This model shows the COVID-19 outbreaks in Burnie and the Government intervention to alleviate the crisis and also how is the intervention affect the economy.
It is assumed that the Government intervention is triggered when the COVID-19 case is equal to or more than 10.
Government intervention - lock down the state, suppress the development of COVID-19 effectively. It is related to most of people stay at home to reduce the exposure in public area.
On the other hand, it also bring the economy of Burnie in the recession, as no tourists, no dining out activities and decrease in money spending in the city.
Clone of Burnie COVID-19 outbreaks and economic impacts_Pui Chu Daisy Cheung 524767
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.
Parameters:
We set some fixed and adjusted variables.
Covid-19 outbreak's parameter
Fixed parameter: Background
disease.
Adjusted parameters: Infection rate, recovery rate. 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.
BMA708_Assignment 3_Nguyen Dang Khoa Vo_520272_COVID-19 outbreak and Burnie economy
This model shows COVID-19 outbreak in Burnie have some impact for local economy situation and government policy. The main government policy is lockdown during the spreading period which can help reduce the infected rate, and also increase the test scale to help susceptible confirm their situation.
Variables;
Infection rate, Death rate, Recovery rate, test rate, susceptible, immunity rate, economy growth rate
These variables are influenced by different situation.
When cases over 10, government will implement lockdown policy.
Conclusion;
When cases increase too much , they will influence the economic situation.
Interesting insights:
If the recover rate is higher, more people will recover from the disease. It seems to be a positive sign. However, it would lead to a higher number of recovered people and more susceptible. As a result, there would be more cases, and would have a negative impact on the economic growth.
Model of COVID-19 Outbreak in Burnie, Tamania ( WANTING BAO, 536865)
This simulation is about the covid 19 virus and its ability to evolve and mutate in order to survive killing humans in the process. Here you will see that the infected doesn't stop however the number of recovery is increasing at a higher speed and the susceptible increases slowly.
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
Scratchpad of Upgrade of Kermack–McKendrick Epidemic SIR Infectious Disease Model - Metrics by Guy Lakeman
Clique aqui para ver um vídeo com a apresentação sobre a construção e uso deste modelo. É recomendável ver o vídeo num computador de mesa para se poder ver os detalhes do modelo.
Dados diários sobre infectados, recuperados e óbitos para diversos países (incluindo o Brasil) podem ser obtidos aqui neste site.
Dados diários para o município de Juiz de Fora podem ser obtidos no site da Prefeitura.
