Designing group dose-response studies in the presence of transmission

Related Staff:

David J.Price a,b , Nigel G. Bean c,d , Joshua V. Ross c,d , Jonathan Tuke c,d. Designing group dose-response studies in the presence of transmission. Mathematical Biosciences, Volume 304,October 2018, Pages 62-78. .


Dose-response studies are used throughout pharmacology, toxicology and in clinical research to determine safe, effective, or hazardous doses of a substance. When involving animals, the subjects are often housed in groups; this is in fact mandatory in many countries for social animals, on ethical grounds. An issue that may consequently arise is that of unregulated between-subject dosing (transmission), where a subject may transmit the substance to another subject. Transmission will obviously impact the assessment of the dose-response relationship, and will lead to biases if not properly modelled. Here we present a method for determining the optimal design – pertaining to the size of groups, the doses, and the killing times – for such group dose-response experiments, in a Bayesian framework. Our results are of importance to minimising the number of animals required in order to accurately determine dose-response relationships. Furthermore, we additionally consider scenarios in which the estimation of the amount of transmission is also of interest. A particular motivating example is that of Campylobacter jejuni in chickens. Code is provided so that practitioners may determine the optimal design for their own studies.


a Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, VIC 3010, Australia

b Victorian Infectious Diseases Reference Laboratory Epidemiology Unit, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Royal Melbourne Hospital, VIC 3000, Australia

c School of Mathematical Sciences, University of Adelaide, SA 5005, Australia

d ARC Centre of Excellence for Mathematical & Statistical Frontiers, School of Mathematical Sciences, University of Adelaide, SA 5005, Australia