Epidemic

COSMO-SkyMed/SAR imagery (ESA)

Data Type: 

satdata

Costs: 

rfree
English

Spatial Coverage: 

Global

Temporal Coverage: 

arch

Data accessibility: 

exportdata

File types: 

GeoTIFF
HDF5
JPEGJPG
TIFF

Disaster Cycle Phase: 

drm
rr

Spatial Resolution: 

1.00

Requirements: 

<p>Submission of Project Proposal is required for Restrained Datasets</p>

Restrictions / Citation of the dataset: 

Satellites and Sensors: 

Remote Sensing and Geographic Information Systems and Risk of American Visceral Leishmaniasis in Bahia, Brazil

 

External Contact Person: 

Bavia, M.E.

Email: 

newmeb2004 [at] yahoo.com.br
English

Bibliographic reference: 

Bavia, M.E. et al. (2005): Remote Sensing and Geographic Information Systems and Risk of American Visceral Leishmaniasis in Bahia, Brazil. Parassitologia, Vol. 47, 165-169.

Rift Valley Fever in a Zone Potentially Occupied by Aedes Vexans in Senegal: Dynamics and Risk Mapping

 

External Contact Person: 

Cécile Vignolles

Email: 

cecile.vignolles [at] cnes.fr
English

Bibliographic reference: 

Vignolles, C. et al. (2009): Rift Valley Fever in a Zone Potentially Occupied by Aedes Vexans in Senegal: Dynamics and Risk Mapping. Geospatial Health, Vol. 3, No. 2, 211-220.

Early Prediction of Malaria in Forest Hills of Bangladesh Using AVHRR Based Satellite Data

 

External Contact Person: 

Mohammad Nizamuddin

Email: 

nizam89 [at] gmail.com
English

Bibliographic reference: 

Nizamuddin, M. et al. (2009): Early Prediction of Malaria in Forest Hills of Bangladesh Using AVHRR Based Satellite Data. 16th Conference on Satellite Meteorology and Oceanography, Phoenix, AZ, January 11-15, 2009.

Satellite Imagery Characterizes Local Animal Reservoir Populations of Sin Nombre Virus in the Southwestern United States

 

External Contact Person: 

Gregory E. Glass

Email: 

gglass [at] jhsph.edu
English

Bibliographic reference: 

Glass, G.E. et al. (2002): Satellite Imagery Characterizes Local Animal Reservoir Populations of Sin Nombre Virus in the Southwestern United States. Proceedings of the National Academy of Sciences of the United States of America, Vol. 99, No. 26, 16817-16822.

Early detection of tick-borne encephalitis virus spatial distribution and activity in the province of Trento, northern Italy

 

External Contact Person: 

Rizzoli A.

Email: 

rizzoli [at] cealp.it
English

Bibliographic reference: 

Rizzoli, A. et al. (2007): Early Detection of Tick-Borne Encephalitis Virus Spatial Distribution and Activity in the Province of Trento, Northern Italy. Geospatial Health, Vol. 2, 169-176.

Predicting the distribution of tsetse flies in West Africa using temporal Fourier processed meteorological satellite data.

 

External Contact Person: 

Rogers, D.J.

Email: 

david.rogers [at] zoo.ox.ac.uk
English

Bibliographic reference: 

Rogers, D.J. et al. (1996): Predicting the Distribution of Tsetse Flies in West Africa Using Temporal Fourier Processed Meteorological Satellite Data. Annals of Tropical Medicine and Parasitology, Vol. 90, No. 3, 225-241.

Remote Sensing and Climate Data as a Key for Understanding Fasciolosis Transmission in the Andes: Review and Update of an Ongoing Interdisciplinary Project

 

External Contact Person: 

Mario V. Fuentes

Email: 

mario.v.fuentes [at] uv.es
English

Bibliographic reference: 

Fuentes, M.V. (2006): Remote Sensing and Climate Data as a Key for Understanding Fasciolosis Transmission in the Andes: Review and Update of an Ongoing Interdisciplinary Project. Geospatial Health, Vol. 1, 59-70.

Upscale or downscale: applications of fine scale remotely sensed data to Chagas disease in Argentina and schistosomiasis in Kenya

 

External Contact Person: 

Kitron, U.

Email: 

ukitron [at] uiuc.edu
English

Bibliographic reference: 

Kitron, U. et al. (2006): Upscale or Downscale: Applications of Fine Scale Remotely Sensed Data to Chagas Disease in Argentina and Schistosomiasis in Kenya. Geospatial Health, Vol. 1, 49-58.

Geographical Information System (GIS) in Decision Support to Control Malaria - A Case Study of Koraput District in Orissa, India

Vector-borne diseases such as malaria cause tremendous public health burden globally. Malaria is endemic in >100 countries and ~40% of the world’s population is at malaria risk. Malaria is a local and focal disease. Besides ecological parameters which influence the disease there are some important local factors such as socioeconomic, socio-cultural and behaviour patterns of the community which play a major role in disease transmission.

External Contact Person: 

Annjaan Daash

Email: 

b_n_nagpal [at] hotmail.com
English

Bibliographic reference: 

Daash, A. et al. (2009): Geographical Information System (GIS) in Decision Support to Control Malaria - A Case Study of Koraput District in Orissa, India. Journal of Vector Borne Diseases, Vol. 46, 72-74.

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