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Philip D O'Neill

Publications and source records attributed to Philip D O'Neill.

4 recordsLinked to original sources
PubMed2006

Estimating vaccine effects from studies of outbreaks in household pairs.

The traditional way to measure efficacy of a vaccine, with respect to reduced susceptibility and reduced infectivity once infected, is to look at relative attack rates. Although straightforward to apply, such measures do not take disease transmission into account, with the consequence that they can depend strongly on the community setting, the duration of the study period, the way participants are recruited into the study and the virulence of the infection. Sometimes they give a very misleading assessment of the vaccine, as we illustrate by examples. Here measures of vaccine efficacy are considered that avoid these defects, and estimation procedures are presented for studies based on outbreaks in household pairs. Such studies enable estimation of vaccine effects on susceptibility, infectivity and transmission. We propose that the vaccine efficacy measures be estimated, without making any assumptions about the nature of the vaccine response, by consistent estimates of bounds for the measures.

Disease Outbreaks↗
PubMed2005

Bayesian model choice and infection route modelling in an outbreak of Norovirus.

A data set from an outbreak of gastroenteritis in a school is analysed using a stochastic transmission model. The causative agent of the outbreak is believed to be a Norovirus, spread through person-to-person contact. Particular attention is given to the question of whether or not vomiting episodes enhance the spread of the virus via aerosol transmission. The methodology developed uses Bayesian model choice, implemented with reversible-jump Markov chain Monte Carlo methods. The methodology appears to be highly sensitive to assumptions made concerning the data, which provides some assurance that the conclusions are driven by observations rather than the underlying model and methodology.

Bayes Theorem↗
PubMed2003

Estimating vaccine effects on transmission of infection from household outbreak data.

This article is concerned with a method for making inferences about various measures of vaccine efficacy. These measures describe reductions in susceptibility and in the potential to transmit infection. The method uses data on household outbreaks; it is based on a model that allows for transmission of infection both from within a household and from the outside. The use of household data is motivated by the hope that these are informative about vaccine-induced reduction of the potential to transmit infection, as household outbreaks contain some information about the possible source of infection. For illustration, the method is applied to observed data on household outbreaks of smallpox. These data are of the form needed and the number of households is of a size that can be managed in a vaccine trial. It is found that vaccine effects, such as the mean reduction in susceptibility and the mean reduction in the potential to infect others, per infectious contact, can be estimated with precision. However, a more specific parameter reflecting the reduction in infectivity for individuals partially responding to vaccination is not estimated well in the application. An evaluation of the method using artificial data shows that this parameter can be estimated with greater precision when we have outbreak data on a large number of small households.

Biometry↗