Vesta: Visualization and Exploratory Space-Time data Analysis software 

This project is pursuing the development and release of new software, Vesta, funded by SBIR grants from NIEHS and NCI to Pierre Goovaerts at BioMedware. Future blog updates will cover some of the science in Vesta to come – multivariate geostatistical methods for environmental and exposure analysis, and joinpoint regression methods for health outcomes such as cancer rates. 

Vesta 1.0 provides data import and visualization capabilities, along with data exploration tools such as time animation, and of course statistical and cartographic brushing, the hallmark of BioMedware’s software.  Future Vesta versions will sequentially bring in sets of modeling and analysis methods.  The detailed functionality in the releases has yet to be determined, but may lead off with joinpoint, followed by multivariate geostatistical methods and related regression techniques. 

So, what about science and its relevance to environmental health and exposure assessment?  I’ll finish with the Project Description as taken from Pierre’s multivariate geostatistical methods grant.  This is a Phase II SBIR from the NIEHS. 

Project Description: Multivariate Space-Time Geostatistical Analysis for Health Data 

A key component in any investigation of association and/or cause-effect relationships between the environment and health outcomes is the availability of accurate models of exposure. Because the cost of collecting field data is often prohibitive, it is critical to incorporate any source of secondary information available to supplement sparse datasets. Secondary data can take many forms (e.g., continuous or categorical measurement scale), display various sampling densities (e.g., data available everywhere or at specific locations), and be recorded over different spatial supports (e.g., point observations, census tracts, rasters). Surprisingly, there is currently no commercial software for the geostatistical treatment of multivariate space-time data, including the merging of data layers measured on different spatial supports. 

This SBIR project is developing the first commercial software to offer tools for geostatistical multivariate space-time (ST) interpolation and modeling of uncertainty. The research product will be a stand-alone desktop ST tool, building on the legacy core software developed by BioMedware. These tools will be suited for the analysis of data outside health sciences, such as in remote sensing, geochemistry or soil science, significantly broadening the commercial market for the end product. 

Call to action.  An Invited Perspective (Suk 2022) “Integrating Data Reveals Benefits of Remediation for Children’s Exposure to Hazardous Substances” observes: 

“Ye et al. (2022) demonstrate the utility of leveraging and combining large data sets from different disciplines, such as medical biomonitoring and soil monitoring data, to reveal stronger evidence supporting the value of cleaning up hazardous substances in the environment.” 

Vesta will provide powerful multivariate methods and visualization techniques for leveraging and combining large data sets in a manner that accounts for spatial and temporal correlations, as well as the multivariate dependencies across the variables themselves.  As further noted in the Invited Perspective: 

“As we strive to clean up more Superfund sites across the nation, advances in data science and data sharing will continue to reveal new discoveries and tools to support decision makers. By promoting and expanding data science initiatives across disciplines, we will be better positioned to address historical problems (such as lead) and longstanding environmental health disparities (Ramírez-Andreotta et al. 2021), as well as new and emerging challenges, such as shedding light on factors that influence a community’s vulnerability to environmental disasters and climate change (Newman et al. 2021). “ 

This is the promise of the Vesta project. 

References 

Suk, W. 2022. Invited Perspective: Integrating Data Reveals Benefits of Remediation for Children’s Exposure to Hazardous Substances. Environmental Health Perspectives 130:3 CID: 031301 https://doi.org/10.1289/EHP10594 

Ye D, Brown J, Umbach D, Adams J, Thayer W, Follansbee MH, et al.2022. Estimating the effects of soil remediation on children’s blood lead near a former lead smelter in Omaha, Nebraska, USA. Environ Health Perspect130(3):037008, 10.1289/EHP8657