Even within the UN and coordinated international humanitarian reporting mechanisms there
is inconsistency in the way different populations
are described and counted, with some estimates based on “people affected” and others
on “people in need” or “people targeted”.
Many terms and expressions are specific to
internal displacement, and our database captures
the most common ones (see table A.9). They may
refer to individuals, groups of people such as
families or households, or housing. We use the
number of houses destroyed as a proxy because
it shows that at least one household has been left
homeless. We calculate the number of individuals
by applying the AHHS available for each country.
Housing information
Housing information is important in estimating
displacement associated with disasters. To
produce our 2016 estimates, we analysed more
than 300 reports that mentioned housing
damage or destruction rather than the number of
people displaced. In order to use housing data as
a valid proxy, we only consider figures for homes
that have been damaged to the extent they are
no longer habitable.
Terms that indicate the extent of damage include
“houses at risk [of collapse]”, “houses severely
affected/damaged” and “houses destroyed”. We
consider housing to be any place where people
have established a habitual residence. We include
hospitals if the information provided suggests
that long-term patients have been displaced.
We also include shelters in refugee and displacement camps. “Collapsed tents” in Jordan’s Zaatari
refugee camp, for example, are counted as uninhabitable housing. Such cases constitute multiple
displacement, in which people have already fled
once, only to become displaced again when their
camp is flooded.
Evacuation data
We often use data on mandatory evacuations
and people staying in official evacuation centres
to estimate event-based displacement. This was
the case for 8.4 million of the new displacements
we reported on in 2016.
On the one hand, the number of people counted
in evacuation centres may underestimate the
108
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2017
total number of evacuees, as others may take
refuge elsewhere. On the other, the number of
people ordered to evacuate may overstate the
true number, given that some are likely not to
heed the order. The potential for such discrepancies is much greater when authorities advise
rather than order evacuation, and as a result we
do not incorporate such figures into our estimates.
Quality assurance and
independent peer review
As in previous years, and in order to improve
our methodology, we submitted this year’s estimates to a quality assurance process to verify the
data. The verification stage is as important as the
data collection itself, because it allows possible
discrepancies to be identified, and the data to be
refined before it is finalised. This year’s process
was mainly led in-house, and all of our entries
have been double-checked, through rigorous
analysis by experts previously not involved in
the data collection and analysis for each of the
events.
Colleagues were assigned each country with
displacement associated with conflict and disasters involving more than 500 people. They dug
through all the data collected and collated by
others, asking questions and highlighting potential gaps, and so ensuring the highest possible
level of transparency and clarity. As an example
of an entry having undergone changes following
the internal review process, reports of displacements associated with violence in India were
questioned, leading to a rigorous follow-up
process with existing and new sources. This
allowed us to solidify our data and present it
with a much higher level of confidence in its
accuracy and value.
Our data on the huge volumes of historical
displacement in Colombia also underwent
intense scrutiny, including exchanges with OCHA,
the government’s victims’ registry and NGOs. The
review unearthed previously unknown information on the primary source’s methodology and
data treatment processes, which led to significant
changes (see spotlight, p.29).
The quality assurance process for displacement associated with conflict was supported by
external advice. We presented our figures and
methodology to NRC country offices, IOM teams,
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