Efficient Bayesian inference of fully stochastic epidemiological models with applications to COVID-19.

Epidemiological forecasts are beset by uncertainties about the underlying epidemiological processes, and the surveillance process through which data are acquired. We present a Bayesian inference methodology that quantifies these uncertainties, for epidemics that are modelled by (possibly) non-stationary, continuous-time, Markov population processes. The efficiency of the method derives from a functional central limit theorem approximation of the likelihood, valid for large populations. We demonstrate the methodology by analysing the early stages of the COVID-19 pandemic in the UK, based on age-structured data for the number of deaths. This includes maximum a posteriori estimates, Markov chain Monte Carlo sampling of the posterior, computation of the model evidence, and the determination of parameter sensitivities via the Fisher information matrix. Our methodology is implemented in PyRoss, an open-source platform for analysis of epidemiological compartment models

TESS Reveals HD 118203 b to be a Transiting Planet

The exoplanet HD 118203 b, orbiting a bright (V = 8.05) host star, was discovered using the radial velocity method by da Silva et al., but was not previously known to transit. Transiting Exoplanet Survey Satellite (TESS) photometry has revealed that this planet transits its host star. Nine planetary transits were observed by TESS, allowing us to measure the radius of the planet to be 1.136^(+0.029)_(-0.028) R_J, and to calculate the planet mass to be 2.166^(+0.074)_(-0.079) M_J. The host star is slightly evolved with an effective temperature of T_(eff) = 5683^(+84)_(-85) K and a surface gravity of log g = 3.889^(+0.017)_(-0.018). With an orbital period of 6.134985^(+0.000029_(-0.000030) days and an eccentricity of 0.314 ± 0.017, the planet occupies a transitional regime between circularized hot Jupiters and more dynamically active planets at longer orbital periods. The host star is among the 10 brightest known to have transiting giant planets, providing opportunities for both planetary atmospheric and asteroseismic studies

Nomenclature- and Database-Compatible Names for the Two Ebola Virus Variants that Emerged in Guinea and the Democratic Republic of the Congo in 2014

In 2014, Ebola virus (EBOV) was identified as the etiological agent of a large and still expanding outbreak of Ebola virus disease (EVD) in West Africa and a much more confined EVD outbreak in Middle Africa. Epidemiological and evolutionary analyses confirmed that all cases of both outbreaks are connected to a single introduction each of EBOV into human populations and that both outbreaks are not directly connected. Coding-complete genomic sequence analyses of isolates revealed that the two outbreaks were caused by two novel EBOV variants, and initial clinical observations suggest that neither of them should be considered strains. Here we present consensus decisions on naming for both variants (West Africa: “Makona”, Middle Africa: “Lomela”) and provide database-compatible full, shortened, and abbreviated names that are in line with recently established filovirus sub-species nomenclatures

Two Warm Super-Earths Transiting the Nearby M Dwarf TOI-2095

We report the detection and validation of two planets orbiting TOI-2095 (TIC 235678745). The host star is a 3700K M1V dwarf with a high proper motion. The star lies at a distance of 42 pc in a sparsely populated portion of the sky and is bright in the infrared (K=9). With data from 24 Sectors of observation during TESS's Cycles 2 and 4, TOI-2095 exhibits two sets of transits associated with super-Earth-sized planets. The planets have orbital periods of 17.7 days and 28.2 days and radii of 1.30 and 1.39 Earth radii, respectively. Archival data, preliminary follow-up observations, and vetting analyses support the planetary interpretation of the detected transit signals. The pair of planets have estimated equilibrium temperatures of approximately 400 K, with stellar insolations of 3.23 and 1.73 times that of Earth, placing them in the Venus zone. The planets also lie in a radius regime signaling the transition between rock-dominated and volatile-rich compositions. They are thus prime targets for follow-up mass measurements to better understand the properties of warm, transition radius planets. The relatively long orbital periods of these two planets provide crucial data that can help shed light on the processes that shape the composition of small planets orbiting M dwarfs.Comment: Submitted to AAS Journal

Resurgence of Ebola virus in 2021 in Guinea suggests a new paradigm for outbreaks

These authors contributed equally: Alpha K. Keita, Fara R. Koundouno, Martin Faye, Ariane Düx, Julia Hinzmann.International audienc

An Eccentric Massive Jupiter Orbiting a Subgiant on a 9.5-day Period Discovered in the <i>Transiting Exoplanet Survey Satellite</i> Full Frame Images

We report the discovery of TOI-172 b from the Transiting Exoplanet Survey Satellite (TESS) mission, a massive hot Jupiter transiting a slightly evolved G star with a 9.48-day orbital period. This is the first planet to be confirmed from analysis of only the TESS full frame images, because the host star was not chosen as a two-minute cadence target. From a global analysis of the TESS photometry and follow-up observations carried out by the TESS Follow-up Observing Program Working Group, TOI-172 (TIC 29857954) is a slightly evolved star with an effective temperature of T eff = 5645 ± 50 K, a mass of M ⋆ = {1.128}-0.061+0.065 M ⊙, radius of R ⋆ = {1.777}-0.044+0.047 R ⊙, a surface gravity of log g ⋆ = {3.993}-0.028+0.027, and an age of {7.4}-1.5+1.6 {Gyr}. Its planetary companion (TOI-172 b) has a radius of R P = {0.965}-0.029+0.032 R J, a mass of M P = {5.42}-0.20+0.22 M J, and is on an eccentric orbit (e={0.3806}-0.0090+0.0093). TOI-172 b is one of the few known massive giant planets on a highly eccentric short-period orbit. Future study of the atmosphere of this planet and its system architecture offer opportunities to understand the formation and evolution of similar systems

Large-Scale Gene-Centric Meta-Analysis across 39 Studies Identifies Type 2 Diabetes Loci

To identify genetic factors contributing to type 2 diabetes (T2D), we performed large-scale meta-analyses by using a custom similar to 50,000 SNP genotyping array (the ITMAT-Broad-CARe array) with similar to 2000 candidate genes in 39 multiethnic population-based studies, case-control studies, and clinical trials totaling 17,418 cases and 70,298 controls. First, meta-analysis of 25 studies comprising 14,073 cases and 57,489 controls of European descent confirmed eight established T2D loci at genome-wide significance. In silico follow-up analysis of putative association signals found in independent genome-wide association studies (including 8,130 cases and 38,987 controls) performed by the DIAGRAM consortium identified a T2D locus at genome-wide significance (GATAD2A/CILP2/PBX4; p = 5.7 x 10(-9)) and two loci exceeding study-wide significance (SREBF1, and TH/INS; p <2.4 x 10(-6)). Second, meta-analyses of 1,986 cases and 7,695 controls from eight African-American studies identified study-wide-significant (p = 2.4 x 10(-7)) variants in HMGA2 and replicated variants in TCF7L2 (p = 5.1 x 10(-15)). Third, conditional analysis revealed multiple known and novel independent signals within five T2D-associated genes in samples of European ancestry and within HMGA2 in African-American samples. Fourth, a multiethnic meta-analysis of all 39 studies identified T2D-associated variants in BCL2 (p = 2.1 x 10(-8)). Finally, a composite genetic score of SNPs from new and established T2D signals was significantly associated with increased risk of diabetes in African-American, Hispanic, and Asian populations. In summary, large-scale meta-analysis involving a dense gene-centric approach has uncovered additional loci and variants that contribute to T2D risk and suggests substantial overlap of T2D association signals across multiple ethnic groups

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives