Filling the Ark: Animal Welfare in Disasters

(Darren Dugan) #1

120 / Conclusion


Three R’s, which is intended to reduce the numbers of animals used
in research. The National Institutes of Health (NIH) should with-
hold funding from facilities built in high-risk areas, such as fl ood
plains and fault lines. As I mention in Chapter 4, animal advocates
have pressured the NIH to withhold funds in the past, and the orga-
nization has ignored them or responded that it does not have the
capacity to take such action. Although the bureaucratic complexi-
ties of the NIH’s authority are beyond the scope of my investiga-
tion, it would seem that if the agency can grant funding it could
also withhold funding. Buying more animals to live in fl ood-prone
basements seems a misguided use of taxpayer dollars.
Some research facilities, such as the University of Texas, have
learned through sad experience that however carefully conceived,
disaster plans do not always hold up. Flooding can prevent staff
members from reaching a facility and caring for animals. An ill-
placed generator can fail. Or, as in the case of Hurricane Andrew,
“concerned” citizens can take matters into their own hands and kill
animals released by the event. The best and fi nal recommendation
I can make applies not only to disasters in research labs but to all
kinds of disasters.


“We Never Imagined”


Each chapter of this book underscores our inability to envision
“worst case” scenarios. In every disaster I studied, the accounts of
the event incorporated some version of “we never imagined this
would happen.” Sometimes it took the form of “we never expected
it would be this bad.” Meanwhile, every disaster planning event I
have attended and all the literature I have read sends a message to
“expect the unexpected.” Clearly, there are obstacles to doing so. The
work of Karen Cerulo offers some insights into what these might
be.^11 According to Cerulo, we tend to focus on the best to the exclu-
sion of fl aws and defi ciencies. She calls this bias “positive asymme-
try.” For example, when Cerulo polled her students, she found that
they quickly and easily described the best things that could happen
to them, but when asked to imagine the worst, they came up with

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