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How was research for this document conducted? Who participated?

margauxf

“Since asthma surveillance data were not available at the census tract level for most of Louisiana, we estimated asthma burden using the inpatient discharge data available through LDH.”  (4)

“Case counts are not provided for CTs with a 2018 population of less than 800 to safeguard privacy.” (4)

“To minimize the need for suppression, inpatient discharge data was aggregated for the three most recent years available (2017–2019) and average annual crude rates were calculated for cases where asthma (ICD-10 code J45) was the primary diagnosis, as well as where asthma was any diagnosis.” (4)

“Spearman’s Rank Correlation was utilized to analyze the correlation between various social and environmental vulnerability factors, COVID-19 incidence, and the measures of asthma risk by CT.” (4)

 

“This was performed by first ranking the values in each dataset using RANK.AVG function in MS Excel 2016, followed by applying the PEARSON function to compare two datasets. Significance was set at alpha less than 0.05 (α < 0.05), with degrees of freedom (df) equal to two less than the total number of data points represented in both datasets” (4)

The research team works for the Section of Environmental Epidemiology and Toxicology, Office of Public Health, Louisiana Department of Health in Baton Rouge. Team members included Arundhati Bakshi; Shanon Soileau; Collete Stewart; Kate Friedman; Collete Maser; Alexis Williams; Kathleen Aubin; and Alicia Van Doren. 

How are the links between environmental conditions and health articulated?

margauxf

“Currently, much of the environmental focus of the pandemic remains on PM2.5 levels; however, we noted that higher levels of ozone was consistently associated with higher incidence rates of COVID-19, and it was the only environmental factor that appeared to have an additive effect over SVI on COVID-19 incidence (Fig 1).” (11)

“Specifically, our data show a moderately strong positive correlation between SVI due to minority status/language barrier and three health data variables: asthma hospitalization; estimated asthma prevalence; and cumulative COVID-19 incidence at 3 months (Table 2). Interestingly, SVI measures were either negatively or not significantly correlated COVID-19 incidence at the 9-and 12-month time points, indicating that social vulnerability factors may have played a greater role in COVID-19 spread early in the pandemic, but may have been of diminishing importance as the pandemic wore on (Fig 1 and Table 2).” (9)

Bakshi A, Van Doren A, Maser C, Aubin K, Stewart C, Soileau S, et al. (2022) Identifying Louisiana communities at the crossroads of environmental and social vulnerability, COVID-19, and asthma. PLoS ONE 17(2): e0264336. https:// doi.org/10.1371/journal.pone.0264336. 

What forms of evidence and expertise are used in the document?

margauxf

This document uses data resources from the Center for Disease Control/Agency for Toxic Substances and Disease Registry (CDC/ATSDR), the Environmental Protection Agency (EPA), and the Louisiana Department of Health (LDH).

These data resources include the Social Vulnerability Index (2018 - CDC/ATSDR), the NATA Respiratory Hazard Index (EPA 2014), PM2.5level (average annual concentration in ug/m3, EPA 2016), ozone level (summer seasonal average of daily maximum 8-hour concentration in air in parts per billion, EPA 2016), indoor mold concerns reported to IEQES program (average annual number of calls, LDH 2017-2019), cumulative COVID-19 incidence rate at 3-, 6-, 9- and 12-month increments (LDH March 2020 - March 2021), asthma hospitalization (average annual crude rate, where asthma was a primary diagnosis among hospitalization cases, LDH 2017-2019), and estimated asthma prevalence (average annual crude rate, where asthma was any diagnosis among hospitalization cases, LDH 2017-2019).

What steps does a user need to take to produce analytically sharp or provocative data visualizations with this data resource?

albrowne

The UI for the portal is straightforward and easy to use and also doubles as a GIS. Through the advanced search function users can use either the criteria or filter tabs to narrow their searches to specific sites. For example when you narrow down the search to RMP facilities only you can quickly pinpoint all of these facilities on a map of an area to show how burdened an area may be with these types of facilities.

What data visualizations illustrate how this data set can be leveraged to characterize environmental injustice in different sett

albrowne

The data can very quickly show you how many facilities a geographical area may have. This can allow users to see how burdened a neighborhood for example may be with specific facilities.

What visualizations can be produced with this data resource and what can they be used to demonstrate?

albrowne

One of the only data visualizations this site offers is plotting down pinpoints on a map showing individual facilities. If there is more than one site in a certain geographical area then it will group the sites together and provide a circle for where the sites are contained with the number of sites listed on the circle. This makes this data resource not super flexible in ways it can display information. However this is a helpful visualization as it can quickly show you how many specific facilities a certain location may have

 

You can also generate simple graphs with the data that displays the amounts of certain facilities throughout the state. This is a good tool for tracking all regulated facilities which can help users address Ej on a statewide scale.

What can be demonstrated or interpreted with this data set?

albrowne

What this lacks in visualizations it makes up for drastically in easy to use UI and for creating one location for all of the state's facility data. By using its advanced search tool users can quickly find a plethora of data on extremely specific sites. This tool will show when the facilities had their most recent evaluations and whether or not there were violations, rough estimates on onsite stored chemicals, which regulatory programs they are a part of, CalEnviroScreen percentile ranges, and a contact list for facility employees.

How scales (county, regional, neighborhood, census tract) can be seen through this data resource?

albrowne

This data resource can scale from the state level down to the census tract in terms of facility locations. For data visuals it groups sites together so you can not get a comprehensive visualization of regulated sites beyond the neighborhood and census tract level.