Kinematics of the Sicily and Calabria Subduction System from Elastic Block Modeling of GPS Data

We use data from about 700 GPS stations in the EuroMediterranen region to investigate the present-day behavior of the the Calabrian subduction zone within the Mediterranean-scale plates kinematics and to perform local scale studies about the strain accumulation on active structures. We focus attenction on the Messina Straits and Crati Valley faults where GPS data show extentional velocity gradients of ∼3 mm/yr and ∼2 mm/yr, respectively. We use dislocation model and a non-linear constrained optimization algorithm to invert for fault geometric parameters and slip-rates and evaluate the associated uncertainties adopting a bootstrap approach. Our analysis suggest the presence of two partially locked normal faults. To investigate the impact of elastic strain contributes from other nearby active faults onto the observed velocity gradient we use a block modeling approach. Our models show that the inferred slip-rates on the two analyzed structures are strongly impacted by the assumed locking width of the Calabrian subduction thrust. In order to frame the observed local deformation features within the present- day central Mediterranean kinematics we realyze a statistical analysis testing the indipendent motion (w.r.t. the African and Eurasias plates) of the Adriatic, Cal- abrian and Sicilian blocks. Our preferred model confirms a microplate like behaviour for all the investigated blocks. Within these kinematic boundary conditions we fur- ther investigate the Calabrian Slab interface geometry using a combined approach of block modeling and χ2ν statistic. Almost no information is obtained using only the horizontal GPS velocities that prove to be a not sufficient dataset for a multi-parametric inversion approach. Trying to stronger constrain the slab geometry we estimate the predicted vertical velocities performing suites of forward models of elastic dislocations varying the fault locking depth. Comparison with the observed field suggest a maximum resolved locking depth of 25 km.

Choosing Smoothness Parameters for Smoothing Splines by Minimizing and Estimate of Risk

Smoothing splines are a popular approach for non-parametric regression problems. We use periodic smoothing splines to fit a periodic signal plus noise model to data for which we assume there are underlying circadian patterns. In the smoothing spline methodology, choosing an appropriate smoothness parameter is an important step in practice. In this paper, we draw a connection between smoothing splines and REACT estimators that provides motivation for the creation of criteria for choosing the smoothness parameter. The new criteria are compared to three existing methods, namely cross-validation, generalized cross-validation, and generalization of maximum likelihood criteria, by a Monte Carlo simulation and by an application to the study of circadian patterns. For most of the situations presented in the simulations, including the practical example, the new criteria out-perform the three existing criteria.

RANDOM EFFECTS MODELS IN A META-ANALYSIS OF THE ACCURACY OF DIAGNOSTIC TESTS WITHIN A GOLD STANDARD IN THE PRESENCE OF MISSING DATA

In evaluating the accuracy of diagnosis tests, it is common to apply two imperfect tests jointly or sequentially to a study population. In a recent meta-analysis of the accuracy of microsatellite instability testing (MSI) and traditional mutation analysis (MUT) in predicting germline mutations of the mismatch repair (MMR) genes, a Bayesian approach (Chen, Watson, and Parmigiani 2005) was proposed to handle missing data resulting from partial testing and the lack of a gold standard. In this paper, we demonstrate an improved estimation of the sensitivities and specificities of MSI and MUT by using a nonlinear mixed model and a Bayesian hierarchical model, both of which account for the heterogeneity across studies through study-specific random effects. The methods can be used to estimate the accuracy of two imperfect diagnostic tests in other meta-analyses when the prevalence of disease, the sensitivities and/or the specificities of diagnostic tests are heterogeneous among studies. Furthermore, simulation studies have demonstrated the importance of carefully selecting appropriate random effects on the estimation of diagnostic accuracy measurements in this scenario.

Toxoplasma gondii Infection in Kyrgyzstan: Seroprevalence, Risk Factor Analysis, and Estimate of Congenital and AIDS-Related Toxoplasmosis

Background HIV-prevalence, as well as incidence of zoonotic parasitic diseases like cystic echinococcosis, has increased in the Kyrgyz Republic due to fundamental socio-economic changes after the breakdown of the Soviet Union. The possible impact on morbidity and mortality caused by Toxoplasma gondii infection in congenital toxoplasmosis or as an opportunistic infection in the emerging AIDS pandemic has not been reported from Kyrgyzstan. Methodology/Principal Findings We screened 1,061 rural and 899 urban people to determine the seroprevalence of T. gondii infection in 2 representative but epidemiologically distinct populations in Kyrgyzstan. The rural population was from a typical agricultural district where sheep husbandry is a major occupation. The urban population was selected in collaboration with several diagnostic laboratories in Bishkek, the largest city in Kyrgyzstan. We designed a questionnaire that was used on all rural subjects so a risk-factor analysis could be undertaken. The samples from the urban population were anonymous and only data with regard to age and gender was available. Estimates of putative cases of congenital and AIDS-related toxoplasmosis in the whole country were made from the results of the serology. Specific antibodies (IgG) against Triton X-100 extracted antigens of T. gondii tachyzoites from in vitro cultures were determined by ELISA. Overall seroprevalence of infection with T. gondii in people living in rural vs. urban areas was 6.2% (95%CI: 4.8–7.8) (adjusted seroprevalence based on census figures 5.1%, 95% CI 3.9–6.5), and 19.0% (95%CI: 16.5–21.7) (adjusted 16.4%, 95% CI 14.1–19.3), respectively, without significant gender-specific differences. The seroprevalence increased with age. Independently low social status increased the risk of Toxoplasma seropositivity while increasing numbers of sheep owned decreased the risk of seropositivity. Water supply, consumption of unpasteurized milk products or undercooked meat, as well as cat ownership, had no significant influence on the risk for seropositivity. Conclusions We present a first seroprevalence analysis for human T. gondii infection in the Kyrgyz Republic. Based on these data we estimate that 173 (95% CI 136–216) Kyrgyz children will be born annually to mothers who seroconverted to toxoplasmosis during pregnancy. In addition, between 350 and 1,000 HIV-infected persons are currently estimated to be seropositive for toxoplasmosis. Taken together, this suggests a substantial impact of congenital and AIDS-related symptomatic toxoplasmosis on morbidity and mortality in Kyrgyzstan.

A new methodological protocol for the use of dendrogeomorphological data in flood risk analysis

Dendrogeomorphology uses information sources recorded in the roots, trunks and branches of trees and bushes located in the fluvial system to complement (or sometimes even replace) systematic and palaeohydrological records of past floods. The application of dendrogeomorphic data sources and methods to palaeoflood analysis over nearly 40 years has allowed improvements to be made in frequency and magnitude estimations of past floods. Nevertheless, research carried out so far has shown that the dendrogeomorphic indicators traditionally used (mainly scar evidence), and their use to infer frequency and magnitude, have been restricted to a small, limited set of applications. New possibilities with enormous potential remain unexplored. New insights in future research of palaeoflood frequency and magnitude using dendrogeomorphic data sources should: (1) test the application of isotopic indicators (16O/18O ratio) to discover the meteorological origin of past floods; (2) use different dendrogeomorphic indicators to estimate peak flows with 2D (and 3D) hydraulic models and study how they relate to other palaeostage indicators; (3) investigate improved calibration of 2D hydraulic model parameters (roughness); and (4) apply statistics-based cost–benefit analysis to select optimal mitigation measures. This paper presents an overview of these innovative methodologies, with a focus on their capabilities and limitations in the reconstruction of recent floods and palaeofloods.

Reliability of operational data from pig herds and performance ratings by veterinarians and pig farmers collected during telephone interviews for the evaluation of a PCV2 piglet vaccination

BackgroundThe aim of the present study was to evaluate the feasibility of using a telephone survey in gaining an understanding of the possible herd and management factors influencing the performance (i.e. safety and efficacy) of a vaccine against porcine circovirus type 2 (PCV2) in a large number of herds and to estimate customers¿ satisfaction.ResultsDatasets from 227 pig herds that currently applied or have applied a PCV2 vaccine were analysed. Since 1-, 2- and 3-site production systems were surveyed, the herds were allocated in one of two subsets, where only applicable variables out of 180 were analysed. Group 1 was comprised of herds with sows, suckling pigs and nursery pigs, whereas herds in Group 2 in all cases kept fattening pigs. Overall 14 variables evaluating the subjective satisfaction with one particular PCV2 vaccine were comingled to an abstract dependent variable for further models, which was characterized by a binary outcome from a cluster analysis: good/excellent satisfaction (green cluster) and moderate satisfaction (red cluster). The other 166 variables comprised information about diagnostics, vaccination, housing, management, were considered as independent variables. In Group 1, herds using the vaccine due to recognised PCV2 related health problems (wasting, mortality or porcine dermatitis and nephropathy syndrome) had a 2.4-fold increased chance (1/OR) of belonging to the green cluster. In the final model for Group 1, the diagnosis of diseases other than PCV2, the reason for vaccine administration being other than PCV2-associated diseases and using a single injection of iron had significant influence on allocating into the green cluster (P¿<¿0.05). In Group 2, only unchanged time or delay of time of vaccination influenced the satisfaction (P¿<¿0.05).ConclusionThe methodology and statistical approach used in this study were feasible to scientifically assess ¿satisfaction¿, and to determine factors influencing farmers¿ and vets¿ opinion about the safety and efficacy of a new vaccine.

Bexar County's dental safety net for children: An estimate of our current capacity and need

Introduction. It has been well established that poor uninsured children lack access to dental care and have greater dental needs than their insured counterparts. ^ Objective. To assess the capacity of Bexar County's dental safety net to treat children. To assess the dental needs of Bexar County children ages 0-18 who are uninsured or are Medicaid or SCHIP recipients. ^ Methods. Information was requested from dental safety net clinics that treat children ages 0-18. Data from the census, NHANES and other sources was used to estimate the dental needs. ^ Results. The capacity of the current safety net to treat children is 33,537 patient encounters per year. The dental needs of the community are 227,124 patient encounters per year. ^ Conclusion. The results of the study indicate that Bexar County is not prepared to treat the dental needs of the underserved children in San Antonio.^

Aedes aegypti, Aedes albopictus, and Dengue virus in Harris county: An estimate of risk

Recent outbreaks of dengue fever (DF) along the United States/Mexico border, coupled with the high number of reported cases in Mexico suggest that there is the possibility for DF emergence in Houston, Texas1,2. To determine the presence of DF, populations of Aedes aegypti and Aedes albopictus were identified and tested for dengue virus. Maps were created to identify "hot spots" (Figure 1) based on historical data on Ae. aegypti and Ae. albopictus, demographic information, and locations of human cases of dengue fever. BG Sentinel Traps®, in conjunction with BG Lure® attractant, octanol and dry ice, were used to collect mosquitoes, which were then tested for presence of dengue virus using ELISA techniques. All samples tested were negative for dengue virus (DV). Survival of DV ultimately comes down to whether or not it will be vectored by a mosquito to a susceptible human host. The presence of infected humans and contact with the mosquito vectors are two critical factors necessary in the establishment of DF. Historical records indicate the presence of Ae. aegypti and Ae. albopictus in Harris County, which would support localized dengue transmission if infected individuals are present.^ (1) Brunkard JM, Robles-Lopez JL, Ramirez J, Cifuentes E, Rothenberg SJ, Hunsperger EA, Moore CG, Brussolo RM, Villarreal NA, Haddad BM, 2007. Dengue fever seroprevalence and risk factors, Texas-Mexico border, 2004. Emerg Infect Dis 13: 1477-1483. (2) Ramos MM, Mohammed H, Zielinski-Gutierrez E, Hayden MH, Lopez JL, Fournier M, Trujillo AR, Burton R, Brunkard JM, Anaya-Lopez L, Banicki AA, Morales PK, Smith B, Munoz JL, Waterman SH, 2008. Epidemic dengue and dengue hemorrhagic fever at the Texas-Mexico Border: results of a household-based seroepidemiologic survey, December 2005. Am J Trop Med Hyg 78: 364-369.^

Data quality in trauma transfusion studies and the impact of missing data on predicting massive transfusion

Maximizing data quality may be especially difficult in trauma-related clinical research. Strategies are needed to improve data quality and assess the impact of data quality on clinical predictive models. This study had two objectives. The first was to compare missing data between two multi-center trauma transfusion studies: a retrospective study (RS) using medical chart data with minimal data quality review and the PRospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study with standardized quality assurance. The second objective was to assess the impact of missing data on clinical prediction algorithms by evaluating blood transfusion prediction models using PROMMTT data. RS (2005-06) and PROMMTT (2009-10) investigated trauma patients receiving ≥ 1 unit of red blood cells (RBC) from ten Level I trauma centers. Missing data were compared for 33 variables collected in both studies using mixed effects logistic regression (including random intercepts for study site). Massive transfusion (MT) patients received ≥ 10 RBC units within 24h of admission. Correct classification percentages for three MT prediction models were evaluated using complete case analysis and multiple imputation based on the multivariate normal distribution. A sensitivity analysis for missing data was conducted to estimate the upper and lower bounds of correct classification using assumptions about missing data under best and worst case scenarios. Most variables (17/33=52%) had <1% missing data in RS and PROMMTT. Of the remaining variables, 50% demonstrated less missingness in PROMMTT, 25% had less missingness in RS, and 25% were similar between studies. Missing percentages for MT prediction variables in PROMMTT ranged from 2.2% (heart rate) to 45% (respiratory rate). For variables missing >1%, study site was associated with missingness (all p≤0.021). Survival time predicted missingness for 50% of RS and 60% of PROMMTT variables. MT models complete case proportions ranged from 41% to 88%. Complete case analysis and multiple imputation demonstrated similar correct classification results. Sensitivity analysis upper-lower bound ranges for the three MT models were 59-63%, 36-46%, and 46-58%. Prospective collection of ten-fold more variables with data quality assurance reduced overall missing data. Study site and patient survival were associated with missingness, suggesting that data were not missing completely at random, and complete case analysis may lead to biased results. Evaluating clinical prediction model accuracy may be misleading in the presence of missing data, especially with many predictor variables. The proposed sensitivity analysis estimating correct classification under upper (best case scenario)/lower (worst case scenario) bounds may be more informative than multiple imputation, which provided results similar to complete case analysis.^

Annual layer thicknesses and age-depth (oldest estimate) of Derwael Ice Rise (IC12), Dronning Maud Land, East Antarctica

A 120 m-long ice core was drilled in 2012 on the Derwael Ice Rise, coastal Dronning Maud Land, East Antarctica. Water stable isotopes (d18O and dD) stratigraphy is supplemented by discontinuous major ion profiles and continuous electrical conductivity measurements. The base of the ice core is dated to AD 1759 ± 16, providing a climate proxy for the past ~250 years. This data set presents the core's annual layer thickness history in meters water equivalent for the oldest age-depth estimate before correction for the influence of ice deformation.