This extends the City Infection Model to include an agent which introduces a vaccine at time step vaccination_step defined in globals.json.
People agents have a likelihood of vaccine_uptake to become vaccinated. By modifying the vaccine_uptake rate, we can demonstrate the effects "anti-vax" misinformation in reducing the impact a vaccine could have in stopping an infection.
When vaccine_uptake is 0.7, most of the susceptible population still contracts the disease.
Comparing a vaccine_uptake of 0.7 with 0.95, almost double the population becomes infected, from 7% to 15%. This is also dependent on the timestep at which the vaccine is introduced.
See also HASH user Ben Glotzer's information spread model and the rumor mill (public health) simulation
Individual behaviors in this simulation have been published independently, including:
