Skip to main content

Analyze

NIEHS Dashboard Data Sources

tschuetz

GitHub Repository

“To empower additional modeling efforts, the complete time series of all daily PVI scores and data are available at https://github.com/COVID19PVI/data. “

12 Key Indicators

“[The authors] assembled U.S. county- and state-level datasets into 12 key indicators across four major domains: current infection rates (infection prevalence, rate of increase), baseline population concentration (daytime density/traffic, residential density), current interventions (social distancing, testing rates), and health and environmental vulnerabilities (susceptible populations, air pollution, age distribution, comorbidities, health disparities, and hospital beds).”

Three types of modeling

“Our modeling efforts directly address the discussion in [6], by contextualizing factors such as racial differences with corrections for socioeconomic factors, health resource allocation, and co-morbidities, plus highlighting place- based risks and resource deficits that might explain spatial distributions. Specifically, three types of modeling efforts were performed and are regularly updated. First, epidemiological modeling on cumulative case- and death-related outcomes provides insights into the epidemiology of the pandemic. Second, dynamic time-dependent modeling provides similar outcome estimates as national-level models, but with county-level resolution. Finally, a Bayesian machine learning approach provides data-driven, short-term forecasts. “

Blackness and PM 2.5

“With respect to factors affecting COVID-19 related mortality, we find that the proportion of Black residents and the PM2.5 index of small-particulate air pollution are the most significant predictors among those included, reinforcing conclusions from previous reports[7]. An increase of one percentage point of Black residents is associated with a 3.3% increase in the COVID-19 death rate. The effect of a 1 g/m3 increase in PM2.5 is associated with an approximately 16% increase in the COVID-19 death rate, a value at the high end of a previously reported confidence interval from a report in late April 2020[7] when deaths had reached 38% of the current total.”

Machine learning and prediction

“To accurately predict future cases and mortality, it is necessary to account for the fluid nature of the data. Accordingly, we developed a Bayesian spatiotemporal random-effects model that jointly describes the log-observed and log-death counts to build local forecasts. Log-observed cases for a given day are predicted using known covariates (e.g., population density, social distancing metrics), a spatiotemporal random-effect smoothing component, and the time- weighted average number of cases for these counts. This smoothed time-weighted average is related to a Euler approximation of a differential equation; it provides modeling flexibility while approximating potential mechanistic models of disease spread. The smoothed case estimates are used in a similar spatiotemporal model predicting future log-death counts based on a geometric mean estimate of the estimated number of observed cases for the previous seven days as well as the other data streams. The resulting county-level predictions and corresponding confidence intervals are shown (Fig. 1)."

Source: https://www.researchgate.net/publication/343642027_The_COVID-19_Pandemi…

US NIEHS Dashboard Creators and Curators

tschuetz

Skylar W. Marvel1, John S. House2, Matthew Wheeler2, Kuncheng Song1, Yihui Zhou1, Fred A. Wright1,3, Weihsueh A. Chiu4, Ivan Rusyn4, Alison Motsinger-Reif2*, David M. Reif1*

Affiliations:

1 Bioinformatics Research Center, Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA.

2 Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, USA.

3 Department of Statistics, North Carolina State University, Raleigh, NC 27695, USA

4 Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77845, USA.

US NIEHS Dashboard Types of Data

tschuetz

“Data sources in the current model (version 11.2.1) include the Social Vulnerability Index (SVI) of the Centers for Disease Control and Prevention (CDC) for emergency response and hazard mitigation planning (Horney et al. 2017), testing rates from the COVID Tracking Project (Atlantic Monthly Group 2020), social distancing metrics from mobile device data ( https://www.unacast.com/covid19/social-distancing-scoreboard), and dynamic measures of disease spread and case numbers ( https://usafacts.org/issues/coronavirus/). Methodological details concerning the integration of data streams—plus the complete, daily time series of all source data since February 2020 and resultant PVI scores—are maintained on the public Github project page (COVID19PVI 2020). Over this period, the PVI has been strongly associated with key vulnerability-related outcome metrics (by rank-correlation), with updates of its performance assessment posted with model updates alongside data at the Github project page (COVID19PVI 2020).”

Source: https://ehp.niehs.nih.gov/doi/10.1289/EHP8690

US NIEHS Dashboard Motivations

tschuetz

Empowering local actoors

“We present the PVI Dashboard as a dynamic container for contextualizing these disparities. It is a modular tool that will evolve to incorporate new data sources and analytics as they emerge (e.g., concurrent flu infections, school and business reopening statistics, heterogeneous public health practices). This flexibility positions it well as a resource for integrated prioritization of eventual vaccine distribution and monitoring its local impact. The PVI Dashboard can empower local and state officials to take informed action to combat the pandemic by communicating interactive, visual profiles of vulnerability atop an underlying statistical framework that enables the comparison of counties and the evaluation of the PVI’s component data.”

US NIEHS Dashboard Visualization

tschuetz

Built with toxicology knowledge

“The software used to generate PVI scores and profiles from these data is freely available at https://toxpi.org

General visualization capabilities

“The interactive visualization within the PVI Dashboard is intended to communicate factors underlying vulnerability and empower community action [...] The visualization and quantification of county-level vulnerability indicators are displayed by a radar chart, where each of the 12 indicators comprises a “slice” of the overall PVI profile. On loading, the Dashboard displays the top 250 PVI profiles (by rank) for the current day. The data, PVI scores, and predictions are updated daily, and users can scroll through historical PVI and county outcome data. Individual profiles are an interactive map layer with numerous display options/filters that include sorting by overall score, filtering by combinations of slice scores, clustering by profile similarity (i.e. vulnerability “shape”), and searching for counties by name or state (Additional functionality is detailed in the Supplement). User selection of any county overlays the summary Scorecard and populates surrounding panels with county- specific information (Figure 1). The scrollable panels at left include plots of vulnerability drivers relative to the nation-wide distribution across all U.S. counties, with the location of the selected county delineated. The panels across the bottom of the Dashboard report cumulative county numbers of cases and deaths; timelines of cumulative cases, deaths, PVI score, and PVI rank; daily changes in cases and deaths for the most recent 14-day period (commonly used in reopening guidelines[6]; and predicted cases and deaths for a 7-day forecast horizon.”

Visualizing comparison and "peer counties"

“the multi-criteria filtering capabilities in the Dashboard were used to find a “peer county” for comparison. “

Source: https://ehp.niehs.nih.gov/doi/10.1289/EHP8690 and https://www.researchgate.net/publication/343642027_The_COVID-19_Pandemi…

Grace Fine Annotation

gracefine

The complaints of Duplin County residents and the Environmental Justice Community Action Network about general permitting for hog farms in Eastern NC. These permits would give way to more ground and water pollution due to the relaxed regulations on corporate farms that hold multiple different numbers of livestock. Plans for the implementationa pipline called the "Grady Road project" interrupt the family and small scale farms in the ares. A quote from the Duplin County NAACP president Robert O. Moore says:

"The corporation has refused to implement any technology to clean up the water, citing the cost of doing so was too expensive. Yet the cost of this biogas project rivals the cost that would have been to implement cleaner and safer technology to ensure the safety of those living near these operations."

Many local groups in Eastern NC counties have previously tried to receive assistance to help with their agriculture waste managment systems, yet fall short due to many government officials only focusing on corporate farms. 

Read more at the link: https://southerlymag.org/2022/03/24/biogas-could-do-more-harm-than-good…
 

Grace Katona

GraceKatona

Early local organizing that uses conflict and difference as a way to generate transformative solutions. Solutions that serve more then one worldview instead of growing otherness, separateness, and hierarchy. In the book Emergent Strategy by adrienne maree brown, brown states... 

At the human scale, in order to create a world that works for more people, for more life, we have to collaborate on the process of dreaming and visioning and implementing that world. We have to recognize that a multitude of realities have, do, and will exist.

An example of success using this strategy is the Dogwood Alliance in joint with other partners who put a stop to a wood pellet mill in Lumberton, NC. The article located on the Dogwood Alliance webpage about this victory states the following. 

THE CLOSURE OF THIS FACILITY IS ALSO A WIN FOR OUR CLIMATE. THE BURNING OF THESE PELLETS WOULD HAVE ADDED THOUSANDS OF TONS OF CARBON DIOXIDE TO THE ATMOSPHERE, THE EQUIVALENT OF 155,580 CARS ON THE ROAD.

Link to this webpage: https://www.dogwoodalliance.org/2022/04/statement-wood-pellet-mill-stop…

    

Duplin County, NC Action: Local Challenges to the DEQ's General Permit for Hog Farms

josiepatch

In an article written in August 2022 details the complaints of residents of Duplin County and the Environmental Justice Community Action Network in response to a general permit for hog farms in Eastern North Carolina that would pollute the ground and water by relaxing regulations on farms with varying numbers of livestock. A quote from Sheri White-Williamson, cofounder of the Community Action Network, says, 

“A general permit is a one-size fits all system, regardless of the number of animals you have,” she said. “That doesn’t seem to make good environmental sense. At the very minimum we would like to see the denitrification system that has shown to be better for taking care of the toxins that come out of this process. Unfortunately, that hasn’t happened.”

Local groups urge the DEQ to set regulations on a case by case basis depending on the size of biogas operations and should require cleaner systems and ways of getting rid of waste.

The article is linked here:https://coastalreview.org/2022/08/groups-challenge-ncs-biogas-general-p…