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COVID-19 Stakeholder map
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Modèle simple de causalité entre mesures et impact
COVID-19
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This model indicate indicates the modeling COVID-19 outbreaks and responses from government policies with the effect on the local economy. Model was occurred at Burnie, Tasmania. The model mainly contains three parts: COVID-19 pandemic outbreak, four differences government policies and what the impact on economy from those policies.

 

Assumptions:

(1) Various variables influence the model, which can result in varied outcomes. The following values are based on an estimate and may differ from actual values. Government initiatives are focused at reducing Covid-19 infections and, as a result, affecting (both positive and negative) economic growth.

 

(2) 42% of infected people will recovery. 10% of people who are infected will die and the rate relatively higher due to the much old people living in Burnie, Tasmania.

78% of cases get tested.

 

(3) Government policy will only be implemented when there are ten or more recorded cases. Four government policies have had influences on infection.  

 

(4) The rising number of instances will have a negative impact on Burnie's economic growth.

 

Insights:

1. As a result of the government's covid 19 rules, fewer people will be vulnerable. Less people going to be susceptible.

 

2. After the government policy intervention, there is a effectively reduce of infected people.

 

3. Overall, there is no big differences of economic performance from the graph, might due to the positive and negative effect of economy. And after two weeks, the economy maintained a level of development without much decline.

BMA708 Yanglin Hu
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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.

The initial parametrization is based on the suggested current data. The initial population is set for Catalonia.

Clone of SEIRD 01: COVID-19 spread
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This is a mitigated model showing the potential spread of COVID-19 across the healthcare system.

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Evolution of Covid-19 in Brazil:
A System Dynamics Approach

Villela, Paulo (2020)
paulo.villela@engenharia.ufjf.br

This model is based on Crokidakis, Nuno. (2020). Data analysis and modeling of the evolution of COVID-19 in Brazil. For more details see full paper here.

Clone of Evolution of Covid-19 in Brazil: A System Dynamics Approach
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Ковид-19 в Китае
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Өзіндік жұмыс 1
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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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COVID-19 Systemigram
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Ковид-19 в Германии