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Data is from Lesener, T., Gusy, B., & Wolter, C. (2019). The job demands-resources model: A meta-analytic review of longitudinal studies.  Work & Stress ,  33 (1), 76-103. [PDF] academia.edu  
Data is from Lesener, T., Gusy, B., & Wolter, C. (2019). The job demands-resources model: A meta-analytic review of longitudinal studies. Work & Stress, 33(1), 76-103.
JD-R model of Burnout (High-qual studies)
Kjell Ivar Øvergård
2 weeks ago
Clusters of interacting methods for improving health services network design and delivery. Includes Forrester quotes on statistical vs SD methods and the Modeller's dilemma. Simplified version of IM-14982  combined with  IM-17598  and  IM-9773
Complexity Health Care Platform Methods Hybrid ABM Decision Making EHealth Technology Systems Engineering Forrester Data Science
Clusters of interacting methods for improving health services network design and delivery. Includes Forrester quotes on statistical vs SD methods and the Modeller's dilemma. Simplified version of IM-14982 combined with IM-17598 and IM-9773
Complex Decision Technologies
Geoff McDonnell
31
Modelado por Leandro Scala com suporte de Paulo Villela, baseado no modelo original de Geoff McDonnell (*) Simulador do gerenciamento de projeto de instalação de luminárias elétricas. (*)  https://insightmaker.com/insight/3Jp8YeBpzomjPpkYAuegeL/Project-management-104
project management gerenciamento de projetos

Modelado por Leandro Scala com suporte de Paulo Villela, baseado no modelo original de Geoff McDonnell (*)

Simulador do gerenciamento de projeto de instalação de luminárias elétricas.

(*) https://insightmaker.com/insight/3Jp8YeBpzomjPpkYAuegeL/Project-management-104

Simulador de Gerenciamento de Projeto de Instalação de Luninárias
Paulo Villela
last week
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
Disease Coronavirus Infection Corona Virus COVID-19 SARS-CoV-19 Pandemic
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
Lucia Vega Resto
63
The SEIRS(D) model for the purpose of experimenting with the phenomena of viral spread. I use it for COVID-19 simulation.
COVID-19 Coronavirus
The SEIRS(D) model for the purpose of experimenting with the phenomena of viral spread. I use it for COVID-19 simulation.
SEIR - COVID-19 (v.1)
Remigiusz Kinas
58
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
Mat375 SIR Math Modeling COVID-19 Coronavirus SIRD
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

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:
Coronavirus: A Simple SIR (Susceptible, Infected, Recovered) with death
Andrew E Long
41