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Ben Snaith

Coronavirus response in the UK and France - 0 views

www.tomforth.co.uk/coronavirusinfranceandtheuk

Coronavirus Data Health Government France UK

shared by Ben Snaith on 23 Apr 20 - No Cached
  • Perhaps the largest difference between the UK and France has been in the quality of data that is being provided to the public, to the media, and (I suspect) to the politicians making decisions about what to do. National, regional, sub-regional, and demographic breakdowns of deaths, hospital admissions, intensive care capacity and occupancy, excess deaths, and much more are provided regularly by French government bodies. The data.gouv.fr site hosts discussions where data is improved, improvements are requested, and analysis is shared. While The Financial Times has undoubtedly provided the best data analysis to the world, no UK paper has access to the data that would let it provide as good analysis to the country as the French press and French society have been able to provide to the French public and its politicians.
fionntan

The Systems Thinker - Introduction to Systems Thinking - The Systems Thinker - 0 views

thesystemsthinker.com/troduction-to-systems-thinking

UX Design Explainer Papers

shared by fionntan on 12 Jun 20 - No Cached
  • This volume explores these questions and introduces the principles and practice of a quietly growing field: systems thinking. With roots in disciplines as varied as biology, cybernetics, and ecology, systems thinking provides a way of looking at how the world works that differs markedly from the traditional reductionistic, analytic view. Why is a systemic perspective an important complement to analytic thinking? One reason is that understanding how systems work – and how we play a role in them – lets us function more effectively and proactively within them. The more we understand systemic behavior, the more we can anticipate that behavior and work with systems (rather than being controlled by them) to shape the quality of our lives.
Ben Snaith

If We're Not Careful, Tech Could Hurt the Fight against COVID-19 - Scientific American ... - 0 views

blogs.scientificamerican.com/...urt-the-fight-against-covid-19

shared by Ben Snaith on 04 Jun 20 - No Cached
  • Call out the risks of new technologies. Understanding technologies often makes you uniquely equipped to explain their risks. Investigate the technologies others are proposing, make sure you understand them, and if necessary sound the alarm bells.
  • Respond to technological and nontechnological calls to action.
  • Finally, consider whom your project shifts power away from and whom it shifts power to. Ownership of data is a form of power: Do you provide meaningful opt-in to data collection? Whom are you giving access to this data?
  • ...4 more annotations...
  • 4. How does your technology shift power?
  • As an example, see this paper on the privacy implications of contact tracing and the authors’ explicit statement of how their ideas should and should not be used. In many cases, your technology’s limitations mean it should not influence policy decisions; state this up front and repeat it as necessary. 
  • these spaces often obscure the voices of the most vulnerable—including communities without access to technology; people who are unhoused, in nursing homes or in prisons; and those who cannot speak freely. Find people and organizations that center vulnerable communities. Listen carefully. What do they think is most pressing? Do they want you to build your technology for them, with them, or not at all?
    • fionntan
      fionntan on 04 Jun 20
       
      Interesting to think about this mobility data. What is and isn't collected about vulnerable people?
    • Ben Snaith
      Ben Snaith on 04 Jun 20
       
      agree. we made this point in a mobility policy consultation, so I can recycle some thinking
  • 1. Are you listening to experts and vulnerable communities?
fionntan

Prediction models for diagnosis and prognosis of covid-19 infection: systematic review ... - 1 views

www.bmj.com/...bmj.m1328

Coronavirus Models Research Papers

shared by fionntan on 11 May 20 - No Cached
  • fionntan on 11 May 20
     
    This review indicates that proposed models are poorly reported, at high risk of bias, and their reported performance is probably optimistic. Immediate sharing of well documented individual participant data from covid-19 studies is needed for collaborative efforts to develop more rigorous prediction models and validate existing ones. The predictors identified in included studies could be considered as candidate predictors for new models.
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