People of India are very susceptible to many infectious diseases like malaria, TB, HIV etc. There are many epidemic models that are used to predict new cases of disease. Some of the popular epidemic models are SI (Susceptible-Infectious), SIR (Susceptible-Infectious-Recovered), SIRS, SIS etc. In this research quarterly data of TB disease in Uttarakhand (India) for 7 years is collected and on th...

The SIR-model is a basic epidemic model that classifies a population into three subgroups: susceptible S, infected I and removed R. This model does not take into consideration the spatial distribution of each subgroup, but considers the total number of individuals belonging to each subgroup. There are many variants of the SIR-model. For studying the spatial distribution, stochastic processes ha...

The nonpopulation conserving SIR (SIR-NC) model to describe the spread of infections in a community is studied. Unlike standard model, this does not assume population conservation. Although similar form SIR, SIR-NC admits closed solution while allowing us mortality and also provides different, arguably more realistic, interpretation parameters. Numerical comparisons with standard, conserving, a...

Memory has a great impact on the evolution of every process related to human societies. Among them, the evolution of an epidemic is directly related to the individuals' experiences. Indeed, any real epidemic process is clearly sustained by a non-Markovian dynamics: memory effects play an essential role in the spreading of diseases. Including memory effects in the susceptible-infected-recovered ...

We model the effect of vaccination on an epidemic which, like current one, exhibits a climate-induced seasonality. Our study is carried out using simple SIR model. One important feature our approach that recruitment: by gradually introducing susceptible individuals we mimic spatial evolution epidemic, which absent in classic SIR. focus number hospital admissions. show any delay campaign results...

The study of epidemics on social networks has attracted considerable attention recently. In this paper, we consider a stochastic SIR (susceptible-->infective-->removed) model for the spread of an epidemic on a finite network, having an arbitrary but specified degree distribution, in which individuals also make casual contacts, i.e. with people chosen uniformly from the population. The behaviour...

The epidemic spreading on arbitrary complex networks is studied in SIR (Susceptible Infected Recovered) compartment model. We propose our implementation of a Naive SIR algorithm for epidemic simulation spreading on networks that uses data structures efficiently to reduce running time. The Naive SIR algorithm models full epidemic dynamics and can be easily upgraded to parallel version. We also p...

An accurate closed-form solution is obtained to the SIR Epidemic Model through use of Asymptotic Approximants (Barlow et. al, 2017, Q. Jl Mech. Appl. Math, 70 (1), 21-48). The created by analytically continuing divergent power series such that it matches long-time asymptotic behavior epidemic model. utility analytical form demonstrated its application COVID-19 pandemic.

In social networks, control of rumor spread is an active area of research. SIR model is generally used to study the rumor dynamics in network while considering the rumor as an epidemic. In disease spreading model, epidemic is controlled by removing central nodes in the network. Full network information is needed for such removal. To have the information of complete network is difficult proposit...