‘It is not fashionable to suffer nowadays’: Community motivations to repeatedly participate in outreach HIV testing indicate UHC potential in Tanzania

OBJECTIVE: This study examined people’s motivations for (repeatedly) utilizing HIV testing services during community-based testing events in urban and rural Shinyanga, Tanzania and potential implications for Universal Health Coverage (UHC). METHODS: As part of a broader multidisciplinary study on the implementation of a HIV Test and Treat model in Shinyanga Region, Tanzania, this ethnographic study focused on community-based testing campaigns organised by the implementing partner. Between April 2018 and December 2019, we conducted structured observations (24), short questionnaires (42) and in-depth interviews with HIV-positive (23) and HIV-negative clients (8). Observations focused on motivations for (re-)testing, and the counselling and testing process. Thematic analysis based on inductive and deductive coding was completed using NVivo software. RESULTS: Regular HIV testing was encouraged by counsellors. Most participants in testing campaigns were HIV-negative; 51.1% had tested more than once over their lifetimes. Testing campaigns provided an accessible way to learn one’s HIV status. Motivations for repeat testing included: monitoring personal health to achieve (temporary) reassurance, having low levels of trust toward sexual partners, feeling at risk, seeking proof of (ill)-health, and acting responsibly. Repeat testers also associated testing with a desire to start treatment early to preserve a healthy-looking body, should they prove HIV positive. CONCLUSIONS: Community-based testing campaigns serve three valuable functions related to HIV prevention and treatment: 1) enable community members to check their HIV status regularly as part of a personalized prevention strategy that reinforces responsible behaviour; 2) identify recently sero-converted clients who would not otherwise be targeted; and 3) engage community with general prevention and care messaging and services. This model could be expanded to include routine management of other (chronic) diseases and provide an entry for scaling up UHC

How 5G wireless (and concomitant technologies) will revolutionize healthcare?

The need to have equitable access to quality healthcare is enshrined in the United Nations (UN) Sustainable Development Goals (SDGs), which defines the developmental agenda of the UN for the next 15 years. In particular, the third SDG focuses on the need to “ensure healthy lives and promote well-being for all at all ages”. In this paper, we build the case that 5G wireless technology, along with concomitant emerging technologies (such as IoT, big data, artificial intelligence and machine learning), will transform global healthcare systems in the near future. Our optimism around 5G-enabled healthcare stems from a confluence of significant technical pushes that are already at play: apart from the availability of high-throughput low-latency wireless connectivity, other significant factors include the democratization of computing through cloud computing; the democratization of Artificial Intelligence (AI) and cognitive computing (e.g., IBM Watson); and the commoditization of data through crowdsourcing and digital exhaust. These technologies together can finally crack a dysfunctional healthcare system that has largely been impervious to technological innovations. We highlight the persistent deficiencies of the current healthcare system and then demonstrate how the 5G-enabled healthcare revolution can fix these deficiencies. We also highlight open technical research challenges, and potential pitfalls, that may hinder the development of such a 5G-enabled health revolution

Waste Reduction, Construction and Demolition Debris: Guide for Building, Construction and Environmental Professionals, Revised November 2008

This document is intended to lay the foundation for resource reduction strategies in new construction, renovation and demolition. If you have an innovative idea or information that you believe should be included in future updates of this manual please email Shelly Codner at [email protected] or Jan Loyson at [email protected]. Throughout this manual, we use the term “waste reduction” to define waste management initiatives that will result in less waste going to the landfill. In accordance with the waste management hierarchy these practices include reducing (waste prevention), reusing (deconstruction and salvage), recycling and renewing (making old things new again) - in that order. This manual will explain what these practices are and how to incorporate them into your projects

Enabling Adaptive Grid Scheduling and Resource Management

Wider adoption of the Grid concept has led to an increasing amount of federated computational, storage and visualisation resources being available to scientists and researchers. Distributed and heterogeneous nature of these resources renders most of the legacy cluster monitoring and management approaches inappropriate, and poses new challenges in workflow scheduling on such systems. Effective resource utilisation monitoring and highly granular yet adaptive measurements are prerequisites for a more efficient Grid scheduler. We present a suite of measurement applications able to monitor per-process resource utilisation, and a customisable tool for emulating observed utilisation models. We also outline our future work on a predictive and probabilistic Grid scheduler. The research is undertaken as part of UK e-Science EPSRC sponsored project SO-GRM (Self-Organising Grid Resource Management) in cooperation with BT

Improved metrics collection and correlation for the CERN cloud storage test framework

Storage space is one of the most important ingredients that the European Organization for Nuclear Research (CERN) needs for its experiments and operation. Part of the Data & Storage Services (IT-DSS) group’s work at CERN is focused on testing and evaluating the cloud storage system that is provided by the openlab partner Huawei, Huawei Universal Disk Storage System (UDS). As a whole, the system consists of both software and hardware. The objective of the Huawei-CERN partnership is to investigate the performance of the cloud storage system. Among the interesting questions are the system’s scalability, reliability and ability to store and retrieve files. During the tests, possible bugs and malfunctions can be discovered and corrected. Different versions of the storage software that runs inside the storage system can also be compared to each other. The nature of testing and benchmarking a storage system gives rise to several small tasks that can be done during a short summer internship. In order to test the storage system a test framework developed by the DSS group is used. The framework consists of various types of file transfer tests, client and server monitoring programs and log file analysis programs. Part of the work done was additions to the existing framework and part was developing new tools. Metrics collection was the central theme. Metrics are to be understood as system statistics, such as memory consumption or processor usage. Memory usage and disk reads/writes were added to the existing client real-time monitoring framework. CPU and memory usage, network traffic (bytes received/sent) and the number of processes running are collected from a client computer before and after a daily test. Two other additions are visualization for storage system log files, as well as a new monitoring tool for the storage system. This report is divided into parts describing each part of the framework that was improved or added, the problem and the final solution. A short description of the code and the architecture are also included

A Data-informed Public Health Policy-Makers Platform

Hearing loss is a disease exhibiting a growing trend due to the number of factors, including but not limited to the mundane exposure to the noise and ever-increasing amount of older population. In the framework of a public health policymaking process, modeling of the hearing loss disease based on data is a key factor in alleviating the issues related to the disease issuing effective public health policies. First, the paper describes the steps of the data-driven policymaking process. Afterward, a scenario along with the part of the proposed platform, responsible for supporting policymaking are presented. With the aim of demonstrating the capabilities and usability of the platform for the policy-makers, some initial results of preliminary analytics are presented in a framework of a policy-making process. Ultimately, the utility of the approach is validated throughout the results of the survey which was presented to the health system policy-makers professionals involved in the policy development process in Croatia