Establishing a Demographic, Development and Environmental Geospatial Surveillance Platform in India: Planning and Implementation

Abstract

BackgroundInadequate administrative health data, suboptimal public health infrastructure, rapid and unplanned urbanization, environmental degradation, and poor penetration of information technology make the tracking of health and well-being of populations and their social determinants in the developing countries challenging. Technology-integrated comprehensive surveillance platforms have the potential to overcome these gaps.ObjectiveThis paper provides methodological insights into establishing a geographic information system (GIS)-integrated, comprehensive surveillance platform in rural North India, a resource-constrained setting.MethodsThe International Clinical Epidemiology Network Trust International established a comprehensive SOMAARTH Demographic, Development, and Environmental Surveillance Site (DDESS) in rural Palwal, a district in Haryana, North India. The surveillance platform evolved by adopting four major steps: (1) site preparation, (2) data construction, (3) data quality assurance, and (4) data update and maintenance system. Arc GIS 10.3 and QGIS 2.14 software were employed for geospatial data construction. Surveillance data architecture was built upon the geospatial land parcel datasets. Dedicated software (SOMAARTH-1) was developed for handling high volume of longitudinal datasets. The built infrastructure data pertaining to land use, water bodies, roads, railways, community trails, landmarks, water, sanitation and food environment, weather and air quality, and demographic characteristics were constructed in a relational manner.ResultsThe comprehensive surveillance platform encompassed a population of 0.2 million individuals residing in 51 villages over a land mass of 251.7 sq km having 32,662 households and 19,260 nonresidential features (cattle shed, shops, health, education, banking, religious institutions, etc). All land parcels were assigned georeferenced location identification numbers to enable space and time monitoring. Subdivision of villages into sectors helped identify socially homogenous community clusters (418/676, 61.8%, sectors). Water and hygiene parameters of the whole area were mapped on the GIS platform and quantified. Risk of physical exposure to harmful environment (poor water and sanitation indicators) was significantly associated with the caste of individual household (P=.001), and the path was mediated through the socioeconomic status and density of waste spots (liquid and solid) of the sector in which these households were located. Ground-truthing for ascertaining the land parcel level accuracies, community involvement in mapping exercise, and identification of small habitations not recorded in the administrative data were key learnings.ConclusionsThe SOMAARTH DDESS experience allowed us to document and explore dynamic relationships, associations, and pathways across multiple levels of the system (ie, individual, household, neighborhood, and village) through a geospatial interface. This could be used for characterization and monitoring of a wide range of proximal and distal...

Evaluation of data accuracies within a comprehensive geospatial-health data surveillance platform: SOMAARTH Demographic Development and Environmental Surveillance Site, Palwal, Haryana, India

“…The need for surveillance systems and verification tools for spatial data accuracy are evident through undertaking an evaluation of SOMAARTH DDESS. Dixit et al have demonstrated for this study context preliminary community-level findings on built and physical environmental exposures being associated with individual household socio-economic status [20]. The community and household-level exposures will be able to explain and quantify social determinants of health, as well as exploring associations with diverse individual health outcomes such as diabetes, cardiovascular and infectious disease [25].…”

“…QuickBird™ satellite imagery was used to prepare various geospatial data on rural areas and store the information (digital village layer) within a GIS domain [20]. These layers included detail on features at their finest spatial unit; water bodies were represented as polygons, roads as either polygon or line, railway tracts as line features, landmarks as a point location (e.g.…”

“…Each land parcel was subsequently assigned by the geospatial technician a landuse categorization according to an adapted system [20]. The resulting landuse classification system included three levels.…”

“…The attribute table within the GIS village layer included all land parcels that were characterized within the village. Further information on methodology of SOMAARTH DDESS planning and implementation has been published elsewhere [20].…”

“…To address the identified need for geospatial health surveillance platforms, the International Clinical Epidemiology Network (INCLEN) Trust developed a large-scale surveillance system within the Palwal District, Haryana, India – the SOMAARTH† 1 Demographic Development and Environment Surveillance Site (DDESS) [20]. During the SOMAARTH platform preparation, a field-based evaluation of geospatial data element accuracy was undertaken within rural Indian villages undergoing rapid environmental, economic and social change.…”