Geoscience Reference
In-Depth Information
2006
); Indochina Peninsula (Nihei et al.
2002
); continental Africa (Rogers et al.
2002
) and Korea (Ratana et al.
2005
).
Remote sensing applications for modeling and forecasting vector-borne diseases
are still an emerging field, but epidemiologists and biologists benefit from increasing
satellite coverage, a growing number of higher resolution sensors and the develop-
ment of hyperspectral imagery, combined with GIS and statistical software packages
that are available within an affordable desktop computing environment (Kalluri
et al.
2007
). However, besides these opportunities, epidemiologists face challenges:
Disease patterns are closely linked to poverty and social inequalities, which cannot
be inferred from remote sensing techniques alone. In addition, population growth
and climate change make the dynamics of disease spread more complex. In order
to develop accurate disease early-warning systems, it is necessary to find an effi-
cient way of incorporating the social component, to better understand transmission
dynamics (Rogers et al.
2002
) and to implement an automation of satellite data
processing, so that remotely sensed environmental variables will be processed and
made available to epidemiologists in near-real-time. This will ensure the generation
of vital information relevant to potential disease outbreaks and transmission (e.g.
near-real-time risk maps), thus enabling the initiation of rapid response strategies.
11.4 Cytometry for Life (C4L)
Vector-borne disease mitigation is not the only public health beneficiary of
space-based technologies, as evidenced by an initiative of the Purdue University
Cytometry Laboratory (PUCL), specifically Cytometry for Life (C4L), under the
leadership of Dr. J. Paul Robinson, Director, PUCL and Gary Gurack of i-Cyt,
Inc. The C4L initiative centers on the need for affordable, reliable, and manage-
able CD4 T-lymphocyte cell testing in Africa. The aim for the C4L initiative is to
create a low cost, low maintenance, portable CD4 Counter that will test, and only
test, the amount of CD4 T-lymphocyte cells in humans efficiently and accurately.
Many of the flow cytometers that are currently in use are large, expensive, require
trained technicians and numerous resources to operate and maintain them. The com-
ponents used to effectively accommodate bulky cytometers are scarce in most of
Africa, which translates into the majority of the HIV/AIDS infected population not
receiving critical testing that would result in antiretroviral treatment that would be
life-prolonging (Willyard
2007
; Robinson et al.
2007
).
The current model for CD4 testing in Africa for the past 7-8 years is to create
central labs that house expensive, mostly automated equipment, and train techni-
cians to operate the machines and its complex software. Samples are taken from
all over Africa to be tested in central labs and then sent back to the remote areas
from which the samples came. The patient must therefore spend a great deal of time
waiting, due to the lengthy process of receiving the results. This model is based on
the philosophy of Western health care systems, which rely on heavy infrastructure
