WEBVTT

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[MUSIC PLAYING]

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SVEA CLOSSER: So in addition
to going door to door

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doing vaccination campaigns,
polio eradication also does

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a lot of work for
social mobilization,

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or promoting the
use of polio vaccine

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through a variety
of different means.

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They collect a lot
of data to understand

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how well this social
mobilization is working.

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So there's a number of different
sources of social mobilization

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data.

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There's data collected
from surveys,

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there's data collected from the
social mobilizers themselves,

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there may be information
collected through the AFP

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system, and there's
information collected

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on reasons for refusals
as part of campaigns.

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So all of these
different data sources

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are used to understand how well
social mobilization is working.

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Here's an example
from Pakistan in 2013.

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This is a bar graph that
shows the reasons for refusal

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in different
provinces of Pakistan.

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Take a minute and
look at this as you

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can see the different
colors in the bar graph

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represent different
reasons for refusal,

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whether religious misconception
about the vaccine, frustration

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over repeated campaigns,
demand refusals--

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these are cases when communities
refuse polio vaccine not

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because they have any
concern about polio vaccine

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but as a way to get the
government to give them

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something else that they want.

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So take a minute and
look at this graph

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and think about how
this might affect how

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you would deal with refusals.

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Also think about what this
graph doesn't tell you.

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Looking at some of the areas
with the most refusals,

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KP and what on this graph
is labeled BLN, which

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is the province of
Baluchistan, you

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see that each one
of those places

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has around 5,000 parents
that are refusing vaccine

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because of hear what's
labeled as religious.

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So in some ways this
information is really useful.

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Addressing those
refusals is probably

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going to require working
through religious leaders.

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On the other hand, there's
a lot of this information

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doesn't tell you.

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We have no idea what
anyone in this group's

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religious objection might
be to polio vaccine.

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For the most part, most
religious leaders in Pakistan

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endorse it.

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So it doesn't really tell us
anything about specifically

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why these people are
actually refusing.

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Religious is a pretty
broad category.

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So in some ways, this
information is very helpful.

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In some ways, it just
raises more questions.

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The same is true
of demand refusals.

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You can see in FATA,
there's almost 1,000 parents

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refusing because
of demand refusals.

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They want something
from the government,

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and they refusing polio
vaccine as leverage.

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They think that if they
refuse polio vaccine

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the government will give
them what they want.

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This is interesting
but we don't know

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with these 980
exactly what they're

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demanding, what the political
situation is around it.

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So in some ways, that
is incredibly useful,

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in some ways, there's
a lot we don't know.

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Here's another example
of a data source

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that could be used for
social mobilization.

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This one actually comes from
post-campaign monitoring.

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This means after the
campaign, someone

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went door to door seeing how
many children were covered

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and recording the reasons
why the child didn't

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get vaccinated.

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So what we have here is a
bar graph showing each month

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there's a different
campaign and the reasons

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that children were missed in all
of those different campaigns.

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What we can see here is the
most common reason that children

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are missed is that they
were not available.

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This means they weren't
home when the team came by.

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It also means the team didn't
come back to cover them.

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So this is a
programmatic failure.

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The brown pieces of this,
which are another big piece,

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means the team
didn't visit at all.

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That's another
programmatic failure.

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You can see the orange,
which is refusals,

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is a relatively tiny
slice of the children who

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are missed every round.

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So dealing with refusals,
while important,

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might be less important in
this particular scenario

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than improving the
programmatic performance

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of your own vaccination teams.

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This kind of information
is really important

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to think about.

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All the work you do on
refusals while useful is only

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going to cover a
small percentage

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of the overall children missed.

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So sometimes this question
of what most children entail

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can be a little complicated.

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And we touched on this before.

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But the kinds of
data you collect

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might change your
interpretation of those data.

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So I'm going to use this example
that we mentioned briefly

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before of
under-vaccinated children

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in the early 2000s
in North India.

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And for a while in the
early 2000s, in both India

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and Nigeria, under
vaccinated children

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were predominantly from
Muslim communities.

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So people started talking
about, well, maybe there's

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this link between
Islam and resistance.

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And the programmatic
response was

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to focus on communication
interventions

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around providing
accurate information

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and correcting
misunderstandings.

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But this changed as the
program got better data.

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So in 2004 in Nigeria, in
one area of Nigeria, Kano,

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almost 3/4 of the kids that
were recorded as missed

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were recorded as
religious objections.

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But when new categories for
the reasons that kids weren't

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vaccinated were added
in 2006 and 2007,

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this went from 75%
down to like 10%.

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So it turned out that
Islam or being Muslim

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wasn't really the risk factor.

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It was just that there
weren't enough categories,

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so Islam was getting selected
as sort of a catch-all.

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So asking the right questions
is really, really important.

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Otherwise, the data you
collect can lead you astray.

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And a similar thing
happened in India.

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Monitoring forms for most
children in the early 2000s

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didn't ask enough
questions to be

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able to really drill
down on why children

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might have been missed.

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So social mobilization
data is really important.

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If you want to encourage parents
to vaccinate their children,

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it's really important
to understand

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what their possible
objections are

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or why they might
not be vaccinating.

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At the same time, collecting
this data through a survey

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can be really difficult,
because the kinds of categories

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that you have may not adequately
reflect people's experience.

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And as an example from
Pakistan, sometimes a category

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like religion or demand
refusal doesn't give you

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quite enough information to
design a good intervention.

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Sometimes in addition to
some of the survey data,

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you have to actually
go talk to people.

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