Insight diagram
Curso de Dinâmica de Sistemas com Insight Maker
Modelo Epidemiológico
Prof. Dr. Paulo Villela

Este modelo está baseado no paper Crokidakis, Nuno. (2020). Data analysis and modeling of the evolution of COVID-19 in Brazil. Para mais detalhes veja o paper completo aqui.
Curso DS: Modelo Epidemiologico
12 3 months ago
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Variant of the model "COVID-19 spread" made by Anxo-Lois Pereira and Miquel Martínez de Morentin, including reinfection, permanent immunity and Vaccines. Made for the subject of TAED.
COVID-19 spread with reinfeccion, permanent immunity and vaccines
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Modelo epidemiológico simples
SIR: Susceptíveis - Infectados - Recuperados

Clique aqui para ver um vídeo com a apresentação sobre a construção e uso deste modelo.  É recomendável ver o vídeo num computador de mesa para se poder ver os detalhes do modelo.


Dados iniciais de infectados, recuperados e óbitos para diversos países (incluindo o Brasil) podem ser obtidos aqui neste site.
Modelo SIR simples - Covid 19
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Tugas Kelompok Teknik Pemodelan dan Simulasi
Clone of SIR Model Covid-19
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системное Америка
12 months ago
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COVID-19 in Japan СРС-1
4 months ago
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Covid-19 in Belarus
5 months ago
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Коронавирус в Японии 2021 год агентное моделирование
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Ковид-19 в Германии
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Pada Tugas mata kuliah Metode Penyelesaian Masalah dan Pemodelan , ditugaskan untuk membuat pemodelan penyebaran COVID-19 di negara yang dipilih, dan pada simulasi ini merupakan negara Indonesia

Dosen Pengampu :
Simulasi Pemodelan Penyebaran COVID-19 di Indonesia di Indonesia Dari Data Vaksinasi
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Clone of Demo_Group3_COVID-19
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COVID-19 Systemigram
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Өзіндік жұмыс 1
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Model Corona
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COVID-19 Systemigram
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KO - COVID-19 Systemigram
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Description

Model of Covid-19 outbreak in Burnie, Tasmania

This model was designed from the SIR model(susceptible, infected, recovered) to determine the effect of the covid-19 outbreak on economic outcomes via government policy.

Assumptions

The government policy is triggered when the number of infected is more than ten.

The government policies will take a negative effect on Covid-19 outbreaks and the financial system.

Parameters

We set some fixed and adjusted variables.

Covid-19 outbreak's parameter

Fixed parameters: Infection rate, Background disease, recovery rate.

Adjusted parameter: Immunity loss rate can be changed from vaccination rate.

Government policy's parameters

Adjusted parameters: Testing rate(from 0.15 to 0.95), vaccination rate(from 0.3 to 1), travel ban(from 0 to 0.9), social distancing(from 0.1 to 0.8), Quarantine(from 0.1 to 0.9)

Economic's parameters

Fixed parameter: Tourism

Adjusted parameter: Economic growth rate(from 0.3 to 0.5)

Interesting insight

An increased vaccination rate and testing rate will decrease the number of infected cases and have a little more negative effect on the economic system. However, the financial system still needs a long time to recover in both cases.

Untitled Insight
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COVID-19 in India
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Systemigram for Soft Systems Methodology (SSM) applied to investigating the complexities of the COVID-19 crisis.
SSM for COVID-19
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This Model was first developed from the SIR model (Susceptible, Infected, Recovered). It was designed to explore relationship between the government policies regarding the COVID-19 and its influences on the economy as well as well-being of local residents. 

 

Assumptions:

Government policies will be triggered when reported COVID-19 case are 10 or less;

Government policies reduces the infection and economic growth at the same time.

 


Interesting Insights:

In the first two weeks, the infected people showed an exponential growth, in another word, that’s the most important period to control the number of people who got affected. 

 

Clone of Clone of Model of COVID-19 Outbreak in Burnie, Tasmania