Search Results for author: S. Triambak

Found 4 papers, 0 papers with code

Towards predicting COVID-19 infection waves: A random-walk Monte Carlo simulation approach

no code implementations13 Jan 2022 D. P. Mahapatra, S. Triambak

In light of the present COVID-19 pandemic, there is a pressing need to better understand observed epidemic growth with multiple peak structures, preferably using first-principles methods.

A new logistic growth model applied to COVID-19 fatality data

no code implementations20 Nov 2021 S. Triambak, D. P. Mahapatra, N. Mallick, R. Sahoo

Results: Unlike other logistic growth models, our presented model is shown to consistently make accurate predictions of peak heights, peak locations and cumulative saturation values for incomplete epidemic growth curves.

A random walk Monte Carlo simulation study of COVID-19-like infection spread

no code implementations17 Jun 2020 S. Triambak, D. P. Mahapatra

For $l = \langle r \rangle$, we get intermediate power-law growth exponents that are in general agreement with available data from China.

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