Most of the data used in this analysis originate from the large humanitarian catastrophes
in Sudan, Somalia, DRC and Ethiopia in the mid- and late 2000s and this limits the
generalisability of our findings. Although we expect similar mortality pattern in
the ongoing crises in Syria, Iraq, Gaza and other places in the world, there are only
few recent data in CEDAT available yet. While data sharing among humanitarian agencies
has improved, it usually takes at least about one or two years for survey results
to be disseminated and available to the public.
Our analysis is at risk of bias at two levels: at the individual survey level and
at the meta-analysis level. At the individual survey level, there is for instance
the risk of recall or survival biases. These biases are discussed in detail by Checchi
and Roberts 12] and can lead to either overestimation or underestimation of mortality rates. Our
conclusions are based on the assumption that any biases at survey level are not systematic,
that is in some surveys true mortality rates are overestimated and in others true
mortality rates are underestimated, but the reasons are not related to the displacement
status of the population.
The more crucial assumption underlying our conclusions is that there is no bias at
the meta-analysis level, in particular that the surveys in our analysis can be considered
a representative sample of eligible surveys and that there is no selection bias.
There is no official register for emergency needs assessments, such as they exist
for instance for clinical studies, and it is therefore difficult to determine the
share of potentially eligible surveys that are not included in CEDAT and therefore
missing in our analysis. To our best knowledge, the main reason that potentially eligible
surveys are not included in CEDAT and therefore missing in our analysis is that these
surveys are conducted by organizations not collaborating with CEDAT (a list of organizations
that work with CEDAT can be found here: http://cedat.be/partners). CEDAT partner organizations represent a wide range of humanitarian agencies and
we have no reason to believe that whether or not an organization is collaborating
with CEDAT is associated with the level of mortality among their beneficiaries or
the DDR.
Some surveys might be missing even though there is an agreement to collaborate with
CEDAT: for instance, contacts in collaborating organizations might change, organizations
might forget to submit surveys, or some survey reports might never be finalized and
so on. These reasons for missingness limit the statistical power of our analysis but
do not necessarily introduce a bias. However, a bias might be introduced if any given
survey’s likelihood of inclusion in CEDAT (and consequently in our analysis) depends
on the mortality rate. For instance: most of the studies in CEDAT are needs assessments
and it might be reasonable to assume that if the assessment finds high mortality rates
(high needs), humanitarian agencies have a particular interest in disseminating the
results to attract more funds for their relief operations. If this was true, we would
overestimate mortality in IDPs, refugees and residents in complex emergencies. However,
we believe that the risk associated to this bias is fairly low: mortality surveys
are quite expensive and organizations will be held accountable by their donors to
deliver and disseminate results. Moreover, even if we overestimated mortality rates,
there is no reason to believe that the size of this bias differs between IDPs, refugees
and residents and therefore the bias would not impact our conclusions with regard
to the relative pattern of excess mortality between these population groups.
This analysis would also be biased if agencies were more likely to conduct mortality
surveys in particular locations and time periods, for instance, where they expect
mortality to be high in order to attract more relief funds. From our experience, this
bias is not very likely because small-scale surveys in CEDAT are routinely done at
all stages (assessment, monitoring and evaluation) of relief operations. If an agency’s
intention was to document high levels of mortality for advocacy purposes, a small-scale
survey would probably not be the first choice. As useful as these surveys can be in
a meta-analysis of mortality, individually they are quite limited in scope and detail,
as mortality is just one of many health indicators being assessed. Even if we cannot,
of course, completely exclude the possibility of such a bias, we believe that as in
the case of missing surveys, it would probably affect surveys from IDPs, residents
and refugees in the same way.
Despite improvements in quality of publicly accessible and comparable health data
from humanitarian emergencies, for many of the estimates we still lack sufficient
information needed to perform more robust meta-regressions, such as sample sizes,
design effects for cluster samples, numbers of deaths (instead of aggregated rates),
length of individual recall periods and more precise information on the study area/population.
The surveys were categorised into IDP, refugee, resident and mixed populations by
the aid agencies that have conducted the original research. We were not able to validate
the quality and consistency of this categorisation. Also, we had to exclude mixed
populations from the analysis as we do not have sufficient information on mixing proportions.
Most importantly, this is an observational study and we only show that differences
in excess mortality are associated with population status. We do not show causality.
For instance, in CEDAT, excess mortality generally appears to be lower in surveys
on refugees than in surveys on IDPs, but we cannot say with certainty whether this
is due to the fact that they are refugees and not IDPs. Possibly, some confounding
factor, influencing both mortality and displacement status, might explain this association.
From the (admittedly few) countries that we were able to include in our sensitivity
analysis, it seems though that at least the country where the survey takes place is
unlikely to be such a confounder.
There is a high degree of variability in death rates between individual surveys in
all three population groups. Further research is needed to explain this variability:
What part of it can be explained by sampling error? What other factors play a role?
Above limitations notwithstanding, we believe this analysis provides evidence of substantial
excess mortality in humanitarian emergencies and that displacement status of affected
population is an important determinant of this excess mortality. When compared to
baseline data, aid agencies report the highest death rates among IDPs, with observed
deaths rates more than twice the baseline, followed by death rates in resident populations.
Strikingly, we do not observe any significant excess mortality when comparing refugee
death rates to the death rates in their host communities. This could be due to limitations
in our analysis: Refugee populations might be healthier and/or younger than host populations
– possibly due to some kind of healthy migrant effect – but we are unable to control
for this as we do not have access to age standardized data and baseline data.
However, if there is indeed no significant excess mortality in refugees, this might
show that aid agencies can successfully prevent mortality if they have access to affected
populations and sufficient resources. Being protected by the UNHCR and at least geographically
separated from the origin of the emergency, refugees can arguably be more easily assisted
by aid agencies. They generally benefit from better access to food, shelter and health
services than IDPs or resident populations, who are much more difficult to be identified
and reached 2].
We believe that there is a need to improve the collection of standardized epidemiological
data on all people affected by complex humanitarian emergencies, particularly on hard-to-reach
populations such as IDPs and affected residents. Our estimates suggest that an enormous
number of lives could be saved if mortality could be brought down to baseline levels
in IDP and resident populations. Although IDPs have a higher death rate ratio, the
potential benefit in terms of the absolute number of lives saved is possibly greater
in resident populations which outnumber IDPs by far.