Estimating cause-specfic mortality from community- and facility-based data sources in the United Republic of Tanzania: options and implications for mortality burden estimates

Objective To compare mortality burden estimates based on direct measurement of levels and causes in communities with indirect estimates based on combining health facility cause-specific mortality structures with community measurement of mortality levels. Methods. Data from sentinel vital registration (SVR) with verbal autopsy (VA) were used to determine the cause-specific mortality burden at the community level in two areas of the United Republic of Tanzania. Proportional cause-specific mortality structures from health facilities were applied to counts of deaths obtained by SVR to produce modelled estimates. The burden was expressed in years of life lost. Findings. A total of 2884 deaths were recorded from health facilities and 2167 recorded from SVR/VAs. In the perinatal and neonatal age group cause-specific mortality rates were dominated by perinatal conditions and stillbirths in both the community and the facility data. The modelled estimates for chronic causes were very similar to those from SVR/VA. Acute febrile illnesses were coded more specifically in the facility data than in the VA. Injuries were more prevalent in the SVR/VA data than in that from the facilities. Conclusion. In this setting, improved International classification of diseases and health related problems, tenth revision (ICD-10) coding practices and applying facility-based cause structures to counts of deaths from communities, derived from SVR, appears to produce reasonable estimates of the cause-specific mortality burden in those aged 5 years and older determined directly from VA. For the perinatal and neonatal age group, VA appears to be required. Use of this approach in a nationally representative sample of facilities may produce reliable national estimates of the cause-specific mortality burden for leading causes of death in adults.

Estimating correlations from epidemiological data in the presence of measurement error

Analysis of a major multi-site epidemiologic study of heart disease has required estimation of the pairwise correlation of several measurements across sub-populations. Because the measurements from each sub-population were subject to sampling variability, the Pearson product moment estimator of these correlations produces biased estimates. This paper proposes a model that takes into account within and between sub-population variation, provides algorithms for obtaining maximum likelihood estimates of these correlations and discusses several approaches for obtaining interval estimates. (C) 1997 by John Wiley & Sons, Ltd.

Mapping structural parameters and species composition of riparian vegetation using IKONOS and Landsat ETM+ data in Australian tropical savannahs

Government agencies responsible for riparian environments are assessing the utility of remote sensing for mapping and monitoring vegetation structural parameters. The objective of this work was to evaluate Ikonos and Landsat-7 ETM+ imagery for mapping structural parameters and species composition of riparian vegetation in Australian tropical savannahs for a section of Keelbottom Creek, Queensland, Australia. Vegetation indices and image texture from Ikonos data were used for estimating leaf area index (R-2 = 0.13) and canopy percentage foliage cover (R-2 = 0.86). Pan-sharpened Ikonos data were used to map riparian species composition (overall accuracy = 55 percent) and riparian zone width (accuracy within +/- 3 m). Tree crowns could not be automatically delineated due to the lack of contrast between canopies and adjacent grass cover. The ETM+ imagery was suited for mapping the extent of riparian zones. Results presented demonstrate the capabilities of high and moderate spatial resolution imagery for mapping properties of riparian zones.

V4 region of small subunit rDNA indicates polyphyly of the Fellodistomidae (Digenea) which is supported by morphology and life-cycle data

There is no morphological synapomorphy for the disparate digeneans, the Fellodistomidae Nicoll, 1909. Although all known life-cycles of the group include bivalves as first intermediate hosts, there is no convincing morphological synapomorphy that can be used to unite the group. Sequences from the V4 region of small subunit (18S) rRNA genes were used to infer phylogenetic relationships among 13 species of Fellodistomidae from four subfamilies and eight species from seven other digenean families: Bivesiculidae; Brachylaimidae; Bucephalidae; Gorgoderidae; Gymnophallidae; Opecoelidae; and Zoogonidae. Outgroup comparison was made initially with an aspidogastrean. Various species from the other digenean families were used as outgroups in subsequent analyses. Three methods of analysis indicated polyphyly of the Fellodistomidae and at least two independent radiations of the subfamilies, such that they were more closely associated with other digeneans than to each other. The Tandanicolinae was monophyletic (100% bootstrap support) and was weakly associated with the Gymnophallidae (< 50-55% bootstrap support). Monophyly of the Baccigerinae was supported with 78-87% bootstrap support, and monophyly of the Zoogonidae + Baccigerinae received 77-86% support. The remaining fellodistomid species, Fellodistomum fellis, F. agnotum and Coomera brayi (Fellodistominae) plus Proctoeces maculatus and Complexobursa sp. (Proctoecinae), formed a separate clade with 74-92% bootstrap support. On the basis of molecular, morphological and life-cycle evidence, the subfamilies Baccigerinae and Tandanicolinae are removed from the Fellodistomidae and promoted to familial status. The Baccigerinae is promoted under the senior synonym Faustulidae Poche, 1926, and the Echinobrevicecinae Dronen, Blend & McEachran, 1994 is synonymised with the Faustulidae. Consequently, species that were formerly in the Fellodistomidae are now distributed in three families: Fellodistomidae; Faustulidae (syn. Baccigerinae Yamaguti, 1954); and Tandanicolidae Johnston, 1927. We infer that the use of bivalves as intermediate hosts by this broad range of families indicates multiple host-switching events within the radiation of the Digenea.

Exploring through cover - the integrated interpretation of high resolution aeromagnetic, airborne electromagnetic and ground gravity data from the Grant's Patch area, Eastern Goldfields Province, Archaean Yigarn Craton Part B; Gravity inversion as a

The cost and risk associated with mineral exploration in Australia increases significantly as companies move into deeper regolith-covered terrain. The ability to map the bedrock and the depth of weathering within an area has the potential to decrease this risk and increase the effectiveness of exploration programs. This paper is the second in a trilogy concerning the Grant's Patch area of the Eastern Goldfields. The recent development of the VPmg potential field inversion program in conjunction with the acquisition of high-resolution gravity data over an area with extensive drilling provided an opportunity to evaluate three-dimensional gravity inversion as a bedrock and regolith mapping tool. An apparent density model of the study area was constructed, with the ground represented as adjoining 200 m by 200 m vertical rectangular prisms. During inversion VPmg incrementally adjusted the density of each prism until the free-air gravity response of the model replicated the observed data. For the Grant's Patch study area, this image of the apparent density values proved easier to interpret than the Bouguer gravity image. A regolith layer was introduced into the model and realistic fresh-rock densities assigned to each basement prism according to its interpreted lithology. With the basement and regolith densities fixed, the VPmg inversion algorithm adjusted the depth to fresh basement until the misfit between the calculated and observed gravity response was minimised. The resulting geometry of the bedrock/regolith contact largely replicated the base of weathering indicated by drilling with predicted depth of weathering values from gravity inversion typically within 15% of those logged during RAB and RC drilling.

Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate Data

Binning and truncation of data are common in data analysis and machine learning. This paper addresses the problem of fitting mixture densities to multivariate binned and truncated data. The EM approach proposed by McLachlan and Jones (Biometrics, 44: 2, 571-578, 1988) for the univariate case is generalized to multivariate measurements. The multivariate solution requires the evaluation of multidimensional integrals over each bin at each iteration of the EM procedure. Naive implementation of the procedure can lead to computationally inefficient results. To reduce the computational cost a number of straightforward numerical techniques are proposed. Results on simulated data indicate that the proposed methods can achieve significant computational gains with no loss in the accuracy of the final parameter estimates. Furthermore, experimental results suggest that with a sufficient number of bins and data points it is possible to estimate the true underlying density almost as well as if the data were not binned. The paper concludes with a brief description of an application of this approach to diagnosis of iron deficiency anemia, in the context of binned and truncated bivariate measurements of volume and hemoglobin concentration from an individual's red blood cells.

Estimating and evaluating the statistics of gapped local-alignment scores

We present a novel maximum-likelihood-based algorithm for estimating the distribution of alignment scores from the scores of unrelated sequences in a database search. Using a new method for measuring the accuracy of p-values, we show that our maximum-likelihood-based algorithm is more accurate than existing regression-based and lookup table methods. We explore a more sophisticated way of modeling and estimating the score distributions (using a two-component mixture model and expectation maximization), but conclude that this does not improve significantly over simply ignoring scores with small E-values during estimation. Finally, we measure the classification accuracy of p-values estimated in different ways and observe that inaccurate p-values can, somewhat paradoxically, lead to higher classification accuracy. We explain this paradox and argue that statistical accuracy, not classification accuracy, should be the primary criterion in comparisons of similarity search methods that return p-values that adjust for target sequence length.