Your new post is loading...
Your new post is loading...
The COVID-19 pandemic is the greatest public health crisis of the last 100 years. Countries have responded with various levels of lockdown to save lives and stop health systems from being overwhelmed. At the same time, lockdowns entail large socioeconomic costs. One exit strategy under consideration is a mobile phone app that traces the close contacts of those infected with COVID-19. Recent research has demonstrated the theoretical effectiveness of this solution in different disease settings. However, concerns have been raised about such apps because of the potential privacy implications. This could limit the acceptability of app-based contact tracing in the general population. As the effectiveness of this approach increases strongly with app uptake, it is crucial to understand public support for this intervention. Objective: The objective of this study is to investigate the user acceptability of a contact-tracing app in five countries hit by the pandemic. Methods: We conducted a largescale, multicountry study (N=5995) to measure public support for the digital contact tracing of COVID-19 infections. We ran anonymous online surveys in France, Germany, Italy, the United Kingdom, and the United States and measured intentions to use a contact-tracing app across different installation regimes (voluntary installation vs automatic installation by mobile phone providers) and studied how these intentions vary across individuals and countries. Results: We found strong support for the app under both regimes, in all countries, across all subgroups of the population, and irrespective of regional-level COVID-19 mortality rates. We investigated the main factors that may hinder or facilitate uptake and found that concerns about cybersecurity and privacy, together with a lack of trust in the government, are the main barriers to adoption. Conclusions: Epidemiological evidence shows that app-based contact tracing can suppress the spread of COVID-19 if a high enough proportion of the population uses the app and that it can still reduce the number of infections if uptake is moderate. Our findings show that the willingness to install the app is very high. The available evidence suggests that app-based contact tracing may be a viable approach to control the diffusion of COVID-19. read the study at https://mhealth.jmir.org/2020/8/e19857 Lire l'article complet sur : mhealth.jmir.org
Via nrip
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
Via nrip
Web-based technology has dramatically improved our ability to detect communicable disease outbreaks, with the potential to reduce morbidity and mortality because of swift public health action. Apps accessible through the internet and on mobile devices create an opportunity to enhance our traditional indicator-based surveillance systems, which have high specificity but issues with timeliness. Objective: The aim of this study is to describe the literature on web-based apps for indicator-based surveillance and response to acute communicable disease outbreaks in the community with regard to their design, implementation, and evaluation.
Results: Apps were primarily designed to improve the early detection of disease outbreaks, targeted government settings, and comprised either complex algorithmic or statistical outbreak detection mechanisms or both. We identified a need for these apps to have more features to support secure information exchange and outbreak response actions, with a focus on outbreak verification processes and staff and resources to support app operations. Conclusions: Public health officials designing new or improving existing disease outbreak web-based apps should ensure that outbreak detection is automatic and signals are verified by users, the app is easy to use, and staff and resources are available to support the operations of the app and conduct rigorous and holistic evaluations. read the study at https://publichealth.jmir.org/2021/4/e24330 Lire l'article complet sur : publichealth.jmir.org
Via nrip
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
Via TechinBiz, Sandra Boyer
|
Since the start of the pandemic, new technologies have been developed to help reduce the spread of the infection. Some of the most common safety measures today include measuring a person’s temperature, covering your nose and mouth with a mask, contact tracing, disinfection, and social distancing. Many businesses have adopted various technologies, including those with artificial intelligence (AI) underneath, helping to adhere to the COVID-19 safety measures. As an example, numerous airlines, hotels, subways, shopping malls, and other institutions are already using thermal cameras to measure an individual’s temperature before people are allowed entry. In its turn, public transport in France relies on AI-based surveillance cameras to monitor whether or not people are social-distancing or wearing masks. Another example is requiring the download of contact-tracing apps delivered by governments across the globe. However, there are a number of issues. While many of these solutions help to ensure that COVID-19 prevention practices are observed, many of them have flaws or limits. In this article, we will cover some of the issues creating obstacles for fighting the pandemic. Issue #1. Manual temperature scanning is tricky Issue #2. Monitoring crowds is even more complex Issue #3. Contact tracing leads to privacy concerns Issue #4. UV rays harm eyes and skin Issue #5. UVC robots are extremely expensive Issue #6. No integration, no compliance, no transparency Regardless of the safety measures in place and existing issues, innovations are already playing a vital role in the fight against COVID-19. By improving on existing technology, we can make everyone safer as we all adjust to the new normal. read the details at https://www.altoros.com/blog/whats-wrong-with-ai-tools-and-devices-preventing-covid-19/ Lire l'article complet sur : www.altoros.com
Via nrip
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
Via nrip
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.
more at WIRED : https://www.wired.com/story/two-global-efforts-try-to-trace-the-origin-of-the-covid-virus/?utm_source=pocket-newtab-intl-en Lire l'article complet sur : www.wired.com
Via nrip
|
A lot of research and anecdotal evidence shows that mHealth/Mobile App based contact tracing can suppress the spread of COVID-19 if a high enough proportion of the population uses the app.
that it can still reduce the number of infections if uptake is moderate is interesting to note.