Disease alerts and forecasting of zoonotic diseases: an overview

Abstract

Epidemiologists are adopting new techniques by the use of Geographical Information System (GIS) to study a variety ofanimal and zoonotic diseases. Associations between satellite-derived environmental variables such as temperature, humidity,land cover type and vector density is used for disease prediction. Early warning systems rapidly detect the introduction orsudden increase in incidence of any disease of livestock which has the potential to develop into epidemic proportions and/orcause serious socioeconomic consequences or public health concerns. Early warning activities, mainly based on diseasesurveillance, reporting, and epidemiological analysis, are supported by information systems that enable integration, analysisand sharing of animal health data combined with relevant layers of information such as socioeconomic, production andclimatic data. The convergence of factors such as the availability of multi-temporal satellite data and georeferencedepidemiological data, collaboration between scientists, biologists and the availability of sophisticated, statistical GIS creates afertile research environment. In this paper, we review the Global Early Warning System (GLEWS) that formally bringstogether human and veterinary public health systems and application of environmental data for study of diseases like avianinfluenza and Rift valley fever which offers the capability to demonstrate vector-environment relationships and potentiallyforecast the risk of disease outbreaks or epidemics. An emphasis is also given on components of early warning system and itsuse for forecasting of animal and zoonotic diseases in India.

Keywords

• FAO
• forecasting
• global early warning system
• geographical information system
• OIE
• WHO.