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
Tugas Kelompok Teknik Pemodelan dan Simulasi
Самостоятельная работа Covid-19
Insight diagram
SIRD COVID-19 Seoul
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 Russia
5 months ago
Insight diagram
My Insight 2 covid-19
Insight diagram
COVID-19 Systems Model
Insight diagram
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
Insight diagram
Modèle simple de causalité entre mesures et impact
COVID-19
Insight diagram

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
Insight diagram
Simplified Model_v2
Insight diagram
COVID-19 Section
Insight diagram
өзіндік жұмыс
Insight diagram
Covid-19 SEIRCID Model
Insight diagram
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
Insight diagram
COVID-19 Stakeholder map
Insight diagram
системное Америка
12 months ago
Insight diagram
Covid-19 in Belarus
5 months ago
Insight diagram

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

Clone of Clone of Clone of Clone of Clone of Clone of Clone of Clone of SEIR Infectious Disease Model for COVID-19
Insight diagram
COVID-19 in Japan СРС-1
5 months ago
Insight diagram
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
5 11 months ago
Insight diagram

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

Clone of Clone of Clone of Clone of Clone of Clone of Clone of SEIR Infectious Disease Model for COVID-19