Find Insights | Insight Maker

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-19 in russia

Аяна Нукеева

Clone of Simple SIR System Model for COVID-19_Group 4

Bryan Kovalick

COVID-19 Model of Puerto Princesa City as of May 19,2023.

COVID-19 Model of Puerto Princesa City

Leenard Sayoto

Covid-19 Systemigram Hofher

Robert Hofher

A systems model on the recycling situation in West Philadelphia.

Recycling West Philadelphia

Miles Starr Radin

Semirara island Casual Loop Diagram

Paul Gabriel Fajardo

жүйелік бақылау

ДИАНА ЖАСҰЗАҚ БИО-51

A sample model for class discussion modeling COVID-19 outbreaks and responses from government with the effect on the local economy. Govt policy is dependent on reported COVID-19 cases, which in turn depend on testing rates less those who recover

Assumptions

Govt policy reduces infection and economic growth in the same way.

Govt policy is trigger when reported COVID-19 case are 10 or less.

A greater number of COVID-19 cases has a negative effect on the economy. This is due to economic signalling that all is not well.

Interesting insights

Higher testing rates seem to trigger more rapid government intervention, which reduces infectious cases. The impact on the economy though of higher detected cases though is negative.

Clone of Burnie COVID-19 outbreak demo model version 2

ching tung li

COVID-19

Jennifer

ABM covid -19 seoul

Assel

La meilleur simulation du marché à propos de la Covid-19

Ludovik Arbach

Model di samping adalah model SEIR yang telah dimodifikasi sehingga dapat digunakan untuk menyimulasikan perkembangan penyebaran COVID-19.

SEIR Model for COVID-19 in Indonesia (Revised V2)

Firly Feisal

Introduction

This model simulates the COVID-19 outbreaks in Burnie, the government reactions, as well as the economic impact. The government's strategy is based on the number of COVID-19 cases reported and testing rates and recovered.

Assumptions

In the same trend that government policy decreases infection, it also reduces economic growth.

When there are ten or fewer COVID-19 cases reported, government policy is triggered.

The economy suffers as a result of an increase in COVID-19 cases.

Interesting insights

The higher testing rates appear to result in a more quick government response, resulting in fewer infectious cases. However, it has a negative influence on the economy.

Model of COVID-19 outbreak in Burnie Tasmania - Xiaoqing Ren 525418

Xiaoqing Ren

самостаятельная работа часть 2 Акилбеков Асет

Akilbekov Aset

Modelo SEIR in Covid-19

Amanda Rivera

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

My Insight 1 covid-19

Кенжебекова Асем

This model is to explain the COVID-19 outbreak in Brunie Island, Tasmania, Australia, and the relationship between it and the government policies , also with the local economy.

This model is upgraded on the basis of the SIR model and adds more variables.

A large number of COVID-19 cases will have a negative impact on the local economy. But if the number of cases is too small, it will have no impact on the macro economy

Government policy will help control the growth of COVID-19 cases by getting people tested.

BMA708 Model of COVID-19 Outbreak in Burnie island. Ming Liu 501335