Mathematical modelling approaches to understanding the spread of Campylobacter in broiler flocks

Thesis

Campylobacter spp. are one of the leading causes of human gastroenteritis globally, with the primary route of transmission being poultry meat. Flocks of broilers, chickens grown for their meat, will rapidly become colonised by Campylobacter on the farm, and this infection persists throughout the food chain. Recent attempts to prevent the spread of Campylobacter in broiler flocks have focused on biosecurity measures on farms to reduce the chance of initial infection. Such measures have proved ineffective, resulting in calls for more fundamental research into the ecology of Campylobacter in chicken flocks, and greater investigation of the bacteria-host relationship. This thesis presents a multitude of mathematical frameworks to explore these dynamics, driven by on-farm data from the last several decades. Firstly, I present a mechanistic model system of stochastic differential equations to demonstrate the population dynamics of multiple strains of Campylobacter at both in-host and flock level. I find that in-host dynamics are different from those observed in the flock at large, with single strains of Campylobacter seen to dominate the gut of a host-bird at any given time, compared to the more stable patterns of co-occurrence seen at the wider flock level. I show that Campylobacter outbreaks are most influenced by the demographic capabilities of other native gut microflora within host-birds, raising the hypothesis that further attention to bird gut health may be key to limiting the spread of Campylobacter. Building on this, I investigate data detailing the occurrence of multiple Campylobacter strains within a flock of chickens across a year. By using Bayesian transition models, competition matrix models, and patch-occupancy models, I demonstrate the existence of variation in the response to bacterial challenge amongst birds in the flock, and that this variation may drive the proliferation of Campylobacter. This is further supported by models I present showing that Campylobacter strains exist in a hierarchical system of competition, and that the diversity of strains found cannot be supported without the inclusion of host-bird factors. Lastly, I investigated the causal relationships between a variety of management and welfare factors for multiple commercial flocks by building and comparing logistic regression models with Bayesian network models. I show that measures of poor bird health and Campylobacter status are conditionally dependent upon one another, revealing that decisions in the rearing of these birds simultaneously jeopardise their health, and increase the risk of Campylobacter colonisation.

Authors: Rawson, TE

• DOI: 10.5287/ora-kz7mrqexo
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: Foodborne Disease; Campylobacter; Mathematical Modelling; Broiler
• Subjects: Mathematical models; Campylobacter infections in poultry