Events/HackCovid/2020-03-28/Group3

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data anthropology

Presentation

General questions useful for the hackathon:

From the perspective of medical anthropology, intersectionality:

Target an Application that creates a social profile to be utilized to facilitate social interaction minimizing socioeconomic damage during pandemics (sadly they are here to stay) and unlike SARS1 that ground pockets of economy to a halt, SARS2 has ground the global economy to a halt.

• A central tenet – there is no biomedical (vaccine, antiretroviral) response to COVID19
• As with SARS1, MERS etc, medical treatments are possible, but unlikely
• This is key, our response is a social response (physical distancing, shelter in place) limiting social interaction
• End result is to break the chain of transmission of COVID19 utilizing app that contains a social profile to identify safe interactions
• Allow privacy but health identifiers
• Are the app connections both gouvernment and society-based?
• What is the main target function of the app?
• Data sets and maths to create?
• Critical not to infringe on rights in the West
• Asian approach of lock down can’t be used in the West
• Foucault’s biopower in play, the peoples power and rights fed back up to the government
• The app navigates this contour of human rights versus government control
• Surveys to get profiles? What is the value/danger of profiling?
• How does the app contribute to the social response to COVID19, since that is our only response?

Discussion

1. Started by public health surveillance, and their ethics and laws. Rules of privacy already allow the state to limit the freedom. Enhanced with digital systems, like asking for digital surveillance. What are limits, etc.

2. Starts from the bottom up, difficult to conceptualise. Not part of standard public health surveillance. If imagine new ecosystem of contributors, not to enhance surveillance. Should they need a framework for themselves beyond the laws. What's is the driver?
what's are the limits?
Should we need a framework?

  • Start with anthropology

whats' the model
resources
how many models?
identify how people are living? How exposed they're?
social points of contagion
what's the implication for ethics?

444 answers from the French version of Questionnaire COVID-19 lifestyles and contagion

Very interesting input specially the supermarket visit .

Personas for design: https://docs.google.com/document/d/16-B-CN652Wm8qeEUB2OATsQwL6JEr6xF1rHPyeHPduE/edit?usp=sharing
11 types of at risk profiles were detected

  • kid + single parents
  • teenager + student
  • single person without children with office job (homeworking)
  • doctor in hospital (borderer worker)
  • nurse in mobility
  • delivery person
  • cashier or seller in a supermarket + risky partner
  • independent worker
  • unemployed person healed from COVID-19
  • isolated elder person
  • family with home-school


  • From the data perspective

Which data are relevant from the personas for design)
Possible sources of data: potentially portable COVID testing.
An ultrasensitive, rapid, and portable coronavirus SARS-CoV-2 sequence detection method based on CRISPR-Cas12
https://www.biorxiv.org/content/10.1101/2020.02.29.971127v1

[feature 1: degree of risk for themselves, likelihood to get infected] [how to know?]
-> result of a model with a lot of variables


[feature 2: Based on the configuration of the shelter, what are the degree of risk of contaminating others, likelihood to infect others] [how to know?]
variables: shelter configuration, occupation,


[feature 3: typical contagion channels] [how to know?]
variables: transportation, shared facilities, occupation, leisure, food supply, hospital, pharmacy,


[feature 4: easy to detect/contact/trace] [how to know?]
variables: level of education, gender, age, access to tech, awareness, location (urban/suburban/remote), level of trust in government & health system,

[feature 5: risk of harming by detection/contact/tracing ] [how to know?]
variables[a][b][c][d][e][f]: affair, illegal activities, hard to account, who is accessing the data? for which purposes?
keyword: stigmatization,


[feature 6: communication risks, e.g. miscommunication, fear, stigmatization] [how to assess this?]
variables: age, level of education

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