The Geographic Context of Racial Disparities in Aggressive Endometrial Cancer Subtypes: Integrating Social and Environmental Aspects to Discern Biological Outcomes

Racioethnic Disparities in Endometrial Cancer Outcomes

Black women are twice as likely to die from endometrial cancer (EC) compared with white women. This represents one of the worst racioethnic disparities amongst all cancers globally. Compared with white women, black women are more likely to be diagnosed with advanced EC, have more barriers to accessing care and experience increased delays in obtaining an EC diagnosis and commencing treatment. Histological and molecular differences place black women at higher risk of being diagnosed with more aggressive EC subtypes that carry less favourable outcomes. Furthermore, EC diagnostic pathways are less reliable in black women, and black women are less likely to receive evidence-based treatment for EC. This racioethnic disparity in EC outcomes exists both in the UK and US, despite differences in healthcare systems. This review methodically describes the key factors along the patient journey that contribute to the disparity in black women and proposes multifaceted approaches to lessen these gaps.

Spatial Syndromic Surveillance and COVID-19 in the U.S.: Local Cluster Mapping for Pandemic Preparedness

Maps have become the de facto primary mode of visualizing the COVID-19 pandemic, from identifying local disease and vaccination patterns to understanding global trends. In addition to their widespread utilization for public communication, there have been a variety of advances in spatial methods created for localized operational needs. While broader dissemination of this more granular work is not commonplace due to the protections under Health Insurance Portability and Accountability Act (HIPAA), its role has been foundational to pandemic response for health systems, hospitals, and government agencies. In contrast to the retrospective views provided by the aggregated geographies found in the public domain, or those often utilized for academic research, operational response requires near real-time mapping based on continuously flowing address level data. This paper describes the opportunities and challenges presented in emergent disease mapping using dynamic patient data in the response to COVID-19 for northeast Ohio for the period 2020 to 2022. More specifically it shows how a new clustering tool developed by geographers in the initial phases of the pandemic to handle operational mapping continues to evolve with shifting pandemic needs, including new variant surges, vaccine targeting, and most recently, testing data shortfalls. This paper also demonstrates how the geographic approach applied provides the framework needed for future pandemic preparedness.