Theorizing on neo public assistance: How do race and class impact resource uptake and behavior following disaster?

The consequences of environmental disasters and other ecologic and communal crises are frequently worst in racially/ethnically minoritized and low-income populations relative to other groups. This disproportionality may create or deepen patterns of governmental distrust and stoke health promotion disengagement in these groups. To date, there has been limited contextualization of how historically disenfranchised populations utilize government-administered or facilitated resources following such disasters. Focusing on the water crisis in Flint, Michigan, we examine and theorize on the usage of neo public assistance, free risk reduction resources that are provided to disaster survivors as a liminal means of redressing ills created and/or insufficiently mitigated by the state. We surveyed 331 Flint residents, evaluating their usage of four neo public assistance resources following the FWC, finding low to moderate uptake: 131 residents (39.6%) indicated that they obtained blood lead level (BLL) screenings, 216 (65.3%) had their tap water tested for lead (Pb) and other contaminants, 137 (41.4%) had their home water infrastructure replaced, and 293 (88.5%) had acquired bottled water at community distribution sites. Unemployment, receiving public benefits, and lacking reliable transportation and stable housing were associated with lower uptake of some resources. Compared to White and "Other" race individuals, Black residents were generally more likely to acquire/utilize these resources, suggesting heightened concerns and health promotion proclivities even in the face of observed macro and individual-level challenges. Potential reasons and implications are discussed.

The blueprint of disaster: COVID-19, the Flint water crisis, and unequal ecological impacts.

COVID-19 is unique in the scope of its effects on morbidity and mortality. However, the factors contributing to its disparate racial, ethnic, and socioeconomic effects are part of an expansive and continuous history of oppressive social policy and marginalising geopolitics. This history is characterised by institutionally generated spatial inequalities forged through processes of residential segregation and neglectful urban planning. In the USA, aspects of COVID-19's manifestation closely mirror elements of the build-up and response to the Flint crisis, Michigan's racially and class-contoured water crisis that began in 2014, and to other prominent environmental injustice cases, such as the 1995 Chicago (IL, USA) heatwave that severely affected the city's south and west sides, predominantly inhabited by Black people. Each case shares common macrosocial and spatial characteristics and is instructive in showing how civic trust suffers in the aftermath of public health disasters, becoming especially degenerative among historically and spatially marginalised populations. Offering a commentary on the sociogeographical dynamics that gave rise to these crises and this institutional distrust, we discuss how COVID-19 has both inherited and augmented patterns of spatial inequality. We conclude by outlining particular steps that can be taken to prevent and reduce spatial inequalities generated by COVID-19, and by discussing the preliminary steps to restore trust between historically disenfranchised communities and the public officials and institutions tasked with responding to COVID-19.

Intersectional trauma: COVID-19, the psychosocial contract, and America's racialized public health lineage

This comparative review explores how, during COVID-19 and recent American public health disasters, including the water crisis in Flint, Michigan, Hurricane Katrina, and Hurricane Maria, early failures in public health communications, porous epidemiologic oversight, and lax crisis management created significant gaps in outreach and treatment for historically disenfranchised racial/ethnic minorities. In consideration of each event's broader specter in terms of population health inequities, a highly salient but underresearched dynamic emerges: the development of heightened psychological sequelae including depression, anxiety, and posttraumatic stress, factors linked to civic and health care system disengagement and poorer overall health. This excess mental illness morbidity can be said to fall under the umbrella of intersectional trauma, or psychological harm and psychosocial vulnerability produced through the accumulation of cultural, political, economic, and ecologic stressors tied to salient identity markers such as race or ethnicity. During COVID-19, reports have presaged race- and class-specific disparities in infections and mortality, with evidence highlighting adverse effects on the "psychosocial contract," public trust and faith in government and health care systems which is borne from relational experiences tied to one's identity markers. We discuss how COVID-19's kinetic and fluid political dynamics may add to the burden of mental illness and trauma in racial/ethnic minority communities in the United States and further entrench said disparities, closing with potential strategies for mitigation. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

Integrated Survival Estimates for Cancer Treatment Delay Among Adults With Cancer During the COVID-19 Pandemic.

Importance: Cancer treatment delay has been reported to variably impact cancer-specific survival and coronavirus disease 2019 (COVID-19)-specific mortality during the severe acute respiratory syndrome coronavirus 2 pandemic. During the pandemic, treatment delay is being recommended in a nonquantitative, nonobjective, and nonpersonalized manner, and this approach may be associated with suboptimal outcomes. Quantitative integration of cancer mortality estimates and data on the consequences of treatment delay is needed to aid treatment decisions and improve patient outcomes. Objective: To obtain quantitative integration of cancer-specific and COVID-19-specific mortality estimates that can be used to make optimal decisions for individual patients and optimize resource allocation. Design, Setting, and Participants: In this decision analytical model, age-specific and stage-specific estimates of overall survival pre-COVID-19 were adjusted by the probability of COVID-19 (individualized by county, treatment-specific variables, hospital exposure frequency, and COVID-19 infectivity estimates), COVID-19 mortality (individualized by age-specific, comorbidity-specific, and treatment-specific variables), and delay of cancer treatment (impact and duration). These model estimates were integrated into a web application (OncCOVID) to calculate estimates of the cumulative overall survival and restricted mean survival time of patients who received immediate vs delayed cancer treatment. Using currently available information about COVID-19, a susceptible-infected-recovered model that accounted for the increased risk among patients at health care treatment centers was developed. This model integrated the data on cancer mortality and the consequences of treatment delay to aid treatment decisions. Age-specific and cancer stage-specific estimates of overall survival pre-COVID-19 were extracted from the Surveillance, Epidemiology, and End Results database for 691 854 individuals with 25 cancer types who received cancer diagnoses in 2005 to 2006. Data from 5 436 896 individuals in the National Cancer Database were used to estimate the independent impact of treatment delay by cancer type and stage. In addition, data from 275 patients in a nested case-control study were used to estimate the COVID-19 mortality rate by age group and number of comorbidities. Data were analyzed from March 17 to May 21, 2020. Exposures: COVID-19 and cancer. Main Outcomes and Measures: Estimates of restricted mean survival time after the receipt of immediate vs delayed cancer treatment. Results: At the time of the study, the OncCOVID web application allowed for the selection of up to 47 individualized variables to assess net survival for an individual patient with cancer. Substantial heterogeneity was found regarding the association between delayed cancer treatment and net survival among patients with a given cancer type and stage, and these 2 variables were insufficient to discriminate the net impact of immediate vs delayed treatment. Individualized overall survival estimates were associated with patient age, number of comorbidities, treatment received, and specific local community estimates of COVID-19 risk. Conclusions and Relevance: This decision analytical modeling study found that the OncCOVID web-based application can quantitatively aid in the resource allocation of individualized treatment for patients with cancer during the COVID-19 global pandemic.