Epidemiology of a disease provides a thorough and exhaustive analysis of the transmission and control of viral infections. The intended outcome aims to exercise the Artificial Intelligence and Machine Learning models in order to understand the substantial effects of Tuberculosis in India. Our proposal aligns with the vision of National Strategic Plan 2017-2025 and aims towards understanding the challenges for TB prevention. Our aim is to predict the future outline of TB and understand it’s impact through correlation of the factors such as climatic conditions, pollution parameters and population density on most at risk TB diaspora from state to district level. A host of Tuberculosis data segregated in comorbidities (Pediatric, Geriatric, HIV) from the multiple states and districts of India will be correlated with climate data, accustomed to bring optimal precision to the prediction model in order to increase the efficacy of the system. A graphic user interface will be provided to improve the comprehension of the expected solution to assist in geographically visualizing the control of Tuberculosis in India and its effects in the near future.
The intended solution aims to align with the Sustainable Development Goals of The United Nations[3] under Goal 3 of Good Health and Well Being along with the NSP 2017-2025. NSP TB elimination plan has been integrated into the four strategic pillars of “Detect – Treat – Prevent – Build” (DTPB). Our solution ,
- Aims to provide the hotspots of TB in India by analysing the data from previous years
- Determine TB cases to be detected in India with demographic segregation of comorbidities in HIV, Pediatric and Geriatric.
- Provide a User Interface (UI) for easy accessibility and better understanding of calculated results.
There were four major datasets included in the study.
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TB data (The Central Tuberculosis Division, Government Of India 2001-2018)
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Climatic data (Skymet Weather Services, 2000-2018)
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Pollution data (CPCB India, 2001-2015)
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Population data (The National Health Mission’s (NHM) report on "Population projection for India and states 2011-2036")
We are thankful to our college Vivekanand Education Society’s Institute of Technology for considering our project and extending help at all stages needed during our work of collecting information regarding the project. We are deeply indebted to our Principal Dr. (Mrs.) J.M. Nair, for giving us this valuable opportunity to do this project. We express our hearty thanks to them for their assistance without which it would have been difficult in finishing this project synopsis and project review successfully.
This research would not have been possible without the exceptional support by The Tuberculosis Association of India for their generous grant. Nupur Giri would like to extend her gratitude towards the Revised National Tuberculosis Control Programme, Skymet Pvt. Ltd. and the Central Pollution Control Board for sharing their valuable data which forms the basis of this research.
Dr. Mrs. Nupur Giri, HOD Computer Department, V.E.S.I.T. (P.I.)
Mr. Richard Joseph, Assistant Professor, Computer Department, V.E.S.I.T. (Co -P.I.)
Mr. Rohan Ghosalkar, Student, Computer Department, V.E.S.I.T.
Mr. Jay Dulera, Student, Computer Department, V.E.S.I.T.
Mr. Arnav Bagchi, Student, Computer Department, V.E.S.I.T.
Ms.Khushi Makhijani, Student, Computer Department, V.E.S.I.T.