GIS for public health : A study of Andhra Pradesh

7th IGRSM International Remote Sensing & GIS Conference and Exhibition

地球科学;计算机科学

Shrinagesh, B.^1 ; Kalpana, Markandey^2 ; Kiran, Baktula^2

Department of Geography, Nizam College, Hyderabad, India^1

Department of Geography, Osmania University, Hyderabad, India^2

关键词: Centers of excellence;    Distribution of disease;    Healthcare delivery;    Infrastructural facilities;    Mapping populations;    Rapid communication;    Remote rural areas;    Spatial and temporal trends;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/20/1/012024/pdf
DOI  :  10.1088/1755-1315/20/1/012024

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Geographic information systems and remote sensing have capabilities that are ideally suited for use in infectious disease surveillance and control, particularly for the many vector-borne neglected diseases that are often found in poor populations in remote rural areas. They are also highly relevant to meet the demands of outbreak investigation and response, where prompt location of cases, rapid communication of information, and quick mapping of the epidemic's dynamics are vital. The situation has changed dramatically over the past few years. GIS helps in determining geographic distribution of diseases, analysing spatial and temporal trends, Mapping populations at risk, Stratifying risk factors, Assessing resource allocation, Planning and targeting interventions, Monitoring diseases and interventions over time. There are vast disparities in people's health even among the different districts across the state of Andhra Pradesh largely attributed to the resource allocation by the state government. Despite having centers of excellence in healthcare delivery, these facilities are limited and are inadequate in meeting the current healthcare demands. The main objectives are to study the prevalent diseases in Andhra Pradesh, to study the infrastructural facilities available in A.P. The methodology includes the Spatial Database, which will be mostly in the form of digitized format. The Non-Spatial Database includes both secondary data as well as the primary data.