This presentation is a statistical model of the COVID-19 pandemic generated using approximate data.

• The population is originally one million people

• The simulation lasts 1095 days, or 3 years

• Estimated mortality rate is 1% (This falls roughly in line with the US average)

• This model includes reinfection, the assumption that immunity to the disease may be lost after a period of months.

• This model includes vaccines of varying effective levels. Loss of immunity from vaccines has the same rate of immunity loss.

• This model is not meant to be accurate, it is meant to be interesting.

P = Population. The total population that is vulnerable to the virus.

I = Infected. The members of the population currently infected by the Virus

R = Recovered. The members of the population temporarily immune to the virus.

D = Dead.

    P = .999999

    I = .000001

    R = 0.0

    D = 0.0

    ROR = .1428571429

    R0 = 2.0
    
    RIL = .00273972603

    VE = .00136983014

    DR = .01

A virus with a high R0 value quickly spreads throughout the population. Within 175 days, 60% of the population has already had the virus, and 4% have died. As the recovered population loses immunity, there will continue to be a small number of cases until there are only single digit cases by day 365. There continue to be a limited number of cases until the proportion of the population which is immune drops low enough for the virus to take hold again. The virus appears to resurge when the immunity percentage drops below 35%. Another 1% of the population dies between day 900 and 1000.

This may be considered a fairly serious version of COVID-19, since the death chance is shared evenly across the population, rather than concentrated in a small but extremely vulnerable portion. It is relatively simple to keep a small part of the population safe from an infectious disease, but much more complicated if the disease effects the entire population evenly. This simulation also does not factor time to develop a vaccine, or issues in the vaccine or its distribution.

In this model, the disease will slowly destroy the population. There is no vaccine, it is more infectious, and everyone will always be somewhat susceptible.

This slide is our least accurate, and simulates periodic outbreaks of disease from outside exposure. The scale and time of the death rate is actually fairly accurate past the initial spike. A growth rate of 2% is also included, which keeps the total population stable throughout the simulation.