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Coronavirus

SARS-CoV-19 model

Lucia Vega Resto
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 COVID-19 Corona Coronavirus Virus Disease Infection Pandemic

  • 2 weeks 1 day ago

Infectious Disease Model (Covid)

David Plummer
Modelling of the SARS-Cov-2 viral outbreak using an SEIR model plus specific extensions to model demand for health and care resources.
The model includes biths and deaths, and migration to accommodate import and export of infected individuals from other areas.
Healthcare resources identifies need for hospital beds and critical care.
The model is uses arrays to reflect the different impacts of modelled parameters by age and sex.

Health And Social Care Infectious Disease COVID-19 SARS-Cov-2 Coronavirus

  • 1 day 15 hours ago

Virus Simulation with Quarantine Leakage

Simon Allen

Modified PBG virus by David Meyer.

Added a global population which is added to the pool based on the leakage rate of people out of quarantine.

With no leakage, even if an entire population gets infected the outbreak is contained. The leakage rate determines how much of the global population gets exposed prior to the virus running its course. Oh, and a very small re-infection rate.

Can produce some very large results. I have limited the simulation to 170 days, but if you clone it you can run it for a full year.

Coronavirus

  • 3 weeks 5 days ago

Understanding Covid-19 mortality

Cezary Zając
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 cases2 weeks for death casesDelays 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)  

COVID-19 Coronavirus Pandemic

  • 2 weeks 2 days ago

Coronavirus: A Simple SIR (Susceptible, Infected, Recovered) with death

Andrew E Long
Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.

With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.
We start with an SIR model, such as that featured in the MAA model featured inhttps://www.maa.org/press/periodicals/loci/joma/the-sir-model-for-spread-of-disease-the-differential-equation-model
Without mortality, with time measured in days, with infection rate 1/2, recovery rate 1/3, and initial infectious population I_0=1.27x10-4, we reproduce their figure
With a death rate of .005 (one two-hundredth of the infected per day), an infectivity rate of 0.5, and a recovery rate of .145 or so (takes about a week to recover), we get some pretty significant losses -- about 3.2% of the total population.
Resources:
  1. http://www.nku.edu/~longa/classes/2020spring/mat375/mathematica/SIRModel-MAA.nb
  2. https://www.maa.org/press/periodicals/loci/joma/the-sir-model-for-spread-of-disease-the-differential-equation-model

SIR Math Modeling Mat375 COVID-19 Coronavirus SIRD

  • 11 hours 30 min ago

Virus Simulation with Quarantine Leakage -250days

Simon Allen

Modified PBG virus by David Meyer.

Added a global population which is added to the pool based on the leakage rate of people out of quarantine.

With no leakage, even if an entire population gets infected the outbreak is contained. The leakage rate determines how much of the global population gets exposed prior to the virus running its course. Oh, and a very small re-infection rate.

Can produce some very large results. I have limited the simulation to 150 days, but if you clone it you can run it for a full year.

Coronavirus

  • 3 weeks 5 days ago

Clone of SARS-CoV-19 model

Mark Dav
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

SARS-CoV-19 COVID-19 Corona Coronavirus Virus Disease Infection Pandemic

  • 2 weeks 1 day ago

CoronaVirus Sim US No controls (treat as flu)

Simon Allen

Modified PBG virus by David Meyer.

Added a global population which is added to the pool based on the leakage rate of people out of quarantine.

With no leakage, even if an entire population gets infected the outbreak is contained. The leakage rate determines how much of the global population gets exposed prior to the virus running its course. Oh, and a very small re-infection rate.

Can produce some very large results. I have limited the simulation to 170 days, but if you clone it you can run it for a full year.

Coronavirus

  • 3 weeks 5 days ago

Clone of SARS-CoV-19 model

Lohitha Meduri
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 COVID-19 Corona Coronavirus Virus Disease Infection Pandemic

  • 6 days 12 hours ago

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