Accounting for reporting delays in real-time phylodynamic analyses with preferential sampling

Oregon Convention Center 

The ongoing pandemic demonstrated that fast and accurate analysis of continually collected infectious disease surveillance data is crucial for situational awareness and policy making. Phylodynamic analysis uses genetic sequences of a pathogen to estimate changes in its genetic diversity in a population of interest, the effective population size, which under certain conditions can be connected to the number of infections in the population. Phylodynamics is an important tool because its methods utilize a data source in a way that is resilient to the ascertainment biases present in traditional surveillance data. Unfortunately, it takes weeks or months to sequence and obtain the sampled pathogen genome for use in such analyses. When the number of infections depends on the sampling frequency, the missing data results in underestimation of the effective population size. Here we present a method that affords reliable estimation of the effective population size trajectory closer to the time of data collection, allowing for policy decisions to be based on more recent data, with a better understanding of the limitations and uncertainties of such inference.

infectious disease dynamics

disease surveillance

Bayesian phylogenetics

genomic epidemiology

Bayesian nonparametrics 

Section on Bayesian Statistical Science