title: Fitting Birth-Death Processes to Panel Data with Applications to Bacterial DNA Fingerprinting.
abstract: Continuous-time linear birth-death-immigration (BDI) processes are frequently used in ecology and epidemiology to model stochastic dynamics of the population of interest. In clinical settings, multiple birth-death processes can describe disease trajectories of individual patients, allowing for estimation of the effects of individual covariates on the birth and death rates of the process. Such estimation is usually accomplished by analyzing patient data collected at unevenly spaced time points, referred to as panel data in the biostatistics literature. Fitting linear BDI processes to panel data is a nontrivial optimization problem because birth and death rates can be functions of many parameters related to the covariates of interest. We propose a novel expectation-maximization (EM) algorithm for fitting linear BDI models with covariates to panel data. We derive a closed-form expression for the joint generating function of some of the BDI process statistics and use this generating function to reduce the E-step of the EM algorithm, as well as calculation of the Fisher information, to one-dimensional integration. This analytical technique yields a computationally efficient and robust optimization algorithm that we implemented in an open-source R package. We apply our method to DNA fingerprinting ofMycobacterium tuberculosis, the causative agent of tuberculosis, to study intrapatient time evolution of IS6110copy number, a genetic marker frequently used during estimation of epidemiological clusters ofMycobacterium tuberculosisinfections. Our analysis reveals previously undocumented differences in IS6110birth-death rates among three major lineages ofMycobacterium tuberculosis, which has important implications for epidemiologists that use IS6110for DNA fingerprinting ofMycobacterium tuberculosis.
authors.affiliation: University of Washington, Seattle.
authors.forename: Charles R
authors.initials: CR
authors.lastname: Doss
authors.affiliation: University of California, Los Angeles.
authors.forename: Marc A
authors.initials: MA
authors.lastname: Suchard
authors.affiliation: University of California, Berkeley.
authors.forename: Ian
authors.initials: I
authors.lastname: Holmes
authors.affiliation: University of California, San Francisco.
authors.forename: Midori
authors.initials: M
authors.lastname: Kato-Maeda
authors.affiliation: University of Washington, Seattle.
authors.forename: Vladimir N
authors.initials: VN
authors.lastname: Minin
keywords: EM algorithm; IS6110; Missing data; transposable element; tuberculosis