Literature DB >> 23345705

Temporal duration and event size distribution at the epidemic threshold.

V J Haas1, A Caliri, M A da Silva.   

Abstract

The epidemic event, seen as a nonequilibrium dynamic process, is studied through a simple stochastic system reminiscent of the classical SIR model. The system is described in terms of global and local variables and was mainly treated by means of Monte Carlo simulation; square lattices N×N, with N=23, 51, 100, 151, and 211 were used. Distinct extensive runs were performed and then classified as corresponding to epidemic or non-epidemic phase. They were examined with detail through the analysis of the event duration and event size; illustrations, such as density-like plots in the space of the model's parameters, are provided. The epidemic/non-epidemic phase presents smaller/larger relative fluctuations, whereas closer to the threshold the uncertainty reaches its highest values. Far enough from the threshold, the distribution φ(t) of the events time duration t shows a step-like appearance. However at the threshold line it shows an exponential behavior of the form φ (t) ∼ exp (-ωt); the same behavior is observed for the event size distribution. These results help to explain why the approach to epidemic threshold would be hard to anticipate with standard census data.

Entities:  

Keywords:  Epidemic size; Monte Carlo; global/local variables; phase; scaling; threshold

Year:  1999        PMID: 23345705      PMCID: PMC3456028          DOI: 10.1023/A:1005115117228

Source DB:  PubMed          Journal:  J Biol Phys        ISSN: 0092-0606            Impact factor:   1.365


  4 in total

1.  Temporal and spatial scales in epidemiological concepts.

Authors:  D W Onstad
Journal:  J Theor Biol       Date:  1992-10-21       Impact factor: 2.691

2.  Influence of time-dependent rates of mass transfer on the kinetics of domain growth.

Authors: 
Journal:  Phys Rev Lett       Date:  1992-02-03       Impact factor: 9.161

3.  Power laws governing epidemics in isolated populations.

Authors:  C J Rhodes; R M Anderson
Journal:  Nature       Date:  1996-06-13       Impact factor: 49.962

4.  Are critical phenomena relevant to large-scale evolution?

Authors:  R V Solé; J Bascompte
Journal:  Proc Biol Sci       Date:  1996-02-22       Impact factor: 5.349

  4 in total
  3 in total

1.  The predictive power of r(0) in an epidemic probabilistic system.

Authors:  D Alves; V J Haas; A Caliri
Journal:  J Biol Phys       Date:  2003-03       Impact factor: 1.365

2.  On the spread of epidemics in a closed heterogeneous population.

Authors:  Artem S Novozhilov
Journal:  Math Biosci       Date:  2008-08-03       Impact factor: 2.144

3.  Efficient method for comprehensive computation of agent-level epidemic dissemination in networks.

Authors:  Gilberto M Nakamura; Ana Carolina P Monteiro; George C Cardoso; Alexandre S Martinez
Journal:  Sci Rep       Date:  2017-01-20       Impact factor: 4.379

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.