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EEC is the writing team for 10Strands,  CCEJ project for 8th grade curriculum.

EEC is organized as a collaborative (initially they were made up of over 75 organizations that include School District representation) with a board of trustees (13 members). Mary Walls, who is on a 10S writing team, is the chair of this org. In addition they have an Advisory Board. Their website lists 13 sponsors and 3 "grantors' including SoCal Edison. They describe themselves as a grassroots alliance.

The EEC seems to have officially started in Feb 2015 with their first EEC Symposium although planning meetings began in 2014 following the Stanford University Collaborative Impact Model.

On their website the EEC thanks the iecf Inland Empire Community Foundation a non-profit, public charity

The EEC offers piad workshops--their most recent on in Winter 2022 features Mary V and Mary Walls (Board Chair of EEC) as Workshop leaders on Land Acknowledgements and Decolonializing educaiton.

The EEC's websites lists many resources (organizations, guides) focused on Environmental; Agricultural, Professional development

In addition, they sponsor a bilingual art/writing and video contest annually seemingly for school age children. Recent topics include: Air and Justice (2021); Water & Water Justice (2022)

Mission statement:  Creating a sustainable and just future through environmental learning experiences for all.

They execute their mission through funding, policy and program resources In Riverside and San Bernardino Counties

In addition they envision communities where a) every person can experience nature everyday; b) teachers and envied providers have resources; c) enviro literacy is an essential component of child development

The SVI has been used to assess hazard mitigation plans in the southeastern US, evaluate social vulnerability in connection to obesity, explore the impact of climate change on human health, create case studies for community resilience policy, and even to look beyond disasters in examining a community’s physical fitness. 

The SVI was also used by public health researchers to explore the association between vulnerability and covid-19 incidence in Louisiana Census Tracts. Previous research examining associations between the CDC SVI and early covid-19 incidence had mixed results at a county level, but Biggs et al.’s study found that all four CDC SVI sub-themes demonstrated association with covid-19 incidence (in the first six months of the pandemic). Census tracts with higher levels of social vulnerability experienced higher covid-19 incidence rates. Authors of this paper point to the long history of racial residential segregation in the United States as an important factor shaping vulnerability and covid-19 incidence along racialized lines, with primarily Black neighborhoods typically most disadvantaged relative to primarily white neighborhoods. The compounding factors shaping vulnerability along racialized lines—high rates of poverty, low household income, and lower educational attainment—are identified as shaping the likelihood of covid-19 infection. The authors encourage policy initiatives that not only mitigate covid-19 transmission through allocation of additional resources and planning, but that also “address the financial and emotional distress following the covid-19 epidemic among the most socially vulnerable populations” (Biggs et al., 2021).

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Biggs, Erin N., Patrick M. Maloney, Ariane L. Rung, Edward S. Peters, and William T. Robinson. 2021. “The Relationship Between Social Vulnerability and COVID-19 Incidence Among Louisiana Census Tracts.” Frontiers in Public Health 8. https://www.frontiersin.org/article/10.3389/fpubh.2020.617976.

Lehnert, Erica Adams, Grete Wilt, Barry Flanagan, and Elaine Hallisey. 2020. “Spatial Exploration of the CDC’s Social Vulnerability Index and Heat-Related Health Outcomes in Georgia.” International Journal of Disaster Risk Reduction 46 (June): 101517. https://doi.org/10.1016/j.ijdrr.2020.101517.

The CDC SVI has been acknowledged to be limited in capturing accurate representations of small-area populations that experience rapid change between censuses (e.g. New Orleans in the years following Hurricane Katrina).

The Index is also limited, like other mapping tools, by the lack of homogeneity within any census tract or county/parish. There may very well be more vulnerable communities and individuals living in overall less vulnerable areas. Homeless populations may also specifically not be represented within studies that rely on geocoding by residential address. Length of residence within a geographic area may also impact results.  

The index is also limited by calculations that account for where people live, but not necessarily where they work or play. The lives of individuals are not necessarily restricted to the boundaries of a census tract or county/parish. 

Lastly, vulnerability is only one component of several components that are important for public health officials and policymakers to consider—the hazard itself, the vulnerability of physical infrastructure, and community assets and resources are other elements that must be taken into account for reducing the effects of a hazard.

This data resource has also been critiqued by Bakkensen et al. for not having been explicitly tested and empirically validated to demonstrate that the index performs well (a problem they identify as characterizing multiple indices).

Bakkensen, Laura A., Cate Fox-Lent, Laura K. Read, and Igor Linkov. 2017. “Validating Resilience and Vulnerability Indices in the Context of Natural Disasters.” Risk Analysis 37 (5): 982–1004. https://doi.org/10.1111/risa.12677.

There is a national data set that ranks all counties or census tracts within the entire data set (useful for a multi-state analysis). The user also has the option to utilize a state data set, which ranks counties or census tracts only within the state selected.

The CDC/ATSDR SVI draws on the U.S. Census Bureau’s American Community Survey (ACS), 5-year estimates. The most recently available SVI dataset is for 2018, which utilizes the ACS 2014-2018 data.

Users must select the ranking variable for either the overall vulnerability index score or for one of the four sub themes: Socioeconomic Status, Household Composition & Disability, Minority Status & Language, or Housing Type & Transportation.

A dictionary of terms used in this data resource are available at the bottom of this webpage: https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/SVI_documentation_2018.html.