Question 2: Susceptible, Infected, Recovered (SIR) Model- A hypothetical case of Covid-19 on campus for Winter 2023-2024 (60 Points)

As of October 2023, there are a few new strains of covid-19 beginning to circulate in the greater NYC area as well as the Stevens campus. In this problem, we will aim at simulating the spread of one of these new variants during the winter months on campus.

In lecture 6, we modeled the SARS infection, and we ran the model and compared it against the actual data that we had from the case of SARS. In this question, recreate the following SIR (susceptible, infected, recovered) model in Figure 9-5 in Vensim to also include the following variables and stocks:

Recovered population

Delay in recovery or average duration of infectivity

Figure 9-5 from Business Dynamics, page 304, shows the schematics of such model (you can keep the model in session 6 as it is, change the values of constants and variables according to this new problem, and only add the loops and the stock of Recovered Population R).

Source: Business Dynamics, J. Sterman. Page 304

Assume that we are running this model from October 1st 2023-March 1st 2024 for Stevens student, faculty, and staff population. Lets assume that the variant that we will be modeling is BF.7.

Use the following assumptions:

Total population of students, faculty, and staff =9700,

Contact rate= 8 people/day,

Infectivity=0.025,

The average duration of infectivity= 14 days.

Run the model from October 1st 2023- March 1st 2024 (5 months duration of simulation)

Assume First positive case on campus is on October 1st.

B1-Rebuild and complete the model in Figure 9.5. Run the model and present the major stock and flow results (graphs) and discuss the results you observe for the baseline case model. Run the model and present the graphs for major variables and discuss their behavior. (20 pts)

B2- Perform a sensitivity analysis on relevant variables by changing the variables based on your chosen granularity, run the model a few times again and present your graphs in your response. Dont forget to label the resulting graphs. Discuss what variables have the highest impact on new strain epidemic. (10 pts)

B3- Vaccination scenario: Assuming 60% of the students, faculty and staff have received the new Covid vaccine by October 1st. However, we assume that the new vaccine only protects people against 70% of the new strain, calculate how many people are still vulnerable on campus? Run the model based on this assumption and compare it against the base scenario that no one is vaccinated, and everyone is susceptible. (10 pts)

B4- Quarantine scenario: Assume that as soon as an individuals covid test is positive, the person quarantine at home and will have contact rate with one more person only. Run the model with this new assumption and compare it against the baseline. (10 pts)

B5- Paxlovid Scenario: Assume that upon identification of covid, the students, faculty and staff are prescribed Paxlovid that shortens the duration of infectivity/recovery to 5 days only. How does that affect the model? Present the graphs and discuss the results. (10 pts)