COVID-19 | Insight Maker

Introduction:

This model aims to show that how the Tasmania government's COVID-19 policy can address the spread of the pandemic and in what way these policies can damage the economy.

Assumption:

Variables such as infection rate, death rate and the recovery rate are influenced by the actual situation.

The government will implement stricter travel bans and social distant policies as there are more cases.

Government policies reduce infection and limit economic growth at the same time.

A greater number of COVID-19 cases has a negative effect on the economy.

Interesting insights:

A higher testing rate will make the infection increase and the infection rate will slightly increase as well.

Government policies are effective to lower the infection, however, they will damage the local economy. While the higher number of COVID-19 cases also influences economic activities.

Model of COVID-19 outbreak in Burnie_Guoyu Shen

Guoyu Shen

The SEIRS(D) model for the purpose of experimenting with the phenomena of viral spread. I use it for COVID-19 simulation.

Clone of SEIRS MODEL

Luay Assidmi

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

Lin Ling

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

The government has reduced both the epidemic and economic development by controlling immigration.

Yuhao c, BMA708_Marketing insights into Big Data.

Yuhao Chen

The SEIRS(D) model for the purpose of experimenting with the phenomena of viral spread. I use it for COVID-19 simulation.

Clone of SEIR - COVID-19 (v.1)

sanjeev k

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 SEIR Infectious Disease Model for COVID-19

Muhammad Grandiv Lava Putra (Grandiv)

9 months ago

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

Clone of SEIR Infectious Disease Model for COVID-19

Wen Xin

11 months ago

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

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

Clone of SEIR Infectious Disease Model for COVID-19

Indriana Hidayah

This is the second in a series of models that explore the dynamics of and policy impacts on infectious diseases. This basic SIR model explores the impact of a simple test and isolate policy. The first model can be found here.

Clone of Future Learn Basic SIR Model with Sample Testing

kmolenda

This is the third in a series of models that explore the dynamics of infectious diseases. This model looks at the impact of two types of suppression policies.

Press the simulate button to run the model with no policy. Then explore what happens when you set up a lockdown and quarantining policy by changing the settings below. First explore changing the start date with a policy duration of 60 days.

Clone of SIRD Epidemic Model with Suppression Policies

kmolenda

Clone of SEIR Model_John

Max

Two infectious stages. Consider an infectious disease model based on the standard SIR model, where an individual passes through two infectious states with different degrees of infectivity, with transmission coefficients β1 and β2 (this could be due to different rates of virus shedding or to different contact rates, for example). Ignoring any births or deaths, formulate a model as three differential equations, for S the number of susceptible, I1 the first infectious state, and I2 the second infectious state. Recovery (with lifelong immunity) can only occur when the individual has passed through the second infectious state.

Two Infections disease

Mr.P

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 in

https://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:

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

23746494826

9 months ago

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

juan jose

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

Clone of SEIR Infectious Disease Model for COVID-19

Alex Thomas

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

Clone of SEIR Infectious Disease Model for COVID-19

Wafi Afdi Alfaruqhi

9 months ago

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

Clone of SEIR Infectious Disease Model for COVID-19

Bechara Assouad

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

Clone of SEIR Infectious Disease Model for COVID-19

Alex Thomas

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 Clone of SEIR Infectious Disease Model for COVID-19

juan jose

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 in

https://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:

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

Анастасия

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

5 months ago

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

Clone of SEIR Infectious Disease Model for COVID-19

David Gilding

19

An SIR model for Covid-19

This is a simple example of an SIR model for my Mathematics for Liberal Arts classes at Northern Kentucky University, Spring of 2022.

Let's think about things on the scale of a week. What happens over a week?

With an Ro of 2 (2 people infected for each infected individual, over the course of a week); recovery rate of 1 (every infected person loses their infectiousness after a week), and resusceptible rate of .05 (meaning .05, or a twentieth of the recovered lose their immunity each week), the disease peaks -- does the wave, then waves again before the year is out, then ultimately becomes

"endemic" (that is, it's never going away, which is clear after two years -- that is, a time of 104 weeks). This is like our seasonal flu (only the disease in this simulation doesn't illustrate seasonality -- that requires a more complicated model).

With an Ro of .9, recovery rate of 1, and resusceptible rate of .05, the disease is eliminated.

Masking, social distancing (including quarantining following contact), and quarantines all serve to reduce infectivity. And if we can drive infectivity down far enough, the disease can be eliminated. Other things that help is slowing down the resusceptibility, by vaccinating. Vaccines (in general) impart an immune response that reduces -- or even eliminates -- your susceptibility. We are still learning the extent to which these vaccines impart long-term immunity.

Other tools at our disposal include Covid-19 treatments, which increase the recovery rate, and vaccinations, which reduce the resusceptible rate. These can also serve to help us eradicate a disease, so that it doesn't become endemic (and so plague us forever).

Andy Long

Mathematics and Statistics

Some resources:

Wear a good mask: https://www.cdc.gov/coronavirus/2019-ncov/your-health/effective-masks.html
Gotta catch those sneezes: https://www.dailymail.co.uk/sciencetech/article-8221773/Video-shows-26-foot-trajectory-coronavirus-infected-sneeze.html

Clone of MAT115 Covid Simulation

Paula Galvez

COVID-19 Models