A statistical modelling approach for source attribution meta-analysis of sporadic infection with foodborne pathogens

Numerous source attribution studies for foodborne pathogens based on epidemiological and microbiological methods are available. These studies provide empirical data for modelling frameworks that synthetize the quantitative evidence at our disposal and reduce reliance on expert elicitations. Here, we develop a statistical model within a Bayesian estimation framework to integrate attribution estimates from expert elicitations with estimates from microbial subtyping and case-control studies for sporadic infections with four major bacterial zoonotic pathogens in the Netherlands (Campylobacter, Salmonella, Shiga toxin-producing E. coli [STEC] O157 and Listeria). For each pathogen, we pooled the published fractions of human cases attributable to each animal reservoir from the microbial subtyping studies, accounting for the uncertainty arising from the different typing methods, attribution models, and year(s) of data collection. We then combined the population attributable fractions (PAFs) from the case-control studies according to five transmission pathways (domestic food, environment, direct animal contact, human-human transmission and travel) and 11 groups within the foodborne pathway (beef/lamb, pork, poultry meat, eggs, dairy, fish/shellfish, fruit/vegetables, beverages, grains, composite foods and food handlers/vermin). The attribution estimates were biologically plausible, allowing the human cases to be attributed in several ways according to reservoirs, transmission pathways and food groups. All pathogens were predominantly foodborne, with Campylobacter being mostly attributable to the chicken reservoir, Salmonella to pigs (albeit closely followed by layers), and Listeria and STEC O157 to cattle. Food-wise, the attributions reflected those at the reservoir level in terms of ranking. We provided a modelling solution to reach consensus attribution estimates reflecting the empirical evidence in the literature that is particularly useful for policy-making and is extensible to other pathogens and domains

Stellar population synthesis of post-AGB stars: the s-process in MACHO47.2496.8

The low-metallicity RV Tauri star MACHO47.2496.8, recently discovered in the Large Magellanic Cloud, is highly enriched in carbon and heavy elements produced by the slow neutron capture process (s-process), and is most probably a genuine post-C(N-type) asymptotic giant branch (AGB) star. We use the analysis of the abundances of MACHO47.2496.8 to constrain free parameters in AGB models. We test which values of the free parameters describing uncertain physical mechanisms in AGB stars, namely the third dredge-up and the features of the 13C neutron source, produce models that better match the abundances observed in MACHO47.2496.8. We carry out stellar population synthesis coupled with s-process nucleosynthesis using a synthetic stellar evolution code. The s-process ratios observed in MACHO47.2496.8 can be matched by the same models that explain the s-process ratios of Galactic AGB and post-AGB stars of metallicity > Z_sun/10, except for the choice of the effectiveness of 13C as a neutron source, which has to be lower by roughly a factor of 3 to 6. The less effective neutron source for lower metallicities is also required when comparing population synthesis results to observations of Galactic halo $s$-enhanced stars, such as Pb stars. The 12C/13C ratio in MACHO47.2496.8 cannot be matched simultaneously and requires the occurrence of extra-mixing processes. The confirmed trend of the decreased efficiency of the 13C neutron source with metallicity requires an explanation from AGB s-process models. The present work is to date the first comparison between theoretical models and the detailed abundances of an extragalactic post-AGB star.Comment: accepted for publication on Astronomy & Astrophysics Letter

Orbital eccentricities of binary systems with a former AGB star

Many binary stellar systems in which the primary star is beyond the asymptotic giant branch (AGB) evolutionary phase show significant orbital eccentricities whereas current binary interaction models predict their orbits to be circularised. We analyse how the orbital parameters in a system are modified under mass loss and mass exchange among its binary components and propose a model for enhanced mass-loss from the AGB star due to tidal interaction with its companion, which allows a smooth transition between the wind and Roche-lobe overflow mass-loss regimes. We explicitly follow its effect along the orbit on the change of eccentricity and orbital semi-major axis, as well as the effect of accretion by the companion. We calculate timescales for the variation of these orbital parameters and compare them to the tidal circularisation timescale. We find that in many cases, due to the enhanced mass loss of the AGB component at orbital phases closer to the periastron, the net eccentricity growth rate in one orbit is comparable to the rate of tidal circularisation. We show that with this eccentricity enhancing mechanism it is possible to reproduce the orbital period and eccentricity of the Sirius system, which under the standard assumptions of binary interaction is expected to be circularised. We also show that this mechanism may provide an explanation for the eccentricities of most barium star systems, which are expected to be circularised due to tidal dissipation. By proposing a tidally enhanced model of mass loss from AGB stars we find a mechanism which efficiently works against the tidal circularisation of the orbit, which explains the significant eccentricities observed in binary systems containing a white dwarf and a less evolved companion, such as Sirius and systems with barium stars.Comment: 9 pages, 5 figures, accepted for publication in Astronomy and Astrophysics on 24th of October of 200

A statistical modelling approach for source attribution meta-analysis of sporadic infection with foodborne pathogens

Numerous source attribution studies for foodborne pathogens based on epidemiological and microbiological methods are available. These studies provide empirical data for modelling frameworks that synthetize the quantitative evidence at our disposal and reduce reliance on expert elicitations. Here, we develop a statistical model within a Bayesian estimation framework to integrate attribution estimates from expert elicitations with estimates from microbial subtyping and case-control studies for sporadic infections with four major bacterial zoonotic pathogens in the Netherlands (Campylobacter, Salmonella, Shiga toxin-producing E. coli [STEC] O157 and Listeria). For each pathogen, we pooled the published fractions of human cases attributable to each animal reservoir from the microbial subtyping studies, accounting for the uncertainty arising from the different typing methods, attribution models, and year(s) of data collection. We then combined the population attributable fractions (PAFs) from the case-control studies according to five transmission pathways (domestic food, environment, direct animal contact, human-human transmission and travel) and 11 groups within the foodborne pathway (beef/lamb, pork, poultry meat, eggs, dairy, fish/shellfish, fruit/vegetables, beverages, grains, composite foods and food handlers/vermin). The attribution estimates were biologically plausible, allowing the human cases to be attributed in several ways according to reservoirs, transmission pathways and food groups. All pathogens were predominantly foodborne, with Campylobacter being mostly attributable to the chicken reservoir, Salmonella to pigs (albeit closely followed by layers), and Listeria and STEC O157 to cattle. Food-wise, the attributions reflected those at the reservoir level in terms of ranking. We provided a modelling solution to reach consensus attribution estimates reflecting the empirical evidence in the literature that is particularly useful for policy-making and is extensible to other pathogens and domains

Detection of opsonizing antibodies directed against a recently circulating Bordetella pertussis strain in paired plasma samples from symptomatic and recovered pertussis patients.

Correlates of protection (CoPs) against the highly contagious respiratory disease whooping cough, caused by Bordetella pertussis, remain elusive. Characterizing the antibody response to this pathogen is essential towards identifying potential CoPs. Here, we evaluate levels, avidity and functionality of B. pertussis-specific-antibodies from paired plasma samples derived from symptomatic and recovered pertussis patients, as well as controls. Natural infection is expected to induce protective immunity. IgG levels and avidity to nine B. pertussis antigens were determined using a novel multiplex panel. Furthermore, opsonophagocytosis of a B. pertussis clinical isolate by neutrophils was measured. Findings indicate that following infection, B. pertussis-specific antibody levels of (ex-) pertussis patients waned, while the avidity of antibodies directed against the majority of studied antigens increased. Opsonophagocytosis indices decreased upon recovery, but remained higher than controls. Random forest analysis of all the data revealed that 28% of the opsonophagocytosis index variances could be explained by filamentous hemagglutinin- followed by pertussis toxin-specific antibodies. We propose to further explore which other B. pertussis-specific antibodies can better predict opsonophagocytosis. Moreover, other B. pertussis-specific antibody functions as well as the possible integration of these functions in combination with other immune cell properties should be evaluated towards the identification of CoPs against pertussis

Test, trace, isolate:Evidence for declining SARS-CoV-2 PCR sensitivity in a clinical cohort

Real-time reverse transcription-polymerase chain reaction (RT-PCR) on upper respiratory tract (URT) samples is the primary method to diagnose SARS-CoV-2 infections and guide public health measures, with a supportive role for serology. We reinforce previous findings on limited sensitivity of PCR testing, and solidify this fact by statistically utilizing a firm basis of multiple tests per individual. We integrate stratifications with respect to several patient characteristics such as severity of disease and time since onset of symptoms. Bayesian statistical modelling was used to retrospectively determine the sensitivity of RT-PCR using SARS-CoV-2 serology in 644 COVID-19-suspected patients with varying degrees of disease severity and duration. The sensitivity of RT-PCR ranged between 80% − 95%; increasing with disease severity, it decreased rapidly over time in mild COVID-19 cases. Negative URT RT-PCR results should be interpreted in the context of clinical characteristics, especially with regard to containment of viral transmission based on ‘test, trace and isolate’

The Blue Stragglers of the Old Open Cluster NGC 188

The old (7 Gyr) open cluster NGC 188 has yielded a wealth of astrophysical insight into its rich blue straggler population. Specifically, the NGC 188 blue stragglers are characterized by: A binary frequency of 80% for orbital periods less than $10^4$ days;Typical orbital periods around 1000 days;Typical secondary star masses of 0.5 M$_{\odot}$; At least some white dwarf companion stars; Modestly rapid rotation; A bimodal radial spatial distribution; Dynamical masses greater than standard stellar evolution masses (based on short-period binaries); Under-luminosity for dynamical masses (short-period binaries). Extensive $N$-body modeling of NGC 188 with empirical initial conditions reproduces the properties of the cluster, and in particular the main-sequence solar-type binary population. The current models also reproduce well the binary orbital properties of the blue stragglers, but fall well short of producing the observed number of blue stragglers. This deficit could be resolved by reducing the frequency of common-envelope evolution during Roche lobe overflow. Both the observations and the $N$-body models strongly indicate that the long-period blue-straggler binaries - which dominate the NGC 188 blue straggler population - are formed by asymptotic-giant (primarily) and red-giant mass transfer onto main sequence stars. The models suggest that the few non-velocity-variable blue stragglers formed from mergers or collisions. Several remarkable short-period double-lined binaries point to the importance of subsequent dynamical exchange encounters, and provide at least one example of a likely collisional origin for a blue straggler.Comment: Chapter 3, in Ecology of Blue Straggler Stars, H.M.J. Boffin, G. Carraro & G. Beccari (Eds), Astrophysics and Space Science Library, Springe

Mass Transfer by Stellar Wind

I review the process of mass transfer in a binary system through a stellar wind, with an emphasis on systems containing a red giant. I show how wind accretion in a binary system is different from the usually assumed Bondi-Hoyle approximation, first as far as the flow's structure is concerned, but most importantly, also for the mass accretion and specific angular momentum loss. This has important implications on the evolution of the orbital parameters. I also discuss the impact of wind accretion, on the chemical pollution and change in spin of the accreting star. The last section deals with observations and covers systems that most likely went through wind mass transfer: barium and related stars, symbiotic stars and central stars of planetary nebulae (CSPN). The most recent observations of cool CSPN progenitors of barium stars, as well as of carbon-rich post-common envelope systems, are providing unique constraints on the mass transfer processes.Comment: Chapter 7, in Ecology of Blue Straggler Stars, H.M.J. Boffin, G. Carraro & G. Beccari (Eds), Astrophysics and Space Science Library, Springe