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Here is a sample of public Insights made by Insight Maker users. This list is auto-generated and updated daily.

This is a food chain of BIOTIC factors. They are animals or plants that have been alive or are alive. Dead rodents or bacteria are both biotic factors. Food webs are 100% consisted of biotic factors.
This is a food chain of BIOTIC factors. They are animals or plants that have been alive or are alive. Dead rodents or bacteria are both biotic factors. Food webs are 100% consisted of biotic factors.
 This model is derived from the paper " Nobody Ever Gets Credit for Fixing Problems that Never Happened: Creating and Sustaining Process Improvement " by Nelson P. Repenning and John D Sterman. See  Insight 752  for a causal loop version of this model.  @ LinkedIn ,  Twitter ,  YouTube

This model is derived from the paper "Nobody Ever Gets Credit for Fixing Problems that Never Happened: Creating and Sustaining Process Improvement" by Nelson P. Repenning and John D Sterman. See Insight 752 for a causal loop version of this model.

@LinkedInTwitterYouTube

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
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
 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
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
A model demonstrating the differences in productivity and cost in an arbitrary workforce (this could be one company/institution or an entire area). I used AI to assist me in creating this model, by explaining to it what I would like to have as my main stocks and what I'd like to model, and then had
A model demonstrating the differences in productivity and cost in an arbitrary workforce (this could be one company/institution or an entire area). I used AI to assist me in creating this model, by explaining to it what I would like to have as my main stocks and what I'd like to model, and then had it suggest variables, flows, and links (and thus equations for the flows and variables as well). The actual initial values were also suggested by the AI.
 Here we have a basic SEIR model and we will investigate what changes would be appropriate for modelling the 2019 Coronavirus 

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