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Simulation of the spread of COVID-19 in Wuhan.
COVID-19
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COVID-19 SEIR Model for Indonesia
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Introduction;

This model shows COVID-19 outbreak in Burnie have some impact for local economy situation and government policy. The main government policy is lockdown during the spreading period which can help reduce the infected rate, and also increase the test scale to help susceptible confirm their situation.


Variables;

Infection rate, Death rate, Recovery rate, test rate, susceptible, immunity rate, economy growth rate

These variables are influenced by different situation.


When cases over 10, government will implement lockdown policy.


Conclusion;

When cases increase too much , they will influence the economic situation.


Interesting insights:

If the recover rate is higher, more people will recover from the disease. It seems to be a positive sign. However, it would lead to a higher number of recovered people and more susceptible. As a result, there would be more cases, and would have a negative impact on the economic growth. 

Model of COVID-19 Outbreak in Burnie, Tamania ( WANTING BAO, 536865)
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Өзіндік жұмыс 2 АҚШ
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Here we have a basic SEIR model and we will investigate what changes would be appropriate for modelling the 2019 Coronavirus 

Modelo SEIR para COVID-19
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A Susceptible-Infected-Recovered (SIR) disease model with waning immunity

COVID-19 Delta Variant Spread Among Emory Students
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COVID-19 Pakistan
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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
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COVID-19 Kazakstan Abdrakhman
12 months ago
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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 - v2
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COVID-19 cases in Barangay Candawaga, Municipality of Rizal
COVID-19 MODEL2 (OPERIANO, GLIANNE BETH O.)
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Өзіндік жұмыс Аида 1
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Simulation of how a virus infects after entering the body, how it replicates inside living cells, and how the body's immune system responds towards the virus
System Dynamic Model 1b (Previously-infected individual)
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Das SEIRS(D)-Modell zum Simulieren der COVID-19 - Epidemie.
SEIR - COVID-19 (v.1) von Remigiusz Kinas
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Өзіндік жұмыс 2
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Өздік жұмыс(жүйелік модельдеу)
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COVID-19 в Бразилии за 2020-2024 года (динамика заболеваний)
5 months ago
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An Agent Based Model of Covid-19. Disease Dynamics of Agent Based Model, aims to present the Covid-19 status


Ph_Covid19ABM_Shanea Betorin
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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
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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:
  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
Coronavirus: A Simple SIR (Susceptible, Infected, Recovered) with death