Effectively with this announcement today, Oregon has abandoned it’s smart phone contact tracing apps, joining half the US states that chose to not pursue these apps.
Oregon pausing exposure notification app
This week, OHA decided to pause the ongoing planning of the Exposure Notification (EN) application project rollout for Oregon to focus on vaccinations and other priority efforts to end the COVID-19 pandemic.
Over the past six months, OHA has benefited from discussions with local public health departments and other partners, which highlighted the benefits and costs of any early notification app, including the intensive efforts state and local health officials would need to undertake to promote the app and address likely gaps in its adoption across Oregon’s diverse communities, as well as the added contact tracing demands full adoption would place on county public health staff.
OHA appreciates the feedback agency staff heard from our partners working in local communities. State health officials reached the decision after consultation with Gov. Kate Brown’s office.
OHA Public Health Director Rachael Banks said: “Approximately two dozen states have chosen not to deploy smartphone-based apps at this time and instead to rely on other tools to stop the spread of COVID-19. Oregon is focused on building trust with people in communities across the state to get all Oregonians vaccinated and sustain the other COVID-19 prevention practices, such as wearing a mask, staying physically distant and limiting the size and frequency of indoor social get-togethers. These strategies have prevented more than 4,000 COVID-19 deaths in our state. We’ll continue to prioritize these approaches because they remain our best bet to end the pandemic.”
April 1 – Google has updated its Android OS default camera app with a new “mask filter”. The apps uses AI techniques to automatically identify face masks and then filters them out of the photo, using AI to automatically generate the missing face area.
The update is available on all Android phones as of April 1.
Reviewers say the mask filter works as effectively as masks work in real life, which is to say, not that good. Google suggests applying the mask filter twice for more effective mask removal.
Months after agency officials said they were actively “assessing the results” of a trial conducted at Oregon State University, state officials now say they have no final documentation about efforts to evaluate the project.
The decision by state officials not to formally assess the technology helps explain why the project has been delayed for months, leaving Oregon as one of just four states along or west of the Continental Divide that has failed to adopt the technology.
One year ago, the tech sector jumped in with a plan to develop smart phone based contact detection apps. These would use Bluetooth to estimate potential contacts with someone later testing positive for Covid-19.
I predicted at the time (see past posts) that this technology was not likely to be successful for many reasons.
Here we are, one year later, and we are only now developing testing criteria for these apps.
The Science and Technology Directorate (S&T) of the Department of Homeland Security (DHS) awarded $959,305 to the University of Washington’s Applied Physics Laboratory this week to create testing criteria for a COVID-19 digital contact tracing app. The award was granted … Read More »
The media gave much attention to alleged privacy issues but that was never the problem – the problem was the nature of the technology and the high false negative and false positive rates and that huge numbers of people would need to use it for it to deliver mediocre results.
One year later, these apps are mostly non-existent and public health and has found very few potential cases through the technology. In spite of being a brain injured idiot, my analysis was correct.
Update: As of March 2021, essentially no one is using contact tracing apps in Canada either. In Alberta, the app has found 0.02% (that is 1% divided by 50!) of the positive Covid-19 cases. And some of those cases might have been determined by other means eventually anyway. The score card: 0.02% by contact tracing app and 99.98% by other methods.
In reality, adoption of contract tracing apps by citizens was largely sporadic and unenthusiastic. A trio of researchers in Australia decided to explore why contract tracing apps weren’t more widely adopted. Their results, published on 23 December in IEEE Software, emphasize the importance of social factors such as trust and transparency.
I wrote a lot about these apps in the past. I have yet to see evidence that Bluetooth-based radio signal strength measurements are anything but error prone when used in the real world. Plus, they cannot detect contacts “across time” – that is, person with Covid gets off bus, you board and sit in their seat. The BT systems cannot detect this surface and airspace contact. One study found a 40+% false positive rate, others found high false negatives, for example. Others found decreased battery life of their smart phones, and many privacy questions, particularly about network-side tracking but I identified privacy issues even with anonymous Bluetooth methods.
If you carried a cell phone with you near the Capitol on January 6th, the FBI will be contacting you. The FBI has gone through cellular network databases and retrieved all cell phone data. If your phone was turned on, you will be contacted by the FBI – perhaps to provide witness testimony or as a potential suspect.
Can energy usage data tell us anything about the quality of our programming languages? Last year a team of six researchers in Portugal from three different universities decided to investigate this question, ultimately releasing a paper titled “Energy Efficiency Across Programming Languages.” They ran the solutions to 10 programming problems written in 27 different languages,…
With some exceptions, this problem is a hard one to sort out – yet it matters when using battery operated portable devices.
The paper took a hard look at the common assumption that a faster program will always use less energy, pointing out that it’s not as simple as the law of physics that says E(nergy) = T(ime) x P(ower).
I proved this in my Masters in Software Engineering thesis eight years ago. Software developers have long operated on the belief that a “fast” and efficient program would use less energy. But ultimately it depends on how their high level code is translated into compiled code or pseudo-code, or interpreted, and the underlying implementation of any virtual machines that execute the pseudo-code.
Paradoxically, less efficient algorithms can indeed use less electric energy – it ultimately depends on how the hardware is put to use. And in the case of pseudo-code – this means a power optimized app running on one Android phone might even be less – or more – efficient when run on a phone from a different manufacturer using a different virtual machine to execute the pseudo code!
There is a complex, and non-obvious trade-off between algorithm efficiency, memory usage, and power consumption – and it varies by language, and by device.
On phones, the big power users tend to be the display, and GPS, and the camera – and of course, the CPU. Most power reduction strategies work to keep hardware turned off, or in a low energy state, as much as possible.
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