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
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:
 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
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:
Simple box model for atmospheric and ocean carbon cycle, with surface and deep water, including DIC system, carbonate alkalinity, weathering, O2, and PO4 feedbacks.
Simple box model for atmospheric and ocean carbon cycle, with surface and deep water, including DIC system, carbonate alkalinity, weathering, O2, and PO4 feedbacks.
The model is designed to provide a general understanding of the wear and tear on roads or a community's circulation system as a result of vehicle traffic generated by development within and outside of a community. It is not based on realistic assumptions regarding those impacts, it simply attempts t
The model is designed to provide a general understanding of the wear and tear on roads or a community's circulation system as a result of vehicle traffic generated by development within and outside of a community. It is not based on realistic assumptions regarding those impacts, it simply attempts to convey the flow of influence.

The imaginary city has a set area of roads measured in linear yards (width of roads is ignored) and an assumed number of vehicles on those roads set at 30,000 (per day). With those assumptions the wear and tear requiring repair is .02 or 2% Vehicle wear based on the 30,000 per year. There is also a calculated replacement cost of an additional 3% plus through vehicle wear or 5% per year.  An increase in vehicles increases this vehicle wear impact exponentially. The model assumes that there will not be less than 30,000 vehicles.

Expenditures for repair or replacement are set to balance out on an as needed based on 30,000 vehicles. An minimum additional 50 cars from external sources is then assumed. Adding New Homes and/or New Businesses places an even greater burden on the circulation system. 

The model does not consider additional funding. This will be added as a political factor but would need to consider the possibility of decreasing funding for other purposes.

Future additions to the model will include an inflation factor. Unfunded road work will get increasingly more expensive over time. Also a diminished revenue factor. A lack of capacity of the community's roads could likely result in a diminishment of the community's business sector thus reducing sales and property taxes and municipal revenue to expend on the roads. 
 This map is a WIP derived from the MIT D-memo 4641 presentation by Nelson Repenning 1996 and 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.  http://bit.ly/jCXGKL  See  Insight 9781  

This map is a WIP derived from the MIT D-memo 4641 presentation by Nelson Repenning 1996 and 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. http://bit.ly/jCXGKL See Insight 9781 for a simulation of this model. This map adds additional features mentioned in the article to the bare bones simulation in IM-9781