Interoperable and accessible census and survey data from IPUMS

Kugler, Tracy A.; Fitch, Catherine A

doi:10.1038/sdata.2018.7

Cited by 17 publications

(35 citation statements)

References 26 publications

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“… 41 US census data are publicly available as Public Use Microdata Areas (PUMAs), which provide geographic substate demographic data. 43 PUMAs have been used in research 44 and have helped catalyze knowledge generation across a wide range of social science and other disciplines. 44 This data integration strategy facilitates population health surveillance by the geographic distribution of the population.…”

Section: Workplace Programsmentioning

confidence: 99%

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Model for Mitigation of Workplace Transmission of COVID-19 Through Population-Based Testing and Surveillance

Plantes¹,

Fragala

Clarke³

et al. 2021

Population Health Management

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The coronavirus disease-2019 (COVID-19) pandemic is having a widespread impact on societies across the globe. As part of the effort to control transmission in the United States, many businesses either closed or instituted nonpharmaceutical control measures and allowed only essential workers on-site. During summer and fall of 2020, employers began formulating “return to work” strategies designed to mitigate the risk of transmission among employees. On a population level, several countries implemented national testing and surveillance strategies that proved effective in mitigating citizen-to-citizen transmission and contributed to suppressing COVID-19. A crucial component of many such strategies is population-based testing to identify and engage individuals with asymptomatic or presymptomatic infection, which also is relevant to return-to-work strategies. The authors describe an approach that multisite employers might use to help mitigate transmission of COVID-19 in the workplace. This approach leverages a bioinformatics platform informed by real-time PCR test data at the county and subcounty (eg, Public Use Microdata Area) level, allowing for population-based testing to be selectively targeted for employees in geographies with elevated SARS-CoV-2 positivity. A “Command Center” application integrates data from multiple sources (eg, local infection trends, employee symptom diaries, Bluetooth thermometers) in real time, which can be used to inform decisions regarding surveillance and employee self-isolation or quarantine; a mobile phone-based application provides for rapid, secure communication with employees. This overview is based on peer-reviewed literature and the early experience of a large employer with implementing bioinformatics tools to mitigate the impact of the pandemic on the workplace.

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Section: Workplace Programsmentioning

confidence: 99%

“…43 PUMAs have been used in research 44 and have helped catalyze knowledge generation across a wide range of social science and other disciplines. 44 This data integration strategy facilitates population health surveillance by the geographic distribution of the population. 41 …”

Section: Workplace Programsmentioning

confidence: 99%

Model for Mitigation of Workplace Transmission of COVID-19 Through Population-Based Testing and Surveillance

Plantes¹,

Fragala

Clarke³

et al. 2021

Population Health Management

View full text Add to dashboard Cite

show abstract

“…ISRDI focuses on providing curated datasets that promote compatibility and comparability for researchers. The center disseminates approximately one terabyte of data each month to thousands of researchers, resulting in hundreds of publications each year (Kugler & Fitch, 2018). The development of this Spatial Data Infrastructure (SDI) project is important because it provides simplified access to big data through its big data integration processes.…”

Section: Introductionmentioning

confidence: 99%

IPUMS-Terra: integrated big heterogeneous spatiotemporal data analysis system

2018

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Big Geo Data promises tremendous benefits to the GIS Science community in particular and the broader scientific community in general, but has been primarily of use to the relatively small body of GI-Scientists who possess the specialized knowledge and methods necessary for working with this class of data. Much of the greater scientific community is not equipped with the expert knowledge and techniques necessary to fully take advantage of the promise of big spatial data. IPUMS-Terra provides integrated spatiotemporal data to these scholars by simplifying access to thousands of raster and vector datasets, integrating them and providing them in formats that are useable to a broad array of research disciplines. IPUMS-Terra exemplifies a new class of National Spatial Data Infrastructure because it connects a large spatial data repository to advanced computational resources, allowing users to access the needle of information they need from the haystack of big spatial data. The project is trailblazing in its commitment to the open sharing of spatial data and spatial tool development, including describing its architecture, process development workflows, and openly sharing its products for the use general use of the scientific community.

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“…The first of these pertains to individual microdata, which is organised by household to capture information about both the individual and housing unit. While the collective microdata is a powerful resource, variations in questions asked, possible responses, and record structure often present difficulties in comparing results across years [15]. The second challenge relates to the specific methods used by the agencies that gather and report census data, in protecting the anonymity of individuals.…”

mentioning

confidence: 99%

Creating a surrogate commuter network from Australian Bureau of Statistics census data

2019

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Between the 2011 and 2016 national censuses, the Australian Bureau of Statistics changed its anonymity policy compliance system for the distribution of census data. The new method has resulted in dramatic inconsistencies when comparing low-resolution data to aggregated high-resolution data. Hence, aggregated totals do not match true totals, and the mismatch gets worse as the data resolution gets finer. Here, we address several aspects of this inconsistency with respect to the 2016 usual-residence to place-of-work travel data. We introduce a re-sampling system that rectifies many of the artifacts introduced by the new ABS protocol, ensuring a higher level of consistency across partition sizes. We offer a surrogate high-resolution 2016 commuter dataset that reduces the difference between the aggregated and true commuter totals from ~34% to only ~7%, which is on the order of the discrepancy across partition resolutions in data from earlier years.

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Interoperable and accessible census and survey data from IPUMS

Cited by 17 publications

References 26 publications

Model for Mitigation of Workplace Transmission of COVID-19 Through Population-Based Testing and Surveillance

Model for Mitigation of Workplace Transmission of COVID-19 Through Population-Based Testing and Surveillance

IPUMS-Terra: integrated big heterogeneous spatiotemporal data analysis system

Creating a surrogate commuter network from Australian Bureau of Statistics census data

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