‘I arranged my own marriage': arranged marriages and post-colonial feminism

This article looks at the practice of arranged marriage among women of Indian, Pakistani and Bangladeshi origin resident in Britain. It examines the conflation of arranged marriages with forced marriages and the assumption that arranged marriages are examples of cultural practices that thwart individual agency. Drawing upon original empirical data, this article will argue that in the practice of arranged marriage, some South Asian women are able to exercise agency while choosing their marriage partner. They adapt traditional arranged marriage practices to navigate their way around strict cultural expectations and to negotiate with their family members the choice of a match that is favourable for them. It provides a corrective account of arranged marriages by challenging the stereotype of the ‘oppressed third world women' and their experiences of such marriages. The article will do this by employing the idea of post-colonial feminism and by highlighting two long-standing issues in feminist debates: the idea of agency and the conception and role of power in the struggle for women's rights. It will make a case for a post-colonial approach to feminism as one way of reconciling feminism with the politics of multiculturalism

New technologies to improve healthcare in low- and middle-income countries: Global Grand Challenges satellite event, Oxford University Clinical Research Unit, Ho Chi Minh City, 17th-18th September 2019

We report the outputs of a satellite event in Ho Chi Minh City, Vietnam, organized as part of the "2 nd Global Grand Challenges of Engineering Summit". The event considered challenges and potential solutions for improving low- and middle-income country (LMIC) healthcare systems, with particular reference to critical care. Participants from key regional and local stakeholders in healthcare and engineering discussed how new advances in technology, especially in the field of Artificial Intelligence, could be of potential benefit. This article summarizes the perspectives and conclusions of a group of key stakeholders from LMICs across South and South East Asia

Trends in invasive bacterial diseases during the first 2 years of the COVID-19 pandemic: analyses of prospective surveillance data from 30 countries and territories in the IRIS Consortium.

BACKGROUND The Invasive Respiratory Infection Surveillance (IRIS) Consortium was established to assess the impact of the COVID-19 pandemic on invasive diseases caused by Streptococcus pneumoniae, Haemophilus influenzae, Neisseria meningitidis, and Streptococcus agalactiae. We aimed to analyse the incidence and distribution of these diseases during the first 2 years of the COVID-19 pandemic compared to the 2 years preceding the pandemic. METHODS For this prospective analysis, laboratories in 30 countries and territories representing five continents submitted surveillance data from Jan 1, 2018, to Jan 2, 2022, to private projects within databases in PubMLST. The impact of COVID-19 containment measures on the overall number of cases was analysed, and changes in disease distributions by patient age and serotype or group were examined. Interrupted time-series analyses were done to quantify the impact of pandemic response measures and their relaxation on disease rates, and autoregressive integrated moving average models were used to estimate effect sizes and forecast counterfactual trends by hemisphere. FINDINGS Overall, 116 841 cases were analysed: 76 481 in 2018-19, before the pandemic, and 40 360 in 2020-21, during the pandemic. During the pandemic there was a significant reduction in the risk of disease caused by S pneumoniae (risk ratio 0·47; 95% CI 0·40-0·55), H influenzae (0·51; 0·40-0·66) and N meningitidis (0·26; 0·21-0·31), while no significant changes were observed for S agalactiae (1·02; 0·75-1·40), which is not transmitted via the respiratory route. No major changes in the distribution of cases were observed when stratified by patient age or serotype or group. An estimated 36 289 (95% prediction interval 17 145-55 434) cases of invasive bacterial disease were averted during the first 2 years of the pandemic among IRIS-participating countries and territories. INTERPRETATION COVID-19 containment measures were associated with a sustained decrease in the incidence of invasive disease caused by S pneumoniae, H influenzae, and N meningitidis during the first 2 years of the pandemic, but cases began to increase in some countries towards the end of 2021 as pandemic restrictions were lifted. These IRIS data provide a better understanding of microbial transmission, will inform vaccine development and implementation, and can contribute to health-care service planning and provision of policies. FUNDING Wellcome Trust, NIHR Oxford Biomedical Research Centre, Spanish Ministry of Science and Innovation, Korea Disease Control and Prevention Agency, Torsten Söderberg Foundation, Stockholm County Council, Swedish Research Council, German Federal Ministry of Health, Robert Koch Institute, Pfizer, Merck, and the Greek National Public Health Organization

Ценностные ориентации, как основа для формирования профессиональных компетенций учащихся специальности «Медико-профилактическое дело»

ОБРАЗОВАНИЕ МЕДИЦИНСКОЕМЕДИЦИНСКИЕ УЧЕБНЫЕ ЗАВЕДЕНИЯПРОФЕССИОНАЛЬНЫЕ КОМПЕТЕНЦИИСТУДЕНТЫ МЕДИЦИНСКИХ УЧЕБНЫХ ЗАВЕДЕНИЙКОМПЕТЕНТНОСТНЫЙ ПОДХОДЦЕННОСТНЫЕ ОРИЕНТАЦИИМЕДИКО-ПРОФИЛАКТИЧЕСКОЕ ДЕЛО (СПЕЦИАЛЬНОСТЬ

eulerAPE: Drawing Area-proportional 3-Venn Diagrams Using Ellipses

Venn diagrams with three curves are used extensively in various medical and scientific disciplines to visualize relationships between data sets and facilitate data analysis. The area of the regions formed by the overlapping curves is often directly proportional to the cardinality of the depicted set relation or any other related quantitative data. Drawing these diagrams manually is difficult and current automatic drawing methods do not always produce appropriate diagrams. Most methods depict the data sets as circles, as they perceptually pop out as complete distinct objects due to their smoothness and regularity. However, circles cannot draw accurate diagrams for most 3-set data and so the generated diagrams often have misleading region areas. Other methods use polygons to draw accurate diagrams. However, polygons are non-smooth and non-symmetric, so the curves are not easily distinguishable and the diagrams are difficult to comprehend. Ellipses are more flexible than circles and are similarly smooth, but none of the current automatic drawing methods use ellipses. We present eulerAPE as the first method and software that uses ellipses for automatically drawing accurate area-proportional Venn diagrams for 3-set data. We describe the drawing method adopted by eulerAPE and we discuss our evaluation of the effectiveness of eulerAPE and ellipses for drawing random 3-set data. We compare eulerAPE and various other methods that are currently available and we discuss differences between their generated diagrams in terms of accuracy and ease of understanding for real world data