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The System Dynamics Model presents the the COVID-19 status in Сhina

Жангир Шаханов Covid-19 in china

Шаханов Жангир

8 8 months ago

Modelo Epidemiológico para os Casos de Covid-19

Insigh Authors:

Luis Felipe (UFSM)

Carlos Heitor (UFSM)

Paulo Vilella (UFJF)

Modelo UFSM - COVID-19

Luis Felipe Dias Lopes

COVID-19

Наурызбай Мерейлі

5

S-I-R covid-19 model

KRISTIAN SABATINO

The System Dynamics Model presents the the COVID-19 status in Puerto Princesa City

Ph_Covid19SDM_AngelKateCacayan

angel kate cacayan

36

Model description:

This model is designed to simulate the Covid-19 outbreak in Burnie, Tasmania by estimating several factors such as exposed population, infection rate, testing rate, recovery rate, death rate and immunity loss. The model also simulates the measures implemented by the government which will impact on the local infection and economy.

Assumption:

Government policies will reduce the mobility of the population as well as the infection. In addition, economic activities in the tourism and hospitality industry will suffer negative influences from the government measures. However, essential businesses like supermarkets will benefit from the health policies on the contrary.

Variables:

Infection rate, recovery rate, death rate, testing rate are the variables to the cases of Covid-19. On the other hand, the number of cases is also a variable to the government policies, which directly influences the number of exposed.

The GDP is dependent on the variables of economic activities. Nonetheless, the government’s lockdown measure has also become the variable to the economic activities.

Interesting insights:

Government policies are effective to curb infection by reducing the number of exposed when the case number is greater than 10. The economy becomes stagnant when the case spikes up but it climbs up again when the number of cases is under control.

Sample Model of COVID-19 outbreak in Burnie Tasmania by Yim Fong Ng (544885)

Chrissie Ng

Covid-19 Russia

Инкар Мухамедкаримова

last month

Introduction:

This model demonstrates the COVID-19 outbreak in Burnie, Tasmania. It shows how the government policy tries to reduce the spread of COVID-19 whilst also impacting the local economy.

Assumptions:

This model has four variables that influence the number of COVID-19 cases: infection rate, immunity loss rate, recovery rate and death rate.

In order to reduce the pandemic spread, in this model, assume the government released six policies when Burnie COVID-19 cases are equal or over 10 cases. Policies are vaccination promotion, travel restriction to Burnie, quarantine, social distance, lockdown and testing rate.

Government policies would reduce the pandemic. However, it decreases economic growth at the same time. In this model, only list three variable that influence local economic activities.

Travel restrictions and quarantine will reduce Burnie tourism and decrease the local economy. On the other hand, quarantine, social distance, lockdown allow people to stay at home, increasing E-commerce business.

As a result, policies that cause fewer COVID-19 cases also cause more considerable negative damage to the economy.

Interesting insights:

One of the interesting findings is that the government policy would reduce the COVID-19 spread significantly if I adjust the total government policies are over 20% (vaccine promotion, travel restriction, quarantine, social distance, lockdown), 3560 people will die, then no more people get COVID-19.

However, if I change the total government policy to less than 5%, the whole Burnie people will die according to the model. Therefore, we need to follow the polices, which saves our lives.

BMA708 assignment3 - Model of COVID-19 outbreak in Burnie

Zhiyuan Wang

Covid-19 TAED

Jose

COVID-19 SEIR Model for Indonesia

Daffa Muhammad Romero

COVID-19

ERMAKOV SEMEN

Covid-19 in Germany

Мадияр Сейтмуратов

Covid-19 pandemi

Ali Berkay Çetin

4

Системная динамика COVID-19

Barabarabara Berebere

4 weeks ago

Check how different times of recovery and deths in cases of covid-19 infulence 2 key mortality indicators:

Overall mortalityr ate (ratio of all deaths to all cases)

Resolved cases mortality rate (ratio of all deaths to recovered cases)

Assumed delays are:

5 weeks for recovery cases

2 weeks for death cases

Delays are built into conveyor stocks, so cannot be adjusted by slider

keep in mind Insigth uses similar but made-up numbers and linear flow of new cases (in opposition to exponential in real world)

Understanding Covid-19 mortality

Cezary Zając

Introduction:

This model aims to show that how the Tasmania government's COVID-19 policy can address the spread of the pandemic and in what way these policies can damage the economy.

Assumption:

Variables such as infection rate, death rate and the recovery rate are influenced by the actual situation.

The government will implement stricter travel bans and social distant policies as there are more cases.

Government policies reduce infection and limit economic growth at the same time.

A greater number of COVID-19 cases has a negative effect on the economy.

Interesting insights:

A higher testing rate will make the infection increase and the infection rate will slightly increase as well.

Government policies are effective to lower the infection, however, they will damage the local economy. While the higher number of COVID-19 cases also influences economic activities.

Model of COVID-19 outbreak in Burnie_Guoyu Shen

Guoyu Shen

SIR Modeling of Covid-19 in Cameroon

Briana Soriano

The complex model reflects the COVID-19 outbreak in Burnie, Tasmania. The model explains how the COVID-19 outbreak will influence the government policies and economic impacts. The infected population will be based on how many susceptible, infected, and recovered individuals in Burnie. It influences the probability of infected population meeting with susceptible individuals.

The fatality rate will be influenced by the elderly population and pre-existing medical conditions. Even though individuals can recover from COVID-19 disease, some of them will have immunity loss and become part of the susceptible individuals, or they will be diagnosed with long term illnesses (mental and physical). Thus, these variables influence the number of confirmed cases in Burnie and the implementation of government policies.

The government policies depend on the confirmed COVID-19 cases. The government policies include business restrictions, lock down, vaccination and testing rate. These variables have negative impacts on the infection of COVID-19 disease. However, these policies have some negative effects on commercial industry and positive effects on e-commerce and medical industry. These businesses growth rate can influence the economic growth of Burnie with the economic

Most of the variables are adjustable with the slider provided below. They can be adjusted from 0 to 1, which illustrates the percentages associated with the specific variables. They can also be adjusted to three decimal points, i.e., from 0.1 to 0.001.

Assumptions

- The maximum population of Burnie is 20000.
- The maximum number of infected individuals is 100.
- Government policies are triggered when the COVID-19 cases reach 10 or above.
- The government policies include business restrictions, lock down, vaccination and testing rates only. Other policies are not being considered under this model.
- The vaccination policy implemented by the government is compulsory.
- The testing rate is set by the government. The slider should not be changed unless the testing rate is adjusted by the government.
- The fatality rate is influenced by the elderly population and pre-existing medical conditions only. Other factors are not being considered under this model.
- People who recovered from COVID-19 disease will definitely suffer form immunity loss or any other long term illnesses.
- Long term illnesses include mental illnesses and physical illnesses only. Other illnesses are not being considered under this model.
- Economic activities are provided with an assumption value of 1000.
- The higher the number of COVID-19 cases, the more negative impact they have on the economy of Burnie.

Interesting Insights

A higher recovery rate can decrease the number of COVID-19 cases as well as the probability of infected population meeting with susceptible persons, but it takes longer for the economy to recover compared to a lower recovery rate. A higher recovery rate can generate a larger number of people diagnosed with long term illnesses.

Testing rate triggers multiple variables, such as government policies, positive cases, susceptible and infected individuals. A lower testing rate can decrease the COVID-19 confirmed cases, but it can increase the number of susceptible people. And a higher testing rate can trigger the implementation of government policies, thus decreasing the infection rate. As the testing rate has a strong correlation with the government policies, it can also influence the economy of Burnie.

BMA708 COVID-19 Outbreak in Burnie, Tasmania

ching tung li

4

Model di samping adalah model SEIR yang telah dimodifikasi sehingga dapat digunakan untuk menyimulasikan perkembangan penyebaran COVID-19.

Modified by Rio dan Pras

SEIR Model for COVID-19 in Indonesia - case study SLEMAN

prazi.antoro

13

Agent based Modeling Simulation for Pandemic COVID-19 Disease

Covid-19(ABM)_VHK

Venkata Habiram Koppaka

8

COVID-19 SEIR Model (Indonesia values)

Daffa Muhammad Romero

16

Агентное моделирование по COVID-19

Наурызбай Мерейлі

Examen - Covid-19 3ra ola

Stalin Celis

Sike Liu's model on COVID-19 & Burnie Economy

This model contains three parts, the first part stimulates the COVID-19 pandemic outbreak in Burnie; the second part describes possible government policies on pandemic control; and the third part examines the possible negative impact on economy growth from those policies.

Assumptions:

1. The state boarder has already been closed and all new arrivals in Burnie need to enter a fixed period of quarantine. And the quarantine rate measures the strength of the government policy on quarantine (such as length and method).

2. Patient zero refers to the initial number of undetected virus carriers in the community.

3. Government policies such as social distancing, compulsory mask and lock down could effectively reduce community’s exposure to the virus.

4. Social distancing and compulsory mask will be triggered when COVID-19 cases reach and beyond 10 and lock down will be triggered when cases reach and beyond 1000.

4. High vaccine rate, on the other hand, could effectively reduce the exposed people’s chance of getting infected.

5. Only when vaccine rate reaches 0.6 and beyond, then the spread of COVID-19 will be significantly slowed.

6. Vaccine can’t 100% prevent the infection of the virus.

7.The infected people will need to be tested so that they could be counted as COVID-19 cases and the test rate decides the percentage of infected people being tested.

8. After people recover, there are chances of them losing immunity and the immunity lost rate measures that.

9. The COVID-19 cases could also be detected at quarantine facilities, and the quarantine process will effectively reduce the Infection and exposure rate.

10. Social distancing and compulsory mask wearing are considered as light restrictions in this model and will have less impact on both supply and demand side, and lockdown is considered as heavy restriction which will have strong negative impact on economy growth in this model.

11. In this model, light restrictions will have more negative impacts on the demand side compared to the supply side.

12. In this model, both supply side and demand side will power the economy growth.

Interest hints:

The vaccine could significantly reduce the spread of COVID-19 and effectively reduce the number of COVID-19 cases.

The number of the COVID-19 cases will eventually be stabilized when the number of susceptible is running out in a community (reached community immunity).

Quarantine could slightly reduce the cases numbers, but the most effective way is to reduce the number of new arrivals.

BMA708_Assignment 3_Sike Liu_567871_COVID-19 outbreak and Burnie economy

Sike Liu