Epidemic modelling by ripple-spreading network and genetic algorithm [PDF]
, 2013 Mathematical analysis and modelling is central to infectious disease epidemiology. This paper, inspired by the natural ripple-spreading phenomenon, proposes a novel ripple-spreading network model for the study of infectious disease transmission.
Hu, Xiao-Bing +3 more
core +1 more source
The Effects of School Closures on Influenza Outbreaks and Pandemics: Systematic Review of Simulation Studies [PDF]
, 2014 Background School closure is a potential intervention during an influenza pandemic and has been investigated in many modelling studies. Objectives To systematically review the effects of school closure on influenza outbreaks as predicted by simulation ...
Babatunde Olowokure (226511) +19 more
core +1 more source
Mathematical modeling of the spread of the coronavirus under strict social restrictions
Mathematical Methods in the Applied Sciences, EarlyView., 2021 We formulate a simple susceptible‐infectious‐recovery (SIR) model to describe the spread of the coronavirus under strict social restrictions. The transmission rate in this model is exponentially decreasing with time. We find a formula for basic reproduction function and estimate the maximum number of daily infected individuals.
Mo'tassem Al‐arydah +3 more
wiley +1 more source
Integrating stochasticity and network structure into an epidemic model [PDF]
, 2009 While the foundations of modern epidemiology are based upon deterministic models with homogeneous mixing, it is being increasingly realized that both spatial structure and stochasticity play major roles in shaping epidemic dynamics.
Dangerfield, C. E. +4 more
core +1 more source
Disease prevention versus data privacy : using landcover maps to inform spatial epidemic models [PDF]
, 2012 The availability of epidemiological data in the early stages of an outbreak of an infectious disease is vital for modelers to make accurate predictions regarding the likely spread of disease and preferred intervention strategies.
Michael J. Tildesley (123224) +7 more
core +1 more source
Spatio-temporal epidemic modelling using additive-multiplicative intensity models [PDF]
, 2008 An extension of the stochastic susceptible-infectious-recovered (SIR) model is proposed in order to accommodate a regression context for modelling infectious disease surveillance data. The proposal is based on a multivariate counting process specified by
Höhle, Michael
core +1 more source
Pair-based likelihood approximations for stochastic epidemic models
, 2021 Fitting stochastic epidemic models to data is a non-standard problem because data on the infection processes defined in such models are rarely observed directly. This in turn means that the likelihood of the observed data is intractable in the sense that
Kypraios, Theodore +2 more
core +1 more source
COVID-19 Spread Simulation in a Crowd Intelligence Network
International Journal of Crowd Science, 2022 In this paper, the Crowd Intelligence Network Model is applied to the simulation of epidemic spread. This model combines the multi-layer coupling network model and the two-stage feedback member model to study the epidemic spread mechanisms under multiple-
Linzhi Shan, Hongbo Sun
doaj +1 more source
Episimmer : Epidemic Simulation Platform
, 2022 Episimmer is an Epidemic Simulation Platform. It aims to provide Decision and Recommendation Support to help answer your questions related to policies and restrictions during an epidemic. Using simulation techniques widely applied to other fields, we can
Enaganti, Inavamsi, Dheeshjith, Surya
core +1 more source
From Markovian to pairwise epidemic models and the performance of moment closure approximations [PDF]
, 2011 Many if not all models of disease transmission on networks can be linked to the exact state-based Markovian formulation. However the large number of equations for any system of realistic size limits their applicability to small populations.
Kiss, Istvan Z. +26 more
core +1 more source