Selected article for: "basic model and infected people"

Author: Michal Ben-Nun; Pete Riley; James Turtle; David P. Bacon; Steven Riley
Title: National and Regional Influenza-Like-Illness Forecasts for the USA
  • Document date: 2018_4_27
  • ID: cheiabv0_1
    Snippet: Basic model 98 The DICE package has been designed to implement meta-population epidemic modeling 99 on an arbitrary spatial scale with or without coupling between the regions. Our model 100 for coupling between spatial regions follows ref [24] . We assume a system of coupled 101 S-I-R equations (susceptible-infectious-recovered) for each spatial region. In this 102 scenario, the rate at which a susceptible person in region j becomes infectious (t.....
    Document: Basic model 98 The DICE package has been designed to implement meta-population epidemic modeling 99 on an arbitrary spatial scale with or without coupling between the regions. Our model 100 for coupling between spatial regions follows ref [24] . We assume a system of coupled 101 S-I-R equations (susceptible-infectious-recovered) for each spatial region. In this 102 scenario, the rate at which a susceptible person in region j becomes infectious (that is 103 transitions to the I compartment in region j) depends on: (1) the risk of infection from 104 those in the same region j, (2) the risk of infection from infected people from region i 105 who traveled to region j, and (3) the risk of infection encountered when traveling from 106 region j to region i. To account for the three mechanisms of transmission, ref [24] 107 defined the force of infection, or the average rate that susceptible individuals in region i 108 become infected per time step as:

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