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 of animal 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 or sudden increase in incidence of any disease of livestock which has the potential to develop into epidemic proportions and/or cause serious socioeconomic consequences or public health concerns. Early warning activities, mainly based on disease surveillance, reporting, and epidemiological analysis, are supported by information systems that enable integration, analysis and sharing of animal health data combined with relevant layers of information such as socioeconomic, production and climatic data. The convergence of factors such as the availability of multi-temporal satellite data and georeferenced epidemiological data, collaboration between scientists, biologists and the availability of sophisticated, statistical GIS creates a fertile research environment. In this paper, we review the Global Early Warning System (GLEWS) that formally brings together human and veterinary public health systems and application of environmental data for study of diseases like avian influenza and Rift valley fever which offers the capability to demonstrate vector-environment relationships and potentially forecast the risk of disease outbreaks or epidemics. An emphasis is also given on components of early warning system and its use for forecasting of animal and zoonotic diseases in India.