Network epidemiology has become a core framework for investigating the role of human contact patterns in the spreadingof infectious diseases.In network epidemiology,one represents the contact structure as a network of...Network epidemiology has become a core framework for investigating the role of human contact patterns in the spreadingof infectious diseases.In network epidemiology,one represents the contact structure as a network of nodes(individuals)connected bylinks(sometimes as a temporal network where the links are not continuously active)and the disease as a compartmental model(whereindividuals are assigned states with respect to the disease and follow certain transition rules between the states).In this paper,we discussfast algorithms for such simulations and also compare two commonly used versions,one where there is a constant recovery rate(the numberof individuals that stop being infectious per time is proportional to the number of such people);the other where the duration of the diseaseis constant.The results show that,for most practical purposes,these versions are qualitatively the same.展开更多
In this paper, a human immunodeficiency virus （HIV） infection model with both the types of immune responses, the antibody and the killer cell immune responses has been introduced. The model has been made more logica...In this paper, a human immunodeficiency virus （HIV） infection model with both the types of immune responses, the antibody and the killer cell immune responses has been introduced. The model has been made more logical by including two delays in the acti-vation of both the immune responses, along with the combination drug therapy. The inclusion of both the delayed immune responses provides a greater understanding of long-term dynamics of the disease. The dependence of the stability of the steady states of the model on the reproduction number R0 has been explored through stability theory. Moreover, the global stability analysis of the infection-free steady state and the infected steady state has been proved with respect to R0. The bifurcation analysis of the infected steady state with respect to both delays has been performed. Numerical simulations have been carried out to justify the results proved. This model is capable of explaining the long-term dynamics of HIV infection to a greater extent than that of the existing model as it captures some basic parameters involved in the system such as immunological delay and immune response. Similarly, the model also explains the basic understanding of the disease dynamics as a result of activation of the immune response toward the virus.展开更多
基金Basic science research program through the national research foundation of Korea(NRF)funded by the ministry of education(2013R1A1A2011947)
文摘Network epidemiology has become a core framework for investigating the role of human contact patterns in the spreadingof infectious diseases.In network epidemiology,one represents the contact structure as a network of nodes(individuals)connected bylinks(sometimes as a temporal network where the links are not continuously active)and the disease as a compartmental model(whereindividuals are assigned states with respect to the disease and follow certain transition rules between the states).In this paper,we discussfast algorithms for such simulations and also compare two commonly used versions,one where there is a constant recovery rate(the numberof individuals that stop being infectious per time is proportional to the number of such people);the other where the duration of the diseaseis constant.The results show that,for most practical purposes,these versions are qualitatively the same.
文摘In this paper, a human immunodeficiency virus （HIV） infection model with both the types of immune responses, the antibody and the killer cell immune responses has been introduced. The model has been made more logical by including two delays in the acti-vation of both the immune responses, along with the combination drug therapy. The inclusion of both the delayed immune responses provides a greater understanding of long-term dynamics of the disease. The dependence of the stability of the steady states of the model on the reproduction number R0 has been explored through stability theory. Moreover, the global stability analysis of the infection-free steady state and the infected steady state has been proved with respect to R0. The bifurcation analysis of the infected steady state with respect to both delays has been performed. Numerical simulations have been carried out to justify the results proved. This model is capable of explaining the long-term dynamics of HIV infection to a greater extent than that of the existing model as it captures some basic parameters involved in the system such as immunological delay and immune response. Similarly, the model also explains the basic understanding of the disease dynamics as a result of activation of the immune response toward the virus.
