Selected article for: "individual probability and infection rate"

Author: Chandrika Prakash Vyasarayani; Anindya Chatterjee
Title: New approximations, and policy implications, from a delayed dynamic model of a fast pandemic
  • Document date: 2020_4_14
  • ID: ca92pbvi_6
    Snippet: In the above equations, the free parameters are interpreted as follows:β is the infection rate, m is the density of contacts, γ is the self-recovery rate, p is the probability of identifying and isolating an infected individual, and α is the rate of immunity loss. We have not introduced any simplifications of our own so far. We note, first, that E and Q in equations (2) and (4) are influenced by S and I along with their delayed values, but E a.....
    Document: In the above equations, the free parameters are interpreted as follows:β is the infection rate, m is the density of contacts, γ is the self-recovery rate, p is the probability of identifying and isolating an infected individual, and α is the rate of immunity loss. We have not introduced any simplifications of our own so far. We note, first, that E and Q in equations (2) and (4) are influenced by S and I along with their delayed values, but E and Q do not themselves influence S, I and R. In other words, E and Q are slave variables, and we henceforth ignore them.

    Search related documents:
    Co phrase search for related documents
    • immunity loss and infection rate: 1, 2
    • infection rate and self recovery: 1, 2, 3, 4, 5
    • infection rate and self recovery rate: 1