Dataset Information

The BC Radon Data Repository (BCRDR) and BC Radon Map: Integrating disparate data sources for improved public health communication.

ABSTRACT:

Setting

The potential for exposure to indoor radon varies dramatically across British Columbia (BC) due to varied geology. Individuals may struggle to understand their exposure risk and agencies may struggle to understand the value of population-level programs and policies to mitigate risk.

Intervention

The BC Centre for Disease Control (BCCDC) established the BC Radon Data Repository (BCRDR) to facilitate radon research, public awareness, and action in the province. The BCRDR aggregates indoor radon measurements collected by government agencies, industry professionals and organizations, and research and advocacy groups. Participation was formalized with a data sharing agreement, which outlines how the BCCDC anonymizes and manages the shared data integrated into the BCRDR.

Outcomes

The BCRDR currently holds 38,733 measurements from 18 data contributors. The repository continues to grow with new measurements from existing contributors and the addition of new contributors. A prominent use of the BCRDR was to create the online, interactive BC Radon Map, which includes regional concentration summaries, risk interpretation messaging, and health promotion information. Anonymized BCRDR data are also available for external release upon request.

Implications

The BCCDC leverages existing radon measurement programs to create a large and integrated database with wide geographic coverage. The development and application of the BCRDR informs public health research and action beyond the BCCDC, and the repository can serve as a model for other regional or national initiatives.

SUBMITTER: Trieu J

PROVIDER: S-EPMC11303615 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The BC Radon Data Repository (BCRDR) and BC Radon Map: Integrating disparate data sources for improved public health communication.

Trieu Jeffrey J Young Cheryl C Nguyen Phuong D M PDM Nicol Anne-Marie AM Henderson Sarah B SB McVea David D

Canadian journal of public health = Revue canadienne de sante publique 20240528 4

<h4>Setting</h4>The potential for exposure to indoor radon varies dramatically across British Columbia (BC) due to varied geology. Individuals may struggle to understand their exposure risk and agencies may struggle to understand the value of population-level programs and policies to mitigate risk.<h4>Intervention</h4>The BC Centre for Disease Control (BCCDC) established the BC Radon Data Repository (BCRDR) to facilitate radon research, public awareness, and action in the province. The BCRDR agg ...[more]

PMID: 38806937

Similar Datasets

Project description:BackgroundRadon is a carcinogenic, radioactive gas that can accumulate indoors and is undetected by human senses. Therefore, accurate knowledge of indoor radon concentration is crucial for assessing radon-related health effects or identifying radon-prone areas.ObjectivesIndoor radon concentration at the national scale is usually estimated on the basis of extensive measurement campaigns. However, characteristics of the sampled households often differ from the characteristics of the target population owing to the large number of relevant factors that control the indoor radon concentration, such as the availability of geogenic radon or floor level. Furthermore, the sample size usually does not allow estimation with high spatial resolution. We propose a model-based approach that allows a more realistic estimation of indoor radon distribution with a higher spatial resolution than a purely data-based approach.MethodsA multistage modeling approach was used by applying a quantile regression forest that uses environmental and building data as predictors to estimate the probability distribution function of indoor radon for each floor level of each residential building in Germany. Based on the estimated probability distribution function, a probabilistic Monte Carlo sampling technique was applied, enabling the combination and population weighting of floor-level predictions. In this way, the uncertainty of the individual predictions is effectively propagated into the estimate of variability at the aggregated level.ResultsThe results show an approximate lognormal distribution of indoor radon in dwellings in Germany with an arithmetic mean of 63 Bq/m3, a geometric mean of 41 Bq/m3, and a 95th percentile of 180 Bq/m3. The exceedance probabilities for 100 and 300 Bq/m3 are 12.5% (10.5 million people affected) and 2.2% (1.9 million people affected), respectively. In large cities, individual indoor radon concentration is generally estimated to be lower than in rural areas, which is due to the different distribution of the population on floor levels.DiscussionThe advantages of our approach are that is yields a) an accurate estimation of indoor radon concentration even if the survey is not fully representative with respect to floor level and radon concentration in soil, and b) an estimate of the indoor radon distribution with a much higher spatial resolution than basic descriptive statistics. https://doi.org/10.1289/EHP14171.

Project description:BackgroundDAS is a widely adopted protocol for providing syntactic interoperability among biological databases. The popularity of DAS is due to a simplified and elegant mechanism for data exchange that consists of sources exposing their RESTful interfaces for data access. As a growing number of DAS services are available for molecular biology resources, there is an incentive to explore this protocol in order to advance data discovery and integration among these resources.ResultsWe developed DASMiner, a Matlab toolkit for querying DAS data sources that enables creation of integrated biological models using the information available in DAS-compliant repositories. DASMiner is composed by a browser application and an API that work together to facilitate gathering of data from different DAS sources, which can be used for creating enriched datasets from multiple sources. The browser is used to formulate queries and navigate data contained in DAS sources. Users can execute queries against these sources in an intuitive fashion, without the need of knowing the specific DAS syntax for the particular source. Using the source's metadata provided by the DAS Registry, the browser's layout adapts to expose only the set of commands and coordinate systems supported by the specific source. For this reason, the browser can interrogate any DAS source, independently of the type of data being served. The API component of DASMiner may be used for programmatic access of DAS sources by programs in Matlab. Once the desired data is found during navigation, the query is exported in the format of an API call to be used within any Matlab application. We illustrate the use of DASMiner by creating integrative models of histone modification maps and protein-protein interaction networks. These enriched datasets were built by retrieving and integrating distributed genomic and proteomic DAS sources using the API.ConclusionThe support of the DAS protocol allows that hundreds of molecular biology databases to be treated as a federated, online collection of resources. DASMiner enables full exploration of these resources, and can be used to deploy applications and create integrated views of biological systems using the information deposited in DAS repositories.

Project description:BackgroundGlobal action to reduce obesity prevalence requires digital transformation of the public health sector to enable precision public health (PPH). Useable data for PPH of obesity is yet to be identified, collated and appraised and there is currently no accepted approach to creating this single source of truth. This scoping review aims to address this globally generic problem by using the State of Queensland (Australia) (population > 5 million) as a use case to determine (1) availability of primary data sources usable for PPH for obesity (2) quality of identified sources (3) general implications for public health policymakers.MethodsThe Preferred Reporting Items for Systematic Review and Meta-Analyses extension for scoping reviews (PRISMA-ScR) was followed. Unique search strategies were implemented for 'designed' (e.g. surveys) and 'organic' (e.g. electronic health records) data sources. Only primary sources of data (with stratification to Queensland) with evidence-based determinants of obesity were included. Primary data source type, availability, sample size, frequency of collection and coverage of determinants of obesity were extracted and curated into an evidence map. Data source quality was qualitatively assessed.ResultsWe identified 38 primary sources of preventive data for obesity: 33 designed and 5 organic. Most designed sources were survey (n 20) or administrative (n 10) sources and publicly available but generally were not contemporaneous (> 2 years old) and had small sample sizes (10-100 k) relative to organic sources (> 1 M). Organic sources were identified as the electronic medical record (ieMR), wearables, environmental (Google Maps, Crime Map) and billing/claims. Data on social, biomedical and behavioural determinants of obesity typically co-occurred across sources. Environmental and commercial data was sparse and interpreted as low quality. One organic source (ieMR) was highly contemporaneous (routinely updated), had a large sample size (5 M) and represented all determinants of obesity but is not currently used for public health decision-making in Queensland.ConclusionsThis review provides a (1) comprehensive data map for PPH for obesity in Queensland and (2) globally translatable framework to identify, collate and appraise primary data sources to advance PPH for obesity and other noncommunicable diseases. Significant challenges must be addressed to achieve PPH, including: using designed and organic data harmoniously, digital infrastructure for high-quality organic data, and the ethical and social implications of using consumer-centred health data to improve public health.

Dataset Information

The BC Radon Data Repository (BCRDR) and BC Radon Map: Integrating disparate data sources for improved public health communication.

Setting

Intervention

Outcomes

Implications

Publications

The BC Radon Data Repository (BCRDR) and BC Radon Map: Integrating disparate data sources for improved public health communication.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets