A framework exploring flood risk management in a developing city, under
the new paradigm of coexist - characterised by broader, system-wide goals, a recognition of the role played and benefits provided by flood processes, and higher levels of flood risk awareness.
This model is comparing healthy and sick residents in Burnie, Tasmania after the Covid-19 Outbreak in 2020. It will also show how the Burnie economy is effected by the disease, how the Government Health Policies are implemented and how they are enforced.
This model is based on the SIR, Susceptible, Infection, Recovery (or
Removed) These are the three possible states related to the members of
the Burnie population when a contagious decease spreads.
The Government/Government Health Policy, played a big part in the successful decrease in Covid-19 infections. The Government enforced the following. - No travel (interstate or international) - Isolation within the residents homes - Social distancing by 1.5m - Quarantine - Non essential companies to be temporarily closed - Limitations on public gatherings - And limits on time and kilometers aloud to travel from ones home within a local community
This resulted in lower reported infection rates of Covid-19 and higher recovery rates. In my opinion: When the first case was reported the Government could have been even faster to enforce these rules to decrease the fatality rates further for the Burnie, population.
Assumption: Government policies were only triggered when 10 cases were recorded. Also, more cases that had been recorded effected the economic growth during this time.
Interesting Findings: In the simulation it shows as the death rates increases towards the end of the week, the rate of testing goes down. You would think that the government would have enforced a higher testing rate over the duration of this time to decrease the number of infections, exposed which would increase the recovery rates faster and more efficiently.
Figures have been determined by the population of Burnie being 19,380 at the time of assignment.
Complex Systems How Burnie Tasmania dealt with Covid-19 Outbreak BMA708
THE 2020 MODEL (BY GUY LAKEMAN) EMPHASIZES THE PEAK IN POLLUTION BEING CREATED BY OVERPOPULATION. WITH THE CARRYING CAPACITY OF ARABLE LAND NOW BEING 1.5 TIMES OVER A SUSTAINABLE FUTURE (PASSED IN 1990) AND NOW INCREASING IN LOSS OF HUMAN SUSTAINABILITY DUE TO SEA RISE AND EXTREME GLOBAL WATER RELOCATION IN WEATHER CHANGES IN FLOODS AND DROUGHTS AND EXTENDED TROPICAL AND HORSE LATTITUDE CYCLONE ACTIVITY AROUND HADLEY CELLS
The World3 model is a detailed simulation of human population growth from 1900 into the future. It includes many environmental and demographic factors.
THIS MODEL BY GUY LAKEMAN, FROM METRICS OBTAINED USING A MORE COMPREHENSIVE VENSIM SOFTWARE MODEL, SHOWS CURRENT CONDITIONS CREATED BY THE LATEST WEATHER EXTREMES AND LOSS OF ARABLE LAND BY THE ALBEDO EFECT MELTING THE POLAR CAPS TOGETHER WITH NORTHERN JETSTREAM SHIFT NORTHWARDS, AND A NECESSITY TO ACT BEFORE THERE IS HUGE SUFFERING.
BY SETTING THE NEW ECOLOGICAL POLICIES TO 2015 WE CAN SEE THAT SOME POPULATIONS CAN BE SAVED BUT CITIES WILL SUFFER MOST.
CURRENT MARKET SATURATION PLATEAU OF SOLID PRODUCTS AND BEHAVIORAL SINK FACTORS ARE ALSO ADDED
Use the sliders to experiment with the initial amount of non-renewable resources to see how these affect the simulation. Does increasing the amount of non-renewable resources (which could occur through the development of better exploration technologies) improve our future? Also, experiment with the start date of a low birth-rate, environmentally focused policy.
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.
Assumptions
·
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.
Insights
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.
Simulation model of COVID outbreak in Burnie Tasmania_Yuchen Zhang_574644
