Multi-level zero-inflated Poisson regression modelling of correlated count data with excess zeros

Count data with excess zeros relative to a Poisson distribution are common in many biomedical applications. A popular approach to the analysis of such data is to use a zero-inflated Poisson (ZIP) regression model. Often, because of the hierarchical Study design or the data collection procedure, zero-inflation and lack of independence may occur simultaneously, which tender the standard ZIP model inadequate. To account for the preponderance of zero counts and the inherent correlation of observations, a class of multi-level ZIP regression model with random effects is presented. Model fitting is facilitated using an expectation-maximization algorithm, whereas variance components are estimated via residual maximum likelihood estimating equations. A score test for zero-inflation is also presented. The multi-level ZIP model is then generalized to cope with a more complex correlation structure. Application to the analysis of correlated count data from a longitudinal infant feeding study illustrates the usefulness of the approach.

Molecular systematics of the Philippine malaria vector Anopheles flavirostris

Allozyme and molecular sequence data from the malaria vector Anopheles flavirostris (Ludlow) (Diptera: Culicidae) were analysed from 34 sites throughout the Philippines, including the type locality, to test the hypothesis that this taxon is a single panmictic species. A finer-scaled allozyme study, of mainly Luzon samples, revealed no fixed genetic differences in sympatric sites and only low levels of variation. We obtained data from partial sequences for the internal transcribed spacer 2 (ITS2) (483 bp), the third domain (D3) (330 bp) of the 28S ribosomal DNA subunit and cytochrome c oxidase subunit I (COI) of mitochondrial DNA (261 bp). No sequence variation was observed for ITS2, only a one base pair difference was observed between Philippine and Indonesian D3 sequences and An. flavirostris sequences were unique, confirming their diagnostic value for this taxon. Sixteen COI haplotypes were identified, giving 25 parsimony informative sites. Neighbour-Joining, Maximum Parsimony, Maximum Likelihood and Bayesian phylogenetic analysis of COI sequences for An. flavirostris and outgroup taxa revealed strong branch support for the monophyly of An. flavirostris, thus confirming that Philippine populations of this taxon comprise a single separate species within the Minimus Subgroup of the Funestus Group. Variation in the behaviour of An. flavirostris is likely to be intraspecific rather than interspecific in origin. © 2006 The Royal Entomological Society.

Bias, precision and heritability of self-reported and clinically measured height in Australian twins

Many studies of quantitative and disease traits in human genetics rely upon self-reported measures. Such measures are based on questionnaires or interviews and are often cheaper and more readily available than alternatives. However, the precision and potential bias cannot usually be assessed. Here we report a detailed quantitative genetic analysis of stature. We characterise the degree of measurement error by utilising a large sample of Australian twin pairs (857 MZ, 815 DZ) with both clinical and self-reported measures of height. Self-report height measurements are shown to be more variable than clinical measures. This has led to lowered estimates of heritability in many previous studies of stature. In our twin sample the heritability estimate for clinical height exceeded 90%. Repeated measures analysis shows that 2-3 times as many self-report measures are required to recover heritability estimates similar to those obtained from clinical measures. Bivariate genetic repeated measures analysis of self-report and clinical height measures showed an additive genetic correlation > 0.98. We show that the accuracy of self-report height is upwardly biased in older individuals and in individuals of short stature. By comparing clinical and self-report measures we also showed that there was a genetic component to females systematically reporting their height incorrectly; this phenomenon appeared to not be present in males. The results from the measurement error analysis were subsequently used to assess the effects of error on the power to detect linkage in a genome scan. Moderate reduction in error (through the use of accurate clinical or multiple self-report measures) increased the effective sample size by 22%; elimination of measurement error led to increases in effective sample size of 41%.

Origin of the West Nile virus responsible for an outbreak of encephalitis in the northeastern United States

In Late summer 1999, an outbreak of human encephalitis occurred in the northeastern United States that was concurrent with extensive mortality in crows (Corvus species) as well as the deaths of several exotic birds at a zoological park in the same area. Complete genome sequencing of a flavivirus isolated from the brain of a dead Chilean flamingo (Phoenicopterus chilensis), together with partial sequence analysis of envelope glycoprotein (E-glycoprotein) genes amplified from several other species including mosquitoes and two fatal human cases, revealed that West Nile (WN) virus circulated in natural transmission cycles and was responsible for the human disease. Antigenic mapping with E-glycoprotein-specific monoclonal antibodies and E-glycoprotein phylogenetic analysis confirmed these viruses as WN. This North American WN virus was most closely related to a WN virus isolated from a dead goose in Israel in 1998.