Étiquette : health (Page 1 of 3)


“The policies are significantly stronger than Facebook’s typical rules against misinformation, under which false claims are marked as such and suppressed by the curation algorithms, but are not removed from Facebook and Instagram entirely. The distinction, the company said, was because misinformation about Covid and Covid vaccinations “could lead to imminent physical harm”.”
The topic has a personal connection for the Facebook founder and chief executive, Mark Zuckerberg. His philanthropic organisation, the Chan Zuckerberg Initiative, has embarked on a flagship effort to “cure all disease”, with a number of avenues of research being pursued, including a specific focus on vaccinations, through the Chan Zuckerberg Biohub.

Source : Facebook to remove false claims about Covid vaccines | Technology | The Guardian

StopCovid ou encore ? – Cédric O

Le choix, selon Cédric O !

“Le choix est donc très simple : tant que l’immunité collective n’est pas atteinte (ce qui est un horizon lointain), l’alternative se résume ainsi :
1. Tout faire pour couper les « départs de feu » le plus rapidement possible, y compris en utilisant des outils numériques comme StopCovid, dans des conditions très encadrées et proportionnées (et dans un contexte où l’ensemble des pays européens prévoient de déployer de tels outils) ;
2. Refuser ces outils pour des raisons philosophiques, mais dans ce cas accepter un risque significatif de malades et de morts supplémentaires.”

Source : StopCovid ou encore ? – Cédric O – Medium


“Les mesures de surveillance, via nos usages des technologies, que suggèrent nos gouvernants relèvent en réalité d’une stratégie pour détourner notre attention de la cause réelle du problème que constitue l’abandon de l’hôpital public. Ils tablent sur la culpabilisation des citoyens désireux d’agir pour faire adopter des outils toujours plus intrusifs et évitent soigneusement de mettre en lumière les multiples réseaux de solidarité qui se forment, les besoins criants des associations pour aider les plus précaires, les multiples critiques de notre mode de vie qui émergent même des plus libéraux. Plutôt que d’assumer les conséquences désastreuses d’une politique de santé défaillante, leur diversion consiste à inverser les rôles, à nous faire passer, nous, pour ceux qui refuseront d’aider les autres. Comme si nous devions être coupable de vouloir protéger notre vie privée, d’exprimer notre colère, ou simplement de suggérer des alternatives. ”

Source : Urgence partout, État nul part – La Quadrature du Net

Genomic epidemiology of novel coronavirus

“This phylogeny shows evolutionary relationships of hCoV-19 (or SARS-CoV-2) viruses from the ongoing novel coronavirus COVID-19 pandemic. This phylogeny shows an initial emergence in Wuhan, China, in Nov-Dec 2019 followed by sustained human-to-human transmission leading to sampled infections. Although the genetic relationships among sampled viruses are quite clear, there is considerable uncertainty surrounding estimates of transmission dates and in reconstruction of geographic spread. Please be aware that specific inferred transmission patterns are only a hypothesis.”

Source : Nextstrain / ncov

“We are not epidemiologists—we are the design, engineering, and support teams at a mapping company. Just as we don’t spend every moment thinking about how to track and slow the spread of infectious disease, most public health teams we work with are not experts in spatial data visualization. In the environment of a growing epidemic, maps have a way of spreading fast, too — making it imperative that they are accurate, informative, and thoughtfully designed. To answer common questions and help our partners make thoughtful design decisions while mapping this and other health crises, we have put together a number of best practices and common pitfalls to avoid.”

Source : 7 best practices for mapping a pandemic – Points of interest

MIT researchers used a machine-learning algorithm to identify a drug called halicin that kills many strains of bacteria. Halicin (top row) prevented the development of antibiotic resistance in E. coli, while ciprofloxacin (bottom row) did not.

“Using a machine-learning algorithm, MIT researchers have identified a powerful new antibiotic compound. In laboratory tests, the drug killed many of the world’s most problematic disease-causing bacteria, including some strains that are resistant to all known antibiotics. It also cleared infections in two different mouse models. The computer model, which can screen more than a hundred million chemical compounds in a matter of days, is designed to pick out potential antibiotics that kill bacteria using different mechanisms than those of existing drugs.”

Source : Artificial intelligence yields new antibiotic | MIT News


“A pop-up would appear, asking about a patient’s level of pain. Then, a drop-down menu would list treatments ranging from a referral to a pain specialist to a prescription for an opioid painkiller. Click a button, and the program would create a treatment plan. From 2016 to spring 2019, the alert went off about 230 million times. The tool existed thanks to a secret deal. Its maker, a software company called Practice Fusion, was paid by a major opioid manufacturer to design it in an effort to boost prescriptions for addictive pain pills — even though overdose deaths had almost tripled during the previous 15 years, creating a public-health disaster. The software was used by tens of thousands of doctors’ offices.”

Source : In secret deal with drugmaker, health-records tool pushed opioids – Los Angeles Times

How top health websites are sharing sensitive data with advertisers

A network diagram showing how ad tracker patterns vary for the same website from country to country. Using the example of health.com, it shows 113 nodes with 246 connections in the US, but only 39 nodes and 39 connections in the UK

“The data shared included:

  • drug names entered into Drugs.com were sent to Google’s ad unit DoubleClick.
  • symptoms inputted into WebMD’s symptom checker, and diagnoses received, including “drug overdose”, were shared with Facebook.
  • menstrual and ovulation cycle information from BabyCentre ended up with Amazon Marketing, among others.
  • keywords such as “heart disease” and “considering abortion” were shared from sites like the British Heart Foundation, Bupa and Healthline to companies including Scorecard Research and Blue Kai (owned by software giant Oracle).

In eight cases (with the exception of Healthline and Mind), a specific identifier linked to the web browser was also transmitted — potentially allowing the information to be tied to an individual — and tracker cookies were dropped before consent was given. Healthline confirmed that it also shared unique identifiers with third parties.

None of the websites tested asked for this type of explicit and detailed consent.”

Source : How top health websites are sharing sensitive data with advertisers | Financial Times

« Older posts

© 2021 no-Flux

Theme by Anders NorenUp ↑