Homeland

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University of Pennsylvania Institute for
Strategic Threat Analysis and Response (ISTAR)
Climate
Information Networks
Geopolitics
Homeland defense
Geographic data
Infectious diseases
Remote sensors
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• Contents
• Foreword Don de Savigny, Luc Loslier, and Jim
  Chauvin
• Preface Don de Savigny, Lori Jones-Arsenault,
  and Pandu Wijeyaratne
• Context
• The present state of GIS and future trends
  Steven Reader
• GIS from a health perspective Luc Loslier
• Spatial and temporal analysis of epidemiological
  data Flavio Fonseca Nobre and Marilia Sa
  Carvalho
• Case studies from the South
• Towards a rural information system David le
  Sueur, Sipho Ngxongo, Maria Stuttaford, Brian
  Sharp, Rajendra Maharaj, Carrin Martin, and Dawn
  Brown
• A GIS approach to the determination of catchment
  populations around Local Health Facilities in
  Developing Countries H.M. Oranga
• GIS management tools for the control of tropical
  diseases applications in Botswana, Senegal, and
  Morocco Isabelle Nuttall, D.W. Rumisha, T.R.K.
  Pilatwe, H.I. Ali, S.S. Mokgweetsinyana, A.H.
  Sylla, and I. Talla
• The use of low-cost remote sensing and GIS for
  identifying and monitoring the environmental
  factors associated with vector-borne disease
  transmission S.J. Connor, M.C. Thompson, S.
  Flasse, and J.B. Williams
• GIS for the study and control of malaria
  Gustavo Bretas
• Spatial analysis of malaria risk in an endemic
  region of Sri Lanka D.M. Gunawardena, Lal
  Muthuwattac, S. Weerasingha, J. Rajakaruna,
  Wasantha Udaya Kumara, Tilak Senanayaka, P. Kumar
  Kotta, A.R. Wickremasinghe, Richard Carter, and
  Kamini N. Mendis
• Diagnostic features of malaria transmission in
  Nadiad using remote sensing and GIS M.S.
  Malhotra and Aruna Srivastava
• Monitoring zoonotic cutaneous leishmaniasis with
  GIS L. Mbarki, A. Ben Salah, S. Chlif, M.K.
  Chahed, A. Balma, N. Chemam, A. Garraoui, and R.
  Ben-Ismail
• Use of RAISON for rural drinking water sources
  management C.W. Wang

http//www.idrc.ca/acb/showdetl.cfm?DID6Product
_ID495CATID15
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Climate and Satellite Indicators to Forecast Rift
Valley Fever Epidemics in Kenya Kenneth J.
Linthicum, 1 Assaf Anyamba, 2 Compton J.
Tucker, 2 Patrick W. Kelley, 1 Monica F. Myers, 2
Clarence J. Peters 3
The best fit to the RVF outbreak data was
achieved when equatorial Pacific and Indian Ocean
SST and NDVI anomaly data were used
together. These data could have been used to
successfully predict each of the three RVF
outbreaks that occurred between 1982 and
1998 without predicting any false RVF events for
an overall prediction of risk of 100.
Predictive models that use either SOI and Indian
Ocean or NDVI and Indian Ocean anomaly data would
have predicted all three RVF events but falsely
predicted either one or two disease events,
respectively.
Science. 1999 Jul 16285(5426)397-400.
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The Sverdlovsk Anthrax Outbreak
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New initiatives Global and local
syndromic surveillancehuman and animal Genomic
characterization of species and strains of
organisms Global and local micro-organism
surveillance Distributed sensors Massively
networked information systems Education
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Research/Education Agenda Dynamic
Integration and Analysis of Data
Sets Data Geographic Syndromic
Microorganisms Climate Political
alignmentsstate and non-state Technology--theor
y Sensorshybrid systems Network
communicationartificial intelligence Securityau
thentication, privacy Conflictasymmetric,
multi-agent game theory Education (K-12) underg
raduates graduate and professional
students practitioners Policy
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