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Home Regions Health

GIS for epidemic control in India

M. Palaniyandi
Digital Mapping Laboratory, Vector Control Research Centre, (ICMR)
Pondicherry -India

In the recent past, dengue and chikungunya epidemics have been two major problems for the public healthcare system in India. They have killed hundreds of people in the past few years. Environmental determinants and manmade factors have never stopped be favourable to the Aedes aegypti, the mosquito responsible for the spread of these dreaded diseases. General public, administrative and healthcare officials have found themselves helpless. Nobody wants a repeat in 2013. How could lives be saved? How could we get to know about the patterns in which these diseases spread across the country? Could something as technical as GIS be a solution? Possibly, yes.


The Chickunqunea Epidemics in India (2012)


In 2006, 213 districts in 18 Indian states were hit by the deadly chikungunya virus. Thousands suffered from severe fever. A total of 15,504 blood samples were screened, and 1,985 cases were clinically confirmed as chikungunya. In 2012, Chikungunya hit 18 Indian states again. This time there were 14,277 clinically confirmed cases of chikungunya fever. The data showed a decline in number of confirmed cases of chikungunya. It should have come as a breather for the administration and healthcare departments. On the contrary, Indians were in for an even bigger shock. In 2012, as many as 24 Indian states were hit by dengue. It caused 37,070 confirmed cases of dengue. A total of 227 deaths were reported.

Actually, the authorities have enough data on both the diseases. Where did the outbreak take place? What was the pattern in which the diseases spread across the country? What kind of people was hit most severely? What were the environmental determinants? How much casualties did each district witness? We have answers to almost all these questions. All this information could very well be utilized to generate maps that could give a crystal clear understanding of the “how”, the “when”, the “where” and the “how much” questions? GIS could really come in handy! It has not only been assisting in mapping of diseases but also has become an important supporting tool for disease surveillance and public health information systems.


The dengue epidemics in India (2012)


Web maps offering GIS analysis have been frequently used in commerce, engineering, agriculture, business networks, law enforcement, forestry etc. However, web maps using GIS analysis for disease surveillance and health information management systems in India is less than 10% of all GIS applications. There is an urgent need of web maps that could use GIS analysis to depict how chikungunya and dengue spread across India. Layers of information would enrich these maps ever further. Detailed maps showing the pattern of disease transmission will play a vital role in controlling vector breeding.

The system would allow integration of data from any desktop, database, software or worksheet. It will facilitate updating of data from different nodes or centres. Nodal offices will be able to collate the data within no time. Mapping past and present situation of the chikungunya and dengue surveillance will enable the administrative and the healthcare system to control the wildfire-like spread of these diseases. It could be used to map site specifications of chikungunya and dengue vector breeding habitats (house locations, water storage plastic and cement containers, tires, plastic cups, coconut shells, tree holes, flower vessels, refrigerators, drains, wells, pools, tanks etc.) in the domestic and peripheral domestic areas. It could be used for converting the information between geographic geometric projection and the object information, and hyperlinks of spatial and non-spatial data. This technology could be essentially useful for the ongoing disease control operations and for decision making tool for chikungunya epidemics control measures in future at the national level. The GIS tool could allow the online database connectivity (ODBC) for updating and mapping the real time epidemiological information for quick and clear visualisation of the disease with site specifications from anywhere in India.



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