title: Constructing the effect of alternative intervention strategies on historic epidemics.
abstract: Data from historical epidemics provide a vital and sometimes under-used resource from which to devise strategies for future control of disease. Previous methods for retrospective analysis of epidemics, in which alternative interventions are compared, do not make full use of the information; by using only partial information on the historical trajectory, augmentation of control may lead to predictions of a paradoxical increase in disease. Here we introduce a novel statistical approach that takes full account of the available information in constructing the effect of alternative intervention strategies in historic epidemics. The key to the method lies in identifying a suitable mapping between the historic and notional outbreaks, under alternative control strategies. We do this by using the Sellke construction as a latent process linking epidemics. We illustrate the application of the method with two examples. First, using temporal data for the common human cold, we show the improvement under the new method in the precision of predictions for different control strategies. Second, we show the generality of the method for retrospective analysis of epidemics by applying it to a spatially extended arboreal epidemic in which we demonstrate the relative effectiveness of host culling strategies that differ in frequency and spatial extent. Some of the inferential and philosophical issues that arise are discussed along with the scope of potential application of the new method.
authors.affiliation: Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, UK. a.r.cook@ma.hw.ac.uk
authors.forename: A R
authors.initials: AR
authors.lastname: Cook
authors.forename: G J
authors.initials: GJ
authors.lastname: Gibson
authors.forename: T R
authors.initials: TR
authors.lastname: Gottwald
authors.forename: C A
authors.initials: CA
authors.lastname: Gilligan
mesh_terms: D002957:Citrus; D003139:Common Cold / Q000453:epidemiology; D004196:Disease Outbreaks / Q000517:prevention & control*; D006801:Humans; D008390:Markov Chains; D015233:Models, Statistical; D009010:Monte Carlo Method; D010935:Plant Diseases / Q000382:microbiology; D012189:Retrospective Studies