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Publication Date
4-2020
Document Type
Poster
Degree Type
Graduate
Mentor
Olcay Akman
Abstract
When mortality statistics are reported for infectious diseases, they commonly reflect the ratio for the entire population impacted from it. This causes an underestimation since the frail members of the population are impacted at a higher rate. With the remaining healthy members, the mortality rate becomes skewed. With this project, we study predicting mortality under varying frailty conditions to account for the hidden heterogeneity's impact on the parameter estimates.
Recommended Citation
Hasan, Kazi Tanvir, "Infectious Disease Mortality Prediction" (2020). Mathematics. 1.
https://ir.library.illinoisstate.edu/ursmat/1
Notes
This project has not received IRB approval.