Biomedical subjects

Y C MacNab

Publications and source records attributed to Y C MacNab.

3 recordsLinked to original sources

PubMed2006

A conceptual model of water's role as a reservoir in Helicobacter pylori transmission: a review of the evidence.

Helicobacter pylori infection plays a role in the development of chronic gastritis, peptic ulcer and gastric cancer, yet the route of transmission into susceptible hosts remains unknown. Studies employing microbiological techniques have demonstrated that H. pylori has the ability to survive when introduced into water and that H. pylori is present in water and other environmental samples all over the world. Epidemiological studies have shown that water source and exposures related to water supply, including factors related to sewage disposal and exposure to animals, are risk factors for infection. This review describes the microbiological and epidemiological evidence for, and proposes a model of, waterborne H. pylori transmission outlining important features in the transmission cycle. In the model, humans and animals shed the bacteria in their faeces and the mechanisms for entry into water, and for survival, ingestion and infection are dependent upon a range of environmental influences. Verification of the proposed model pathways has important implications for public-health prevention strategies.

Animals↗

PubMed2001

Autoregressive spatial smoothing and temporal spline smoothing for mapping rates.

This article proposes generalized additive mixed models for the analysis of geographic and temporal variability of mortality rates. This class of models accommodates random spatial effects and fixed and random temporal components. Spatiotemporal models that use autoregressive local smoothing across the spatial dimension and B-spline smoothing over the temporal dimension are developed. The objective is the identification of temporal treads and the production of a series of smoothed maps from which spatial patterns of mortality risks can be monitored over time. Regions with consistently high rate estimates may be followed for further investigation. The methodology is illustrated by analysis of British Columbia infant mortality data.

Biometry↗

PubMedDate not supplied

Parametric bootstrap and penalized quasi-likelihood inference in conditional autoregressive models.

This paper discusses a variety of conditional autoregressive (CAR) models for mapping disease rates, beyond the usual first-order intrinsic CAR model. We illustrate the utility and scope of such models for handling different types of data structures. To encourage their routine use for map production at statistical and health agencies, a simple algorithm for fitting such models is presented. This is derived from penalized quasi-likelihood (PQL) inference which uses an analogue of best-linear unbiased estimation for the regional risk ratios and restricted maximum likelihood for the variance components. We offer the practitioner here the use of the parametric bootstrap for inference. It is more reliable than standard maximum likelihood asymptotics for inference purposes since relevant hypotheses for the mapping of rates lie on the boundary of the parameter space. We illustrate the parametric bootstrap test of the practically relevant and important simplifying hypothesis that there is no spatial autocorrelation. Although the parametric bootstrap requires computational effort, it is straightforward to implement and offers a wealth of information relating to the estimators and their properties. The proposed methodology is illustrated by analysing infant mortality in the province of British Columbia in Canada.

Algorithms↗