Analyze

“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).

The article focuses on the analysis of border control agencies and practices of coordinating, classifying and deploying data.  The authors' primarily goal is outlining these processes, opening up possibilities for future analysis of power relations (p. 65). Our shared research question further encourages us to ask how different actors and publics could critically engage with the data practices.

Nanjala Nyabola, a Kenyan journalist and author tweeted: 'There were two anti-police brutality protests in Nairobi today. The one featuring white people made it's way to the US embassy undisturbed. The one led by working class and poor folks ended in teargas and arbitrary arrests.'

On March 25, 2020 the Kenyan government imposed a curfew to limit movement in Nairobi to prevent the spreading of COVID-19. In the ensuing months, the police 'enforced' the curfew by killing as many people as COVID-19 in Nairobi. The police have had a long and bloody history in Nairobi. Missing Voices Kenya have documented the shocking number of people who have lots their lives to police brutality over the years. Although groups in poor neighbourhoods such as Mathare have long held protests against police violence, the recent murder of George Floyd in the US has lent momentum to this movement. Thus, these groups took to the street to walk to the apartment where Yasin Moyo, a 13 year old playing on his balcony was killed by police, to demand that Black lives mattered- everywhere. The protests ended in the police tear gassing protestors.

A separate group comprising of many white protestors marched to the US Embassy to protest extrajudicial killings in the US and Kenya. From reports I have been reading about the protests on Twitter, these groups were left unharmed by the police. It is thus important that we recognize the the situatedness of protests agains police violence in different parts of the world, and the specific histories and contexts that shape each one of them, while recognizing their common themes.