In an exciting development, Dr Anirban Ghosh, Dr Anuj Deshpande, and Dr Sibendu Samanta, Assistant Professors from the Department of Electronics and Communication Engineering, have recently achieved a significant milestone with the publication of their paper titled “An Indigenous Computational Platform for Nowcasting and Forecasting Non-Linear Spread of COVID-19 across the Indian Sub-continent: A Geo-Temporal Visualization of Data” in the esteemed journal, Procedia Computer Science.
The paper focuses on the development of a state-of-the-art computational platform specifically tailored for nowcasting and forecasting the non-linear spread of COVID-19 across the Indian sub-continent. This pioneering work promises to offer valuable insights into the geo-temporal visualisation of data related to the COVID-19 pandemic, with potential implications for public health interventions and policy decisions.
The publication of this paper serves as a testament to the innovative research being conducted by the faculty members at the Department of Electronics and Communication Engineering. Their dedication and expertise in the field have not only contributed to advancing scientific knowledge but also hold considerable promise for making a real-world impact in the ongoing fight against the COVID-19 pandemic. We extend our congratulations to Dr Anirban Ghosh, Dr Anuj Deshpande, and Dr Sibendu Samanta for this remarkable accomplishment and look forward to witnessing the continued impact of their research in addressing critical challenges facing the world today.
Abstract
The rapid spread of the COVID-19 pandemic necessitated unprecedented collective action against coronavirus disease. In this light,we are proposing a novel online platform for the visualisation of epidemiological data incorporating social determinants for understanding the patterns associated with the spread of COVID- 19. The current AI computational platform combines modelling methodologies along with temporal, geospatial visualisation of COVID-19 data, providing real-time sharing of graphic analytical simulation of vulnerable hotspots of recurrent (nowcasting) and emergent (forecasting) infections visualised on a spatiotemporal scale on geoportals. The proposed study will be a secondary data analysis of primary data accessed from the national portal (Indian Council of Medical Research (ICMR)) incorporating 766 districts in India. Epidemiological data related to spatiotemporal visualisation of the demographic spread of COVID-19 will be displayed using a compartmental socio-epidemiological model, reproduction number R, epi-curve diagrams, as well as choropleth maps for different levels of administrative and development units at the district levels.
Explanation of the Research in Layperson’s Terms
The rapid spread of COVID-19 required quick and coordinated action. To aid the process, we have created a new online platform to help visualise COVID-19 data, including social factors that affect its spread. Our platform uses advanced computer models and shows COVID-19 data over time and across locations. It allows real-time sharing of visual analyses, highlighting areas at risk for current and future infections. The effectiveness of the platform lies in the fact that it is not limited to COVID-19. It can be suitably modified and employed for capturing similar trends for any future pandemic.
Title of the Research in the Citation Format
Priya Ranjan, Dhruva Nandi, Karuna Nidhi Kaur, Rohan Rajiv, Kumar Dron Shrivastav, Anirban Ghosh, Anuj Deshpande, Sibendu Samanta, Rajiv Janardhanan, “An Indigenous Computational Platform for Nowcasting and Forecasting Non-Linear Spread of COVID-19 across the Indian Sub-continent: A Geo-Temporal Visualization of Data”, Procedia Computer Science, Volume 235, 2024, Pages 496-505, ISSN 1877-0509,
https://doi.org/10.1016/j.procs.2024.04.049
Practical Implementation and Social Implications Associated
As mentioned earlier, the platform can be used to present real-time data analysis and identify emerging and current hotspots of the COVID-19 pandemic. However, the beauty or robustness of the platform lies in the fact that it can be suitably adapted for similar analysis for any future pandemic with minimum effort.
Collaborations
- University of Petroleum and Energy Studies, Energy Acres, Dehradun, Uttarakhand, India
- SRM Medical College Hospital and Research Centre, SRMIST, Kattankulathur, Tamil Nadu, 603203, India
- Amity Institute of Public Health, Amity University, Noida, Uttar Pradesh, 201303, India
Future Research Plans
The future plan includes improving the visual and graphical presentation of the platform to provide more insightful and intuitive information. Aggregation of data from other international databases would further augment the effectiveness of the platform by not limiting it to only the national scenario.