Mois : mars 2020 (Page 2 of 3)

Epidemic Calculator

“At the time of writing, the coronavirus disease of 2019 remains a global health crisis of grave and uncertain magnitude. To the non-expert (such as myself), contextualizing the numbers, forecasts and epidemiological parameters described in the media and literature can be challenging.
Gabriel Goh created this calculator as an attempt to address this gap in understanding. This calculator implements a classical infectious disease model — SEIR (Susceptible → Exposed → Infected → Removed), an idealized model of spread still used in frontlines of research e.g. [Wu, et. al, Kucharski et. al].”

Source : Epidemic Calculator

Infodemics

“About 100M public messages have been collected and analyzed to understand the digital response in online social media to COVID-19 outbreak. Specifically, we used machine learning techniques to quantify: collective sentiment & psychology: lexicon-based and rule-based emotional and psychological state social bot pollution: The fraction of activities due to social bots and the exposure of the Twitterverse to unreliable news News reliability: the fraction of URLs pointing to reliable news and scientific sources”

Source : COVID19 Infodemics Observatory

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

“We recently discovered a new strain of Android malware. The Trojan (detected as: Trojan-Spy.AndroidOS.Cookiethief) turned out to be quite simple. Its main task was to acquire root rights on the victim device, and transfer cookies used by the browser and Facebook app to the cybercriminals’ server. This abuse technique is possible not because of a vulnerability in Facebook app or browser itself. Malware could steal cookie files of any website from other apps in the same way and achieve similar results.”

Source : Cookiethief: a cookie-stealing Trojan for Android | Securelist

a woman retrieving info from file catalouge

“For well over a decade, identity thieves, phishers, and other online scammers have created a black market of stolen and aggregated consumer data that they used to break into people’s accounts, steal their money, or impersonate them. In October, dark web researcher Vinny Troia found one such trove sitting exposed and easily accessible on an unsecured server, comprising 4 terabytes of personal information—about 1.2 billion records in all.”

Source : 1.2 Billion Records Found Exposed Online in a Single Server  | WIRED

http://www.beaude.net/no-flux/wp-content/uploads/2020/03/1582126936038-credit-card.jpeg

“Yodlee, the largest financial data broker in the U.S., sells data pulled from the bank and credit card transactions of tens of millions of Americans to investment and research firms, detailing where and when people shopped and how much they spent. The company claims that the data is anonymous, but a confidential Yodlee document obtained by Motherboard indicates individual users could be unmasked.”

Source : Leaked Document Shows How Big Companies Buy Credit Card Data on Millions of Americans – VICE

“Sensor Tower, a popular analytics platform for tech developers and investors, has been secretly collecting data from millions of people who have installed popular VPN and ad-blocking apps for Android and iOS, a BuzzFeed News investigation has found. These apps, which don’t disclose their connection to the company or reveal that they feed user data to Sensor Tower’s products, have more than 35 million downloads.”

Source : Sensor Tower Secretly Owns Ad Blocker And VPN Apps That Collect User Data

« Older posts Newer posts »

© 2021 no-Flux

Theme by Anders NorenUp ↑