Pandemic | Insight Maker

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Asty Ayu Mutiari

A SEIR Model of SARS Pandemic With Isolation and Quarantine, based on Introduction to Computational Science by Shiflet

A SEIR Model of SARS Pandemic With Isolation and Quarantine, based on Introduction to Computational Science by Shiflet and Shiflet

Quarantine is when someone exposed to infected people, whether infected or not, and advised to stay at home.

Isolation is when someone exposed to infected people, get infected, detected, and send to hospital.

Assumption:

- No births

- Dead only caused by SARS

- Contact between susceptible and infected are constant. Contact does not affected by population density

- Quarantine factor for susceptible and exposed is same.

- Quarantine and isolation is fully efective. Someone who quarantined or isolated cannot transmit or exposed to SARS

- Someone who has already recovered from SARS gained fully effective immunity, thus cannot re-infected

Clone of SEIR Model of SARS

Diego Bryllian

A simple SI (Susceptible-Infectious) model that captures the dynamics of COVID-19.

Clone of SI Model

kaylei kambak

This basic pandemic model explores the dynamics and healthcare burden associated with of a novel infection.

Clone of Pandemic: Exploring the Dynamics of a Novel Infection

Anni Chen

A SEIR Model of SARS Pandemic With Isolation and Quarantine, based on Introduction to Computational Science by Shiflet and Shiflet

Quarantine is when someone exposed to infected people, whether infected or not, and advised to stay at home.

Isolation is when someone exposed to infected people, get infected, detected, and send to hospital.

Assumption:

- No births

- Dead only caused by SARS

- Contact between susceptible and infected are constant. Contact does not affected by population density

- Quarantine factor for susceptible and exposed is same.

- Quarantine and isolation is fully efective. Someone who quarantined or isolated cannot transmit or exposed to SARS

- Someone who has already recovered from SARS gained fully effective immunity, thus cannot re-infected

Clone of SEIR Model of SARS

Muhammad Grandiv Lava Putra (Grandiv)

8 months ago

A simple SI (Susceptible-Infectious) model that captures the dynamics of COVID-19.

SI Model - Pre CSV

Ali Ozdagli

35 last week

SARS-CoV-19 spread in different countries

- please adjust variables accordingly

Italy

elderly population (>65): 0.228
estimated undetected cases factor: 4-11
starting population size: 60 000 000
high blood pressure: 0.32 (gbe-bund)
heart disease: 0.04 (statista)
free intensive care units: 3 100

Germany

elderly population (>65): 0.195 (bpb)
estimated undetected cases factor: 2-3 (deutschlandfunk)
starting population size: 83 000 000
high blood pressure: 0.26 (gbe-bund)
heart disease: 0.2-0.28 (herzstiftung)
free intensive care units: 5 880

France

elderly population (>65): 0.183 (statista)
estimated undetected cases factor: 3-5
starting population size: 67 000 000
high blood pressure: 0.3 (fondation-recherche-cardio-vasculaire)
heart disease: 0.1-0.2 (oecd)
free intensive care units: 3 000

As you wish

numbers of encounters/day: 1 = quarantine, 2-3 = practicing social distancing, 4-6 = heavy social life, 7-9 = not caring at all // default 2
practicing preventive measures (ie. washing hands regularly, not touching your face etc.): 0.1 (nobody does anything) - 1 (very strictly) // default 0.8
government elucidation: 0.1 (very bad) - 1 (highly transparent and educating) // default 0.9
Immunity rate (due to lacking data): 0 (you can't get immune) - 1 (once you had it you'll never get it again) // default 0.4

Key

Healthy: People are not infected with SARS-CoV-19 but could still get it
Infected: People have been infected and developed the disease COVID-19
Recovered: People just have recovered from COVID-19 and can't get it again in this stage
Dead: People died because of COVID-19
Immune: People got immune and can't get the disease again
Critical recovery percentage: Chance of survival with no special medical treatment

Clone of SARS-CoV-19 model

João Garrido

4 months ago

This basic pandemic model explores the dynamics and healthcare burden associated with of a novel infection.

Clone of Pandemic: Exploring the Dynamics of a Novel Infection

Steven D'Alessandro

This basic pandemic model explores the dynamics and healthcare burden associated with of a novel infection.

Clone of Pandemic: Exploring the Dynamics of a Novel Infection

Lioua Kolsi

This basic pandemic model explores the dynamics and healthcare burden associated with of a novel infection.

Clone of Pandemic: Exploring the Dynamics of a Novel Infection

Lioua Kolsi

This basic pandemic model explores the dynamics and healthcare burden associated with of a novel infection.

Clone of Pandemic: Exploring the Dynamics of a Novel Infection

bakhtiyor ismailov

This basic pandemic model explores the dynamics and healthcare burden associated with of a novel infection.

Clone of Pandemic: Exploring the Dynamics of a Novel Infection

Ruixin Zhang

A model of an infectious disease and control

Clone of Disease Dynamics (Agent Based Modeling) Guy Lakeman

TDebord

7 months ago

A model of an infectious disease and control

Clone of Disease Dynamics (Agent Based Modeling) Guy Lakeman

NangManCat

4 months ago

SARS-CoV-19 spread in different countries

- please adjust variables accordingly

Italy

elderly population (>65): 0.228
estimated undetected cases factor: 4-11
starting population size: 60 000 000
high blood pressure: 0.32 (gbe-bund)
heart disease: 0.04 (statista)
free intensive care units: 3 100

Germany

elderly population (>65): 0.195 (bpb)
estimated undetected cases factor: 2-3 (deutschlandfunk)
starting population size: 83 000 000
high blood pressure: 0.26 (gbe-bund)
heart disease: 0.2-0.28 (herzstiftung)
free intensive care units: 5 880

France

elderly population (>65): 0.183 (statista)
estimated undetected cases factor: 3-5
starting population size: 67 000 000
high blood pressure: 0.3 (fondation-recherche-cardio-vasculaire)
heart disease: 0.1-0.2 (oecd)
free intensive care units: 3 000

As you wish

numbers of encounters/day: 1 = quarantine, 2-3 = practicing social distancing, 4-6 = heavy social life, 7-9 = not caring at all // default 2
practicing preventive measures (ie. washing hands regularly, not touching your face etc.): 0.1 (nobody does anything) - 1 (very strictly) // default 0.8
government elucidation: 0.1 (very bad) - 1 (highly transparent and educating) // default 0.9
Immunity rate (due to lacking data): 0 (you can't get immune) - 1 (once you had it you'll never get it again) // default 0.4

Key

Healthy: People are not infected with SARS-CoV-19 but could still get it
Infected: People have been infected and developed the disease COVID-19
Recovered: People just have recovered from COVID-19 and can't get it again in this stage
Dead: People died because of COVID-19
Immune: People got immune and can't get the disease again
Critical recovery percentage: Chance of survival with no special medical treatment

Zoes clone the pretty the smart and the science

Zoe

2 months ago

My Insight-COVID-19

Аяна Мусина

3 days ago

SARS-CoV-19 spread in different countries

- please adjust variables accordingly

Italy

elderly population (>65): 0.228
estimated undetected cases factor: 4-11
starting population size: 60 000 000
high blood pressure: 0.32 (gbe-bund)
heart disease: 0.04 (statista)
free intensive care units: 3 100

Germany

elderly population (>65): 0.195 (bpb)
estimated undetected cases factor: 2-3 (deutschlandfunk)
starting population size: 83 000 000
high blood pressure: 0.26 (gbe-bund)
heart disease: 0.2-0.28 (herzstiftung)
free intensive care units: 5 880

France

elderly population (>65): 0.183 (statista)
estimated undetected cases factor: 3-5
starting population size: 67 000 000
high blood pressure: 0.3 (fondation-recherche-cardio-vasculaire)
heart disease: 0.1-0.2 (oecd)
free intensive care units: 3 000

As you wish

numbers of encounters/day: 1 = quarantine, 2-3 = practicing social distancing, 4-6 = heavy social life, 7-9 = not caring at all // default 2
practicing preventive measures (ie. washing hands regularly, not touching your face etc.): 0.1 (nobody does anything) - 1 (very strictly) // default 0.8
government elucidation: 0.1 (very bad) - 1 (highly transparent and educating) // default 0.9
Immunity rate (due to lacking data): 0 (you can't get immune) - 1 (once you had it you'll never get it again) // default 0.4

Key

Healthy: People are not infected with SARS-CoV-19 but could still get it
Infected: People have been infected and developed the disease COVID-19
Recovered: People just have recovered from COVID-19 and can't get it again in this stage
Dead: People died because of COVID-19
Immune: People got immune and can't get the disease again
Critical recovery percentage: Chance of survival with no special medical treatment

Clone of SARS-CoV-19 model