Optimal population-level infection detection strategies for malaria control and elimination in a spatial model of malaria transmission

Mass campaigns with antimalarial drugs are potentially a powerful tool for local elimination of malaria, yet current diagnostic technologies are insufficiently sensitive to identify all individuals who harbor infections. At the same time, overtreatment of uninfected individuals increases the risk of accelerating emergence of drug resistance and losing community acceptance. Local heterogeneity in transmission intensity may allow campaign strategies that respond to index cases to successfully target subpatent infections while simultaneously limiting overtreatment. While selective targeting of hotspots of transmission has been proposed as a strategy for malaria control, such targeting has not been tested in the context of malaria elimination. Using household locations, demographics, and prevalence data from a survey of four health facility catchment areas in southern Zambia and an agent-based model of malaria transmission and immunity acquisition, a transmission intensity was fit to each household based on neighborhood age-dependent malaria prevalence. A set of individual infection trajectories was constructed for every household in each catchment area, accounting for heterogeneous exposure and immunity. Various campaign strategies (mass drug administration, mass screen and treat, focal mass drug administration, snowball reactive case detection, pooled sampling, and a hypothetical serological diagnostic) were simulated and evaluated for performance at finding infections, minimizing overtreatment, reducing clinical case counts, and interrupting transmission. For malaria control, presumptive treatment leads to substantial overtreatment without additional morbidity reduction under all but the highest transmission conditions. Selective targeting of hotspots with drug campaigns is an ineffective tool for elimination due to limited sensitivity of available field diagnostics

Une analyse lexicaliste des affixes pronominaux en français

Cet article considère comme acquis que les pronoms faibles du français sont des affixes flexionnels morphologiquement attachés à une base verbale et introduit le terme affixe pronominal pour les désigner. Nous proposons une analyse syntaxique strictement lexicaliste, dans le cadre HPSG, des formes verbales fléchies pour des affixes pronominaux objets. Cette analyse explique les propriétés spécifiques de ces formes verbales au niveau de la syntaxe de la phrase, notamment (i) l’impossibilité d’un complément plein si la forme verbale est fléchie pour l’affixe correspondant; (ii) le phénomène des affixes pronominaux « non locaux », c’est-à-dire les cas où les affixes pronominaux n’apparaissent pas sur la base verbale dont ils sont des arguments sémantiques; (iii) les corrélations entre la syntaxe des dépendances qu- et des affixes pronominaux, notamment au niveau du flottement des quantificateurs. Nous faisons crucialement appel à une forme de composition de fonctions, qui permet à une tête exigeant normalement un complément saturé de se combiner avec un complément non saturé et avec les compléments exigés par celui-ci.This paper takes as its premise the idea that French weak pronouns are in fact morphologically attached inflectional affixes, and introduces the term pronominal affix for them. We propose a strictly lexicalist syntactic analysis for verbs inflected for object pronominal affixes, couched in the framework of HPSG. This analysis explains the special syntactic properties of these verb forms, especially (i) the impossibility of a full complement in the presence of the corresponding affix on the verb; (ii) the phenomenon of "non local" pronominal affixes, i.e. cases where the affixes do not appear on the verb of which they are semantic arguments; (iii) the correlations between the syntax of wh- dependencies and that of pronominal affixes specifically with respect to quantifier floating. We crucially rely on a form of function composition that allows a head which normally requires a saturated complement to combine with a non-saturated complemement and with those complements which the latter normally requires

The Prediction of Broadband Shock-Associated Noise from Dualstream and Rectangular Jets Using RANS CFD

Supersonic jets operating off-design produce broadband shock-associated noise. Broadband shock-associated noise is characterized by multiple broadband peaks in the far-field and is often the dominant source of noise towards the sideline and upstream direction relative to the jet axis. It is due to large scale coherent turbulence structures in the jet shear layers interacting with the shock cell structure. A broadband shock-associated noise model recently developed by the authors predicts this noise component from solutions to the Reynolds averaged Navier-Stokes equations using a two-equation turbulence model. The broadband shock-associated noise model is applied to dualstream and rectangular nozzles operating supersonically, heated, and off-design. The dualstream jet broadband shock-associated noise predictions are conducted for cases when the core jet is supersonic and the fan jet is subsonic, the core jet is subsonic and the fan jet is supersonic, and when both jet streams operate supersonically. Rectangular jet predictions are shown for a convergent-divergent nozzle operating both over- and under-expanded for cold and heated conditions. The original model implementation has been heavily modified to make accurate predictions for the dualstream jets. It is also argued that for over-expanded jets the oblique shock wave attached to the nozzle lip contributes little to broadband shock-associated noise. All predictions are compared with experiments

New Corn Hybrids for Iowa

Four new lines in the cooperative Iowa corn breeding program are available for the production of several new hybrids in 1951. The lines themselves won\u27t be released this year. They\u27ll be released in single-cross combintions. The release procedure to be used is similar to that of the other north-central states and is called delayed release

A difference boosting neural network for automated star-galaxy classification

In this paper we describe the use of a new artificial neural network, called the difference boosting neural network (DBNN), for automated classification problems in astronomical data analysis. We illustrate the capabilities of the network by applying it to star galaxy classification using recently released, deep imaging data. We have compared our results with classification made by the widely used Source Extractor (SExtractor) package. We show that while the performance of the DBNN in star-galaxy classification is comparable to that of SExtractor, it has the advantage of significantly higher speed and flexibility during training as well as classification.Comment: 9 pages, 1figure, 7 tables, accepted for publication in Astronomy and Astrophysic

Optical studies of the ultraluminous X-ray source NGC1313 X-2

NGC1313 X-2 was among the first ultraluminous X-ray sources discovered, and has been a frequent target of X-ray and optical observations. Using the HST/ACS multi-band observations, this source is identified with a unique counterpart within an error circle of 0\farcs2. The counterpart is a blue star on the edge of a young cluster of $\le10^7$ years amid a dominant old stellar population. Its spectral energy distribution is consistent with that for a Z=0.004 star with 8.5 $M_\odot$ about $5\times10^6$ years old, or for an O7 V star at solar metallicity. The counterpart exhibited significant variability of $\Delta m = 0.153\pm0.033$ mag between two F555W observations separated by three months, reminiscent of the ellipsoidal variability due to the orbital motion of this ULX binary.Comment: 21 pages, 7 figures, scheduled for the ApJ June 10, 2007, v662n 1 issu

Malaria elimination campaigns in the Lake Kariba region of Zambia: a spatial dynamical model

Background As more regions approach malaria elimination, understanding how different interventions interact to reduce transmission becomes critical. The Lake Kariba area of Southern Province, Zambia, is part of a multi-country elimination effort and presents a particular challenge as it is an interconnected region of variable transmission intensities. Methods In 2012-13, six rounds of mass-screen-and-treat drug campaigns were carried out in the Lake Kariba region. A spatial dynamical model of malaria transmission in the Lake Kariba area, with transmission and climate modeled at the village scale, was calibrated to the 2012-13 prevalence survey data, with case management rates, insecticide-treated net usage, and drug campaign coverage informed by surveillance. The model was used to simulate the effect of various interventions implemented in 2014-22 on reducing regional transmission, achieving elimination by 2022, and maintaining elimination through 2028. Findings The model captured the spatio-temporal trends of decline and rebound in malaria prevalence in 2012-13 at the village scale. Simulations predicted that elimination required repeated mass drug administrations coupled with simultaneous increase in net usage. Drug campaigns targeted only at high-burden areas were as successful as campaigns covering the entire region. Interpretation Elimination in the Lake Kariba region is possible through coordinating mass drug campaigns with high-coverage vector control. Targeting regional hotspots is a viable alternative to global campaigns when human migration within an interconnected area is responsible for maintaining transmission in low-burden areas

Estimating correlation between multivariate longitudinal data in the presence of heterogeneity

Abstract Background Estimating correlation coefficients among outcomes is one of the most important analytical tasks in epidemiological and clinical research. Availability of multivariate longitudinal data presents a unique opportunity to assess joint evolution of outcomes over time. Bivariate linear mixed model (BLMM) provides a versatile tool with regard to assessing correlation. However, BLMMs often assume that all individuals are drawn from a single homogenous population where the individual trajectories are distributed smoothly around population average. Methods Using longitudinal mean deviation (MD) and visual acuity (VA) from the Ocular Hypertension Treatment Study (OHTS), we demonstrated strategies to better understand the correlation between multivariate longitudinal data in the presence of potential heterogeneity. Conditional correlation (i.e., marginal correlation given random effects) was calculated to describe how the association between longitudinal outcomes evolved over time within specific subpopulation. The impact of heterogeneity on correlation was also assessed by simulated data. Results There was a significant positive correlation in both random intercepts (ρ = 0.278, 95% CI: 0.121–0.420) and random slopes (ρ = 0.579, 95% CI: 0.349–0.810) between longitudinal MD and VA, and the strength of correlation constantly increased over time. However, conditional correlation and simulation studies revealed that the correlation was induced primarily by participants with rapid deteriorating MD who only accounted for a small fraction of total samples. Conclusion Conditional correlation given random effects provides a robust estimate to describe the correlation between multivariate longitudinal data in the presence of unobserved heterogeneity (NCT00000125)