Computational applications of extended SIR models: A review focused on airborne pandemics
T Lazebnik - Ecological Modelling, 2023 - Elsevier
Epidemiological-Mathematical models are powerful tools for estimating the course of a
pandemic and exploring different scenarios through pandemic intervention policies (PIPs) …
pandemic and exploring different scenarios through pandemic intervention policies (PIPs) …
Merits and limitations of mathematical modeling and computational simulations in mitigation of COVID-19 pandemic: A comprehensive review
A Afzal, CA Saleel, S Bhattacharyya, N Satish… - … Methods in Engineering, 2022 - Springer
Mathematical models have assisted in describing the transmission and propagation
dynamics of various viral diseases like MERS, measles, SARS, and Influenza; while the …
dynamics of various viral diseases like MERS, measles, SARS, and Influenza; while the …
Vaccination effect conjoint to fraction of avoided contacts for a Sars-Cov-2 mathematical model
S Allegretti, IM Bulai, R Marino… - Mathematical …, 2021 - dergipark.org.tr
In this paper, we consider a modified SIR (susceptible-infected-recovered/removed) model
that describes the evolution in time of the infectious disease caused by Sars-Cov-2 (Severe …
that describes the evolution in time of the infectious disease caused by Sars-Cov-2 (Severe …
New perspective on the conventional solutions of the nonlinear time‐fractional partial differential equations
The role of integer and noninteger order partial differential equations (PDE) is essential in
applied sciences and engineering. Exact solutions of these equations are sometimes difficult …
applied sciences and engineering. Exact solutions of these equations are sometimes difficult …
Diffusion–reaction compartmental models formulated in a continuum mechanics framework: application to COVID-19, mathematical analysis, and numerical study
The outbreak of COVID-19 in 2020 has led to a surge in interest in the research of the
mathematical modeling of epidemics. Many of the introduced models are so-called …
mathematical modeling of epidemics. Many of the introduced models are so-called …
Machine learning and OLAP on big COVID-19 data
In the current technological era, huge amounts of big data are generated and collected from
a wide variety of rich data sources. These big data can be of different levels of veracity in the …
a wide variety of rich data sources. These big data can be of different levels of veracity in the …
Learning the dynamics of physical systems from sparse observations with finite element networks
We propose a new method for spatio-temporal forecasting on arbitrarily distributed points.
Assuming that the observed system follows an unknown partial differential equation, we …
Assuming that the observed system follows an unknown partial differential equation, we …
[HTML][HTML] Epi-DNNs: Epidemiological priors informed deep neural networks for modeling COVID-19 dynamics
Differential equations-based epidemic compartmental models and deep neural networks-
based artificial intelligence (AI) models are powerful tools for analyzing and fighting the …
based artificial intelligence (AI) models are powerful tools for analyzing and fighting the …
SARS-CoV-2 rate of spread in and across tissue, groundwater and soil: A meshless algorithm for the fractional diffusion equation
The epidemiological aspects of the viral dynamic of the SARS-CoV-2 have become
increasingly crucial due to major questions and uncertainties around the unaddressed …
increasingly crucial due to major questions and uncertainties around the unaddressed …
Multi-regional COVID-19 epidemic forecast in Sweden
Y **ng, O Gaidai - Digital health, 2023 - journals.sagepub.com
The novel coronavirus disease 2019 (COVID-19) is a contagious disease with high
transmissibility to spread worldwide, reported to present a certain burden on worldwide …
transmissibility to spread worldwide, reported to present a certain burden on worldwide …