pandemic
A Virus detection network to stop the next Pandemic
How can we stop the next pandemic before it starts? Disease researchers Pardis Sabeti and Christian Happi introduce Sentinel, an early warning system that detects and tracks viral threats in real time -- and could help stop them before they spre
Source: www.technology-in-business.net
With cases soaring across the globe, the Covid-19 pandemic is nowhere near its end, but with three vaccines reporting trial data and two apparently nearing approval by the US FDA, it may be reaching a pivot point.
In what feels like a moment of drawing breath and taking stock, international researchers are turning their attention from the present back to the start of the pandemic, aiming to untangle its origin and asking what lessons can be learned to keep this from happening again.
Two efforts are happening in parallel. On November 5, the World Health Organization quietly published the rules of engagement for a long-planned and months-delayed mission that creates a multinational team of researchers who will pursue how the virus leaped species. Meanwhile, last week, a commission created by The Lancet and headed by the economist and policy expert Jeffrey Sachs announced the formation of its own international effort, a task force of 12 experts from nine countries who will undertake similar tasks.
Both groups will face the same complex problems. It has been approximately a year since the first cases of a pneumonia of unknown origin appeared in Wuhan, China, and about 11 months since the pneumonia’s cause was identified as a novel coronavirus, probably originating in bats.
The experts will have to retrace a chain of transmission—one or multiple leaps of the virus from the animal world into humans—using interviews, stored biological samples, lab assays, environmental surveys, genomic data, and the thousands of papers published since the pandemic began, all while following a trail that may have gone cold.
The point is not to look for patient zero, the first person infected—or even a hypothetical bat zero, the single animal from which the novel virus jumped.
It’s likely neither of those will ever be found. The goal instead is to elucidate the ecosystem—physical, but also viral—in which the spillover happened and ask what could make it likely to happen again.
Lire l'article complet sur : www.wired.com
Contact tracing apps are potentially useful tools for supporting national COVID-19 containment strategies. Various national apps with different technical design features have been commissioned and issued by governments worldwide.
Objective: Our goal was to develop and propose an item set that was suitable for describing and monitoring nationally issued COVID-19 contact tracing apps.
This item set could provide a framework for describing the key technical features of such apps and monitoring their use based on widely available information.
Methods: We used an open-source intelligence approach (OSINT) to access a multitude of publicly available sources and collect data and information regarding the development and use of contact tracing apps in different countries over several months (from June 2020 to January 2021). The collected documents were then iteratively analyzed via content analysis methods. During this process, an initial set of subject areas were refined into categories for evaluation (ie, coherent topics), which were then examined for individual features.
These features were paraphrased as items in the form of questions and applied to information materials from a sample of countries (ie, Brazil, China, Finland, France, Germany, Italy, Singapore, South Korea, Spain, and the United Kingdom [England and Wales]). This sample was purposefully selected; our intention was to include the apps of different countries from around the world and to propose a valid item set that can be relatively easily applied by using an OSINT approach.
Results: Our OSINT approach and subsequent analysis of the collected documents resulted in the definition of the following five main categories and associated subcategories:
(1) background information (open-source code, public information, and collaborators);
(2) purpose and workflow (secondary data use and warning process design);
(3) technical information (protocol, tracing technology, exposure notification system, and interoperability);
(4) privacy protection (the entity of trust and anonymity); and
(5) availability and use (release date and the number of downloads).
Based on this structure, a set of items that constituted the evaluation framework were specified. The application of these items to the 10 selected countries revealed differences, especially with regard to the centralization of the entity of trust and the overall transparency of the apps’ technical makeup.
Conclusions: We provide a set of criteria for monitoring and evaluating COVID-19 tracing apps that can be easily applied to publicly issued information. The application of these criteria might help governments to identify design features that promote the successful, widespread adoption of COVID-19 tracing apps among target populations and across national boundaries.
read the study at https://mhealth.jmir.org/2021/3/e27232
Lire l'article complet sur : mhealth.jmir.org
The enormous pressure of the increasing case numbers experienced during the COVID-19 pandemic has given rise to a variety of novel digital systems designed to provide solutions to unprecedented challenges in public health.
The field of algorithmic contact tracing, in particular, an area of research that had previously received limited attention, has moved into the spotlight as a crucial factor in containing the pandemic.
The use of digital tools to enable more robust and expedited contact tracing and notification, while maintaining privacy and trust in the data generated, is viewed as key to identifying chains of transmission and close contacts, and, consequently, to enabling effective case investigations.
Scaling these tools has never been more critical, as global case numbers have exceeded 100 million, as many asymptomatic patients remain undetected, and as COVID-19 variants begin to emerge around the world.
In this context, there is increasing attention on blockchain technology as a part of systems for enhanced digital algorithmic contact tracing and reporting. By analyzing the literature that has emerged from this trend, the common characteristics of the designs proposed become apparent.
An archetypal system architecture can be derived, taking these characteristics into consideration. However, assessing the utility of this architecture using a recognized evaluation framework shows that the added benefits and features of blockchain technology do not provide significant advantages over conventional centralized systems for algorithmic contact tracing and reporting.
From our study, it, therefore, seems that blockchain technology may provide a more significant benefit in other areas of public health beyond contact tracing.
more at https://publichealth.jmir.org/2021/4/e26460
Lire l'article complet sur : publichealth.jmir.org