Este modelo está baseado no paper Crokidakis, Nuno. (2020). Data analysis and modeling of the evolution of COVID-19 in Brazil. Para mais detalhes veja o paper completo aqui.
This model was designed from the SIR model(susceptible, infected, recovered) to determine the effect of the covid-19 outbreak on economic outcomes via government policy.
Assumptions
The government policy is triggered when the number of infected is more than ten.
The government policies will take a negative effect on Covid-19 outbreaks and the financial system.
Adjusted parameter: Immunity loss rate can be changed from vaccination rate.
Government policy's parameters
Adjusted parameters: Testing rate(from 0.15 to 0.95), vaccination rate(from 0.3 to 1), travel ban(from 0 to 0.9), social distancing(from 0.1 to 0.8), Quarantine(from 0.1 to 0.9)
Economic's parameters
Fixed parameter: Tourism
Adjusted parameter: Economic growth rate(from 0.3 to 0.5)
Interesting insight
An increased vaccination rate and testing rate will decrease the number of infected cases and have a little more negative effect on the economic system. However, the financial system still needs a long time to recover in both cases.
A simple ABM example illustrating how the SEIR model works. It can be a basis for experimenting with learning the impact of human behavior on the spread of a virus, e.g. COVID-19.
