Analyze

The authors examine the practice of “hot spotting,” a form of surveillance and intervention through which health care systems in the US intensively direct health and social services towards high-cost patients.  Health care hot spotting is seen as a way to improve population health while also reducing financial expenditures on healthcare for impoverished people. The authors argue that argue that ultimately hot spotting targets zones of racialized urban poverty—the same neighborhoods and individuals that have long been targeted by the police. These practices produce “a convergence of caring and punitive strategies of governance” (474). The boundaries between the spaces of healthcare and policing have shifted as a “financialized logic of governance has come to dominate both health and criminal justice” (474).

The authors offer a review of themes within occupational health and environmental public health surveillance over the past decade. In reviewing the history of public health surveillance, the authors highlight key acts of Congress in the 1970s that have made the development of “modern” occupational health and environmental health surveillance possible—but which also failed to develop into a cohesive and well-connected data management systems across federal agencies. Separate agencies were tasked with different data collection, management and intervention tasks in ways that fragmented the surveillance system to the point of ineffectiveness.

The authors argue that effective surveillance for occupational and environmental health demands development of a clear purpose for collecting data and having the data available to make meaningful analysis possible. They turn to the CDC’s childhood lead prevention program to demonstrate these points.

Public Health Alliance of Southern California. California Healthy Places Index. 2019. https://healthyplacesindex.org.

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© 2018 California Department of Public Health (CDPH)

Permission is hereby granted to use, reproduce, and distribute these materials for noncommercial purposes, including educational, government, and community uses, with proper attribution to the CDPH, including this copyright notice. Use of this publication does not imply endorsement by the CDPH.

The index does not include certain neighborhood characteristics critical to health because they did not meet the criteria for inclusion (described in question 3). For instance, this included physician ratios (the number of physicians per 100,000 population) because data was missing for a majority of census tracts. In fact, the steering committee was unable to locate much data on health care access or quality at the census-tract level (only data on health care insurance coverage was available).  

 The index was previously critiqued in ways that led to a shift from framing data in terms of “disadvantage” towards a framework of “opportunity”. This led to not only a renaming of the index (from “the Health Disadvantage Index to the Healthy Places Index) but also a shift in reporting of data (e.g. highlight the percentage of the population with a BA degree or higher rather than the percentage of population without a college degree). 

The HPI is also limited in terms of the effects of confounding, with some indicators with strong evidence of health effects showing contrary associations with life expectancy at birth by census tract. The steering committee has also acknowledged that the HPI might not be accurate for census tracts undergoing rapid population change (e.g. due to immigration, rapid gentrification, or other changes).

The HPI notably does not correlate strongly with CalEnviroScreen, which the steering committee for the HPI noted failed to identify one-third of census tracts with the worst conditions for population health. The HPI is ultimately more centered on considering environmental factors as a part of overall health, rather than as a central determinant. However, this disconnect between CalEnviroScreen and the HPI may also be a reflection of the challenges environmental injustice advocates have faced in linking environmental factors to health outcomes (which might not be as visible and geographically direct as the links between health and other indicators).

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.