Using remote sensing to predict outbreaks of Oestrus ovis in Namibia

Flasse, S.; Walker, Chelsea; Biggs, Harry; Stephenson, P.J.; Hutchinson, P. B.

doi:10.1016/s0167-5877(97)00056-1

Cited by 9 publications

(1 citation statement)

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“…It develops at shallow depths in the soil and the timing of its emergence is directly dependent on the number of degree days, i.e. the summed product of soil temperatures above a developmental threshold and the time over which they apply (Flasse et al , 1998). Meteosat satellite sensor imagery provides accumulated soil temperature information to identify trigger conditions conducive to outbreaks and provides a broader warning capability than ground surveillance alone.…”

Section: Types Of Early Warning Systemmentioning

confidence: 99%

Forecasting disease risk for increased epidemic preparedness in public health

Myers

Rogers

Cox

et al. 2000

Advances in Parasitology

111

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Emerging infectious diseases pose a growing threat to human populations. Many of the world's epidemic diseases (particularly those transmitted by intermediate hosts) are known to be highly sensitive to long-term changes in climate and short-term fluctuations in the weather. The application of environmental data to the study of disease offers the capability to demonstrate vector-environment relationships and potentially forecast the risk of disease outbreaks or epidemics. Accurate disease forecasting models would markedly improve epidemic prevention and control capabilities. This chapter examines the potential for epidemic forecasting and discusses the issues associated with the development of global networks for surveillance and prediction. Existing global systems for epidemic preparedness focus on disease surveillance using either expert knowledge or statistical modelling of disease activity and thresholds to identify times and areas of risk. Predictive health information systems would use monitored environmental variables, linked to a disease system, to be observed and provide prior information of outbreaks. The components and varieties of forecasting systems are discussed with selected examples, along with issues relating to further development.

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Section: Types Of Early Warning Systemmentioning

confidence: 99%