Insight diagram
Өздік жұмыс-1
Insight diagram
Өзіндік жұмыс агент
Insight diagram
covid-19
Insight diagram

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.

MM0 - SEIRD 01: COVID-19 spread
Insight diagram
COVID-19 in USA (ag.m) - 2021
Insight diagram
This model demonstrates the impacts of reduced air traffic in Austria due to the new coronavirus on Austrian overall emissions.
Covid-19 impact on emissions (air transport) in Austria
Insight diagram
Covid-19 SSM
Insight diagram
This is a mitigated model showing the potential spread of COVID-19 across the healthcare system.

COVID phased community model DEMO V1.1 Eastern
Insight diagram
The model illustrate the Covid-19 outbreaks.
Ph_Covid19SDM_Shanea Betorin
Insight diagram
March 22nd Clone of "Italian COVID 19 outbreak control"; thanks to Gabo HN for the insight.

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

Andy Long
April 9th, 2020

I have since updated the dataset, to include total cases from February 24th to April 9th.
I went to                                                                                                 
https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/KDFYZW                           
and downloaded the archive for April 9th:                                                                 
https://dataverse.harvard.edu/file.xhtml?persistentId=doi:10.7910/DVN/KDFYZW/C2HSTK&version=19.0          

I dug through the files, and found the file dpc-covid19-ita-regioni.csv, which had regional totals (21 regions); I grabbed the column "totale_casi" and used some lsp code to get the daily totals from the 24th of February til the 9th of April.

The good news is that the cases I obtained in this way matched those used by Gabo HN.

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

You can get a good fit to the data 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.

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
MAT375 Version of Italian COVID 19 outbreak control
Insight diagram
Tugas 1_Akhdhan Muhammad Muaz_04411740000017_Pemodelan Transportasi Laut

Dosen Pengampu: Dr-Ing Ir. Setyo Nugroho
Pemodelan Virus Covid-19 di Indonesia
Insight diagram
Tugas Kelompok Teknik Pemodelan dan Simulasi
Самостоятельная работа Covid-19
Insight diagram
My Insight 2 covid-19
Insight diagram
COVID-19 model
Insight diagram
This diagram will map out the spread of the Coronavirus (SAR-CoV-2) and its complexities of health care.
Covid-19
Insight diagram

Here we have a basic SEIR model and we will investigate what changes would be appropriate for modelling the 2019 Coronavirus.

We add simple containment meassures that affect two paramenters, the Susceptible population and the rate to become infected.

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

The questions that we want to answer in this kind of models are not the shape of the curves, that are almost known from the beginning, but, when this happens, and the amplitude of the shapes. This is crucial, since in the current circumstance implies the collapse of certain resources, not only healthcare.

The validation process hence becomes critical, and allows to estimate the different parameters of the model from the data we obtain. This simulation approach allows to obtain somethings that is crucial to make decisions, the causality. We can infer this from the assumptions that are implicit on the model, and from it we can make decisions to improve the system behavior.

Yes, simulation works with causality and Flows diagrams is one of the techniques we have to draw it graphically, but is not the only one. On https://sdlps.com/projects/documentation/1009 you can review soon the same model but represented in Specification and Description Language.

Clone of Clone of Clone of SEIRD 02: COVID-19 spread with containment measures
Insight diagram
Ковид Африка
Insight diagram
COVID-19 Stakeholder map
Insight diagram
SIR model with deaths by disease. We are working on the speficication of this model for it to represent the global development of the COVID-19 pandemic. This project is ongoing under the responsibility of PPGEA Pandemics Task Force Team, from Universidade Federal de Viçosa - UFV.

More details to be added.

SIR with deaths
Insight diagram
Covid-19 in Belarus
6 months ago
Insight diagram
Simplified Model_v2
Insight diagram
COVID-19 in Japan СРС-1
6 months ago