Social technologies for community response to epidemics

paraderollAI and Robotics

Nov 17, 2013 (3 years and 8 months ago)

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S
ocial technologies for community
response to epidemics

Chris Watkins

Department of Computer Science

Royal Holloway, University of London




The effect of public health measures on the 1918
influenza pandemic in US cities


M
Bootsma

and N Ferguson, PNAS 2007


Public health interventions and epidemic intensity
during the 1918 influenza pandemic


R
Hatchett
, C
Mecher
, and M
Lipsitch
, PNAS 2007



US cities that implemented NPIs in 1918 had lower
mortality rates than those cities that did not.


NPI: non
-
pharmaceutical intervention, such as



closing schools



banning large public gatherings



isolation of the sick



...

Could we implement more effective public
health measures than in 1918?


How much could we reduce the intensity of
a severe pandemic by enabling people not
to catch it?


What social technologies are available?

On
-
line social networking



Localisation and tracking



Voted discussion systems



Distributed community support

On
-
line social networking

Facebook
, but changing rapidly


Localisation and tracking

Smartphones
, using
wifi

signal strength

Our digital footprints


Voted discussion systems

Reddit
, Yahoo answers, MOOCs


Distributed community support

Protocols for local coordination and
discussion ???

Pandemics: mild and severe

Case A: mild

Probable in next 20 years

Health service emergency:
daily life as usual


People unwilling to change
behaviour much


Ordinary public health
measures


Case B: severe

Possible

Societal emergency: supply
-
chain disruption?


People willing to change
behaviour given tools and a
plan

Extraordinary measures?

Pandemics: mild and severe

Case A: mild

Realistic to assume
exponential growth and
uncontrolled spread


Realistic policy aim is
mitigation


Travel restrictions futile


Case B: severe

Fatalistic to assume exponential
growth and uncontrolled
spread


Policy aim could be suppression /
sub
-
exponential growth


If aim is to contain local
outbreaks, travel restrictions
justified.

Is there a plan for case B?

Changing community behaviour

Goals worth
achieving

Communicate a
plan

Provide
information
and tools

Open
discussion

The People

Changing community behaviour

Goals worth
achieving

Communicate a
plan

Provide
information
and tools

Open
discussion

The People

A computer scientist’s reaction:

What?! 1.4 < R
0

< 2.5 !?


That’s incredibly valuable information.


So all we have to do to contain an epidemic
is to ensure that each person who gets sick
infects one person fewer!

On
-
line social networking


Less than 10 years old


Social graph: database of posts, pictures, links
connecting people with unique ids.



Who do we really meet?
Facebook

knows.


Co
-
tagging in photographs; auto face recognition


Locations of home and work known.


Rich local network => contact network?




On
-
line networking: research
questions

Does the spread of infectious disease correlate with
the contact network inferred from
Facebook
?

If so:


-

emerging disease surveillance


-

information on personal infection risk


-

social distancing: when should I stay in?


-

can social conventions be altered so that people

post updates of their health?


Localisation and trail recording

Smartphones
:


-

have their position recorded by network



approx 100 metres


-

could run an app that repeatedly records

pattern of
wifi

signal strengths.



Localisation within buildings, to a single

room or
within a few metres.


-

Trails of locations recorded in encrypted form

and
uploaded for encounter analysis.

Digital footprints
:


-

Payment cards, travel cards.


-

Correlation of multiple evidence of movement and activity

Research questions

Could localisation and trail recording be viably
used for



-

real
-
time epidemiology?



-

automatic contact tracing?


How close to a complete real
-
time picture of an
epidemic could we get with current
technology?



Voted Discussion Systems

Mostly less than 10 years old

Reddit
: as many visitors as New York Times.

Slashdot, Yahoo answers,
Quora
, (
Digg
), (
Stumbleupon
), and many more.

MOOCs are newest and most sophisticated: rapid development !



Searchable discussion threads on many topics


Individual comments get voted up or down


System estimates which posts will be up
-
voted: avoids ‘first post’ problem


Users accumulate individual ‘karma’ score


Effects are:


Posts that are angry, stupid, badly written, crazy, ignorant, or impolite get voted
down out of sight.


Everyone wants to be
upvoted
: huge incentive to


to write well and thoughtfully,


to obey community standards


f
or relevant and courteous discussion



Questions

To what extent can communications technology
enable people to collectively avoid infection?


What information can be generated ?


How can this information best be used?