Speaker: David Price, University of Melbourne and Royal Melbourne Hospital, Australia
Title:“Optimal allocation of resources to learn about infectious diseases”
Design of experiments is not a new concept. However, much of the classical experimental design work was developed for the purpose of hypothesis testing – i.e., how many resources (e.g., individuals, mice, blood samples, etc.), are required to ensure sufficient statistical power to test a formal hypothesis. In contrast, many basic science experiments (e.g., microbiology, immunology or chemistry) and observational studies (e.g., sampling populations or the environment to understand an ongoing phenomenon), are often exploratory – concerned with estimation of a quantity or learning about a system, rather than hypothesis testing. This talk will introduce the optimal design framework, a decision-theoretic approach to the problem of allocating limited resources to optimise statistical information. We will consider scenarios where the purpose is to either estimate parameters or discriminate between competing models as well as possible. Examples in each case will relate to learning about infectious disease dynamics.