Implementation of the INTERGROWTH-21st Project in Kenya

The African site in the INTERGROWTH-21(st) Project was Parklands, a wealthy suburb of Nairobi, Kenya, with a largely middle-to-high socio-economic status population. There are three hospitals with obstetric units in Parklands, with approximately 4300 births per year. The Newborn Cross-Sectional Study (NCSS) sample was drawn from all three hospitals, covering 100% of births in this target population. The Fetal Growth Longitudinal Study (FGLS) sample was recruited from antenatal clinics serving these hospitals, using the eligibility criteria in the INTERGROWTH-21(st) protocol. Special activities to raise awareness of the study included securing media coverage and distributing leaflets in antenatal clinic waiting rooms. FGLS required women to be recruited in the first trimester; therefore, a major challenge at this study site was the high background frequency of first antenatal consultations in the second trimester. The problem was overcome by the study awareness campaign, as a result of which more women started attending antenatal care earlier in pregnancy

D 3 -MapReduce: Towards MapReduce for Distributed and Dynamic Data Sets

International audienceSince its introduction in 2004 by Google, MapRe-duce has become the programming model of choice for processing large data sets. Although MapReduce was originally developed for use by web enterprises in large data-centers, this technique has gained a lot of attention from the scientific community for its applicability in large parallel data analysis (including geographic, high energy physics, genomics, etc.). So far MapReduce has been mostly designed for batch processing of bulk data. The ambition of D 3-MapReduce is to extend the MapReduce programming model and propose efficient implementation of this model to: i) cope with distributed data sets, i.e. that span over multiple distributed infrastructures or stored on network of loosely connected devices; ii) cope with dynamic data sets, i.e. which dynamically change over time or can be either incomplete or partially available. In this paper, we draw the path towards this ambitious goal. Our approach leverages Data Life Cycle as a key concept to provide MapReduce for distributed and dynamic data sets on heterogeneous and distributed infrastructures. We first report on our attempts at implementing the MapReduce programming model for Hybrid Distributed Computing Infrastructures (Hybrid DCIs). We present the architecture of the prototype based on BitDew, a middleware for large scale data management, and Active Data, a programming model for data life cycle management. Second, we outline the challenges in term of methodology and present our approaches based on simulation and emulation on the Grid'5000 experimental testbed. We conduct performance evaluations and compare our prototype with Hadoop, the industry reference MapReduce implementation. We present our work in progress on dynamic data sets that has lead us to implement an incremental MapReduce framework. Finally, we discuss our achievements and outline the challenges that remain to be addressed before obtaining a complete D 3-MapReduce environment

Social gradient of birthweight in England assessed using the INTERGROWTH-21st gestational age-specific standard.

OBJECTIVE: To determine the socioeconomic gradient of birthweights in England with reference to the prescriptive INTERGROWTH-21st Birthweight Standard. DESIGN: National cross-sectional study using data from Hospital Episode Statistics. SETTING: National Health Service in England. PARTICIPANTS: All singleton babies, live born between 34 weeks' gestation and 42 weeks' gestation, between 1 April 2011 and 31 March 2012. MAIN OUTCOME MEASURES: Birthweight distribution of babies with a birthweight of 90th centile, that is, small for gestational age (SGA) or large for gestational age (LGA) using Index of Multiple Deprivation quintiles as a proxy for socioeconomic status. RESULTS: Of 508 230 babies born alive between 1 April 2011 and 31 March 2012, 38 838 (7.6%) were SGA and 81 026 (15.9%) were LGA. Median birthweight was 3405 g, median z-score was 0.25 (SD 1.06). Birthweight z-score demonstrated a social gradient, from 0.26 (SD 1.1) in the most deprived areas to 0.53 (1.0) in the least deprived. Women in the most deprived areas were twice as likely to have SGA babies using the INTERGROWTH-21st chart (OR 1.94; 95% CI 1.87 to 2.01) compared with those in the least deprived areas. If all women had the same rate of SGA equivalent to those living in the least deprived areas, approximately 12 410 (30%) fewer babies would be born SGA in England each year. CONCLUSIONS: This study gives a measure of the social gradient in singleton SGA and LGA babies across England using an international standard of newborn size at birth

Managing data for the international, multicentre INTERGROWTH-21st Project

The INTERGROWTH-21st Project data management was structured incorporating both a centralised and decentralised system for the eight study centres, which all used the same database and standardised data collection instruments, manuals and processes. Each centre was responsible for the entry and validation of their country-specific data, which were entered onto a centralised system maintained by the Data Coordinating Unit in Oxford. A comprehensive data management system was designed to handle the very large volumes of data. It contained internal validations to prevent incorrect and inconsistent values being captured, and allowed online data entry by local Data Management Units, as well as real-time management of recruitment and data collection by the Data Coordinating Unit in Oxford. To maintain data integrity, only the Data Coordinating Unit in Oxford had access to all the eight centres’ data, which were continually monitored. All queries identified were raised with the relevant local data manager for verification and correction, if necessary. The system automatically logged an audit trail of all updates to the database with the date and name of the person who made the changes. These rigorous processes ensured that the data collected in the INTERGROWTH-21st Project were of exceptionally high quality

A Thermoresponsive and Magnetic Colloid for 3D Cell Expansion and Reconfiguration

A dual thermoresponsive and magnetic colloidal gel matrix is described for enhanced stem-cell culture. The combined properties of the material allow enzyme-free passaging and expansion of mesenchymal stem cells, as well as isolation of cells postculture by the simple process of lowering the temperature and applying an external magnetic field. The colloidal gel can be reconfigured with thermal and magnetic stimuli to allow patterning of cells in discrete zones and to control movement of cells within the porous matrix during culture

The Potential and Challenges of Nanopore Sequencing

A nanopore-based device provides single-molecule detection and analytical capabilities that are achieved by electrophoretically driving molecules in solution through a nano-scale pore. The nanopore provides a highly confined space within which single nucleic acid polymers can be analyzed at high throughput by one of a variety of means, and the perfect processivity that can be enforced in a narrow pore ensures that the native order of the nucleobases in a polynucleotide is reflected in the sequence of signals that is detected. Kilobase length polymers (single-stranded genomic DNA or RNA) or small molecules (e.g., nucleosides) can be identified and characterized without amplification or labeling, a unique analytical capability that makes inexpensive, rapid DNA sequencing a possibility. Further research and development to overcome current challenges to nanopore identification of each successive nucleotide in a DNA strand offers the prospect of ‘third generation’ instruments that will sequence a diploid mammalian genome for ~$1,000 in ~24 h.Molecular and Cellular BiologyPhysic

Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data. Methods: We estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting. Findings: Globally, for females, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and haemoglobinopathies and haemolytic anaemias in both 1990 and 2017. For males, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and tuberculosis including latent tuberculosis infection in both 1990 and 2017. In terms of YLDs, low back pain, headache disorders, and dietary iron deficiency were the leading Level 3 causes of YLD counts in 1990, whereas low back pain, headache disorders, and depressive disorders were the leading causes in 2017 for both sexes combined. All-cause age-standardised YLD rates decreased by 3·9% (95% uncertainty interval [UI] 3·1-4·6) from 1990 to 2017; however, the all-age YLD rate increased by 7·2% (6·0-8·4) while the total sum of global YLDs increased from 562 million (421-723) to 853 million (642-1100). The increases for males and females were similar, with increases in all-age YLD rates of 7·9% (6·6-9·2) for males and 6·5% (5·4-7·7) for females. We found significant differences between males and females in terms of age-standardised prevalence estimates for multiple causes. The causes with the greatest relative differences between sexes in 2017 included substance use disorders (3018 cases [95% UI 2782-3252] per 100 000 in males vs 1400 [1279-1524] per 100 000 in females), transport injuries (3322 [3082-3583] vs 2336 [2154-2535]), and self-harm and interpersonal violence (3265 [2943-3630] vs 5643 [5057-6302]). Interpretation: Global all-cause age-standardised YLD rates have improved only slightly over a period spanning nearly three decades. However, the magnitude of the non-fatal disease burden has expanded globally, with increasing numbers of people who have a wide spectrum of conditions. A subset of conditions has remained globally pervasive since 1990, whereas other conditions have displayed more dynamic trends, with different ages, sexes, and geographies across the globe experiencing varying burdens and trends of health loss. This study emphasises how global improvements in premature mortality for select conditions have led to older populations with complex and potentially expensive diseases, yet also highlights global achievements in certain domains of disease and injury

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security