outbreak of a disease with data that is collected from different sources, for examples-post with metadata, tags on social media passenger lists, smart cards used in metros, where vehicles were parked, what all places credit and debit cards were used and the travel history. The methodology used is gathering secondary data of contact of what all locations the affected person visited. Data from social media and social networks can be worked upon and reconstructed to predict the outbreak of communicable diseases. A pandemic can be mitigated depending on the ability to identify the affected areas, individuals, and potential hotspots on a global level. Analyzing data using big data analytics from the hotspots, where data is easily available with countries and cities. If this data is modeled mathematically and used with AI, important predictions could be made. Information about the movement of people like done in Taiwan where travel history of a woman suffering from cough and diarrhea was correctly used to diagnose that she had covid19. AI and Big Data will help in preparing us for emergencies. The research will help in tackling the disease in real-time and help governments and organizations to plan and respond to sudden emergencies, lift public health, identify vaccine candidates. The research paper will help researchers to uncover relationships within massive datasets and help them in decision-making. This paper will help them in integrating information from multiple resources and predicting disease outbreaks. [ABSTRACT FROM AUTHOR]