Insight diagram
Das SEIRS(D)-Modell zum Simulieren der COVID-19 - Epidemie.
SEIR - COVID-19 (v.1) von Remigiusz Kinas
Insight diagram
Covid-19 in England
Insight diagram
Simulating virus infecting a body after entering, replicating inside living cells, and the body's immune response towards the virus
VirusModel
Insight diagram
COVID-19 S&F PT1
Insight diagram
spread model of COVID-19
Insight diagram
This is a mitigated model showing the potential spread of COVID-19 across the healthcare system.

COVID phased community model
Insight diagram
Germany COVID-19
Insight diagram
Systemigram Model Building Exercise (COVID-19)
Insight diagram
agent base of covid-19 in Republic France 2019-2023
Insight diagram
Environment, Health, & Business
Covid-19 Systemigram
Insight diagram
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
Insight diagram
Самостоятельная работа COVID-19 2023г.
Insight diagram
The SEIRS(D) model for the purpose of experimenting with the phenomena of viral spread. I use it for COVID-19 simulation.
SEIR - COVID-19 (v.1)
Insight diagram
Tugas mata kuliah pemodelan modifikasi model Covid -19 an. Faqih, Aji, dan Wahyu
Tugas Modifikasi Model Covid-19
Insight diagram
Covid-19 in Italy
Insight diagram
 Develop a basic Systemigram / Rich Picture to tell the story of covid 19 mitigation 
Systemigram Covid-19
Insight diagram
Өзіңдік жұмыс дұрысы
Insight diagram
SIRD COVID-19 Хубэй
Insight diagram
Recent COVID-19 Outbreak in Burnie Tasmania
Insight diagram
SEIR Model_John
Insight diagram

Here we have a basic SEIR model and we will investigate what changes would be appropriate for modelling the 2019 Coronavirus 

MscT CSE - SEIR Infectious Disease Model for COVID-19
Insight diagram
Системная динамика COVID-19
Insight diagram

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
Insight diagram
Influenza vs COVID-19