Role of GIS in Epidemiology of infectious diseases
Geographic Information systems have emerged as an innovative, important component of public health and epidemiology. These system connects geographic locations with features of phenomenon viz., disease incidence, disease outbreaks, demographics in place and time. In our Institute, we are using R environment, ArcGIS, EpiInfo for creation of disease maps, resource maps and predicted risk maps. Risk maps are more useful for optimum allocation of resources such as man, material and money and also helpful to develop controls measures well in advance to control the infectious diseases. Satellite derived environmental variables viz., temperature, vegetative index, humidity and with other metrological variables, we are predicting the diseases two months in advances using ArcGIS and R- environment.
Spatial analysis and GIS
GIS applications show the powerful and potential system for addressing important veterinary health issues at the International, national and local levels. Spatial analysis capabilities allows users to examine and display health data in new and highly effective ways. Spatial relationships, those based on proximity and relative location , form the core of spatial analysis.,
a). Training on GIS using ArcGIS, R, QGIS
b). Disease Mapping
c). GIS Modelling
d). Risk Map Prediction
e). Remote Sensing Data Measurements
f). Grid Creation and Prediction
Role of Bioinformatics in Epidemiology of infectious diseases
There has been a tremendous focus in bioinformatics on translation of data from the bench into information and knowledge for public health decision-making. This involves data acquisition, integration, and analyses of molecular information to infer origin, spread, and evolution such as the emergence of new strains. The relevant scientific fields for this practice include certain aspects of molecular epidemiology and phytogeography. Recent attention has focused on viruses of zoonotic origin, which are defined as pathogens that are transmittable between animals and humans.
Current early warning systems detect large outbreaks but shows delays and low sensitivity in detecting moderate and small epidemics. It is also estimated that a one week delay in implementation of control measures will results in many fold increase in mean epidemic size and extension of mean epidemic duration. The Body of knowledge on the molecular profiles and epidemiology of pathogens stored in databases and molecular literatures is expanding and that the bio-informatics such as pathogen profiling can help to predict disease outbreak early and enable tailored interventions.
a). Phylogenetic / Phylogeographic Analysis
c). Homology Modelling
d). Molecular Docking
e). Sequence Similarity and Pattern
f). Gene Prediction
g). Secondary Structure Prediction
For further details contact - Dr.K.P.Suresh