How Many
Iraqis Have Died Since the US Invasion in 2003?
30,000? No. 100,000? No.
By ANDREW COCKBURN
01/09/06 "Counterpunch"
-- -- President Bush's off-hand summation last month of the
number of Iraqis who have so far died as a result of our invasion
and occupation as "30,000, more or less" was quite certainly an
under-estimate. The true number is probably hitting around 180,000
by now, with a possibility, as we shall see, that it has reached as
high as half a million.
But even Bush's number was too much for his handlers to allow.
Almost as soon as he finished speaking, they hastened to downplay
the presidential figure as "unofficial", plucked by the commander in
chief from "public estimates". Such calculations have been
discouraged ever since the oafish General Tommy Franks infamously
announced at the time of the invasion: "We don't do body counts". In
December 2004, an effort by the Iraqi Ministry of Health to quantify
ongoing mortality on the basis of emergency room admissions was
halted by direct order of the occupying power.
In fact, the President may have been subconsciously quoting figures
published by iraqbodycount.org, a British group that diligently
tabulates published press reports of combat-related killings in
Iraq. Due to IBC's policy of posting minimum and maximum figures,
currently standing at 27787 and 31317, their numbers carry a
misleading air of scientific precision. As the group itself readily
concedes, the estimate must be incomplete, since it omits unreported
deaths.
There is however another and more reliable method for estimating
figures such as these: nationwide random sampling. No one doubts
that, if the sample is truly random, and the consequent data
correctly calculated, the sampled results reflect the national
figures within the states accuracy. That, after all, is how market
researchers assess public opinion on everything from politicians to
breakfast cereals. Epidemiologists use it to chart the impact of
epidemics. In 2000 an epidemiological team led by Les Roberts of
Johns Hopkins School of Public Health used random sampling to
calculate the death toll from combat and consequent disease and
starvation in the ongoing Congolese civil war at 1.7 million. This
figure prompted shocked headlines and immediate action by the UN
Security Council. No one questioned the methodology.
In September 2004, Roberts led a similar team that researched death
rates, using the same techniques, in Iraq before and after the 2003
invasion. Making "conservative assumptions" they concluded that
"about 100,000 excess deaths" (in fact 98,000) among men, women, and
children had occurred in just under eighteen months. Violent deaths
alone had soared twentyfold. But, as in most wars, the bulk of the
carnage was due to the indirect effects of the invasion, notably the
breakdown of the Iraqi health system. Thus, though many commentators
contrasted the iarqbodycount and Johns Hopkins figures, they are not
comparable. The bodycounters were simply recording, or at least
attempting to record, deaths from combat violence, while the medical
specialists were attempting something far more complete, an
accounting of the full death toll wrought by the devastation of the
US invasion and occupation.
Unlike the respectful applause granted the Congolese study, this
one, published in the prestigious British medical journal The
Lancet, generated a hail of abusive criticism. The general outrage
may have been prompted by the unsettling possibility that Iraq's
liberators had already killed a third as many Iraqis as the reported
300,000 murdered by Saddam Hussein in his decades of tyranny. Some
of the attacks were self-evidently absurd. British Prime Minister
Tony Blair's spokesman, for example, queried the survey because it
"appeared to be based on an extrapolation technique rather than a
detailed body count", as if Blair had never made a political
decision based on a poll. Others chose to compare apples with
oranges by mixing up nationwide Saddam-era government statistics
with individual cluster survey results in order to cast doubt on the
latter.
Some questioned whether the sample was distorted by unrepresentative
hot spots such as Fallujah. In fact, the amazingly dedicated and
courageous Iraqi doctors who actually gathered the data visited 33
"clusters" selected on an entirely random basis across the length
and breadth of Iraq. In each of these clusters the teams conducted
interviews in 30 households, again selected by rigorously random
means. As it happened, Fallujah was one of the clusters thrown up by
this process. Strictly speaking, the team should have included the
data from that embattled city in their final result - random is
random after all -- which would have given an overall post-invasion
excess death figure of no less than 268,000. Nevertheless, erring on
the side of caution, they eliminated Fallujah from their sample.
For such dedication to scholarly integrity, Roberts and his
colleagues had to endure the flatulent ignorance of Michael E.
O'Hanlon, sage of the Brookings Institute, who told the New York
Times that the self-evidently deficient Iraqbodycount estimate was
"certainly a more serious work than the Lancet report".
No point in the study attracted more confident assaults by ersatz
statisticians than the study's passing mention of a 95 per cent
"confidence interval" for the overall death toll of between 194,000
and 8,000. This did not mean, as asserted by commentators who ought
to have known better, that the true figure lay anywhere between
those numbers and that the 98,000 number was produced merely by
splitting the difference. In fact, the 98,000 figure represents the
best estimate drawn from the data. The high and low numbers
represented the spread, known to statisticians as "the confidence
interval", within which it is 95 per cent certain the true number
will be found. Had the published study (which was intensively peer
reviewed) cited the 80 per cent confidence interval also calculated
by the team - a statistically respectable option -- then the spread
would have been between 152,000 and 44,000.
Seeking further elucidation on the mathematical tools available to
reveal the hidden miseries of today's Iraq, I turned to
CounterPunch's consultant statistician, Pierre Sprey. He reviewed
not only the Iraq study as published in the Lancet, but also the raw
data collected in the household survey and kindly forwarded me by
Dr. Roberts.
"I have the highest respect for the rigor of the sampling
method used and the meticulous and courageous collection of the
data. I'm certainly not criticizing in any way Robert's data or
the importance of the results. But they could have saved
themselves a lot of trouble had they discarded the straitjacket
of Gaussian distribution in favor of a more practical
statistical approach", says Sprey. "As with all such studies,
the key question is that of 'scatter' i.e. the random spread in
data between each cluster sampled. So cluster A might have a
ratio of twice as many deaths after the invasion as before,
while cluster B might experience only two thirds as many. The
academically conventional approach is to assume that scatter
follows the bell shaped curve, otherwise known as 'normal
distribution,' popularized by Carl Gauss in the early 19th
century. This is a formula dictating that the most frequent
occurrence of data will be close to the mean, or center, and
that frequency of occurrence will fall off smoothly and
symmetrically as data scatters further and further from the mean
- following the curve of a bell shaped mountain as you move from
the center of the data.
"Generations of statisticians have had it beaten in to their
skulls that any data that scatters does so according to the iron
dictates of the bell shaped curve. The truth is that in no case
has a sizable body of naturally occurring data ever been proven
to follow the curve". (A $200,000 prize offered in the 1920s for
anyone who could provide rigorous evidence of a natural
occurrence of the curve remains unclaimed.)
"Slavish adherence to this formula obscures information of
great value. The true shape of the data scatter almost
invariably contains insights of great physical or, in this case
medical importance. In particular it very frequently grossly
exaggerates the true scatter of the data. Why? Simply because
the mathematics of making the data fit the bell curve inexorably
leads one to placing huge emphasis on isolated extreme
'outliers' of the data.
"For example if the average cluster had ten deaths and most
clusters had 8 to 12 deaths, but some had 0 or 20, the Gaussian
math would force you to weight the importance of those rare
points like 0 or 20 (i.e. 'outliers') by the square of their
distance from the center, or average. So a point at 20 would
have a weight of 100 (20 minus 10 squared) while a point of 11
would have a weight of 1 (11 minus 10 squared.)
"This approach has inherently pernicious effects. Suppose for
example one is studying survival rates of plant- destroying
spider mites, and the sampled population happens to be a mix of
a strain of very hardy mites and another strain that is quite
vulnerable to pesticides. Fanatical Gaussians will immediately
clamp the bell shaped curve onto the overall population of mites
being studied, thereby wiping out any evidence that this group
is in fact a mixture of two strains.
"The commonsensical amateur meanwhile would look at the
scatter of the data and see very quickly that instead of a
single "peak" in surviving mites, which would be the result if
the data were processed by traditional Gaussian rules, there are
instead two obvious peaks. He would promptly discern that he has
two different strains mixed together on his plants, a conclusion
of overwhelming importance for pesticide application".
(Sprey once conducted such a statistical study at Cornell - a bad
day for mites.)
So how to escape the Gaussian distortion?
"The answer lies in quite simple statistical techniques
called 'distribution free' or 'non parametric' methods. These
make the obviously more reasonable assumption that one hasn't
the foggiest notion of what the distribution of the data should
be, especially when considering data one hasn't seen -- before
one is prepared to let the data define its own distribution,
whatever that unusual shape may be, rather than forcing it into
the bell curve. The relatively simple computational methods used
in this approach basically treat each point as if it has the
same weight as any other, with the happy result that outliers
don't greatly exaggerate the scatter.
"So, applying that simple notion to the death rates before
and after the US invasion of Iraq, we find that the confidence
intervals around the estimated 100,000 "excess deaths" not only
shrink considerably but also that the numbers move significantly
higher. With a distribution-free approach, a 95 per cent
confidence interval thereby becomes 53,000 to 279,000. (Recall
that the Gaussian approach gave a 95 per cent confidence
interval of 8,000 to 194,000.) With an 80 per cent confidence
interval, the lower bound is 78,000 and the upper bound is
229,000. This shift to higher excess deaths occurs because the
real, as opposed to the Gaussian, distribution of the data is
heavily skewed to the high side of the distribution center".
Sprey's results make it clear that the most cautious estimate
possible for the Iraqi excess deaths caused by the US invasion is
far higher than the 8,000 figure imposed on the Johns Hopkins team
by the fascist bell curve. (The eugenicists of the 1920s were much
enamored of Gaussian methodology.) The upper bounds indicate a
reasonable possibility of much higher excess deaths than the 194,000
excess deaths (95 per cent confidence) offered in the study
published in the Lancet.
Of course the survey on which all these figures are based was
conducted fifteen months ago. Assuming the rate of death has
proceeded at the same pace since the study was carried out, Sprey
calculates that deaths inflicted to date as a direct result of the
Anglo-American invasion and occupation of Iraq could be, at best
estimate, 183,000, with an upper 95 per cent confidence boundary of
511,000.
Given the generally smug and heartless reaction accorded the
initial Lancet study, no such updated figure is likely to resonate
in public discourse, especially when it registers a dramatic
increase. Though the figures quoted by Bush were without a shadow of
a doubt a gross underestimate (he couldn't even be bothered to get
the number of dead American troops right) 30,000 dead among the
people we were allegedly coming to save is still an appalling
notion. The possibility that we have actually helped kill as many as
half a million people suggests a war crime of truly twentieth
century proportions.
In some countries, denying the fact of mass murder is considered
a felony offence, incurring harsh penalties. But then, it all
depends on who is being murdered, and by whom.
Andrew Cockburn is the co-author, with Patrick Cockburn,
of
Out of the Ashes: the Resurrection of Saddam Hussein.
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