Harrison Hong - May 13, 2020

Harrison Hong, PhD, "Implications of Stochastic Transmission Rates for Managing Epidemic Risk"

Dr. Hong presented his analysis of a stochastic three-parameter nonlinear diffusion model as a tool for modeling combined health and economic risk of COVID-19. Using the Hopkins database data for 16 high risk countries from January to February, he estimated a single model which then was used to analytically calculate the conditional distribution going forward. The results from the model were then cross-checked with the real evolution and showed an overall concordant agreement within the uncertainty of the model. He used the calculated distributions to highlight the importance of conditional volatility in cross-country infection outcomes in the short-run and to evaluate global government interventions. One conclusion to draw is that the reproduction number alone is not a sufficient parameter for risk management, when already a value as low as below two might generate long-run benefits.

This study was published recently and can be found here: https://papers.ssrn.com/sol3/papers.c...