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LEIA ANTES DE COMEÇAR

Milhões de pessoas ao redor do mundo estão em QUARENTENA em função da pandemia COVID-19. Se adaptar à quarentena pode ser um PROBLEMA para muitas pessoas.

Nosso DESAFIO é construir um DIAGRAMA CAUSAL que analise este PROBLEMA que é ficar em quarentena. Vamos lá!?


PRIMEIRA TAREFA (até dia 13 de maio)

1) Qual a variável CHAVE que você acha que pode definir o problema? Crie uma VARIÁVEL dentro do folder CHAVE.

2) Quais as outras variáveis SECUNDÁRIAS que estão relacionadas com este problema? Crie variáveis secundárias dentro dos FOLDER que melhor identifica o tipo da variável.


SEGUNDA TAREFA

No dia 15 de maio discutiremos virtualmente no Zoom, as variáveis propostas e faremos um DIAGRAMA CAUSAL RASCUNHO.


TERCEIRA TAREFA

No dia 22 de maio discutiremos virtualmente Zoom, o DIAGRAMA CAUSAL RASCUNHO objetivando construir o DIAGRAMA CAUSAL DEFINITIVO.

Diagrama Causal da Quarentena
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Covid-19 model
Covid-19
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  • tingkat interaksi fisik : 1-10 orang per hari
  • penerapan prokes 0%-100%
  • penanganan pemerintah : minim (<40%) cukup (40%-70%) baik (>70%)


covid-19
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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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This model describes the whole process about government response and economic impact when the covid-19 outbreak in Burnie, Tasmania. When the reported cases increase to a certain level, the government realizes its high risk, then publishes a series of policies to protect the public, such as travel restriction, social distance and quarantine. The economic damage is also severe, especially for tourism and hostility industry and retail industry.

 

Clearly, in the beginning, the number of infected people and death cases increase sharply, but due to government policies and vaccination, it effectively reduces covid-19 cases. For economy, on one hand, the government health policies slow down the pace of growth, on the other hand, the government build vaccine confidence, which leads to more people getting vaccinated, and help the economy back to normal.

Covid-19 outbreak in Burnie Tasmania
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ABM BF
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Part 2 Systems Dynamics- COVID-19
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Covid-19 TAED
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A model of the relationship among covid-19 outbreak and government policy and economic impacts. 

More susceptible people results in more infected people, and then more cases. A greater number of covid-19 cases triggers unemployment and financial crisis. 

COVID-19 outbreak in Burnie Tasmania
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Өзіндік жұмыс Аида 1
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Simulasi persebaran Covid-19 di Provinsi Bali tahun 2020.

Asumsi:
1. Belum ada vaksin karena pada tahun 2020 vaksin belum tersedia.
TA Pemsim - SEIR Covid-19 Model
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Covid-19 Model самостоятельная1
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SIR Modeling of Covid-19 in Cameroon
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COVID-19 Week 7
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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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Here we have a basic SEIR model and we will investigate what changes would be appropriate for modelling the 2019 Coronavirus 

SEIR Infectious Disease Model for COVID-19
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COVID-19 model with hospitalizations and deaths
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Agent based Modeling Simulation for Pandemic COVID-19 Disease
Агентская модель
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This stock-flow simulation model is to show Covid-19 virus spread rate, sources of spreading and safety measures followed by all the countries affected around the world.
The simulation also aims at predicting for how much more period of time the virus will persist, how many people could recover at what kind of rate and also about the virus toughness dependence based on its excessive speed, giving rise to bigger numbers day-by-day.
covid-19 in France
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Өздік жұмыс 2-бөлім
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Самостоятельная работа
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Air Quality and the Effects it has on Human Health in America Post COVID-19
12 months ago
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COVID-19 SEIR Model for Indonesia