A detection of wobbling brightest cluster galaxies within massive galaxy clusters

A striking signal of dark matter beyond the standard model is the existence of cores in the centre of galaxy clusters. Recent simulations predict that a brightest cluster galaxy (BCG) inside a cored galaxy cluster will exhibit residual wobbling due to previous major mergers, long after the relaxation of the overall cluster. This phenomenon is absent with standard cold dark matter where a cuspy density profile keeps a BCG tightly bound at the centre. We test this hypothesis using cosmological simulations and deep observations of 10 galaxy clusters acting as strong gravitational lenses. Modelling the BCG wobble as a simple harmonic oscillator, we measure the wobble amplitude, Aw, in the BAHAMAS suite of cosmological hydrodynamical simulations, finding an upper limit for the cold dark matter paradigm of Aw < 2 kpc at the 95 per cent confidence limit. We carry out the same test on the data finding a non-zero amplitude of Aw=11.82+7.3−3.0 kpc, with the observations dis-favouring Aw = 0 at the 3σ confidence level. This detection of BCG wobbling is evidence for a dark matter core at the heart of galaxy clusters. It also shows that strong lensing models of clusters cannot assume that the BCG is exactly coincident with the large-scale halo. While our small sample of galaxy clusters already indicates a non-zero Aw, with larger surveys, e.g. Euclid, we will be able to not only confirm the effect but also to use it to determine whether or not the wobbling finds its origin in new fundamental physics or astrophysical process

DESI and DECaLS (D&D): galaxy–galaxy lensing measurements with 1 per cent survey and its forecast

The shear measurement from the Dark Energy Camera Legacy Survey (DECaLS) provides an excellent opportunity for galaxy-galaxy lensing study with the Dark Energy Spectroscopic Instrument (DESI) galaxies, given the large (∼9000 deg2) sky overlap. We explore this potential by combining the DESI 1 per cent survey and DECaLS Data Release 8 (DR8). With ∼106 deg2 sky overlap, we achieve significant detection of galaxy-galaxy lensing for Bright Galaxy Survey (BGS) and luminous red galaxy (LRG) as lenses. Scaled to the full BGS sample, we expect the statistical errors to improve from to a promising level of at. This brings stronger requirements for future systematics control. To fully realize such potential, we need to control the residual multiplicative shear bias |m| < 0.006 and the bias in the mean redshift |Δz| < 0.008, requiring the introduced bias in the measurement is <0.31σ. We also expect significant detection of galaxy-galaxy lensing with DESI LRG/emission line galaxy (ELG) full samples as lenses, and cosmic magnification of ELG through cross-correlation with low-redshift DECaLS shear. If such systematical error control can be achieved, we find the advantages of DECaLS, comparing with the Kilo Degree Survey (KiDS) and the Hyper Suprime-Cam (HSC), are at low redshift, large scale, and in measuring the shear ratio (to σR ∼0.04) and cosmic magnification

Early star-forming galaxies and the reionization of the Universe

Star forming galaxies represent a valuable tracer of cosmic history. Recent observational progress with Hubble Space Telescope has led to the discovery and study of the earliest-known galaxies corresponding to a period when the Universe was only ~800 million years old. Intense ultraviolet radiation from these early galaxies probably induced a major event in cosmic history: the reionization of intergalactic hydrogen. New techniques are being developed to understand the properties of these most distant galaxies and determine their influence on the evolution of the universe.Comment: Review article appearing in Nature. This posting reflects a submitted version of the review formatted by the authors, in accordance with Nature publication policies. For the official, published version of the review, please see http://www.nature.com/nature/archive/index.htm

Bayesian modelling of the effect of climate on malaria in Burundi

<p>Abstract</p> <p>Background</p> <p>In Burundi, malaria is a major public health issue in terms of both morbidity and mortality with around 2.5 million clinical cases and more than 15,000 deaths each year. It is the single main cause of mortality in pregnant women and children below five years of age. Due to the severe health and economic cost of malaria, there is still a growing need for methods that will help to understand the influencing factors. Several studies have been done on the subject yielding different results as which factors are most responsible for the increase in malaria. The purpose of this study has been to undertake a spatial/longitudinal statistical analysis to identify important climatic variables that influence malaria incidences in Burundi.</p> <p>Methods</p> <p>This paper investigates the effects of climate on malaria in Burundi. For the period 1996-2007, real monthly data on both malaria epidemiology and climate in the area of Burundi are described and analysed. From this analysis, a mathematical model is derived and proposed to assess which variables significantly influence malaria incidences in Burundi. The proposed modelling is based on both generalized linear models (GLM) and generalized additive mixed models (GAMM). The modelling is fully Bayesian and inference is carried out by Markov Chain Monte Carlo (MCMC) techniques.</p> <p>Results</p> <p>The results obtained from the proposed models are discussed and it is found that malaria incidence in a given month in Burundi is strongly positively associated with the minimum temperature of the previous month. In contrast, it is found that rainfall and maximum temperature in a given month have a possible negative effect on malaria incidence of the same month.</p> <p>Conclusions</p> <p>This study has exploited available real monthly data on malaria and climate over 12 years in Burundi to derive and propose a regression modelling to assess climatic factors that are associated with monthly malaria incidence. The results obtained from the proposed models suggest a strong positive association between malaria incidence in a given month and the minimum temperature (night temperature) of the previous month. An open question is, therefore, how to cope with high temperatures at night.</p

Environmental controls, oceanography and population dynamics of pathogens and harmful algal blooms: connecting sources to human exposure

© 2008 Author et al. This is an open access article distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Environmental Health 7 (2008): S5, doi:10.1186/1476-069X-7-S2-S5.Coupled physical-biological models are capable of linking the complex interactions between environmental factors and physical hydrodynamics to simulate the growth, toxicity and transport of infectious pathogens and harmful algal blooms (HABs). Such simulations can be used to assess and predict the impact of pathogens and HABs on human health. Given the widespread and increasing reliance of coastal communities on aquatic systems for drinking water, seafood and recreation, such predictions are critical for making informed resource management decisions. Here we identify three challenges to making this connection between pathogens/HABs and human health: predicting concentrations and toxicity; identifying the spatial and temporal scales of population and ecosystem interactions; and applying the understanding of population dynamics of pathogens/HABs to management strategies. We elaborate on the need to meet each of these challenges, describe how modeling approaches can be used and discuss strategies for moving forward in addressing these challenges.The authors acknowledge the financial support for the NSF/NIEHS and NOAA Centers for Oceans and Human Healt

The Robotic Multiobject Focal Plane System of the Dark Energy Spectroscopic Instrument (DESI)

A system of 5020 robotic fiber positioners was installed in 2019 on the Mayall Telescope, at Kitt Peak National Observatory. The robots automatically retarget their optical fibers every 10-20 minutes, each to a precision of several microns, with a reconfiguration time of fewer than 2 minutes. Over the next 5 yr, they will enable the newly constructed Dark Energy Spectroscopic Instrument (DESI) to measure the spectra of 35 million galaxies and quasars. DESI will produce the largest 3D map of the universe to date and measure the expansion history of the cosmos. In addition to the 5020 robotic positioners and optical fibers, DESI’s Focal Plane System includes six guide cameras, four wave front cameras, 123 fiducial point sources, and a metrology camera mounted at the primary mirror. The system also includes associated structural, thermal, and electrical systems. In all, it contains over 675,000 individual parts. We discuss the design, construction, quality control, and integration of all these components. We include a summary of the key requirements, the review and acceptance process, on-sky validations of requirements, and lessons learned for future multiobject, fiber-fed spectrographs

Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Cosmological implications from two decades of spectroscopic surveys at the Apache Point Observatory

We present the cosmological implications from final measurements of clustering using galaxies, quasars, and Ly α forests from the completed Sloan Digital Sky Survey (SDSS) lineage of experiments in large-scale structure. These experiments, composed of data from SDSS, SDSS-II, BOSS, and eBOSS, offer independent measurements of baryon acoustic oscillation (BAO) measurements of angular-diameter distances and Hubble distances relative to the sound horizon, r_{d}, from eight different samples and six measurements of the growth rate parameter, fσ_{8}, from redshift-space distortions (RSD). This composite sample is the most constraining of its kind and allows us to perform a comprehensive assessment of the cosmological model after two decades of dedicated spectroscopic observation. We show that the BAO data alone are able to rule out dark-energy-free models at more than eight standard deviations in an extension to the flat, Λ CDM model that allows for curvature. When combined with Planck Cosmic Microwave Background (CMB) measurements of temperature and polarization, under the same model, the BAO data provide nearly an order of magnitude improvement on curvature constraints relative to primary CMB constraints alone. Independent of distance measurements, the SDSS RSD data complement weak lensing measurements from the Dark Energy Survey (DES) in demonstrating a preference for a flat Λ CDM cosmological model when combined with Planck measurements. The combined BAO and RSD measurements indicate σ_{8} = 0.85 ± 0.03, implying a growth rate that is consistent with predictions from Planck temperature and polarization data and with General Relativity. When combining the results of SDSS BAO and RSD, Planck, Pantheon Type Ia supernovae (SNe Ia), and DES weak lensing and clustering measurements, all multiple-parameter extensions remain consistent with a Λ CDM model. Regardless of cosmological model, the precision on each of the three parameters, Ω_{Λ}, H_{0}, and σ_{8}, remains at roughly 1%, showing changes of less than 0.6% in the central values between models. In a model that allows for free curvature and a time-evolving equation of state for dark energy, the combined samples produce a constraint Ω_{k} = −0.0022 ± 0.0022. The dark energy constraints lead to w_{0} = −0.909 ± 0.081 and w_{a} = −0.49^{+0.35}_{-0.30}, corresponding to an equation of state of w_{p} = 1.018 ± 0.032 at a pivot redshift z_{p} = 0.29 and a Dark Energy Task Force Figure of Merit of 94. The inverse distance ladder measurement under this model yields H_{0} = 68.18 ± 0.79 km s^{-1} Mpc^{-1}, remaining in tension with several direct determination methods; the BAO data allow Hubble constant estimates that are robust against the assumption of the cosmological model. In addition, the BAO data allow estimates of H_{0} that are independent of the CMB data, with similar central values and precision under a Λ CDM model. Our most constraining combination of data gives the upper limit on the sum of neutrino masses at ∑m_{v} < 0.115 eV (95% confidence). Finally, we consider the improvements in cosmology constraints over the last decade by comparing our results to a sample representative of the period 2000–2010. We compute the relative gain across the five dimensions spanned by w, Ω_{k}, ∑m_{v}, H_{0}, H_{0}, and σ_{8} and find that the SDSS BAO and RSD data reduce the total posterior volume by a factor of 40 relative to the previous generation. Adding again the Planck, DES, and Pantheon SN Ia samples leads to an overall contraction in the five-dimensional posterior volume of 3 orders of magnitude

Five insights from the Global Burden of Disease Study 2019

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3.5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers.Peer reviewe

Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC. Funding Bill & Melinda Gates Foundation