Hong Kong SARS Outbreak

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The logistic equation with k=1.072 seems to provide the most accurate model for the beginning the outbreak as its prediction value for week 4 is only off by 36 cases. However, beyond week 6, the graph quickly loses its accuracy. Overall, the logistic model without the first three weeks was more accurate than the complete logistic model. This is probably due to the fact that I used data from week 4 and week 5 of the SARS outbreak to solve for my A value in Eqn. (15). Even though these weeks occurred immediately after week 3, there were signs of exponential increase as shown by Figure 1. In the first few weeks however, SARS cases were still slowly increasing, meaning that the A value solved between week 4 and 5 couldn’t be completely representative of the first 3 weeks. If you look at any of the figures, you can also see that my models were generally the most accurate around the end of the curve but less accurate in the middle. Looking back, I realized that an assumption of a constant relative growth was the biggest reason for the discrepancy in the middle of the model. In reality, the spread of SARS depended on a number of factors including that may increase the number of people …show more content…
The SARS experience was much more different than historical outbreaks such as influenza due to our newfound worldwide cooperation and modern medical. The work done by the Hong Kong government and international support made it possible for me to be able to model the total cases with a logistic model, as the SARS outbreak was contained in mere months with a total of only 1755 cases. Had this not been the case like in the Influenza epidemic, data would have been hard to come by as people would become infected with have increased rapidly to the millions, taxing the resources of medical personnel and making record keeping nearly impossible. There would also be a large margin of error for any subsequent

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