Find Insights | Insight Maker

covid-19 with vaccination control

Данная модель отражает распространение COVID-19 в России на основе статистики за 2020 год. Модель построена в среде Insight Maker по типу SEIRD (Susceptible–Exposed–Infected–Recovered–Dead), с упрощённой динамикой.

Основные параметры:

-Исходное население (масштабировано): 1000 человек

-Заражённые в начале: 2.12% → 21 человек

-Выздоровевшие (Recovery period): через 14 дней

-Смертность: 1.71% от заболевших

-Потеря иммунитета: не учитывается (0%)

-Exogenous (внешнее заражение): 2.12%

-Transmit: 0.3 (зависит от количества заражённых и восприимчивых)

covid in russia

Сания

5 10 months ago

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

Covid-19 SEIRCID Model

Yudhistira Ramadhan

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

Spread of Covid-19

Abyyu Abdul Azhim Raihan

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

Covid-19

Taleisha Y. Alcorn

In this activity show the system dynamics model or the SDM, we can see the covid-19 flows and transition or links.

SD MODEL FINAL COVID-19

Nurhusin Dassan

Өзіндік жұмысы агенттік

Бердалы Ақерке

COVID-19 model

Takafumi Ogura

Коронавирус в Японии 2021 год агентное моделирование

Samirova Fatima

Tugas Kelompok Teknik Pemodelan dan Simulasi

Самостоятельная работа Covid-19

ERA

SIRD COVID-19 Seoul

Assel

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

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

My Insight 2 covid-19

Кенжебекова Асем

11 months ago

Корея коронавирус 2021

Kambyl Baldaulet

11 months ago

COVID-19 Stakeholder map

Telly Ayangma

өзіндік жұмыс

Нұрсұлтан Нұрлықасым

11 months ago

Variant of the model "COVID-19 spread" made by Anxo-Lois Pereira and Miquel Martínez de Morentin, including reinfection, permanent immunity and Vaccines. Made for the subject of TAED.

COVID-19 spread with reinfeccion, permanent immunity and vaccines

Miquel Mdm

This model indicate indicates the modeling COVID-19 outbreaks and responses from government policies with the effect on the local economy. Model was occurred at Burnie, Tasmania. The model mainly contains three parts: COVID-19 pandemic outbreak, four differences government policies and what the impact on economy from those policies.

Assumptions:

(1) Various variables influence the model, which can result in varied outcomes. The following values are based on an estimate and may differ from actual values. Government initiatives are focused at reducing Covid-19 infections and, as a result, affecting (both positive and negative) economic growth.

(2) 42% of infected people will recovery. 10% of people who are infected will die and the rate relatively higher due to the much old people living in Burnie, Tasmania.

78% of cases get tested.

(3) Government policy will only be implemented when there are ten or more recorded cases. Four government policies have had influences on infection.

(4) The rising number of instances will have a negative impact on Burnie's economic growth.

Insights:

1. As a result of the government's covid 19 rules, fewer people will be vulnerable. Less people going to be susceptible.

2. After the government policy intervention, there is a effectively reduce of infected people.

3. Overall, there is no big differences of economic performance from the graph, might due to the positive and negative effect of economy. And after two weeks, the economy maintained a level of development without much decline.

BMA708 Yanglin Hu

Yanglin Hu

Covid-19 Russia

Ainur Zhumaliyeva

4 months ago