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Covid vs Gonorrea
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Modelling the demand for health and care resources resulting from the Covid-19 outbreak using an SEIR model.

Infectious Disease Model V1.0
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Covid-19 Model самостоятельная1
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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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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
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Pemodelan Epidemiologi COVID-19
11 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 in russia
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Системная динамика COVID-19 в Казахстане в 2020 году
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COVID PPE Prototype
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This model estimates the deaths due to COVID19 in Bangalore City. 
Assumptions:
City has a population = 80 Million
Initial infected population = 10
Probability of infection = 8%
Contact rate in population = 6
Average duration of recovery = 10 days
Death rate = 1%
Quarantine rate = 80%
Delay in quarantine = 5 days
COVID-19_SIR_MODEL
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Systemigram Model Building Covid Camacho Spring 2026
4 8 months ago
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Modélisation Covid-19
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Zhansultan 4
10 7 months ago
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Dynamics of Covid 19 cases
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Model SEIR Covid-19
1. Alif Nurhadi Maarif
2. Fachrizal Bayu Nugroho
3. Farhan Maulana Firmansyah
4. Irharsy Tara Prasetya
SEIR Covid
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This model shows an SIR model of COVID-19 infection in the Philippines. The data used in this model are recent data from COVID-19 statistics reports this 2022. The format of this Philippine COVID-19 model is guided by an Infection Model developed by martin.
Ph_Covid19SDM_Lilang, Rebekah
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This is a mitigated model showing the potential spread of COVID-19 across the healthcare system.

COVID phased community model
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COVID housing bubble representing a deviation amplifying feedback loop
PUBP6450 - Deviation Amplifying Feedback
9 months ago
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Recent COVID-19 Outbreak in Burnie Tasmania