These models and simulations have been tagged “COVID”.
Upgrade of Kermack–McKendrick Epidemic SIR Infectious Disease Model (circa 2015) - Metrics by Guy Lakeman
This is a simple SIR infectious diseases 3 stock model with Susceptibles, Infectives and Recovereds stocks. In the initial description the R signified Removed and could include Deaths, Recovered with immunity to infection (Resistant) or those who had fled the epidemic. Note the need to initiate the epidemic by adding a pulse of a single infected person at time 0.
Addition of a slider for susceptibles is equivalent to accumulated total cases
SARS, MERS AND COVID are similar virus types only differing in their sub genus
The COVID outbreak has reached 150,000 infected people
This simulation allows an attempt at predicting how long the virus will persist and its longevity dependence on its high speed massive infection numbers that have reached pandemic proportions
SARS reached 8,000 infected total and ran for 9 months before stopping
MERS 2012 is still killing 8 years later with patients dying even after using interferon to try and cure them
updated 16/3/2020 from 5 years ago
This model is designed for the local government of Burnie, Tasmania, aiming to help with balancing COIVD-19 and economic impacts during a possible outbreak.
The model has been developed based upon the SIR model (Susceptible, Infected, Recovered) model used in epidemiology.
It lists several possible actions that can be taken by the government during a COVID-19 outbreak and provide the economic impact simulation.
The model allow users to Change the government policies factors (Strength of Policies) and simulate the total economic impact.
Interestingly, the government plicies largely help with controlling the COVID outbreak. However, the stronger the policies are, the larger impact on local economy
This model simulates a COVID outbreak occurring at Burnie, Tasmania.
It links the extent to the pandemic with governments intervention policies
aiming to limit the spread of the virus. The other part of the model illustrates
how will the COVID statistics and the government enforcement jointly influence
the economic environment in the community. A number of variables are taken into
account, indicating positive or negative relationship in the infection and the
economy model respectively.
Government takes responsive actions when the
number of acquired cases exceeds 10.
Government’s prompt actions, involving closure
of the state border, lockdown within the city, plans on mandatory vaccination
and testing, effectively control the infection status.
Economic activities are reduced due to stagnation
in statewide tourism, closure of brick-and-mortar businesses, and increased unemployment
rate, as results of government restrictions.
Government’s rapid intervention can effectively reduce the
infected cases. The national vaccination rollout campaign raises vaccination
rate in Australians, and particularly influence the death rate in the infection
model. Please drag the slider of vaccination to a higher rate and run the model
to compare the outcomes.
Although local economy is negatively affected by government restriction
policies, consumer demand in online shopping and government support payments
neutralize the negative impact on economy and maintain the level of economic
activities when infections get controlled.