Improving sustainable parasite control in British dairy cattle

Description

The dairy industry is an essential part of UK food security. It faces an increased focus on sustainable farming practices which aim to reduce negative, and promote positive, environmental impacts whilst maintaining high levels of food production, food safety and animal welfare standards.

Pasture-based dairy production can achieve efficient levels of production and have positive environmental impacts (e.g. carbon sequestration). However, these producers face additional challenges including control of parasitic diseases commonly acquired through grazing, namely parasitic gastroenteritis, liver fluke and lungworm. These diseases are widespread across the UK and, without appropriate management, can have a profound impact on animal health, welfare and productivity. Furthermore, their control is largely dependent on use of a limited number of anti-parasitic drugs. Over-reliance on these products poses risks to sustainable production and food security including selection for drug-resistant parasites, environmental contamination and resulting negative impacts on wildlife ecology and food chain integrity via chemical and disease contamination.

Opportunities exist to improve sustainable control of parasitic disease in dairy cattle through improved diagnostics and use of existing data to identify risk periods and better target treatment interventions.

This project aims to improve our understanding of the impact of parasitic diseases on British dairy cattle in terms of epidemiology and impact on animal health and food safety, and to improve the tools available foo dairy farmers to implement sustainable parasite control practices.

This PhD project is a collaboration between universities of Liverpool and Newcastle, and the UK National Milk Records. The successful applicant will work across these institutions, improving understanding of the epidemiology and impacts of parasitic diseases on British dairy cattle, specifically:

1.      Performing seroprevalence studies identifying the temporo-spatial distribution of key parasitic diseases across Great Britain using milk-based sampling and immunoassay techniques (ELISAs).

2.      Using meteorological data to develop and assess use of climate-driven disease risk models, comparing these to seroprevalence and other UK parasitic disease documenting data-sources (eg. APHA VIDA surveillance data).

3.      Using animal health data e.g. fertility, udder health-mastitis, medicines use and milk residue testing to determine parasitic disease impacts on animal productivity, welfare, food security and public health.

4.      Develop tools which combine data analytical and diagnostic techniques to improve control of parasitic diseases in British dairy cattle whilst minimising use of antiparasitic drugs.

HOW TO APPLY

Applications should be made by emailing bbsrcdtp@liverpool.ac.uk with:

·        a CV (including contact details of at least two academic (or other relevant) referees);

·        a covering letter – clearly stating your first choice project, and optionally 2^nd ranked project, as well as including whatever additional information you feel is pertinent to your application; you may wish to indicate, for example, why you are particularly interested in the selected project(s) and at the selected University;

·        copies of your relevant undergraduate degree transcripts and certificates;

·        a copy of your IELTS or TOEFL English language certificate (where required);

·        a copy of your passport (photo page).

A GUIDE TO THE FORMAT REQUIRED FOR THE APPLICATION DOCUMENTS IS AVAILABLE AT https://www.nld-dtp.org.uk/how-apply. Applications not meeting these criteria may be rejected.

In addition to the above items, please email a completed copy of the Additional Details Form (as a Word document) to bbsrcdtp@liverpool.ac.uk. A blank copy of this form can be found at: https://www.nld-dtp.org.uk/how-apply.

Informal enquiries may be made to J.Graham-Brown@liverpool.ac.uk

The deadline for all applications is 12noon on Monday 9^th January 2023.