Large and finite sample properties of a maximum-likelihood estimator for multiplicity of infection.

ABSTRACT: Reliable measures of transmission intensities can be incorporated into metrics for monitoring disease-control interventions. Genetic (molecular) measures like multiplicity of infection (MOI) have several advantages compared with traditional measures, e.g., R0. Here, we investigate the properties of a maximum-likelihood approach to estimate MOI and pathogen-lineage frequencies. By verifying regulatory conditions, we prove asymptotical unbiasedness, consistency and efficiency of the estimator. Finite sample properties concerning bias and variance are evaluated over a comprehensive parameter range by a systematic simulation study. Moreover, the estimator's sensitivity to model violations is studied. The estimator performs well for realistic sample sizes and parameter ranges. In particular, th

SUBMITTER: Schneider KA 

PROVIDER: S-EPMC5890990 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature