Semiparametric Relative-risk Regression for Infectious Disease Transmission Data.

ABSTRACT: This paper introduces semiparametric relative-risk regression models for infectious disease data. The units of analysis in these models are pairs of individuals at risk of transmission. The hazard of infectious contact from i to j consists of a baseline hazard multiplied by a relative risk function that can be a function of infectiousness covariates for i, susceptibliity covariates for j, and pairwise covariates. When who-infects-whom is observed, we derive a profile likelihood maximized over all possible baseline hazard functions that is similar to the Cox partial likelihood. When who-infects-whom is not observed, we derive an EM algorithm to maximize the profile likelihood integrated over all possible combinations of who-infected-whom. This extends the most im

SUBMITTER: Kenah E 

PROVIDER: S-EPMC4489164 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature