Congruity of genomic and epidemiological data in modeling of local cholera outbreaks

TL;DR

This study compares traditional case count models with genomic phylodynamic models for cholera transmission, demonstrating their consistency and paving the way for integrated epidemiological modeling using multiple data types.

Contribution

It introduces a framework for integrating epidemiological and genomic data in cholera modeling, validating phylodynamic methods against traditional case count approaches.

Findings

Phylodynamic estimates align with traditional models.

Genomic data can reliably inform cholera transmission dynamics.

The approach advances integrated disease modeling.

Abstract

Cholera continues to be a global health threat. Understanding how cholera spreads between locations is fundamental to the rational, evidence-based design of intervention and control efforts. Traditionally, cholera transmission models have utilized cholera case count data. More recently, whole genome sequence data has qualitatively described cholera transmission. Integrating these data streams may provide much more accurate models of cholera spread, however no systematic analyses have been performed so far to compare traditional case-count models to the phylodynamic models from genomic data for cholera transmission. Here, we use high-fidelity case count and whole genome sequencing data from the 1991-1998 cholera epidemic in Argentina to directly compare the epidemiological model parameters estimated from these two data sources. We find that phylodynamic methods applied to cholera genomics data provide comparable estimates that are in line with established methods. Our methodology represents a critical step in building a framework for integrating case-count and genomic data sources for cholera epidemiology and other bacterial pathogens.