PhD project title: Towards a strengthened animal health risk assessment process in Denmark

PhD student: Helene Ane Jensen

https://dk.linkedin.com/in/helene-ane-jensen-024b31181 

THE PROJECT 
Animal health risk assessment is used to evaluate the risks posed by animal health threats, providing valuable information for policymakers on the prevention and control of infectious diseases. Assessing the probability of introduction and spread of infectious pathogens requires data from official registries, epidemiological studies, and outbreak investigations. However, such data are often limited, heterogeneous, and uncertain, necessitating quality assessment of the evidence to prevent misleading conclusions. Since risk assessments are often conducted under constraints of limited time and resources, current comprehensive tools for evaluating evidence quality are infeasible, and a practical method is therefore needed.

THE PURPOSE 
The purpose of my PhD thesis was to strengthen the animal health risk assessment process by proposing approaches to critically evaluate the quality of epidemiological evidence. The specific objectives were to: 1) identify types and sources of bias in epidemiological studies relevant to animal health risk assessments, 2) examine the strengths and weaknesses of qualitatively assessing the risk of bias in veterinary studies, 3) evaluate the influence of data input and assumptions on epidemiological outcomes, and 4) develop guidance for rapid systematic assessment of the quality of evidence included in animal health risk assessments. Using qualitative bias assessment tools, I evaluated potential biases in case studies related to biosecurity measures in small-scale pig holdings (Manuscript I), avian influenza risk factors in poultry holdings (Manuscript II), and the use of cannabidiol for dogs with epilepsy (Manuscript III). I also examined the influence of uncertainties in data input and assumptions on epidemiological outcomes through scenario and sensitivity analyses in a quantitative risk assessment of the introduction of African swine fever virus into Denmark (Manuscript IV).

THE RESULTS 
The veterinary case studies were subject to selection bias, information bias, and confounding, arising during study planning, design, data collection, and analysis. For example, responses from animal owners regarding legislative compliance might be skewed or incomplete due to the sensitive nature of such topics. Since epidemiological studies provide valuable information for risk assessments, researchers must aim to minimise potential biases. While available tools offer useful guidance for bias assessment, there is room for improvement and adaptation for veterinary research involving heterogeneous populations. The assumptions made in risk assessments greatly influence the epidemiological outcomes and estimated risks, emphasizing the need for transparent reporting. Based on these findings, I propose practical guidance for evaluating the overall evidence quality in animal health risk assessments, considering peer review, causality, data availability, indirectness, consistency, precision, study design and conduct, risk of bias, sample size, and missing values. This guidance can be used to enhance transparency, improve reporting consistency, and communicate the impact of uncertainties and assumptions to policymakers to prevent misinterpretation of risk assessment results.

THE FUTURE
To summarise, this PhD thesis provides insights into methods for evaluating the quality and robustness of evidence in animal health risk assessments, including risk-of-bias assessment, scenario analyses, and sensitivity analyses. It underlines the need for transparent, systematic reporting of limitations and potential biases in epidemiological studies and demonstrates how these can be accounted for in risk assessments. Finally, the thesis provides guidance and recommendations for improving the quality and robustness of future epidemiological studies and animal health risk assessments.

For more information, please contact Helene Ane Jensen, helene.jensen@sund.ku.dk