Insight diagram
Covid-19 Pandemic
Insight diagram
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
SARS-CoV-19 model
Insight diagram
A model of an infectious disease and control

Disease Dynamics (Agent Based Modeling) Guy Lakeman
Insight diagram
A simple SI (Susceptible-Infectious) model that captures the dynamics of COVID-19.
SI Model
69 3 months ago
Insight diagram
Zombie apocalypse containment plan. This plan is used to simulate a real-world pandemic and propose a solution for containing it.
Zombie Apocalypse Containment Strategy
Insight diagram
A simple SI (Susceptible-Infectious) model that captures the dynamics of COVID-19.
Clone of SI Model
Insight diagram
2 өзіндік жұмыс
Insight diagram
2 өзіндік жұмыс
Insight diagram
RCIM, Aronoff-Spencer et al, UCSD 2023, CC. 

A SEIRI Model for Information/Misinformation dynamics

Quarantine is when someone exposed to infected people, whether infected or not, and advised to stay offline or away from information sources.this might range from targeting “advice” to internet restrictions 

Isolation is when someone exposed to infected people, gets infected, detected, and send is effectively shut off from communication with people they could spread misinformation too.

Assumption:
- Contact between susceptible and infected are constant. Contact not affected by population density
- Quarantine factor for susceptible and exposed is same.
- Quarantine and isolation is partially  effective. Someone who quarantined or isolated transmit transmits variably 
- Someone who has already recovered from SARS gained partial  effective immunity, thus cannot re-infected at a given rate 
Infodemiology Model
Insight diagram
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
Insight diagram

Upgrade of Kermack–McKendrick Epidemic SIR Infectious Disease Model (circa 2015) - Metrics by Guy Lakeman

This is a simple SIR infectious diseases 3 stock model with Susceptibles, Infectives and Recovereds stocks. In the initial description the R signified Removed and could include Deaths, Recovered with immunity to infection (Resistant) or those who had fled the epidemic. Note the need to initiate the epidemic by adding a pulse of a single infected person at time 0.

Addition of a slider for susceptibles is equivalent to accumulated total cases

SARS, MERS AND COVID are similar virus types only differing in their sub genus

The COVID outbreak has reached 150,000 infected people

This simulation allows an attempt at predicting how long the virus will persist and its longevity dependence on its high speed massive infection numbers that have reached pandemic proportions

SARS reached 8,000 infected total and ran for 9 months before stopping

MERS 2012 is still killing 8 years later with patients dying even after using interferon to try and cure them

updated 16/3/2020 from 5 years ago

Clone of Scratchpad of Upgrade of Kermack–McKendrick Epidemic SIR Infectious Disease Model - Metrics by Guy Lakeman
Insight diagram
A model of an infectious disease and control

Clone of Disease Dynamics (Agent Based Modeling)
Insight diagram
Pandemic apocalypse containment plan. This plan is used to simulate a real-world pandemic and propose a solution for containing it.
Pandemic Apocalypse Containment Strategy
Insight diagram
A simple SI (Susceptible-Infectious) model that captures the dynamics of COVID-19.
Clone of Clone of SI Model
Insight diagram
A simple SI (Susceptible-Infectious) model that captures the dynamics of COVID-19.
Clone of SI Model
Insight diagram
Check how different times of recovery and deths in cases of covid-19 infulence 2 key mortality indicators:
Overall mortalityr ate (ratio of all deaths to all cases)
Resolved cases mortality rate (ratio of all deaths to recovered cases)

Assumed delays are:
5 weeks for recovery cases
2 weeks for death cases
Delays are built into conveyor stocks, so cannot be adjusted by slider

keep in mind Insigth uses similar but made-up numbers and linear flow of new cases (in opposition to exponential in real world)  
Understanding Covid-19 mortality
Insight diagram
A SEIR Model of SARS Pandemic With Isolation and Quarantine, based on Introduction to Computational Science by Shiflet
Model Spread of SARS
Insight diagram
This basic pandemic model explores the dynamics and healthcare burden associated with of a novel infection.
Pandemic: Exploring the Dynamics of a Novel Infection
Insight diagram
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
Insight diagram
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
Insight diagram
Модель системной динамики по COVID-19 в Германии
9 months ago
Insight diagram
A SEIR Model of SARS Pandemic With Isolation and Quarantine, based on Introduction to Computational Science by Shiflet
Clone of Model Spread of SARS
Insight diagram
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)

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)

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

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
  • practicing preventive measures (ie. washing hands regularly, not touching your face etc.): 0.1 (nobody does anything) - 1 (very strictly)
  • government elucidation: 0.1 (very bad) - 1 (highly transparent and educating)
  • Immunity rate (due to lacking data): 0 (you can't get immune) - 1 (once you had it you'll never get it again)

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
Clone of Clone of SARS-CoV-19 model
Insight diagram
A model of an infectious disease and control

Clone of Disease Dynamics (Agent Based Modeling) Guy Lakeman