Search

“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. 

“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. 

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).

In her article, Scharenberg (2023) provides methodological reflections on politically engaged or militant social science research. In one section, she discusses the challenge that social movements act as knowledge producers in their own right, often working independent from or outside of academic institutions (2023, 15). This raises questions about what social scientiss add to the mix. I've had similar questions working with and alongside activists in the global anti-plastics movement. Building on Casa-Cortes, Osterweil, and Powell (2013), Scharenberg points out that one response for scholars is to act as "editors" or "curators" of collective knowledge. This argument resonates with the way that I and other collaborators have thought about the engaged ethnographic archive projects:

Activist ethnographers thus become editors of collective knowledges rather than the sole producers of scientific theory. Like a literary editor, the ethnographer works from a position, which does not create knowledges from scratch, but collects the perspectives of others and assembles them with reference to the given context. In this view, objectivity might be achieved, to borrow an expression from Haraway, by assembling “partial views and halting voices” into what she calls a “collective subject position” (1988: 590). Alternatively, we might think of the editor-ethnographer as Berger’s “clerk of the records” (Scheper-Hughes, 1995: 419) who compiles the history of a group of people. Scheper-Hughes understands this position as a kind of witness. (Scharenberg 2023, 16). 

During my thesis project, Tim has served as a collaborator and mentor while he studied data use among activists opposing Formosa Plastics Group (FPG). In addition to connecting me with activists and interview candidates, he also introduced me to a small network of American and Taiwanese students in Taiwan and the United States studying FPG. This community can share resources and knowledge to further our individual studies. Could this academic network serve as a parallel to the transnational activist alliances I am studying? Are the strengths and barriers of research alliances reminiscent of the strengths and barriers of activist alliances?

The authors are Paul E. Farmer, Bruce Nizeye, Sara Stulac, and Salmaan Keshavjee. All of the authors are involved with the nonprofit organization Partners in Health in some capacity, with experience working with rural or poverty stricken areas. Paul E Farmer, the primary author of the article is a medical doctor also working for the United Nations who has published many other articles on similar topics.

The main argument is that susceptibility to certain diseases is not only determined by biology but also social conditions, leading to a disproportionate disease rate among the poor, and minority groups without access to medical services. The author shows that addressing these social conditions leads to a decrease in disease when combining treatment and prevention plans.

The argument is supported through a combination of historical information including rates of AIDS in the early 1990’s and a study done in Baltimore in an effort to reduce AIDS rates in African Americans, who were more likely to be in poverty, by addressing monetary barriers to heath care. Two more recent cases are also used to support the main argument, implementing a method created by the Partners in Health to prevent transmission and provide AIDS care in rural Haiti and rural Rwanda. Throughout the article references were made to the current medical professional’s dilemma, where they are in a position to see the social inequalities contributing to disease rates but not trained to report or change common social contributing factors. This makes the article more relatable to the reader that may have experience in the medical field which elps to support the argument.

“Pioneers of modern public health during the nineteenth century, such as Rudolph Virchow, understood that epidemic disease and dismal life expectancies were tightly linked to social conditions [55,56].” (Farmer 5)

“…large­-scale social forces—racism, gender inequality, poverty, political violence and war, and sometimes the very policies that address them—often determine who falls ill and who has access to care.” (Farmer 1)

“In an attempt to address these ethnic disparities in care, researchers and clinicians in Baltimore reported how racism and poverty— forms of structural violence, though they did not use these specific terms—were embodied [33,34] as excess mortality among African Americans without insurance.” (Farmer 2)

Data collected from a study done in Baltimore in the 1990’s, including statistics and observations is used to support the main argument. The methods used in Haiti and Rwanda as well as the results from implementing those methods are also used as examples for the claim that social conditions greatly impact disease susceptibility.