Story. This data represents the number of COVID-19 deaths worldwide from January 20, 2020 (t=1) to March 8, 2020 (t=47). Graph the data on Desmos

Data set for model 4

17. How accurate was your Model 2? Explain the differences between Model 2 and the new data set on the left. What do you think caused these differences?
18. On the graph, identify some important/weird/confusing day(s) or trends and give a rationale of what is happening.
19. Your job is to develop a model that accurately predicts what is going to happen. Given the new data set on the left, develop a model to predict the behavior of the disease (Model 4)
20. Compare the behavior of Model 3 and Model 4.

Model 4: Total number of deaths (logistic)

logistic model graph using new data set

Model 2 is not accurate because it overestimates the total number of deaths. Model 2 is an exponential function while the data given shows that the number of deaths does not grow exponentially from day 20 to day 40. The number of deaths is not always growing exponentially because there are measures taken to eliminate social contact and prevent the number of people infected with the disease to grow exponentially. When the number of people infected is growing less rapidly, the number of deaths also grows less rapidly. On day 47, the number of deaths increased by a lot, violating the previous trend. This is likely because the coronavirus began to emerge in countries outside of China, and in those countries it was still in its early days of growth, in which this growth obeyed an approximately exponential function.

Comparing Model 3 (infection) and Model 4 (death), they track each other closely but with a bit of a lag between them. Model 3 begins to flatten at an earlier stage than Model 4. This is because deaths from the coronavirus generally take place days or weeks after initial infection. The lower growth rate for the deaths is also (hopefully) due to increased knowledge of how to treat the disease.