Many worldwide epidemic diseases (particularly those transitted by insects) are known to be highly sensitive to climate and weather, but causative realtionships between environmental factors and epidemic disease activity remain poorly understood. This workshop aims to provide updates about the potential for applying remotely sensed data to disease stratification, monitoring and surveillance, as well as its potential to support a predictive capabilty to determine and manage future epidemics.

The following speakers made presentations:

• Panel Chair: Compton J. Tucker, NASA Goddard Space Flight Center, Greenbelt, MD

  Forecasting Rift Valley Fever Epizootics/Epidemics in Kenya
  All known Rift Valley fever virus activity in East Africa from 1950 to May, 1998, is documented to have followed periods of abnormally high rainfall. A predictive model was developed, using a variety of climatological and meteorological parameters. The ability to forecast regional RVF virus activity in Kenya 2-5 months before outbreaks makes possible implementation of control strategies in time to lessen or prevent animal and human diseases. The archive for this talk was lost due to technical reasons, however details about this work are available.

• Simon Iain Hay, TALA Research Group, Dept. of Zoology, Oxford University, Oxford, UK

  Epidemic early warning: untangling intrinsic and extrinsic causes of dengue epidemics
  This talk discusses the issues associated with the development of biological and process--based modeling approaches to predict dengue hemorrhagic fever cases in Bangkok. Issues associated with implementation of a statistical approach will be covered. A statistical model is presented which predicts four months in advance, with an accuracy of c+/- 100 cases per month.

• William K.Reisen, Arbovirus Field Station, School of Veterinary Medicine, Center for Vector Borne Disease Research, University of California, Davis.

  The Use of Satellite-Generated Meteorological Data to Predict Mosquito-Borne Encephaltits Transmission: Preliminary Studies
  Every year mosquito-borne encephalitis virus are responsible for numerous cases of human illness in North America and throughout the world. This paper presents the initial findings from the California segment of a national study examining the environmental links to encephalitis epidemiology.

• Jonathan Cox, Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK

  Climate-Based Models For Predicting Malaria Transmission In Africa
  The MARA (Mapping Malaria Risk in Africa) collaboration has been exploring a number of ways to predict the risk of malaria transmission using relatively simple climate-based models. The emphasis to date has been on developing spatial models of risk. This paper describes the approach used in this exercise and in the subsequent validation of the spatial models. It also outlines plans, currently being designed in conjunction with a number of national malaria control programmes, to carry out prospective malaria surveillance in East Africa in order to evaluate a range of operational epidemic early warning strategies.

More information is available about the International Congress of Ecosystem Health, where these talks took place.

* The video quality on the webcast archive is poor. Often the slides are too detailed to be readable in RealMedia. The lighting wasn't adequate to capture a clear view of the speaker. So the real value of the archive resides mainly in the audio track.

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