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@article{185968,
        author = {Shreyas Vivek and Raghav Pai},
        title = {Epidemiological Modelling and Outbreak Prediction using Hyperbolic Geometry},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {5},
        pages = {4096-4107},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=185968},
        abstract = {This paper introduces a novel approach to modeling disease transmission using hyperbolic geometry, specifically the Poincar´e disk model. Traditional models like Susceptible-Infected-Recovered (SIR) assume homogeneous populations, which oversimplifies real-world interactions. By incorporating hyperbolic distance, the Poincar´e disk model captures spatial clustering and irregular social interactions, offering a more realistic framework for studying epidemics. Simulations of the first wave of COVID-19 in India were performed using both the Poincar´e disk and SIR models. Results show that the Poincar´e disk model better captures localized transmission patterns and spatial dynamics, providing deeper insights into how diseases spread through structured populations. This approach highlights the importance of accounting for social network structures in epidemic modeling, offering valuable guidance for targeted public health interventions such as localized lockdowns and vaccination strategies.Our findings demonstrate the advantages of hyperbolic geometry in epidemiological modeling, with potential applications for improving future outbreak predictions and interventions.},
        keywords = {},
        month = {November},
        }