HST Imaging of Globular Clusters in the Edge--on Spiral Galaxies NGC 4565 and NGC 5907

We present a study of the globular cluster systems of two edge-on spiral galaxies, NGC4565 and NGC5907, from WFPC2 images in the F450W and F814W filters. The globular cluster systems of both galaxies appear to be similar to the Galactic globular cluster system. In particular, we derive total numbers of globular clusters of N_{GC}(4565)= 204+/-38 {+87}{-53} and N_{GC}(5907)=170+/-41 {+47}{-72} (where the first are statistical, the second potential systematic errors) for NGC4565 and NGC5907, respectively. This determination is based on a comparison to the Milky Way system, for which we adopt a total number of globular clusters of 180+/-20. The specific frequency of both galaxies is S_N~0.6: indistinguishable from the value for the Milky Way. The similarity in the globular cluster systems of the two galaxies is noteworthy since they have significantly different thick disks and bulge-to-disk ratios. This would suggest that these two components do not play a major role in the building up of a globular cluster system around late-type galaxies.Comment: Accepted for publication in the Astronomical Journal, 17 pages incl 5 figures, AAS style two columns. Also available at http://www.eso.org/~mkissler, Color version of figure 1 only available at http://www.eso.org/~mkissler (B/W version included

Geographic transmission hubs of the 2009 influenza pandemic in the United States

A key issue in infectious disease epidemiology is to identify and predict geographic sites of epidemic establishment that contribute to onward spread, especially in the context of invasion waves of emerging pathogens. Conventional wisdom suggests that these sites are likely to be in densely-populated, well-connected areas. For pandemic influenza, however, epidemiological data have not been available at a fine enough geographic resolution to test this assumption. Here, we make use of fine-scale influenza-like illness incidence data derived from electronic medical claims records gathered from 834 3-digit ZIP (postal) codes across the US to identify the key geographic establishment sites, or “hubs”, of the autumn wave of the 2009 A/H1N1pdm influenza pandemic in the United States. A mechanistic spatial transmission model is fit to epidemic onset times inferred from the data. Hubs are identified by tracing the most probable transmission routes back to a likely first establishment site. Four hubs are identified: two in the southeastern US, one in the central valley of California, and one in the midwestern US. According to the model, 75% of the 834 observed ZIP-level outbreaks in the US were seeded by these four hubs or their epidemiological descendants. Counter-intuitively, the pandemic hubs do not coincide with large and well-connected cities, indicating that factors beyond population density and travel volume are necessary to explain the establishment sites of the major autumn wave of the pandemic. Geographic regions are identified where infection can be statistically traced back to a hub, providing a testable prediction of the outbreak's phylogeography. Our method therefore provides an important way forward to reconcile spatial diffusion patterns inferred from epidemiological surveillance data and pathogen sequence data. Keywords: Pandemic influenza, Transmission hubs, Metapopulation, Gravity model, Phylogeograph

Targeted surveillance strategies for efficient detection of novel antibiotic resistance variants.

Genotype-based diagnostics for antibiotic resistance represent a promising alternative to empiric therapy, reducing inappropriate antibiotic use. However, because such assays infer resistance based on known genetic markers, their utility will wane with the emergence of novel resistance. Maintenance of these diagnostics will therefore require surveillance to ensure early detection of novel resistance variants, but efficient strategies to do so remain undefined. We evaluate the efficiency of targeted sampling approaches informed by patient and pathogen characteristics in detecting antibiotic resistance and diagnostic escape variants in Neisseria gonorrhoeae, a pathogen associated with a high burden of disease and antibiotic resistance and the development of genotype-based diagnostics. We show that patient characteristic-informed sampling is not a reliable strategy for efficient variant detection. In contrast, sampling informed by pathogen characteristics, such as genomic diversity and genomic background, is significantly more efficient than random sampling in identifying genetic variants associated with resistance and diagnostic escape

Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of SARS-CoV-2 in different settings: a mathematical modelling study.

BACKGROUND: The isolation of symptomatic cases and tracing of contacts has been used as an early COVID-19 containment measure in many countries, with additional physical distancing measures also introduced as outbreaks have grown. To maintain control of infection while also reducing disruption to populations, there is a need to understand what combination of measures-including novel digital tracing approaches and less intensive physical distancing-might be required to reduce transmission. We aimed to estimate the reduction in transmission under different control measures across settings and how many contacts would be quarantined per day in different strategies for a given level of symptomatic case incidence. METHODS: For this mathematical modelling study, we used a model of individual-level transmission stratified by setting (household, work, school, or other) based on BBC Pandemic data from 40 162 UK participants. We simulated the effect of a range of different testing, isolation, tracing, and physical distancing scenarios. Under optimistic but plausible assumptions, we estimated reduction in the effective reproduction number and the number of contacts that would be newly quarantined each day under different strategies. RESULTS: We estimated that combined isolation and tracing strategies would reduce transmission more than mass testing or self-isolation alone: mean transmission reduction of 2% for mass random testing of 5% of the population each week, 29% for self-isolation alone of symptomatic cases within the household, 35% for self-isolation alone outside the household, 37% for self-isolation plus household quarantine, 64% for self-isolation and household quarantine with the addition of manual contact tracing of all contacts, 57% with the addition of manual tracing of acquaintances only, and 47% with the addition of app-based tracing only. If limits were placed on gatherings outside of home, school, or work, then manual contact tracing of acquaintances alone could have an effect on transmission reduction similar to that of detailed contact tracing. In a scenario where 1000 new symptomatic cases that met the definition to trigger contact tracing occurred per day, we estimated that, in most contact tracing strategies, 15 000-41 000 contacts would be newly quarantined each day. INTERPRETATION: Consistent with previous modelling studies and country-specific COVID-19 responses to date, our analysis estimated that a high proportion of cases would need to self-isolate and a high proportion of their contacts to be successfully traced to ensure an effective reproduction number lower than 1 in the absence of other measures. If combined with moderate physical distancing measures, self-isolation and contact tracing would be more likely to achieve control of severe acute respiratory syndrome coronavirus 2 transmission. FUNDING: Wellcome Trust, UK Engineering and Physical Sciences Research Council, European Commission, Royal Society, Medical Research Council

Viral Kinetics of Sequential SARS-CoV-2 Infections

The impact of a prior SARS-CoV-2 infection on the progression of subsequent infections has been unclear. Using a convenience sample of 94,812 longitudinal RT-qPCR measurements from anterior nares and oropharyngeal swabs, we identified 71 individuals with two well-sampled SARS-CoV-2 infections between March 11th, 2020, and July 28th, 2022. We compared the SARS-CoV-2 viral kinetics of first vs. second infections in this group, adjusting for viral variant, vaccination status, and age. Relative to first infections, second infections usually featured a faster clearance time. Furthermore, a person\u27s relative (rank-order) viral clearance time, compared to others infected with the same variant, was roughly conserved across first and second infections, so that individuals who had a relatively fast clearance time in their first infection also tended to have a relatively fast clearance time in their second infection (Spearman correlation coefficient: 0.30, 95% credible interval (0.12, 0.46)). These findings provide evidence that, like vaccination, immunity from a prior SARS-CoV-2 infection shortens the duration of subsequent acute SARS-CoV-2 infections principally by reducing viral clearance time. Additionally, there appears to be an inherent element of the immune response, or some other host factor, that shapes a person\u27s relative ability to clear SARS-CoV-2 infection that persists across sequential infections

Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of SARS-CoV-2 in different settings: a mathematical modelling study.

BACKGROUND: The isolation of symptomatic cases and tracing of contacts has been used as an early COVID-19 containment measure in many countries, with additional physical distancing measures also introduced as outbreaks have grown. To maintain control of infection while also reducing disruption to populations, there is a need to understand what combination of measures-including novel digital tracing approaches and less intensive physical distancing-might be required to reduce transmission. We aimed to estimate the reduction in transmission under different control measures across settings and how many contacts would be quarantined per day in different strategies for a given level of symptomatic case incidence. METHODS: For this mathematical modelling study, we used a model of individual-level transmission stratified by setting (household, work, school, or other) based on BBC Pandemic data from 40 162 UK participants. We simulated the effect of a range of different testing, isolation, tracing, and physical distancing scenarios. Under optimistic but plausible assumptions, we estimated reduction in the effective reproduction number and the number of contacts that would be newly quarantined each day under different strategies. RESULTS: We estimated that combined isolation and tracing strategies would reduce transmission more than mass testing or self-isolation alone: mean transmission reduction of 2% for mass random testing of 5% of the population each week, 29% for self-isolation alone of symptomatic cases within the household, 35% for self-isolation alone outside the household, 37% for self-isolation plus household quarantine, 64% for self-isolation and household quarantine with the addition of manual contact tracing of all contacts, 57% with the addition of manual tracing of acquaintances only, and 47% with the addition of app-based tracing only. If limits were placed on gatherings outside of home, school, or work, then manual contact tracing of acquaintances alone could have an effect on transmission reduction similar to that of detailed contact tracing. In a scenario where 1000 new symptomatic cases that met the definition to trigger contact tracing occurred per day, we estimated that, in most contact tracing strategies, 15 000-41 000 contacts would be newly quarantined each day. INTERPRETATION: Consistent with previous modelling studies and country-specific COVID-19 responses to date, our analysis estimated that a high proportion of cases would need to self-isolate and a high proportion of their contacts to be successfully traced to ensure an effective reproduction number lower than 1 in the absence of other measures. If combined with moderate physical distancing measures, self-isolation and contact tracing would be more likely to achieve control of severe acute respiratory syndrome coronavirus 2 transmission. FUNDING: Wellcome Trust, UK Engineering and Physical Sciences Research Council, European Commission, Royal Society, Medical Research Council

XMM-Newton observations of ultraluminous X-ray sources in nearby galaxies

An XMM-Newton study of ultraluminous X-ray sources (ULX) has been performed in a sample of 10 nearby Seyfert galaxies. Eighteen ULX have been found with positional uncertainty of about 4". The large collecting area of XMM-Newton makes the statistics sufficient to perform spectral fitting with simple models in 8 cases. The main results of the present minisurvey strengthen the theory that the ULX could be accreting black holes in hard or soft state. In some cases, the contribution of the ULX to the overall X-ray flux appears to be dominant with respect to that of the active nucleus. In addition, 6 ULX present probable counterparts at other wavelengths (optical/infrared, radio). A multiwavelength observing strategy is required to better assess the nature of these sources.Comment: 10 pages, 11 figures. Accepted for publication by Astronomy and Astrophysics. If you want figures at full resolution, please send an email to Foschin

Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys

Establishing how many people have been infected by SARS-CoV-2 remains an urgent priority for controlling the COVID-19 pandemic. Serological tests that identify past infection can be used to estimate cumulative incidence, but the relative accuracy and robustness of various sampling strategies have been unclear. We developed a flexible framework that integrates uncertainty from test characteristics, sample size, and heterogeneity in seroprevalence across subpopulations to compare estimates from sampling schemes. Using the same framework and making the assumption that seropositivity indicates immune protection, we propagated estimates and uncertainty through dynamical models to assess uncertainty in the epidemiological parameters needed to evaluate public health interventions and found that sampling schemes informed by demographics and contact networks outperform uniform sampling. The framework can be adapted to optimize serosurvey design given test characteristics and capacity, population demography, sampling strategy, and modeling approach, and can be tailored to support decision-making around introducing or removing interventions. </div

Reductions in commuting mobility correlate with geographic differences in SARS-CoV-2 prevalence in New York City.

SARS-CoV-2-related mortality and hospitalizations differ substantially between New York City neighborhoods. Mitigation efforts require knowing the extent to which these disparities reflect differences in prevalence and understanding the associated drivers. Here, we report the prevalence of SARS-CoV-2 in New York City boroughs inferred using tests administered to 1,746 pregnant women hospitalized for delivery between March 22nd and May 3rd, 2020. We also assess the relationship between prevalence and commuting-style movements into and out of each borough. Prevalence ranged from 11.3% (95% credible interval [8.9%, 13.9%]) in Manhattan to 26.0% (15.3%, 38.9%) in South Queens, with an estimated city-wide prevalence of 15.6% (13.9%, 17.4%). Prevalence was lowest in boroughs with the greatest reductions in morning movements out of and evening movements into the borough (Pearson R = -0.88 [-0.52, -0.99]). Widespread testing is needed to further specify disparities in prevalence and assess the risk of future outbreaks

Viral dynamics of acute SARS-CoV-2 infection and applications to diagnostic and public health strategies.

SARS-CoV-2 infections are characterized by viral proliferation and clearance phases and can be followed by low-level persistent viral RNA shedding. The dynamics of viral RNA concentration, particularly in the early stages of infection, can inform clinical measures and interventions such as test-based screening. We used prospective longitudinal quantitative reverse transcription PCR testing to measure the viral RNA trajectories for 68 individuals during the resumption of the 2019-2020 National Basketball Association season. For 46 individuals with acute infections, we inferred the peak viral concentration and the duration of the viral proliferation and clearance phases. According to our mathematical model, we found that viral RNA concentrations peaked an average of 3.3 days (95% credible interval [CI] 2.5, 4.2) after first possible detectability at a cycle threshold value of 22.3 (95% CI 20.5, 23.9). The viral clearance phase lasted longer for symptomatic individuals (10.9 days [95% CI 7.9, 14.4]) than for asymptomatic individuals (7.8 days [95% CI 6.1, 9.7]). A second test within 2 days after an initial positive PCR test substantially improves certainty about a patient's infection stage. The effective sensitivity of a test intended to identify infectious individuals declines substantially with test turnaround time. These findings indicate that SARS-CoV-2 viral concentrations peak rapidly regardless of symptoms. Sequential tests can help reveal a patient's progress through infection stages. Frequent, rapid-turnaround testing is needed to effectively screen individuals before they become infectious