Precision maps for public health

Reich, Brian J.; Haran, Murali

doi:10.1038/d41586-018-02096-w

Cited by 12 publications

(12 citation statements)

References 3 publications

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“…In recent years, advances in geospatial technologies and GIScience methods have allowed researchers to analyze and visualize geospatial data in great detail (Gutmann et al, 2008;Kwan, 2012;Richardson et al, 2013). For instance, maps have been widely utilized to visualize the complex patterns of diverse social phenomena, such as infectious diseases and human daily mobility (e.g., Kim & Kwan, 2019Kim & Lee, 2019;Kwan, 2004;Reich & Haran, 2018). At the same time, however, mapping people's confidential geospatial data (e.g., people's homes, workplaces, or GPS trajectories) may allow an individual's identity (e.g., name and street address) to be identified from a map (A.J.…”

Section: Introductionmentioning

confidence: 99%

How do people perceive the disclosure risk of maps? Examining the perceived disclosure risk of maps and its implications for geoprivacy protection

Kim

Kwan

Levenstein

et al. 2020

Cartography and Geographic Information Science

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This research examines how people subjectively perceive the disclosure risk of a map using original data collected in an online survey with 856 participants. The results indicate that perceived disclosure risk increases as the amount of locational information displayed on a map increases. Compared to point-based maps, perceived disclosure risk is significantly lower for kernel density maps, convex hull maps, and standard deviational ellipse maps. The results also revealed that perceived disclosure risk is affected by map scale and the presence of information of other people on a map. For geomasking methods, perceived disclosure risk decreases as aggregation level increases and as relocation distance increases. However, aggregation methods (point to polygon) are more effective in preventing the re-identification of individuals when compared to relocation methods (point to point). Lastly, the perceived disclosure risk of a map that displays sociallyvulnerable people is significantly higher than that of a map that displays non-vulnerable groups. Specifically, a map displaying the private locations of elementary school students has the highest perceived disclosure risk. Based on the results, a set of geoprivacy protection guidelines for mapping people's private locations to minimize people's perceived disclosure risk is proposed. Implications for mapping infectious diseases like the COVID-19 are also discussed.

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Section: Introductionmentioning

confidence: 99%

How do people perceive the disclosure risk of maps? Examining the perceived disclosure risk of maps and its implications for geoprivacy protection

Kim

Kwan

Levenstein

et al. 2020

Cartography and Geographic Information Science

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“…Predictive risk maps, together with geospatial modelling, are emerging as important decision tools for public health policy makers [18]. However, to date there have been no studies looking at geographical variation in functional literacy and the associations with its key determinants.…”

Section: Introductionmentioning

confidence: 99%

Functional illiteracy burden in soil-transmitted helminth (STH) endemic regions of the Philippines: An ecological study and geographical prediction for 2017

et al. 2019

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Background Soil-transmitted helminth (STH) infections remain highly endemic across the Philippines, and are believed to be important contributors to delayed cognitive development of school-aged children. Identification of communities where children are at risk of functional illiteracy is important for the attainment of Sustainable Development Goals target for literacy. We aimed to quantify the associations between the spatial variation of STH infections and functional literacy indicators adjusting for other important contributors, and identify priority areas in the Philippines in need of interventions. Methodology/Principal findings We used data from 11,313 school-aged children on functional literacy indicators collected in 2008. Nested fixed-effects multinomial regression models were built to determine associations between STH endemicity and geographical distribution of functional literacy, adjusting for demographics, household level variables, and the prevalence of malaria. Bayesian multinomial geostatistical models were built to geographically predict the prevalence of each level of functional literacy. The number of school-aged children belonging to each of the functional literacy indicator classes was forecast for 2017. We estimated 4.20% of functional illiteracy burden among school-aged children in Mindanao might be averted by preventing T . trichiura infections. Areas predicted with the highest prevalence of functional illiteracy were observed in localised areas of the eastern region of the Visayas, and the south-eastern portion of Mindanao. Conclusions/Significance The study demonstrates significant geographical variation in burden of functional illiteracy in school-aged children associated with STH infections suggesting that targeted helminth control could potentially promote the development of cognitive function of school-aged children in the Philippines. The benefits of a spatially targeted strategy should be tested by future studies.

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“…Most studies that investigate subnational levels, however, are largely confined to macro geographies, such as states or districts in India ( 4 , 5 ) or provinces in China ( 6 ), despite recent studies emphasizing more variation at finer geographic resolutions as small as villages or communities ( 7 , 8 ). With increasing availability and accessibility of data geocoded to smaller geographic units and with varying degrees of precision along with the use of advanced modeling techniques, there are emerging opportunities to assess health and developmental indicators at truly small areas ( 9 , 10 ). The future iterations of the Global Burden of Diseases, Injuries, and Risk Factors study are expected to feature maps of the different burden at a finer spatial resolution (5 × 5 km) ( 11 ).…”

mentioning

confidence: 99%

“…While this interest toward a focus on finer geographic resolution is a welcoming step toward precision public health ( 2 , 3 , 9 , 10 , 16 ), small area estimates with no explicit link to political or administrative jurisdiction have limited practical implications in terms of guiding efficient and equitable interventions. To enable immediate attention and action to take place, the unit of analysis and inferential target in empirical studies need to align with the local governance unit, often within districts or cities, that are accountable for implementation of programs and interventions ( 3 , 16 , 17 ).…”

mentioning

confidence: 99%

Precision mapping child undernutrition for nearly 600,000 inhabited census villages in India

Kim

Bijral

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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There are emerging opportunities to assess health indicators at truly small areas with increasing availability of data geocoded to micro geographic units and advanced modeling techniques. The utility of such fine-grained data can be fully leveraged if linked to local governance units that are accountable for implementation of programs and interventions. We used data from the 2011 Indian Census for village-level demographic and amenities features and the 2016 Indian Demographic and Health Survey in a bias-corrected semisupervised regression framework to predict child anthropometric failures for all villages in India. Of the total geographic variation in predicted child anthropometric failure estimates, 54.2 to 72.3% were attributed to the village level followed by 20.6 to 39.5% to the state level. The mean predicted stunting was 37.9% (SD: 10.1%; IQR: 31.2 to 44.7%), and substantial variation was found across villages ranging from less than 5% for 691 villages to over 70% in 453 villages. Estimates at the village level can potentially shift the paradigm of policy discussion in India by enabling more informed prioritization and precise targeting. The proposed methodology can be adapted and applied to diverse population health indicators, and in other contexts, to reveal spatial heterogeneity at a finer geographic scale and identify local areas with the greatest needs and with direct implications for actions to take place.

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Precision maps for public health

Cited by 12 publications

References 3 publications

How do people perceive the disclosure risk of maps? Examining the perceived disclosure risk of maps and its implications for geoprivacy protection

How do people perceive the disclosure risk of maps? Examining the perceived disclosure risk of maps and its implications for geoprivacy protection

Functional illiteracy burden in soil-transmitted helminth (STH) endemic regions of the Philippines: An ecological study and geographical prediction for 2017

Precision mapping child undernutrition for nearly 600,000 inhabited census villages in India

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