Probabilistic modeling of genome evolution and disease spread of tuberculosis
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Authors
Yao, Lei
Issue Date
2014-12
Type
Electronic thesis
Thesis
Thesis
Language
ENG
Keywords
Mathematics
Alternative Title
Abstract
In the second part, we study the transmission dynamics of TB disease. Based on the DNA fingerprints of the MTBC, TB patients can be clustered in to small groups. This allows us to investigate the dynamics at the individual level. Since immigrants make the majority of TB cases in the United States, we focus our anal- ysis on immigrant TB patients. We propose a model to estimate the probability of an immigrant entering the country latently infected with TB versus he/she being infected after entry, given the entry and diagnosis time of the immigrant patients within the cluster. The transmission routes among the patients increase exponen- tially with the size of the cluster. The fact that individuals outside the cluster could also infect someone within the cluster further complicates the dynamics. We use Mean Field approximations to simplify the complicated transmission routs among patients and the effects of the individuals outside the cluster. The performance of the model is evaluated with Receiver Operating Characteristic (ROC) analysis on simulated data. Finally, we apply our model to the patient data collected from New York City.
Description
December 2014
School of Science
School of Science
Full Citation
Publisher
Rensselaer Polytechnic Institute, Troy, NY