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The System Dynamics Of Covid-19 Pandemic at Puerto Princesa City Palawan
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COVID-19 Week 7
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Covid-19 TAED
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Explanation of the Model

The sample model demonstrate the COVID-19 outbreak in Burnie, Tasmania appearing how the government reacts by executing important health approaches and the impacts on the economy of the region

Assumptions

The economic growth rate is subordinate on the extent of the populace who can be exposed. The number of COVID-19 cases adversely impacts the economy. The government arrangement is activated when the COVID-19 cases are 10 or above

Interesting Insights

1. There is a positive relationship between exposure to COVID- 19 and economic growth rate. Since the more individuals go out, the more trade activity takes place and that ultimately results economic growth

2. Expanding the testing rate results
- Higher cases being recognized
- Strict  government intervention
- Less deaths

BMA708_Assignment3_Md Shihabul Islam_548056
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Covid-19 Model самостоятельная1
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TPS pemodelan covid-19
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COVID-19 Pandemic Systemigram
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Өзіндік жұмыс 2 АҚШ
10 months ago
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Clone of COVID-19
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PROYECTO COVID-19
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New SEIR COVID-19
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Агентное моделирование COVID-19 в Китае
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This stock-flow simulation model is to show Covid-19 virus spread rate, sources of spreading and safety measures followed by all the countries affected around the world.
The simulation also aims at predicting for how much more period of time the virus will persist, how many people could recover at what kind of rate and also about the virus toughness dependence based on its excessive speed, giving rise to bigger numbers day-by-day.
Week-12-Practice
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Системная динамика COVID-19
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COVID-19 SEIR Model for Indonesia
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Modelling of the SARS-Cov-2 viral outbreak using an SEIR model plus specific extensions to model demand for health and care resources.

The model includes biths and deaths, and migration to accommodate import and export of infected individuals from other areas.

Healthcare resources identifies need for hospital beds and critical care.

The model is uses arrays to reflect the different impacts of modelled parameters by age and sex.
Infectious Disease Model (Covid)
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This is the third in a series of models that explore the dynamics of infectious diseases. This model looks at the impact of two types of suppression policies. 

Press the simulate button to run the model with no policy.  Then explore what happens when you set up a lockdown and quarantining policy by changing the settings below.  First explore changing the start date with a policy duration of 60 days.
SIRD Epidemic Model with Suppression Policies
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Model di samping adalah model SEIR yang telah dimodifikasi sehingga dapat digunakan untuk menyimulasikan perkembangan penyebaran COVID-19.
SEIR Model for COVID-19 in Indonesia - v2
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Tentative model of criminal justice reform implemented during the COVID-19 pandemic in Baltimore, MD.
Stock and flow diagram (Baltimore Criminal Justice) Rev. 2
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Covid-19
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Overview:

The COVID-19 Outbreak in Burnie Tasmania shows the process of COVID-19 outbreak, the impacts of government policy on both the COVID-19 outbreak and the GDP growth in Burnie.

Assumptions:

We set some variables at fix rates, including the immunity loss rate, recovery rate, death rate, infection rate and case impact rate, as they usually depend on the individual health conditions and social activities.

It should be noticed that we set the rate of recovery, which is 0.7, is higher than that of immunity loss rate, which is 0.5, so, the number of susceptible could be reduced over time.

Adjustments: (please compare the numbers at week 52)

Step 1: Set all the variables at minimum values and simulate

results: Number of Infected – 135; Recovered – 218; Cases – 597; Death – 18,175; GDP – 10,879.

Step 2: Increase the variables of Health Policy, Quarantine, and Travel Restriction to 0.03, others keep the same as step 1, and simulate

results: Number of Infected – 166 (up); Recovered – 249 (up); Cases – 554 (down); Death – 18,077 (down); GDP – 824 (down).

So, the increase of health policy, quarantine and travel restriction will help increase recovery, decrease confirmed cases, decrease death, but also decrease GDP.

Step 3: Increase the variables of Testing Rate to 0.4, others keep the same as step 2, and simulate

results: Number of Infected – 152 (down); Recovered – 243 (down); Cases – 1022 (up); Death – 17,625 (down); GDP – 824 (same).

So, the increase of testing rate will help to increase the confirmed cases.

Step 4: Change GDP Growth Rate to 0.14, Tourism Growth Rate to 0.02, others keep the same as step 3, and simulate

results: Number of Infected – 152 (same); Recovered – 243 (same); Cases – 1022 (same); Death – 17,625 (same); GDP – 6,632 (up).

So, the increase of GDP growth rate and tourism growth rate will helps to improve the GDP in Burnie.

COVID-19 Outbreak in Burnie Tasmania - Lin Ling 523592