Bayesian Spatio-Temporal Modeling of Schistosoma japonicum Prevalence Data in the Absence of a Diagnostic ‘Gold’ Standard

Schistosomiasis is a serious public health problem in the People's Republic of China and elsewhere, and mapping of risk areas is important for guiding control interventions. Here, a 10-year surveillance database from Dangtu County in the southeastern part of the People's Republic of China was utilized for modeling the spatial and temporal distribution of infections in relation to environmental features and socioeconomic factors. Disease surveillance was done on the basis of a serological test, and we explicitly considered the imperfect sensitivity and specificity of the test when modeling the ‘true’ infection prevalence of Schistosoma japonicum. We then produced a risk map for S. japonicum transmission, which can assist decision making for local control interventions. Our work emphasizes the importance of accounting for the uncertainty in the diagnosis of schistosomiasis, and the potential of predicting the spatial and temporal distribution of the disease when using a Bayesian modeling framework. Our study can therefore serve as a template for future risk profiling of neglected tropical diseases studies, particularly when exploring spatial and temporal disease patterns in relation to environmental and socioeconomic factors, and how to account for the influence of diagnostic uncertainty

Reductions in the Prevalence and Incidence of Geohelminth Infections following a City-wide Sanitation Program in a Brazilian Urban Centre

In the city of Salvador, a large urban centre in Northeast Brazil, a city-wide sanitation intervention started in 1997, aiming to improve the sewerage coverage of households from 26% to 80%. Our aim was to study the impact of the intervention on the prevalence and incidence of geohelminths in the school-aged population. The longitudinal study comprised two cohorts: from the beginning of 1997 to 1998, where data was collected before the intervention, and at the end of 2003 to 2004, after the intervention. Copro-parasitological examinations were carried out on every individual from both cohorts, at the start and nine months later. Demographic, socio-economic, and environmental data were collected using semi-structured questionnaires. The variables utilized to demonstrate the effects of intervention, when utilized together in a multivariate model, accounted for a 100% observed reduction in the prevalence ratio (PR) and incidence ratio (IR). As well as proving that the variables associated with the effect of the program intervention were mediators in this reduction, the reduction in the PR and IR between these periods demonstrated that modifications to the urban environment, particularly those associated with sanitary sewage systems, affected the health of the population, significantly reducing the prevalence of geohelminths

Reaction rates and transport in neutron stars

Understanding signals from neutron stars requires knowledge about the transport inside the star. We review the transport properties and the underlying reaction rates of dense hadronic and quark matter in the crust and the core of neutron stars and point out open problems and future directions.Comment: 74 pages; commissioned for the book "Physics and Astrophysics of Neutron Stars", NewCompStar COST Action MP1304; version 3: minor changes, references updated, overview graphic added in the introduction, improvements in Sec IV.A.

The Global Burden of Disease Study 2010: Interpretation and Implications for the Neglected Tropical Diseases

This article analyzes the "Global Burden of Disease Study 2010" and examines the study's implications for neglected tropical diseases

Reconstructing CNV genotypes using segregation analysis: combining pedigree information with CNV assay

<p>Abstract</p> <p>Background</p> <p>Repeated blocks of genome sequence have been shown to be associated with genetic diversity and disease risk in humans, and with phenotypic diversity in model organisms and domestic animals. Reliable tests are desirable to determine whether individuals are carriers of copy number variants associated with disease risk in humans and livestock, or associated with economically important traits in livestock. In some cases, copy number variants affect the phenotype through a dosage effect but in other cases, allele combinations have non-additive effects. In the latter cases, it has been difficult to develop tests because assays typically return an estimate of the sum of the copy number counts on the maternally and paternally inherited chromosome segments, and this sum does not uniquely determine the allele configuration. In this study, we show that there is an old solution to this new problem: segregation analysis, which has been used for many years to infer alleles in pedigreed populations.</p> <p>Methods</p> <p>Segregation analysis was used to estimate copy number alleles from assay data on simulated half-sib sheep populations. Copy number variation at the Agouti locus, known to be responsible for the recessive self-colour black phenotype, was used as a model for the simulation and an appropriate penetrance function was derived. The precision with which carriers and non-carriers of the undesirable single copy allele could be identified, was used to evaluate the method for various family sizes, assay strategies and assay accuracies.</p> <p>Results</p> <p>Using relationship data and segregation analysis, the probabilities of carrying the copy number alleles responsible for black or white fleece were estimated with much greater precision than by analyzing assay results for animals individually. The proportion of lambs correctly identified as non-carriers of the undesirable allele increased from 7% when the lambs were analysed alone to 80% when the lambs were analysed in half-sib families.</p> <p>Conclusions</p> <p>When a quantitative assay is used to estimate copy number alleles, segregation analysis of related individuals can greatly improve the precision of the estimates. Existing software for segregation analysis would require little if any change to accommodate the penetrance function for copy number assay data.</p

A Research Agenda for Helminth Diseases of Humans: Social Ecology, Environmental Determinants, and Health Systems

In this paper, the Disease Reference Group on Helminth Infections (DRG4), established in 2009 by the Special Programme for Research and Training in Tropical Diseases (TDR), with the mandate to review helminthiases research and identify research priorities and gaps, focuses on the environmental, social, behavioural, and political determinants of human helminth infections and outlines a research and development agenda for the socioeconomic and health systems research required for the development of sustainable control programmes. Using Stockols' social-ecological approach, we describe the role of various social (poverty, policy, stigma, culture, and migration) and environmental determinants (the home environment, water resources development, and climate change) in the perpetuation of helminthic diseases, as well as their impact as contextual factors on health promotion interventions through both the regular and community-based health systems. We examine these interactions in regard to community participation, intersectoral collaboration, gender, and possibilities for upscaling helminthic disease control and elimination programmes within the context of integrated and interdisciplinary approaches. The research agenda summarises major gaps that need to be addressed

Model-based geostatistical mapping of the prevalence of onchocerca volvulus in West Africa.

Background: The initial endemicity (pre-control prevalence) of onchocerciasis has been shown to be an important determinant of the feasibility of elimination by mass ivermectin distribution. We present the first geostatistical map of microfilarial prevalence in the former Onchocerciasis Control Programme in West Africa (OCP) before commencement of antivectorial and antiparasitic interventions. Methods and Findings: Pre-control microfilarial prevalence data from 737 villages across the 11 constituent countries in the OCP epidemiological database were used as ground-truth data. These 737 data points, plus a set of statistically selected environmental covariates, were used in a Bayesian model-based geostatistical (B-MBG) approach to generate a continuous surface (at pixel resolution of 5 km x 5km) of microfilarial prevalence in West Africa prior to the commencement of the OCP. Uncertainty in model predictions was measured using a suite of validation statistics, performed on bootstrap samples of held-out validation data. The mean Pearson’s correlation between observed and estimated prevalence at validation locations was 0.693; the mean prediction error (average difference between observed and estimated values) was 0.77%, and the mean absolute prediction error (average magnitude of difference between observed and estimated values) was 12.2%. Within OCP boundaries, 17.8 million people were deemed to have been at risk, 7.55 million to have been infected, and mean microfilarial prevalence to have been 45% (range: 2–90%) in 1975. Conclusions and Significance: This is the first map of initial onchocerciasis prevalence in West Africa using B-MBG. Important environmental predictors of infection prevalence were identified and used in a model out-performing those without spatial random effects or environmental covariates. Results may be compared with recent epidemiological mapping efforts to find areas of persisting transmission. These methods may be extended to areas where data are sparse, and may be used to help inform the feasibility of elimination with current and novel tools