Abstract
Evidence exists of an increasing prevalence of chronic conditions within developed and developing nations, notably for priority population groups. The need for the collection of geospatial data to monitor the health impact of rapid social-environmental and economic changes occurring in these countries is being increasingly recognized. Rigorous accuracy assessment of such geospatial data is required to enable error estimation, and ultimately, data utility for exploring population health. This research outlines findings from a field-based evaluation exercise of the SOMAARTH DDESS geospatial-health platform. Participatory-based mixed methods have been employed within Palwal-India to capture villager perspectives on built infrastructure across 51 villages. This study, conducted in 2013, included an assessment of data element position and attribute accuracy undertaken in six villages, documenting mapping errors and land parcel changes. Descriptive analyses of 5.1% (n=455) of land parcels highlighted some discrepancies in position (6.4%) and attribute (4.2%) accuracy, and land parcel changes (17.4%). Furthermore, the evaluation led to a refinement of the existing geospatial health platform incorporating ground-truthed reflections from the participatory field exercise. The evaluation of geospatial data accuracies contributes to understandings on global public health surveillance systems, outlining the need to systematically consider assessment of environmental features in relation to lifestyle-related diseases.
Highlights
Increased attention has been drawn to the role of environmental factors in the aetiology of chronic diseases, such as cardiovascular disease and type 2 diabetes [1,2,3]
Public health surveillance systems have been defined by the World Health Organization (WHO) as ‘the continuous, systematic collection, analysis and interpretation of health-related data needed for the planning, implementation, and evaluation of public health practice’ [9]
Residential land parcels represented 31.9% of assessment sample, compared with 57.3% of land parcels represented in the study region, reflecting the under-sampling of residential locations to focus on adequate samples from a range of landuse types
Summary
Increased attention has been drawn to the role of environmental factors in the aetiology of chronic diseases, such as cardiovascular disease and type 2 diabetes [1,2,3]. There is a need to focus on the burden of contemporary population health challenges experienced within low- and middle-income countries [4]. Despite the importance of these recommendations, there has been limited platforms focusing on the need for collection, maintenance and surveillance of geospatial-health data systems to address complex social determinants of health embedded within the places in which people live [6,7,8]. Broadening public health surveillance systems to incorporate geospatial information on risk conditions beyond conventional health-related data will require in the first instance the systematic capture of detailed environmental influences on health. Demographic and health surveillance systems within low- and middle-income countries, such as those aligned with the INDEPTH network [10], have emerged to explore the dynamic nature of population health, within and across communities.
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