RESUMO
BACKGROUND: Nurse navigation can improve quality of cancer care and reduce racial disparities in care outcomes. Addressing persistent structurally-rooted disparities requires research on strategies that support patients by prompting structural changes to systems of care. We applied a novel conceptualization of social support to an analysis of racial equity-focused navigation and patient-reported outcomes. METHOD: We applied an antiracism lens to create a theory-informed definition of system-facing social support: intervening in a care system on a patient's behalf. Participants were adults with early-stage breast or lung cancer, who racially identified as Black or White, and received specialized nurse navigation (n = 155). We coded navigators' clinical notes (n = 3,251) to identify instances of system-facing support. We then estimated models to examine system-facing support in relation to race, perceived racism in health care settings, and mental health. RESULTS: Twelve percent of navigators' clinical notes documented system-facing support. Black participants received more system-facing support than White participants, on average (b = 0.78, 95% confidence interval [CI]: [0.25, 1.31]). The interaction of race*system-facing support was significant in a model predicting perceived racism in health care settings at the end of the study controlling for baseline scores (b = 0.05, 95% CI [0.01, 0.09]). Trends in simple slopes indicated that among Black participants, more system-facing support was associated with slightly more perceived racism; no association among White participants. DISCUSSION: The term system-facing support highlights navigators' role in advocating for patients within the care system. More research is needed to validate the construct system-facing support and examine its utility in interventions to advance health care equity.
RESUMO
Understanding the origins of past and present viral epidemics is critical in preparing for future outbreaks. Many viruses, including SARS-CoV-2, have led to significant consequences not only due to their virulence, but also because we were unprepared for their emergence. We need to learn from large amounts of data accumulated from well-studied, past pandemics and employ modern informatics and therapeutic development technologies to forecast future pandemics and help minimize their potential impacts. While acknowledging the complexity and difficulties associated with establishing reliable outbreak predictions, herein we provide a perspective on the regions of the world that are most likely to be impacted by future outbreaks. We specifically focus on viruses with epidemic potential, namely SARS-CoV-2, MERS-CoV, DENV, ZIKV, MAYV, LASV, noroviruses, influenza, Nipah virus, hantaviruses, Oropouche virus, MARV, and Ebola virus, which all require attention from both the public and scientific community to avoid societal catastrophes like COVID-19. Based on our literature review, data analysis, and outbreak simulations, we posit that these future viral epidemics are unavoidable, but that their societal impacts can be minimized by strategic investment into basic virology research, epidemiological studies of neglected viral diseases, and antiviral drug discovery.
