Insight diagram
3бөлім өзіндік
Insight diagram
Modelo epidemiológico simples
SIR: Susceptíveis - Infectados - Recuperados

Dados iniciais do Brasil em 04 Abr 2020
Fonte:
https://www.worldometers.info/coronavirus/country/brazil/
Clone of Modelo SIR simples - Covid-19
Insight diagram
COVID-19 in USA (dyn.m)
Insight diagram
Group_3_7BUIS021W_MODELS-Impact of COVID-19 on civil aviation_CausalLoop
Insight diagram
The Infection / Recovery & Immune / Rate of a Global a Population of 8.2 Billion People.
The Pandemic Management of COVID-19 - Richard A. Estefan
Insight diagram
COVID-19 Model
Insight diagram
This is a mitigated model showing the potential spread of COVID-19 across the healthcare system.

COVID phased community model (Eastern)
Insight diagram
​Tugas 3 Pemodelan Transportasi Laut 
 
STUDI KASUS : Simulasi Penyebaran Virus Corona atau COVID-19 di Indonesia dengan aplikasi Insight Maker
TUGAS 3_IGedeBagusIndraDanendra_04411740000036_Pemodelan Transportasi Laut
Insight diagram
COVID-19 model with hospitalizations and deaths
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Cameroon COVID-19
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Covid-19 in Swithzerland (2022)
Insight diagram
This insight began as a March 22nd Clone of "Italian COVID 19 outbreak control"; thanks to Gabo HN for the original insight. The following links are theirs:

Initial data from:
Italian data [link] (Mar 4)
Incubation estimation [link]

Andy Long
Northern Kentucky University
May 2nd, 2020

This is an update of our model from April 9th, 2020. As we prepare for our final exam, I read a story in The Guardian about Italy's struggle to return to normalcy. The final paragraphs:

During the debate in the Senate on Thursday, the opposition parties grilled Conte. Ex-prime minister Matteo Renzi, who has called for less restraint in the reopening, remarked, “The people in Bergamo and Brescia who are gone, those who died of the virus, if they could speak, they’d tell us to relaunch the country for them, in their honour.”

Renzi’s controversial statement was harshly criticised by doctors who warned that the spread of the disease, which, as of Thursday, had killed almost 30,000 people in the country and infected more than 205,000 [ael: my emphasis], was not over and that a misstep could take the entire country back to mid-March coronavirus levels.

“We risk a new wave of infections and outbreaks if we’re not careful,” said Tullio Prestileo, an infectious diseases specialist at Palermo’s Benefratelli Hospital. “If we don’t realise this, we could easily find ourselves back where we started. In that case, we may not have the strength to get back up again.”

I have since updated the dataset, to include total cases from February 24th to May 2nd. I went to Harvard's Covid-19 website for Italy  and and then to their daily updates, available at github. I downloaded the regional csv file for May 2nd,  which had regional totals (21 regions); I grabbed the column "totale_casi" and did some processing to get the daily totals from the 24th of February to the 2nd of May.

The cases I obtained in this way matched those used by Gabo HN.

The initial data they used started on March 3rd (that's the 0 point in this Insight).

You can get a good fit to the data through April 9th by choosing the following (and notice that I've short-circuited the process from the Infectious to the Dead and Recovered). I've also added the Infectious to the Total cases.

The question is: how well did we do at modeling this epidemic through May 2nd (day 60)? And how can we change the model to do a better job of capturing the outbreak from March 3rd until May 2nd?

Incubation Rate:  .025
R0: 3
First Lockdown: IfThenElse(Days() == 5, 16000000, 0)
Total Lockdown: IfThenElse(Days() >= 7, 0.7,0)

(I didn't want to assume that the "Total Lockdown" wasn't leaky! So it gets successively tighter, but people are sloppy, so it simply goes to 0 exponentially, rather than completely all at once.)

deathrate: .01
recoveryrate: .03

"Death flow": [deathrate]*[Infectious]
"Recovery flow": [recoveryrate]*[Infectious]

Total Reported Cases: [Dead]+[Surviving / Survived]+[Infectious]



Resources:
  * https://annals.org/aim/fullarticle/2762808/incubation-period-coronavirus-disease-2019-covid-19-from-publicly-reported
Clone of Clone of Final Version of Italian COVID-19 outbreak
Insight diagram
SD 2 COVID-19 Policy
Insight diagram
Tugas 3_Thamara Shaifa Anwar_0441174000035_Pemodelan Transportasi Laut

Dosen Pengampu : Dr-Ing Ir. Setyo Nugroho
Clone of Pemodelan COVID-19 di Indonesia
Insight diagram
The System Dynamics Model presents the the COVID-19 status in Puerto Princesa City
Сомшв
Insight diagram

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 Model of COVID-19 Outbreak in Burnie, Tasmania
Insight diagram
covid-19
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COVID-19 in Brazil
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Өздік жұмыс-1
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covid-19 with vaccination control
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Tugas Kelompok Teknik Pemodelan dan Simulasi
Самостоятельная работа Covid-19
Insight diagram
Modelo epidemiológico simples
SIR: Susceptíveis - Infectados - Recuperados

Dados iniciais do Brasil em 04 Abr 2020
Fonte:
https://www.worldometers.info/coronavirus/country/brazil/
Clone of Modelo SIR simples - Covid-19