Sociology of Big Data and epidemics

This is a wiki post for
(1) interesting reads about sociology, epidemics and data:

(2) draw guidelines of the working group “data anthropology” for this saturday hackathon

(3) formulate the questions for a questionnaire to create sociomedical profiles that target the understanding of lifestyles and health records

the first paper about Ebola is a great, great example that could teach us a lot about what is happening now, i think it is particularly relevant to legal and ethics groups, it raises issues @Lac was worried about.
this suggests, in my opinion, that in our hackathon we should (1) inspect the databases available, how data was collected, and its legal compliance to see what can we reuse, or not, and what we should not do if we plan to collect new data (2) discuss about sharing strategies, what do we want to make public or not, how to protect subjects privacy, also because a lot of information is already online, what to publish that is useful for society and not just alarming. We need to make a report of everything that is already online, what hasn’t been told, visualized, or measured?

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I share here a text @milesf wrote with general questions useful for the hackathon:

HackCOVID- Léman March 28th MyData

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 govt and society-based?
• What is the main target function of the app?
• Data sets and math 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?

One key part is creating a feedback loop on the individual’s view of the government measure, it seems.

@milesf i suggest that you sketch a typical ethnographic process you would do on the field (in contact with society, governments, medical teams) to see how can we implement it online and translate it into the questions i am formulating. What do you think?

un papier intéressant méthodologique pour modéliser / methodological paper for modelling
Greenland et al. Causal diagrams for epidemiologic research

how could we use this for modelling socio lifestyles with contagious causes?

a blog by Prof. Dominique Boullier, sociologist, now posting reflections about COVID-19 from a social and human sciences perspective https://shs3g.hypotheses.org/

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Is there a duty to participate in digital epidemiology?

At the Epicenter of the Covid-19 Pandemic and Humanitarian Crises in Italy: Changing Perspectives on Preparation and Mitigation

les super-spreader: https://www.theguardian.com/world/2020/feb/27/what-are-super-spreaders-and-how-are-they-transmitting-coronavirus c’est difficile de le savoir à l’avance

by @Genferei Samedi, nous avons beaucoup parlé de stigmatisation et de discrimation.

L’OHCR vient de mettre en garde : un virus qui exacerbe la xénophobie, la haine et l’exclusion
https://www.ohchr.org/EN/NewsEvents/Pages/DisplayNews.aspx?NewsID=25757&LangID=E

I was also thinking about some useful references to continue developing the project:
|Social Physics: How Social Networks Can Make Us Smarter
|Author(s):|Alex Pentland|

an article very well-known to look more at the consequences for data privacy and accuracy of methods:

Detecting influenza epidemics using search engine query data

https://www.nature.com/articles/nature07634

@paulolivier suggested including two dimensions for modeling: self-segmentation online (this person is in this facebook group) and the dis-belief in science/medicine (like vaccines)

Georg Simmel to revive avec his notion of social distance!

Infectious SocioPatterns Poster Feb 16, 2011 made with big data to get some inspiration http://www.sociopatterns.org/gallery/infectious-sociopatterns-poster/

How to analyse micro and macro levels of social factors and virus characteristics?
here is an idea from the #metoo case http://metoomentum.com/trending.html
one big challenge to keep in mind, how to say something from that? we can’t stay only in describing and visualizing!

article very very interesting shared by @milesf:

Harvard Business Review – 27 Mar 20

Lessons from Italy’s Response to Coronavirus

Policymakers around the world can avoid making the same mistakes while there’s still time.

we are going in the right direction! learning, sharing knowledge and helping the, I quote: shift urgently needed from patient-centered models of care to a community-system approach that offers pandemic solutions for the entire population (with a specific emphasis on home care).

in addition, here is the scientific paper just published:
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3564800

BeyondR0: the importance of contact tracing when predicting epidemics

[10:05, 03.04.2020] Paul Olivier: it’s mathematical, but it says R0 is a critical error made by epidemiologists in understanding (and presumably fighting) the disease

[10:06, 03.04.2020] Paul Olivier: what this says is that it is only the first order in a series of parameters influenced by many factors (including social structure)

[10:07, 03.04.2020] Paul Olivier: they show for instance that secondary infections are important as well

See here.

  • Right now we have a widespread outbreak and an overloaded healthcare system, so we want to reduce the spread of the virus as soon as possible to an acceptable level.

— but what is R0 ?—

  • R0 is the ‘reproduction factor’ it indicates on a macro level how many new people are contaminated by one contaminated person. When R0 is bigger then one, the virus spreads exponentially, when R0 is less then one, the virus can still be present, but the spread slowly decreases. So saying R0 < 1 is virological lingo for saying ‘keeping the virus in check’

—--------------------

  • A lockdown reduces R0 to something like 0.3, resulting in a rapid decrease of the virus (what becomes visible after appr. 2 weeks because testing, getting ill, hospital admissions and death rates lag 2-4 weeks behind).

  • Once the spread of the virus is at a level that can be handled by the healthcare system and the society, then you want to have a R0 of 1 or just a little less. To avoid a new outbreak but to minimize damage to society by avoiding overreaction.

  • So the timeframe is important too: this is not about the suppression we are doing right now but about the 6-12 month after the lockdown. It is not an alternative for a lockdown.

Articles in french: analysis of current technological solutions to the pandemic from the perspective of Sciences and Technology Studies (STS) and the sociology of quantification (Desrosières)
read 4 chapters:
https://linc.cnil.fr/fr/coronoptiques-14-dispositifs-de-surveillance-et-gestion-de-lepidemie

short press article the author above mentions, Foucault à Wuhan:
https://www.philomag.com/lactu/resonances/surveiller-et-contenir-foucault-a-wuhan-42463
besides surveillance and punition, it is relevant to see the exclusion in a certain form of anonymization, what a paradox we seek now to anonymize personal and sensitive data and de-anonymize infected people to “save” them and others

technologies not capturing social context:

massive tests of immunity in a German city, they hypothesize a causality effect between the carnival and rapid spread but not sure how this link is confirmed if there is no follow up from the people that were in the carnival, their contacts with others in soecific locations with different densities

in english another paper:

A phased lift of control: a practical strategy to achieve herd immunity against Covid-19 at the country level

A phased lift of control: a practical strategy to achieve herd immunity against Covid-19at the country level
math modelling, stochastic individual-based model, heterogeneity is based on contact rate