Regional Transmission and Reassortment of 2.3.4.4b Highly Pathogenic Avian Influenza (HPAI) Viruses in Bulgarian Poultry 2017/18

Between 2017 and 2018, several farms across Bulgaria reported outbreaks of H5 highly-pathogenic avian influenza (HPAI) viruses. In this study we used genomic and traditional epidemiological analyses to trace the origin and subsequent spread of these outbreaks within Bulgaria. Both methods indicate two separate incursions, one restricted to the northeastern region of Dobrich, and another largely restricted to Central and Eastern Bulgaria including places such as Plovdiv, Sliven and Stara Zagora, as well as one virus from the Western region of Vidin. Both outbreaks likely originate from di�erent European 2.3.4.4b virus ancestors circulating in 2017. The viruses were likely introduced by wild birds or poultry trade links in 2017 and have continued to circulate, but due to lack of contemporaneous sampling and sequences from wild bird viruses in Bulgaria, the precise route and timing of introduction cannot be determined. Analysis of whole genomes indicates a complete lack of reassortment in all segments but the matrix protein gene (MP), which presents as multiple smaller clusters associated with di�erent European 2.3.4.4b viruses. Ancestral reconstruction of host states of the hemagglutinin (HA) gene of viruses involved in the outbreaks suggests that transmission is driven by domestic ducks into galliform poultry. Thus, according to present evidence, we suggest the surveillance of domestic ducks as they are an epidemiologically relevant species for subclinical infection. Monitoring the spread due to movement between farms within regions and links to poultry production systems in European countries can help to predict and prevent future outbreaks. The 2.3.4.4b lineage which caused the largest recorded poultry epidemic in Europe continues to circulate, and the risk of further transmission by wild birds during migration remains

Detection of H3N8 influenza A virus with multiple mammalian-adaptive mutations in a rescued Grey seal (Halichoerus grypus) pup

Avian influenza A viruses (IAVs) in different species of seals display a spectrum of pathogenicity, from sub-clinical infection to mass mortality events. Here we present an investigation of avian IAV infection in a 3- to 4-month-old Grey seal (Halichoerus grypus) pup, rescued from St Michael’s Mount, Cornwall in 2017. The pup underwent medical treatment but died after two weeks; post-mortem examination and histology indicated sepsis as the cause of death. IAV NP antigen was detected by immunohistochemistry in the nasal mucosa, and sensitive real-time reverse transcription polymerase chain reaction assays detected trace amounts of viral RNA within the lower respiratory tract, suggesting that the infection may have been cleared naturally. IAV prevalence among Grey seals may therefore be underestimated. Moreover, contact with humans during the rescue raised concerns about potential zoonotic risk. Nucleotide sequencing revealed the virus to be of subtype H3N8. Combining a GISAID database BLAST search and time-scaled phylogenetic analyses, we inferred that the seal virus originated from an unsampled, locally circulating (in Northern Europe) viruses, likely from wild Anseriformes. From examining the protein alignments, we found several residue changes in the seal virus that did not occur in the bird viruses, including D701N in the PB2 segment, a rare mutation, and a hallmark of mammalian adaptation of bird viruses. IAVs of H3N8 subtype have been noted for their particular ability to cross the species barrier and cause productive infections, including historical records suggesting that they may have caused the 1889 pandemic. Therefore, infections such as the one we report here may be of interest to pandemic surveillance and risk and help us better understand the determinants and drivers of mammalian adaptation in influenza

What matters more for South African households’ debt repayment difficulties?

While the increased access to consumer credit has helped many families improve their welfare, the rising repayment burdens upon a background of chronically law savings rate have generated concerns that South African families are becoming ever more financially fragile and less able to meet their consumer debt repayment obligations. Using data from the Cape Area Panel Study (CAPS), this paper investigates whether consumer debt repayment problems are better explained by excessive spending which leaves households financial overstretched or by negative income shocks. The results indicate that households are significantly more likely to be delinquent on their financial obligations when they suffer negative events beyond their control rather than due to the size of the expenditure burden. This suggests that some consumers will experience repayment problems even when they borrow within their means. Thus regulatory efforts to improve mechanisms for debt relief might be more meaningful than restrictions on lending

Can deliberate efforts to realise aspirations increase capabilities? A South African case study

This paper takes up Appadurai's suggestion that aspirations could be used as a key to unlock development for people who are economically marginalised, and that their capabilities could be increased by this approach. The notion of “aspirations” is theoretically and conceptually framed, and then Amartya Sen's use of the term capabilities as the space within which development should be assessed is explored. I subsequently describe a five-year programme in which economically marginalised women in Khayelitsha near Cape Town were assisted in voicing and attempting to realise their aspirations, while being assisted with access to some resources. Capability outcomes and constraints are described and analysed, and the question of adaptive preferences is addressed. I conclude that deliberate efforts to realise aspirations, accompanied by some facilitation, can increase capabilities, but that there are also structural constraints to capability expansion for these women that frustrate their aspiration of class mobility.International Bibliography of Social Science

Automated interpretation of systolic and diastolic function on the echocardiogram:a multicohort study

Background: Echocardiography is the diagnostic modality for assessing cardiac systolic and diastolic function to diagnose and manage heart failure. However, manual interpretation of echocardiograms can be time consuming and subject to human error. Therefore, we developed a fully automated deep learning workflow to classify, segment, and annotate two-dimensional (2D) videos and Doppler modalities in echocardiograms. Methods: We developed the workflow using a training dataset of 1145 echocardiograms and an internal test set of 406 echocardiograms from the prospective heart failure research platform (Asian Network for Translational Research and Cardiovascular Trials; ATTRaCT) in Asia, with previous manual tracings by expert sonographers. We validated the workflow against manual measurements in a curated dataset from Canada (Alberta Heart Failure Etiology and Analysis Research Team; HEART; n=1029 echocardiograms), a real-world dataset from Taiwan (n=31 241), the US-based EchoNet-Dynamic dataset (n=10 030), and in an independent prospective assessment of the Asian (ATTRaCT) and Canadian (Alberta HEART) datasets (n=142) with repeated independent measurements by two expert sonographers. Findings: In the ATTRaCT test set, the automated workflow classified 2D videos and Doppler modalities with accuracies (number of correct predictions divided by the total number of predictions) ranging from 0·91 to 0·99. Segmentations of the left ventricle and left atrium were accurate, with a mean Dice similarity coefficient greater than 93% for all. In the external datasets (n=1029 to 10 030 echocardiograms used as input), automated measurements showed good agreement with locally measured values, with a mean absolute error range of 9–25 mL for left ventricular volumes, 6–10% for left ventricular ejection fraction (LVEF), and 1·8–2·2 for the ratio of the mitral inflow E wave to the tissue Doppler e' wave (E/e' ratio); and reliably classified systolic dysfunction (LVEF <40%, area under the receiver operating characteristic curve [AUC] range 0·90–0·92) and diastolic dysfunction (E/e' ratio ≥13, AUC range 0·91–0·91), with narrow 95% CIs for AUC values. Independent prospective evaluation confirmed less variance of automated compared with human expert measurements, with all individual equivalence coefficients being less than 0 for all measurements. Interpretation: Deep learning algorithms can automatically annotate 2D videos and Doppler modalities with similar accuracy to manual measurements by expert sonographers. Use of an automated workflow might accelerate access, improve quality, and reduce costs in diagnosing and managing heart failure globally. Funding: A*STAR Biomedical Research Council and A*STAR Exploit Technologies

‘We create our own small world’: daily realities of mothers of disabled children in a South African urban settlement

Parents of disabled children face many challenges. Understanding their experiences and acknowledging contextual influences is vital in developing intervention strategies that fit their daily realities. However, studies of parents from a resource-poor context are particularly scarce. This ethnographic study with 30 mothers from a South African township (15 semi-structured interviews and 24 participatory group sessions) unearths how mothers care on their own, in an isolated manner. The complexity of low living standards, being poorly supported by care structures and networks, believing in being the best carer, distrusting others due to a violent context, and resigning towards life shape and are shaped by this solitary care responsibility. For disability inclusive development to be successful, programmes should support mothers by sharing the care responsibility taking into account the isolated nature of mothers’ lives and the impact of poverty. This can provide room for these mothers to increase the well-being of themselves and their children

The Role of Mobile Phones in Tanzania’s Informal Construction Sector:The Case of Dar es Salaam

The Pierre Auger Observatory is currently the largest detector for measurements of cosmic rays with energies beyond 10^18 eV. It uses a hybrid detection method with fluorescence telescopes and surface detector stations. Cosmic rays with energies above 10^15 eV cannot be studied directly but they interact with the atmosphere and produce secondary particle cascades, called extensive air shower. These air showers carry information about the energy, the arrival direction and the chemical composition of the primary cosmic ray particle. The fluorescence telescopes measure the longitudinal air shower profile, whereas the surface detector stations study the lateral profile on the ground. The combination of both detectors provides measurements of cosmic rays with high accuracy.This thesis is focused on the study of the chemical composition of cosmic rays with the virtual fluorescence telescope HECO, which is the combination of the low energy enhancement HEAT (High Elevation Auger Telescopes) and the Coihueco telescope station. HEAT consists of 3 additional fluorescence telescopes, extending the energy range down to below 10^17.0 eV. The cosmic rays with energies between 10^17 eV to 10^18.4 eV are studied, which is the expected transition region from galactic to extra galactic cosmic rays.For the analysis of the chemical composition the atmospheric depth of the air shower maximum Xmax is used. The distribution of Xmax is depending on the atomic mass of the primary cosmic ray particle.An improved profile reconstruction using air shower universality is introduced in the reconstruction and several cross checks on the acquired data and simulations are performed. A complete Monte Carlo based composition analysis is performed to validate the analysis method. The systematic uncertainties of the analysis are studied in detail. The resulting first moments, the mean and the variance of the measured Xmax-distribution per energy bin are compared to theoretical predictions from current cosmic ray interaction models. Additionally, a new fit method is introduced to fit chemical composition fractions based on prediction from interaction models. A parametrization based on Gumbel statistics and air shower simulation is used to describe the Xmax-distribution as a function of energy and primary atomic mass. A superposition model of these parametrization is fitted on a simulated scenario to find the optimal fit routine. The method is applied on the measured Xmax data including all know systematic uncertainties. The findings of this thesis are compared to published results of other experiments. The results of all interaction models suggest a heavy composition at 10^17.0 eV that becomes lighter up to 10^18.4 eV, where it is composed of a mixture of nuclei with light atomic masses