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This is more or less the classical Bass diffusion model [5] that explains how new products get adopted in a population: Potential adopters turn into adopters being affected either by advertising or promotion (i.e., as innovators) or by social interaction ("word of mouth") with adopters (i.e., as imitators).
The basic model for diffusion can also be used to model the spread of infectious diseases (→SIR). Since the disease is ultimately spread by contact with an infected person, the fractionalAdoptionRate in this case should be zero.
While the structure in principle folllows Sterman's implementation [3, chapter 9], the component has been put in a more general form. We have to distinguish the following subgroups that make up the total population of potential contacts for social interaction:
portA
portB
Depending upon the structural parameter nextStageIsInfluencing
we may choose to take the converted adopters out of the group of influencers, e.g., a freshly converted adopter may not yet be entusiastic enough, while more elaborate epidemic models like the SEIR model distinguish an exposed stage, that is not yet infectious.
The behavior of the component is exactly specified by the following equations:
totalPopulation = potentialAdopters + otherPopulation + adopters + otherAdopters
adoptionRate = potentialAdopters · fractionalAdoptionRate
conversionRate = potentialAdopters·(otherAdopters [+ adopters])·adoptionFraction·contactRate / totalPopulation
totalAdoptionRate = adoptionRate + conversionRate
Name | Description |
---|---|
DataOutPort | Output connector |
DataInPort | Input connector |
DataOutPort
and DataInPort
changed to encapsulated expandable connector
classes in v2.1.0.unspecified
in v2.1.0.