Investigating cost effective management strategies for neonatal mortality in broiler breeding stock

Lead Research Organisation: Royal Veterinary College
Department Name: Production and Population Health

Abstract

Strategic Research Priority: World Class Underpinning Bioscience
The threat of antimicrobial resistance has led to increasing societal and media pressure on livestock producers to minimise the use of antibiotics in production. Cobb is currently responding to this challenge, however, production in the absence of antibiotics results in a marked increase in broiler breeder mortality during the first week of rearing. Research into first week mortality (FWM) tends to focus on the effects of one step in the supply chain on FWM. However, in a previous pilot project between the RVC and Cobb, a wide range of interrelated factors from source flock right through to delivery were shown to influence FWM of broiler breeders. This studentship will take a holistic approach to investigating FWM by identifying risk hotspots in the broiler breeder supply chain in order to develop risk management tools for FWM without relying on antimicrobials. This will be done through the following connected studies:

Longitudinal study of FWM:
The Cobb production database collates data on various performance indicators and limited production variables. Macros will be developed to regularly export and analyse production data so that FWM is monitored and risk factor analysis for FWM performed.

Cohort study of FWM:
This study will focus on several key exposures which have the strongest association with FWM, based on analysis of production data and scientific literature. Data on all exposures at different production stages and subsequent performance will be recorded. Potential factors of interest include management of grandparent stock, egg quality, hatch window, incubation profile, transportation of day-old chicks (DOCs), and management upon arrival at the farm.

Development of knowledge-based FWM risk scoring algorithm:
A pilot knowledge-based risk scoring algorithm has been developed, which allows characterising batches of chicks in terms of FWM risk. The results of the longitudinal and cohort study will be used to further develop this algorithm, which will be based on multi-criteria decision analysis methods. Uncertainty and its propagation through the algorithm will be included using the Dempster-Shafer method. Its prognostic performance will be then be assessed against Cobb production data.

Intervention studies:
Based on findings from above, a series of risk management strategies which could feasibly be incorporated into the Cobb production chain will be selected. Expert elicitation, consultation with Cobb and examination of contemporary evidence will be conducted to ensure novel and innovative methods are included. Batches of chicks will be randomly allocated into groups and FWM compared between those receiving an intervention and those which do not. Potential strategies could be:

Changes to maternal diet e.g. supplements, competitive exclusion products
Changes to egg sterilisation and storage e.g. pre-storage incubation
Varying incubation profiles e.g. CO2/O2 concentration, pre-incubation warming
Factors which may change spread of hatch
Managing feeding/water during transport e.g. hydration gels

Economic analysis of FWM impact and selected interventions:
Cost-effectiveness analysis will be performed in order to predict which potential risk management strategies would be most cost-effective if implemented on a larger scale. In addition, break-even points will be identified to predict optimal breeding age and for how long eggs should be stored before being discarded.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/M009513/1 01/10/2015 30/09/2023
1776846 Studentship BB/M009513/1 26/09/2016 30/09/2020 Benjamin Wall