Influenza Vaccine Effectiveness in the Elderly Based on Administrative Databases: Change in Immunization Habit as a Marker for Bias

Administrative databases provide efficient methods to estimate influenza vaccine effectiveness (IVE) against severe outcomes in the elderly but are prone to intractable bias. This study returns to one of the linked population databases by which IVE against hospitalization and death in the elderly was first assessed. We explore IVE across six more recent influenza seasons, including periods before, during, and after peak activity to identify potential markers for bias.Acute respiratory hospitalization and all-cause mortality were compared between immunized/non-immunized community-dwelling seniors ≥65 years through administrative databases in Manitoba, Canada between 2000-01 and 2005-06. IVE was compared during pre-season/influenza/post-season periods through logistic regression with multivariable adjustment (age/sex/income/residence/prior influenza or pneumococcal immunization/medical visits/comorbidity), stratification based on prior influenza immunization history, and propensity scores. Analysis during pre-season periods assessed baseline differences between immunized and unimmunized groups. The study population included ∼140,000 seniors, of whom 50-60% were immunized annually. Adjustment for key covariates and use of propensity scores consistently increased IVE. Estimates were paradoxically higher pre-season and for all-cause mortality vs. acute respiratory hospitalization. Stratified analysis showed that those twice consecutively and currently immunized were always at significantly lower hospitalization/mortality risk with odds ratios (OR) of 0.60 [95%CI0.48-0.75] and 0.58 [0.53-0.64] pre-season and 0.77 [0.69-0.86] and 0.71 [0.66-0.77] during influenza circulation, relative to the consistently unimmunized. Conversely, those forgoing immunization when twice previously immunized were always at significantly higher hospitalization/mortality risk with OR of 1.41 [1.14-1.73] and 2.45 [2.21-2.72] pre-season and 1.21 [1.03-1.43] and 1.78 [1.61-1.96] during influenza circulation.The most pronounced IVE estimates were paradoxically observed pre-season, indicating bias tending to over-estimate vaccine protection. Change in immunization habit from that of the prior two years may be a marker for this bias in administrative data sets; however, no analytic technique explored could adjust for its influence. Improved methods to achieve valid interpretation of protection in the elderly are needed

First observations of separated atmospheric nu_mu and bar{nu-mu} events in the MINOS detector

The complete 5.4 kton MINOS far detector has been taking data since the beginning of August 2003 at a depth of 2070 meters water-equivalent in the Soudan mine, Minnesota. This paper presents the first MINOS observations of nuµ and [overline nu ]µ charged-current atmospheric neutrino interactions based on an exposure of 418 days. The ratio of upward- to downward-going events in the data is compared to the Monte Carlo expectation in the absence of neutrino oscillations, giving Rup/downdata/Rup/downMC=0.62-0.14+0.19(stat.)±0.02(sys.). An extended maximum likelihood analysis of the observed L/E distributions excludes the null hypothesis of no neutrino oscillations at the 98% confidence level. Using the curvature of the observed muons in the 1.3 T MINOS magnetic field nuµ and [overline nu ]µ interactions are separated. The ratio of [overline nu ]µ to nuµ events in the data is compared to the Monte Carlo expectation assuming neutrinos and antineutrinos oscillate in the same manner, giving R[overline nu ][sub mu]/nu[sub mu]data/R[overline nu ][sub mu]/nu[sub mu]MC=0.96-0.27+0.38(stat.)±0.15(sys.), where the errors are the statistical and systematic uncertainties. Although the statistics are limited, this is the first direct observation of atmospheric neutrino interactions separately for nuµ and [overline nu ]µ

Temporal allocation of foraging effort in female Australian fur seals (Arctocephalus pusillus doriferus)

Across an individual\u27s life, foraging decisions will be affected by multiple intrinsic and extrinsic drivers that act at differing timescales. This study aimed to assess how female Australian fur seals allocated foraging effort and the behavioural changes used to achieve this at three temporal scales: within a day, across a foraging trip and across the final six months of the lactation period. Foraging effort peaked during daylight hours (57% of time diving) with lulls in activity just prior to and after daylight. Dive duration reduced across the day (196 s to 168 s) but this was compensated for by an increase in the vertical travel rate (1500–1600 m•h−1) and a reduction in postdive duration (111–90 s). This suggests physiological constraints (digestive costs) or prey availability may be limiting mean dive durations as a day progresses. During short trips (<2.9 d), effort remained steady at 55% of time diving, whereas, on long trips (>2.9 d) effort increased up to 2–3 d and then decreased. Dive duration decreased at the same rate in short and long trips, respectively, before stabilising (long trips) between 4–5 d. Suggesting that the same processes (digestive costs or prey availability) working at the daily scale may also be present across a trip. Across the lactation period, foraging effort, dive duration and vertical travel rate increased until August, before beginning to decrease. This suggests that as the nutritional demands of the suckling pup and developing foetus increase, female effort increases to accommodate this, providing insight into the potential constraints of maternal investment in this specie

Mapping and simulating systematics due to spatially-varying observing conditions in DES Science Verification data

Spatially-varying depth and characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, in particular in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. We illustrate the complementarity of these two approaches by comparing the SV data with the BCC-UFig, a synthetic sky catalogue generated by forward-modelling of the DES SV images. We analyse the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially-varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and well-captured by the maps of observing conditions. The combined use of the maps, the SV data and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on $N(z)$, the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak lensing analyses. The framework presented here is relevant to all multi-epoch surveys, and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope (LSST), which will require detailed null-tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky

Dark energy survey year 1 results: Redshift distributions of the weak-lensing source galaxies

We describe the derivation and validation of redshift distribution estimates and their uncertainties for the populations of galaxies used as weak-lensing sources in the Dark Energy Survey (DES) Year 1 cosmological analyses. The Bayesian Photometric Redshift (BPZ) code is used to assign galaxies to four redshift bins between z ≈ 0.2 and ≈1.3, and to produce initial estimates of the lensing-weighted redshift distributions nPZi(z) ∝ dni/dz for members of bin i. Accurate determination of cosmological parameters depends critically on knowledge of ni, but is insensitive to bin assignments or redshift errors for individual galaxies. The cosmological analyses allow for shifts ni (z) = nPZi(z - Δzi) to correct themean redshift of ni(z) for biases in nPZi. The Δzi are constrained by comparison of independently estimated 30-band photometric redshifts of galaxies in the Cosmic Evolution Survey (COSMOS) field to BPZ estimates made from the DES griz fluxes, for a sample matched in fluxes, pre-seeing size, and lensing weight to the DES weak-lensing sources. In companion papers, the Δzi of the three lowest redshift bins are further constrained by the angular clustering of the source galaxies around red galaxies with secure photometric redshifts at 0.15 < z < 0.9. This paper details the BPZ and COSMOS procedures, and demonstrates that the cosmological inference is insensitive to details of the ni(z) beyond the choice of Δzi. The clustering and COSMOS validation methods produce consistent estimates of Δzi in the bins where both can be applied, with combined uncertainties of σΔzi = 0.015, 0.013, 0.011, and 0.022 in the four bins. Repeating the photo-z procedure instead using the Directional Neighbourhood Fitting algorithm, or using the ni(z) estimated from the matched sample in COSMOS, yields no discernible difference in cosmological inferences

Dark energy survey year 1 results: weak lensing shape catalogues

We present two galaxy shape catalogues from the Dark Energy Survey Year 1 data set, covering 1500 deg2 with a median redshift of 0.59. The catalogues cover two main fields: Stripe 82, and an area overlapping the South Pole Telescope survey region. We describe our data analysis process and in particular our shape measurement using two independent shear measurement pipelines, METACALIBRATION and IM3SHAPE. The METACALIBRATION catalogue uses a Gaussian model with an innovative internal calibration scheme, and was applied to riz bands, yielding 34.8M objects. The IM3SHAPE catalogue uses amaximum-likelihood bulge/disc model calibrated using simulations, and was applied to r-band data, yielding 21.9M objects. Both catalogues pass a suite of null tests that demonstrate their fitness for use in weak lensing science. We estimate the 1σ uncertainties in multiplicative shear calibration to be 0.013 and 0.025 for the METACALIBRATION and IM3SHAPE catalogues, respectively

Dark Energy Survey Year 1 results: galaxy-galaxy lensing

We present galaxy-galaxy lensing measurements from 1321 sq. deg. of the Dark Energy Survey (DES) Year 1 (Y1) data. The lens sample consists of a selection of 660,000 red galaxies with high-precision photometric redshifts, known as redMaGiC, split into five tomographic bins in the redshift range 0.15<z<0.9 . We use two different source samples, obtained from the Metacalibration (26 million galaxies) and Im3shape (18 million galaxies) shear estimation codes, which are split into four photometric redshift bins in the range 0.2<z<1.3 . We perform extensive testing of potential systematic effects that can bias the galaxy-galaxy lensing signal, including those from shear estimation, photometric redshifts, and observational properties. Covariances are obtained from jackknife subsamples of the data and validated with a suite of log-normal simulations. We use the shear-ratio geometric test to obtain independent constraints on the mean of the source redshift distributions, providing validation of those obtained from other photo-z studies with the same data. We find consistency between the galaxy bias estimates obtained from our galaxy-galaxy lensing measurements and from galaxy clustering, therefore showing the galaxy-matter cross-correlation coefficient r to be consistent with one, measured over the scales used for the cosmological analysis. The results in this work present one of the three two-point correlation functions, along with galaxy clustering and cosmic shear, used in the DES cosmological analysis of Y1 data, and hence the methodology and the systematics tests presented here provide a critical input for that study as well as for future cosmological analyses in DES and other photometric galaxy surveys

Dark Energy Survey year 1 results: cosmological constraints from cluster abundances and weak lensing

We perform a joint analysis of the counts and weak lensing signal of redMaPPer clusters selected from the Dark Energy Survey (DES) Year 1 dataset. Our analysis uses the same shear and source photometric redshifts estimates as were used in the DES combined probes analysis. Our analysis results in surprisingly low values for S8=σ8(Ωm/0.3)0.5=0.65±0.04, driven by a low matter density parameter, Ωm=0.179+0.031−0.038, with σ8−Ωm posteriors in 2.4σ tension with the DES Y1 3x2pt results, and in 5.6σ with the Planck CMB analysis. These results include the impact of post-unblinding changes to the analysis, which did not improve the level of consistency with other data sets compared to the results obtained at the unblinding. The fact that multiple cosmological probes (supernovae, baryon acoustic oscillations, cosmic shear, galaxy clustering and CMB anisotropies), and other galaxy cluster analyses all favor significantly higher matter densities suggests the presence of systematic errors in the data or an incomplete modeling of the relevant physics. Cross checks with x-ray and microwave data, as well as independent constraints on the observable-mass relation from Sunyaev-Zeldovich selected clusters, suggest that the discrepancy resides in our modeling of the weak lensing signal rather than the cluster abundance. Repeating our analysis using a higher richness threshold (λ≥30) significantly reduces the tension with other probes, and points to one or more richness-dependent effects not captured by our model