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Somulacion clase 2, retroalimentación + y - , primer versión
Modelo Covid-19 Co
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Systems Project Stock and Flow
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This model estimates the deaths due to COVID19 in Bangalore City. 
Assumptions:
City has a population = 8 Million
Initial infected population = 10
Probability of infection = 8%
Contact rate in population = 6
Average duration of recovery = 10 days
Death rate = 1%
Quarantine rate = 80%
Delay in quarantine = 5 days
COVID-19_SIR_MODEL_No_Quarantine
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Cameroon COVID Sim Cumulative Infections
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The model represents the interaction between influenza and SARS-CoV-2. The data used is for Catalonia region.
Influenza and SARS-CoV-2 interaction v1
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Muertes por COVID-19
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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)
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A simple SI (Susceptible-Infectious) model that captures the dynamics of COVID-19.
SI Model
69 6 months ago
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COVID-19: description des types de population
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COVID-19 modelling with SEIR(D) Model method to predict transmission of COVID-19.
SEIR(D) Model COVID-19
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COVID-19 Model Indonesia
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Covid-19 Pandemie Modell
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Simula las condiciones para una población de 1 millón de habitantes
Covid-19
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Here we have a basic SEIR model and we will investigate what changes would be appropriate for modelling the 2019 Coronavirus 

ECM-Training - SEIR Infectious Disease Model for COVID-19
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[The Model of COVID-19 Pandemic Outbreak in Burnie, TAS]

A model of COVID-19 outbreaks and responses from the government with the impact on the local economy and medical supply. 

It is assumed that the government policy is triggered and rely on reported COVID-19 cases when the confirmed cases are 10 or less. 

Interesting insights
The infection rate will decline if the government increase the testing ranges, meanwhile,  the more confirmed cases will increase the pressure on hospital capacity and generate more demand for medical resources, which will promote government policy intervention to narrow the demand gap and  affect economic performance by increasing hospital construction with financial investment.

The Model of COVID-19 Pandemic Outbreak in Burnie, TAS
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Өзіндік жұмыс агенттік
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Covid-19 model
Covid-19
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Covid-19 Modell
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COVID-19 в Бразилии за 2020-2024 года (динамика заболеваний)
5 months ago
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Tugas 3 Pemodelan Transportasi Laut_Yopy Anjas
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Local transmission - 241
Imported transmission - 9
Recovery - 226
Death Due to Covid19 - 15
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