VARIABILITY FOR CARRIER-BORNE EPIDEMICS AND REED–FROST MODELS INCORPORATING UNCERTAINTIES AND DEPENDENCIES FROM SUSCEPTIBLES AND INFECTIVES

2010 ◽  
Vol 24 (2) ◽  
pp. 303-328 ◽  
Author(s):  
Eva María Ortega ◽  
Laureano F. Escudero
Keyword(s):  
Risk Assessment ◽  
Epidemic Model ◽  
Epidemic Models ◽  
Random Environments ◽  
Random Parameters ◽  
Infection Rates ◽  
Disease Propagation ◽  
Increasing Concave Order ◽  
Special Cases ◽  
Frost Model

This article provides analytical results on which are the implications of the statistical dependencies among certain random parameters on the variability of the number of susceptibles of the carrier-borne epidemic model with heterogeneous populations and of the number of infectives under the Reed–Frost model with random infection rates. We consider dependencies among the random infection rates, among the random infectious times, and among random initial susceptibles of several carrier-borne epidemic models. We obtain conditions for the variability ordering between the number of susceptibles for carrier-borne epidemics under two different random environments, at any time-scale value. These results are extended to multivariate comparisons of the random vectors of populations in the strata. We also obtain conditions for the increasing concave order between the number of infectives in the Reed–Frost model under two different random environments, for any generation. Variability bounds are obtained for different epidemic models from modeling dependencies for a range of special cases that are useful for risk assessment of disease propagation.

On the size distribution for some epidemic models

1980 ◽  
Vol 17 (4) ◽  
pp. 912-921 ◽  
Author(s):  
Ray Watson
Keyword(s):  
Size Distribution ◽  
Epidemic Model ◽  
Time Scale ◽  
Epidemic Models ◽  
Random Time ◽  
Scale Transformation ◽  
Asymptotic Approximations

We consider the standard epidemic model and several extensions of this model, including Downton's carrier-borne epidemic model. A random time-scale transformation is used to obtain equations for the size distribution and to derive asymptotic approximations for the size distribution for each of the models

scholarly journals Coupling of Two SIR Epidemic Models with Variable Susceptibilities and Infectivities

2007 ◽  
Vol 44 (01) ◽  
pp. 41-57 ◽  
Author(s):  
Peter Neal
Keyword(s):  
Size Distribution ◽  
Random Graph ◽  
Epidemic Model ◽  
Epidemic Models ◽  
Final Size ◽  
Sir Epidemic ◽  
Novel Approach ◽  
Stochastic Epidemic ◽  
Sir Epidemic Models ◽  
Variable Susceptibility

The variable generalised stochastic epidemic model, which allows for variability in both the susceptibilities and infectivities of individuals, is analysed. A very different epidemic model which exhibits variable susceptibility and infectivity is the random-graph epidemic model. A suitable coupling of the two epidemic models is derived which enables us to show that, whilst the epidemics are very different in appearance, they have the same asymptotic final size distribution. The coupling provides a novel approach to studying random-graph epidemic models.

Large deviation principle for epidemic models

2017 ◽  
Vol 54 (3) ◽  
pp. 905-920 ◽  
Author(s):  
Etienne Pardoux ◽  
Brice Samegni-Kepgnou
Keyword(s):  
Epidemic Model ◽  
Additional Assumption ◽  
Large Deviation Principle ◽  
Large Deviation ◽  
Poisson Processes ◽  
Epidemic Models ◽  
Sir Epidemic Model ◽  
Deviation Principle ◽  
Sir Epidemic ◽  
Time Changes

Abstract We consider a general class of epidemic models obtained by applying the random time changes of Ethier and Kurtz (2005) to a collection of Poisson processes and we show the large deviation principle for such models. We generalise the approach followed by Dolgoarshinnykh (2009) in the case of the SIR epidemic model. Thanks to an additional assumption which is satisfied in many examples, we simplify the recent work of Kratz and Pardoux (2017).

On the size distribution for some epidemic models

1980 ◽  
Vol 17 (04) ◽  
pp. 912-921 ◽  
Author(s):  
Ray Watson
Keyword(s):  
Size Distribution ◽  
Epidemic Model ◽  
Time Scale ◽  
Epidemic Models ◽  
Random Time ◽  
Scale Transformation ◽  
Asymptotic Approximations

We consider the standard epidemic model and several extensions of this model, including Downton's carrier-borne epidemic model. A random time-scale transformation is used to obtain equations for the size distribution and to derive asymptotic approximations for the size distribution for each of the models

A note on the cost of carrier-borne, right-shift, epidemic models

1976 ◽  
Vol 13 (4) ◽  
pp. 652-661 ◽  
Author(s):  
Richard J. Kryscio ◽  
Roy Saunders
Keyword(s):  
Epidemic Models ◽  
Sufficient Condition ◽  
Initial Number ◽  
Expected Number ◽  
Expected Cost ◽  
Special Cases ◽  
The Cost ◽  
Special Case

We establish a sufficient condition for which the expected area under the trajectory of the carrier process is directly proportional to the expected number of removed carriers in the class of carrier-borne, right-shift, epidemic models studied by Severo (1969a). This result generalizes the previous work of Downton (1972) and Jerwood (1974) for some special cases of these models. We use the result to compute expected costs in the carrier-borne model due to Downton (1968) when it is unlikely that all the susceptibles will be infected. We conclude by showing that for the special case considered by Weiss (1965) this treatment of the expected cost is reasonable for populations with a large initial number of susceptibles.

scholarly journals Epidemic Models with Immunization and Mutations on a Finite Population

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Elcio Lebensztayn
Keyword(s):  
Phase Transition ◽  
Random Walks ◽  
Complete Graph ◽  
Epidemic Model ◽  
Limit Theorems ◽  
Finite Population ◽  
Epidemic Models ◽  
Epidemic Size ◽  
Stochastic Epidemic ◽  
Stochastic Epidemic Model

We propose two variants of a stochastic epidemic model in which the disease is spread by mobile particles performing random walks on the complete graph. For the first model, we study the effect on the epidemic size of an immunization mechanism that depends on the activity of the disease. In the second model, the transmission agents can gain lives at random during their existences. We prove limit theorems for the final outcome of these processes. The epidemic model with mutations exhibits phase transition, meaning that if the mutation parameter is sufficiently large, then asymptotically all the individuals in the population are infected.

scholarly journals Global Behaviors of a Class of Discrete SIRS Epidemic Models with Nonlinear Incidence Rate

2014 ◽  
Vol 2014 ◽  
pp. 1-18 ◽  
Author(s):  
Lei Wang ◽  
Zhidong Teng ◽  
Long Zhang
Keyword(s):  
Incidence Rate ◽  
Endemic Equilibrium ◽  
Epidemic Models ◽  
Asymptotically Stable ◽  
Nonlinear Incidence Rate ◽  
Globally Asymptotically Stable ◽  
Nonlinear Incidence ◽  
General Incidence Rate ◽  
Special Cases ◽  
Disease Free

We study a class of discrete SIRS epidemic models with nonlinear incidence rateF(S)G(I)and disease-induced mortality. By using analytic techniques and constructing discrete Lyapunov functions, the global stability of disease-free equilibrium and endemic equilibrium is obtained. That is, if basic reproduction numberℛ0<1, then the disease-free equilibrium is globally asymptotically stable, and ifℛ0>1, then the model has a unique endemic equilibrium and when some additional conditions hold the endemic equilibrium also is globally asymptotically stable. By using the theory of persistence in dynamical systems, we further obtain that only whenℛ0>1, the disease in the model is permanent. Some special cases ofF(S)G(I)are discussed. Particularly, whenF(S)G(I)=βSI/(1+λI), it is obtained that the endemic equilibrium is globally asymptotically stable if and only ifℛ0>1. Furthermore, the numerical simulations show that for general incidence rateF(S)G(I)the endemic equilibrium may be globally asymptotically stable only asℛ0>1.

On the asymptotic distribution of the maximum number of infectives in epidemic models by immigration

1994 ◽  
Vol 31 (3) ◽  
pp. 606-613 ◽  
Author(s):  
V. M. Abramov
Keyword(s):  
Asymptotic Distribution ◽  
Epidemic Model ◽  
Epidemic Models ◽  
Death Process ◽  
Birth And Death Process ◽  
Initial Number ◽  
Martingale Approach ◽  
Distribution Of The Maximum ◽  
Non Linear

This paper considers the asymptotic distribution of the maximum number of infectives in an epidemic model by showing that, as the initial number of susceptibles converges to infinity, the process of infectives converges almost surely to a birth and death process. The model studied here is more general than usual (see e.g. Bailey (1975), Bharucha-Reid (1960), Keilson (1979)) in that it incorporates immigration and the limiting birth and death process is non-linear. The main novelty of the present paper is the martingale approach used to prove the above-mentioned convergence.

On the asymptotic distribution of the maximum number of infectives in epidemic models by immigration

1994 ◽  
Vol 31 (03) ◽  
pp. 606-613
Author(s):  
V. M. Abramov
Keyword(s):  
Asymptotic Distribution ◽  
Epidemic Model ◽  
Epidemic Models ◽  
Death Process ◽  
Birth And Death Process ◽  
Initial Number ◽  
Martingale Approach ◽  
Distribution Of The Maximum ◽  
Non Linear

This paper considers the asymptotic distribution of the maximum number of infectives in an epidemic model by showing that, as the initial number of susceptibles converges to infinity, the process of infectives converges almost surely to a birth and death process. The model studied here is more general than usual (see e.g. Bailey (1975), Bharucha-Reid (1960), Keilson (1979)) in that it incorporates immigration and the limiting birth and death process is non-linear. The main novelty of the present paper is the martingale approach used to prove the above-mentioned convergence.

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