Source attribution of human <i>Campylobacter</i> infection: a multi-country model in the European Union.

ABSTRACT:

Introduction

Infections caused by Campylobacter spp. represent a severe threat to public health worldwide. National action plans have included source attribution studies as a way to quantify the contribution of specific sources and understand the dynamic of transmission of foodborne pathogens like Salmonella and Campylobacter. Such information is crucial for implementing targeted intervention. The aim of this study was to predict the sources of human campylobacteriosis cases across multiple countries using available whole-genome sequencing (WGS) data and explore the impact of data availability and sample size distribution in a multi-country source attribution model.

Methods

We constructed a machine-learning model using k-mer frequency patterns as

SUBMITTER: Thystrup C 

PROVIDER: S-EPMC11835883 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature