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Коронавирус в С.Ш.А
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COVID-19 Systems Model
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SEIRSD MODEL
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Propagación y recuperación Covid-19
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Covid-19 SSM
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COVID-19 в Китае
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Өзіндік жұмыс 1 covid-19 Russia
6 months ago
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Cálculo de Número de Infectados do COVID-19
Cálculo de Ocupação de Leitos de UTI
Santa Maria Covid-19
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This is a complex model of COVID-19 outbreak in Burnie Tasmania. It show the effect of government policy to local economic and the impact of Covid-19. 

Assumptions
Government policy can reduce the number of infected, however also would reduce the economic growth. 

Interesting insights
Based on changing the value of government policy, it show that the policy can help to reduce on the number of death and infection. 

Covid-19 Out break
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The model here shows the COVID-19 outbreaks in Burnie Tasmania, which has impacted in the local economy. the relationship between COVID-19 and economic situation has been shown in the graph. Based on the susceptible and exposed rate, the period of spreading can be controlled by lockdown policy. 

Susceptible can be exposed by go out.  resident has a possibility to infect and be infected by others. The infection rate, new cases, immunity rate as well as doing exercise can effect the recovery rate. The economy situation is proportionate to the recovery rate. If there are more recovery rate from the pandemic, the economy situation will recover as well.   


BMA 708--Assignment 3
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COVID-19 Indonesia
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COVID-19 Systemigram
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Өзіндік жұмыс агент
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Disease Dynamics
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Cluster DMALIC
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Динамикалық өзіндік жұмыс
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COVID-19 Systemigram
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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 diários sobre infectados, recuperados e óbitos para diversos países (incluindo o Brasil) podem ser obtidos aqui neste site. 
Dados diários para o município de Juiz de Fora podem ser obtidos no site da Prefeitura.
Juiz de Fora - Covid-19
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Озиндик жумыс, ковид германия
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Brief of the model:

The model predicts the outbreak of COVID-19 in the Burnie, Tasmania area. It is imperative to clarify that this model was developed from the SEIR model (Susceptible, Infected, Infected, Recovered). The spread of this pandemic is driven by a combination of infection rates, mortality rates, and recovery rates from the virus itself, as well as government policies.

For COVID-19 itself, vaccination directly reduces the infection rate, thereby reducing the mortality rate of COVID-19 patients and the reduction of confirmed cases. In other words, if the local population is adequately vaccinated, everyday life, shopping, tourism, and even national borders will be open rather than in a closed border situation.

 

Assumption of the model:

The model simulated based on different rates, including Infecting rate, Death Rate, Test Rate, Immunity Loss Rate and Recovery Rate. And, this model lists six elements of government policy, which including border closure, travel ban, social distancing, business restriction, self-quarantine, and vaccination schedule.

Besides, the model considers three economic entities in the Burnie area, one in the brick-and-mortar industry and online business industry. Government policies have somewhat reduced COVID-19 infections. Still, they have also at the same time, online businesses played an essential role in stimulating local economic activity during the pandemic. At the same time, however, online businesses played an indispensable role in promoting regional economic activity during the pandemic.

 

The prediction model is for reference only, and there may be differences between the actual cases and the model.

 

 

Insights of the model:

Due to the high infection and low recovery rates and timely government policy interventions, the number of susceptible individuals changes dramatically in the first four weeks. However, the number of sensitive individuals continues to decline after this period, but the decline is not significant. Secondly, with the implementation of government policies, the number of suspected patients who tested negative for medical follow-up continued to rise, implying that government policy interventions directly affect COVID-19.

BMA708_Model of COVID-19 in Burnie_Yuanyuan Liao
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жуйелик динамика ковид африка
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SYSTEMS DYNAMICS OF COVID-19
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Modelling the demand for health and care resources resulting from the Covid-19 outbreak using an SEIR model.

Infectious Disease Model (Version 4.0)