One of the most important lessons from the Covid 19 pandemic is early detection, which would significantly reduce the impact of an outbreak. With the proliferation of the internet, a new potential for data sources has evolved. An increase in advent of technology, also means it is necessary for a mechanism to monitor the amount of useful and socially relevant data from the social media platforms, especially twitter. The proposed system’s objective would be to estimate the magnitude and level of disease overtime and also estimate the overall mental health status of people in that particular area, and provide assistance to healthcare authorities to provide required medical services and organise awareness camps based on the possible extent of any disease in an area, and ensure safety of the citizens from communicable diseases
- To predict the impact of a particular disease in a particular area, using various NLP (Natural Language Processing) models, after data acquisition using twitter API.
- To evaluate current trends, as well as predict future trends of a particular disease, combining real time streaming data and observed CDC (centres for disease control and prevention data.
- To predict the overall mental health of the people in a particular area using supervised and unsupervised learning, considering that users of social media do not constitute the whole of the population, with the speculation that few people might not post publicly about health status, and people in discomfort might not be active users.