wrong Answer down'vote

2** Box 2 Simple maths of epidemics Epidemiologist have mathematical models for disease spread that use tools that will be familiar to economists. The most famous is a rough-and-ready model of unhindered transmission called the SIR model (developed in 1927). The first bold assumption is that the population can be classified into three categories: Susceptible to infection. Infectious, and Recovered (and thus immune). SIR is an acronym of these group labels. Making the bold assumption that all infectious and susceptible people are equally likely to meet, the number of interactions is the stock of susceptible people, S, times the stock of infectious people, I, per period (the number of days during which an infected person remains infectious). If the transmission rate/probability is 'beta', the number of new cases is beta times S times I. Of course, cach new infection makes the infectious group larger and the susceptible group smaller. Additionally, the size of the I group falls as people get better at the rate r (recovered people are neither infectious nor susceptible). Plainly, this dynamic leads to a logistic-like rise in the stock of affected persons as shown in Figures la, b and c. How many people get the disease in the long run? Simple maths show that the steady-state stock of never-infected people (i.e. susceptible) is s', where S' = expl(1-RS') and RO is the famous 'reproduction rate', i.e. the number of people who catch it from an average infected person. For example, if Ro is two, then eventually 80% of the population is infected in an uncontrolled epidemic. The current estimate for COVID-19 is between two and three;13 for the seasonal flu the number is about 1.3 (R, for the flu is low partly due to the existence of a vaccine).!4 Dr Syra Madad, who runs preparedness efforts for NYC Health and Hospitals, said: This particular virus seems like it is highly transmissible... I think that it is certainly plausible that 40-70% of the world's population could become infected with coronavirus disease, but a large number of cases are [expected to be] mild." 60000.00 O 50000.00 - 40000.00 - Revenue through meal sales (in MUS] 30000.00 20000.00 10000.00 1.00 2.00 3.00 5.00 6.00 7.00 4.00 Price Fig. 10.22 Scatterplot (f) Consider the scatterplot in Fig. 10.22. What's the problem? Describe the effects of the results from regressions one and two on interpretability. How can the problem be eliminated? standard normal distribution values. The last example in Fig. 7.21 shows that due to the symmetry of the standard normal distribution the area to the right of a positive x-value (e.g. to the right of 2.5) is just as large as the area to the left of same x-value with a negative sign (e.g. to the left of -2.5). Thus: P(Z > 1.65) = P(Z 1.96) = P(Z