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The System Dynamics Model presents the the COVID-19 status in Puerto Princesa City

Clone of Clone of Ph_Covid19SDM_AngelKateCacayan

Salima

Covid-19 SSM

Si Senor

The SEIRS(D) model for the purpose of experimenting with the phenomena of viral spread. I use it for COVID-19 simulation.

Clone of SEIR - COVID-19 (v.1)

sanjeev k

covid-19

ChenTzuJung

Contamination COVID-19

larry

SEIR COVID-19

Daffa Muhammad Romero

Spread of Covid-19

Abyyu Abdul Azhim Raihan

Covid-19

Даниил Варшавский

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 COVID-19 spread

Antoni Jubes

covid-19 with vaccination control

Li kuan wei

Model of Covid-19 outbreak in Burnie, Tasmania

This model was designed from SIR model(susceptible, infected, revovered) to find out the effect of covid-19 outbreak into economic outcomes via government policy.

Assumptions

The government policy is triggered when number of infected is more than ten.

The government policies will take negative effect into Covid-19 outbreaks and financial system

Parameters

We set some fixed and adjusted variables.

Covid-19 outbreak's parameter

Fixed parameters: Infection rate, Background disease, recovery rate.

Adjusted parameter: Immunity loss rate can be change from vaccination rate.

Government policy's parameters

Adjusted parameters: Testing rate(from 0.15 to 0.95), vaccination rate(from 0.3 to 1), travel ban(from 0 to 0.9), social distancing(from 0.1 to 0.8), Quarantine(from 0.1 to 0.9)

Economic's parameters

Fixed parameter: Tourism

Adjusted parameter: Economic growth rate(from 0.3 to 0.5)

Interesting insight

Increase vaccination rate and testing rate will decrease the number amount of infected case and a little bit more negative effect to economic system. However economic system still need a long time to recover in both cases.

BMA708_Assignment 3_ndkvo_520272_COVID-19 outbreak and Burnie economy

KV

COVID-19 model

Takafumi Ogura

Covid-19 Russia

Ainur Zhumaliyeva

5 months ago

Tugas Kelompok Teknik Pemodelan dan Simulasi

Самостоятельная работа Covid-19

ERA

This diagram will map out the spread of the Coronavirus (SAR-CoV-2) and its complexities of health care.

Covid-19

Taleisha Y. Alcorn

COVID-19 SD model

Aman Verma

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

Luis Schmidt

3

My Insight 2 covid-19

Кенжебекова Асем

12 months ago

COVID-19 Systems Model

Anuschka Steiner

Modèle simple de causalité entre mesures et impact

COVID-19

Philippe Vallat

Dieses Causal Loop Diagramm (CLD) versucht in vereinfachter Weisse die Wesentliche Dynamik des Mars-CoV-2 zu veranschaulichen. Der Motor hinter den Infektionen ist offensichtlich eine selbstverstärkende Rückkopplungsschleife, und ausschlaggebend in diesem Bezug ist der R-Wert. Wenn der R-Wert unter 1 liegt, dann heisst das, dass eine infizierte Person während des Zeitraums, in dem sie infektiös ist, weniger als eine andere Person infiziert. Liegt der Wert über 1, dann steckt die Infizierte mehr als eine andere Person an, und das Virus verbreitet sich exponentiell. Die Schleifen, die blaue Pfeile enthalten, sind negative Rückkopplungsschleifen – sie bremsen die Verbreitung des Virus. Das Diagramm suggeriert, dass der R-Wert als Schlüssel zur Kontrolle der Verbreitung des Virus dienen könnte. Sollte der Wert über 1 steigen, so müssten Schutzmassnahem eingeführt werden. Ist der Wert unter 1, dann sind die negativen Schleifen dominierend und einige Massnahmen könnten gelockert werden.

Eine Systemische Sicht auf Covid-19

Hanns-Jürgen Hodann

Simplified Model_v2

Sage Gibbons

3

Explanation

This model shows the COVID-19 outbreak in Burnie and how the government policy impacts the economy. The possible phases when the infectious disease spreads in Burnie can be labelled as Susceptible, Infection and Recovery, which are main factors in the model. It is concluded that the government policy can reduce the infectious disease and also the impact in the overall economy.

Assumption

The Government Healthy Policy will affect the decrease in the infection and economy growth rate at the same time.

The Government Health Policy is only triggered when there are more than 10 cases

The increase in number of COVID-19 cases can affect negatively towards the economic growth.

Interesting Insights:

The Government's vaccination promote will reduce the possibility of spreading the infectious disease.

When vaccination rate increase, the dead, infected people and susceptible group will all decrease. This reveals that the crucial role in government's vaccination promote program.

When there is more than 10 confirmed cases, the government policies can effectively reduce the infections and the overall economic activities.

BMA708_Assignment 3_Joleen Tanjaya

Joleen Tanjaya

өзіндік жұмыс

Нұрсұлтан Нұрлықасым

12 months ago