Skip to main content

Home/ ODI Covid-19 Project/ Group items tagged China

Rss Feed Group items tagged

Ben Snaith

Code red - To curb covid-19, China is using its high-tech surveillance tools | China | ... - 0 views

  • The red colour of the QR code on Ms Sun’s “Hangzhou Health Code” app indicated that she was supposed to be undergoing 14 days of self-quarantine. Had the code been yellow, it would have meant she was a lower risk and had to isolate herself for seven days. For free passage around the city, people must produce their phones at checkpoints and show they have a green QR code. Pictured is another method of keeping tabs on people: drivers have to scan the code held up by a drone to register for entry into the city, in this case Shenzhen.
  • But those efforts involve only a single province. Creating such systems is far harder when it entails data-sharing between provinces, or between provincial and central authorities. Co-operation is undermined by competition for favour in Beijing. The boss of a foreign artificial-intelligence developer in China says that fusing datasets within a single firm is often quick, but not if it involves co-operation between different institutions. “The person in charge is unwilling to take the risk,” he says, and usually reckons that doing nothing is safer than sharing.
Ben Snaith

COVID-19 Digital Rights Tracker - 0 views

  • According to the article, the mayor wrote on his website: “Compliance with the regime is constantly monitored, including with the help of facial recognition systems and other technical measures.”
fionntan

Coronavirus exposes the problems and pitfalls of modelling | Science | The Guardian - 1 views

  • The model, based on 13-year-old code for a long-feared influenza pandemic, assumed that the demand for intensive care units would be the same for both infections. Data from China soon showed this to be dangerously wrong, but the model was only updated when more data poured out of Italy, where intensive care was swiftly overwhelmed and deaths shot up.
  • It did not consider the impact of widespread rapid testing, contact tracing and isolation, which can be used in the early stages of an epidemic or in lockdown conditions to keep infections down to such an extent that when restrictions are lifted the virus should not rebound.
Ben Snaith

Which Covid-19 Data Can You Trust? - 2 views

  • In a crisis situation like the one we are in, data can be an essential tool for crafting responses, allocating resources, measuring the effectiveness of interventions, such as social distancing, and telling us when we might reopen economies. However, incomplete or incorrect data can also muddy the waters, obscuring important nuances within communities, ignoring important factors such as socioeconomic realities, and creating false senses of panic or safety, not to mention other harms such as needlessly exposing private information.
  • Unfortunately, many of these technological solutions — however well intended — do not provide the clear picture they purport to. In many cases, there is insufficient engagement with subject-matter experts, such as epidemiologists who specialize in modeling the spread of infectious diseases or front-line clinicians who can help prioritize needs. But because technology and telecom companies have greater access to mobile device data, enormous financial resources, and larger teams of data scientists, than academic researchers do, their data products are being rolled out at a higher volume than high quality studies.
  • To some extent, all data risk breaching the privacy of individual or group identities, but publishing scorecards for specific neighborhoods risks shaming or punishing communities, while ignoring the socioeconomic realities of people’s lives that make it difficult for them to stay home.
  • ...8 more annotations...
  • Even more granular examples, such as footfalls at identifiable business locations, risks de-identifying religious groups; patients visiting cancer hospitals, HIV clinics, or reproductive health clinics; or those seeking public assistance. The medical and public health communities long ago deemed the un-masking of such information without consent unacceptable, but companies have recently been releasing it on publicly available dashboards.
  • Until we know more about how these changing movement patterns impact epidemiological aspects of the disease, we should use these data with caution.
  • Simply presenting them, or interpreting them without a proper contextual understanding, could inadvertently lead to imposing or relaxing restrictions on lives and livelihoods, based on incomplete information.
  • In the absence of a tightly coupled testing and treatment plan, however, these apps risk either providing false reassurance to communities where infectious but asymptomatic individuals can continue to spread disease, or requiring an unreasonably large number of people to quarantine. The behavioral response of the population to these apps is therefore unknown and likely to vary significantly across societies.
  • Some contact-tracing apps follow black-box algorithms, which preclude the global community of scientists from refining them or adopting them elsewhere. These non-transparent, un-validated interventions — which are now being rolled out (or rolled back) in countries such as China, India, Israel and Vietnam — are in direct contravention to the open cross-border collaboration that scientists have adopted to address the Covid-19 pandemic.
  • pidemiological models that can help predict the burden and pattern of spread of Covid-19 rely on a number of parameters that are, as yet, wildly uncertain. We still lack many of the basic facts about this disease, including how many people have symptoms, whether people who have been infected are immune to reinfection, and — crucially — how many people have been infected so far. In the absence of reliable virological testing data, we cannot fit models accurately, or know confidently what the future of this epidemic will look like for all these reasons, and yet numbers are being presented to governments and the public with the appearance of certainty
  • Telenor, the Norwegian telco giant has led the way in responsible use of aggregated mobility data from cell phone tower records. Its data have been used, in close collaboration with scientists and local practitioners, to model, predict, and respond to outbreaks around the world. Telenor has openly published its methods and provided technological guidance on how telco data can be used in public health emergencies in a responsible, anonymized format that does not risk de-identification.
  • The Covid-19 Mobility Data Network, of which we are part, comprises a voluntary collaboration of epidemiologists from around the world analyzes aggregated data from technology companies to provide daily insights to city and state officials from California to Dhaka, Bangladesh.
1 - 4 of 4
Showing 20 items per page