Pharmacists' adoption of nonpharmaceutical supply roles may represent a problem of accepting a paradigm shift in nontraditional roles. Possible shortages of personnel in future disasters may change the pharmacists' approach to disaster management.

A cornerstone of effective disaster management is that response should always begin and end at the local level (1). The response to the Ebola virus disease (EVD) outbreak in Liberia, West Africa, was a combination of independent efforts by many nations and organizations. Many of these independent efforts ignored or were not able to work with the local levels of emergency management in Liberia. This oversight occurred because of the Liberian’s mistrust of both their government and foreign aid groups, as well as the lack of cultural competency demonstrated by the aid groups. The health-care and emergency management infrastructure in Liberia appeared to be non-existent at the beginning of the EVD outbreak. However, there were resources available at the community level: the Liberians and their culture. Although these resources were rarely used, there were some instances in which communities were included in response efforts. It was in these instances that possible improvements to international disaster response protocol were found.

Effective COVID-19 vaccine distribution requires prioritizing locations that are accessible to high-risk target populations. However, little is known about the vaccination location preferences of individuals with underlying chronic conditions. Using data from the 2018 Behavioral Risk Factor Surveillance System (BRFSS), we grouped 162,744 respondents into high-risk and low-risk groups for COVID-19 and analyzed the odds of previous influenza vaccination at doctor’s offices, health departments, community settings, stores, or hospitals. Individuals at high risk for severe COVID-19 were more likely to be vaccinated in doctor’s offices and stores and less likely to be vaccinated in community settings.

Interdisciplinary public health solutions are vital for an effective COVID-19 response and recovery. However, there is often a lack of awareness and understanding of the environmental health workforce capabilities. In the United States, this is a foundational function of health departments and is the second largest public health workforce. The primary role is to protect the public from exposures to environmental hazards, disasters and disease outbreaks. More specifically, this includes addressing risks relating to sanitation, drinking water, food safety, vector control and mass gatherings. This profession is also recognized in the Pandemic and All-Hazards Preparedness and Advancing Innovation Act of 2019. Despite this, the entire profession is often not considered an essential service. Rapid integration into COVID-19 activities can easily occur as most are government employees and experienced working in complex and stressful situations. This role, for example, could include working with leaders, businesses, workplaces and churches to safely reopen, and inspections to inform, educate, and empower employers, employees and the public on safe actions. There is now the legislative support, evidence and a window of opportunity to truly enable interdisciplinary public health solutions by mobilizing the entire environmental health workforce to support COVID-19 response, recovery and resilience activities.

Introduction A nuclear disaster would generate an unprecedented volume of thermal burn patients from the explosion and subsequent mass fires (Figure 1). Prediction models characterizing outcomes for these patients may better equip healthcare providers and other responders to manage large scale nuclear events. Logistic regression models have traditionally been employed to develop prediction scores for mortality of all burn patients. However, other healthcare disciplines have increasingly transitioned to machine learning (ML) models, which are automatically generated and continually improved, potentially increasing predictive accuracy. Preliminary research suggests ML models can predict burn patient mortality more accurately than commonly used prediction scores. The purpose of this study is to examine the efficacy of various ML methods in assessing thermal burn patient mortality and length of stay in burn centers. Methods This retrospective study identified patients with fire/flame burn etiologies in the National Burn Repository between the years 2009 – 2018. Patients were randomly partitioned into a 67%/33% split for training and validation. A random forest model (RF) and an artificial neural network (ANN) were then constructed for each outcome, mortality and length of stay. These models were then compared to logistic regression models and previously developed prediction tools with similar outcomes using a combination of classification and regression metrics. Results During the study period, 82,404 burn patients with a thermal etiology were identified in the analysis. The ANN models will likely tend to overfit the data, which can be resolved by ending the model training early or adding additional regularization parameters. Further exploration of the advantages and limitations of these models is forthcoming as metric analyses become available. Conclusions In this proof-of-concept study, we anticipate that at least one ML model will predict the targeted outcomes of thermal burn patient mortality and length of stay as judged by the fidelity with which it matches the logistic regression analysis. These advancements can then help disaster preparedness programs consider resource limitations during catastrophic incidents resulting in burn injuries.

Introduction:Disaster research is primarily posthoc analysis, locally focused or within response organizations, overlooking the wellness and safety of first and second responders or the broad multi- and interdisciplinary activities necessary to foster and sustain recovery. A broad framework to span locality, institutional, and professional boundaries supports the development of a true learning community–a health EDRM sector that supports society in recognizing lessons, refining findings, and free and fluid global sharing.Method:Several organizations joined to create a robust disaster health learning community: CREDO, GloHSA, ICDM, and ECDM, a multi-national, multi-disciplinary collaborative network of patients, universities, societies, regulators, publishing, healthcare, and technology partners designed to foster expert level education and training with shared educational design concepts, milestones, and core curricula that embrace the strength of a standardized base upon which to link unique pillars of excellence of separate functions, institutions, nations, and regions.Results:The Emergency Disaster Global Health Sciences (EDGHS) model developed by University of Texas Southwestern Medical Center is interactive, open, and responsive. EDGHS addresses critical gaps in applied research by convening leaders across the healthcare and public health continuum to map the way forward, designing and implementing high-quality, evidence-based practical and policy research.This defines essential public health functions for national contexts, including a focus on emergency preparedness and response, strengthening competency-based education on essential public health functions, and mapping and measurement of occupations delivering EDRM functions, offering an exportable model of global relevance.Conclusion:Putting disaster prevention into recovery processes is a strategic opportunity to improve the well-being of future generations. The survivability and well-being needs of present and future generations are contingent on knowledge-based, lived experiences of recoverable disaster loss and damage, and the capacity to thrive sustainably. This presentation serves as an invitation to join the growing momentum of creating a learning health EDRM community.

Introduction:Across the United States (US), there are approximately 2,000 burn beds in 133 burn centers, only 72 of which are verified by the American Burn Association (ABA). As such, many areas in the US are hundreds of miles from the closest burn center. Eight states do not have a burn center, and another 11 do not have an ABA-verified center. Further, the average center has 15 beds, and, on average, there are 90 available beds across the US. Therefore, in addition to patient care complexities, the broader infrastructure for burn patients is severely limited. These constraints suggest the burn healthcare system is particularly vulnerable to disasters, where the needs will exceed the resources available.Method:A literature review was conducted of available burn mass casualty incident (BMCI) plans from stakeholders in each level of a response. These response partners included prehospital agencies, hospitals (those with and without trauma center designations), emergency management agencies (local, state, and federal), healthcare coalitions, public health (district, state, and federal), regional coordinating burn centers, and the ABA.Results:The amalgamation of the BMCI plans yields a tripartite infrastructure not unfamiliar to emergency management professionals. The burn care agencies integrate into a response, similar to the way in which public health integrates into the emergency management infrastructure. The local to state to federal escalation of assets is reflected by an escalation from the local burn center to the regional coordinating burn center to the ABA. However, gaps remain in the communication between response partners. Few plans, particularly at the local level, reflect the integration of the burn system response.Conclusion:The burn healthcare infrastructure in the US is constrained and therefore is particularly vulnerable to a BMCI. Emergency responders should preemptively examine their plans and systems to specifically integrate the burn care and response infrastructure.

Introduction:In general, models for thermal effects of nuclear weapons are not as well developed as models for blast and radiation effects, yet casualties resulting from fires and burns in a nuclear detonation would significantly impact civil defense and emergency healthcare. Previous studies have conducted in-depth analysis of the various atmospheric conditions that affect the thermal radiation transmissivity. However, such models have yet to consider the role that buildings play in the urban environment to estimate the casualties from the thermal effect more accurately.Method:A three-dimensional model of the area within a three-mile radius of the detonation site in Atlanta, Georgia, USA was created in Blender. To represent the thermal energy resulting from a 15 kiloton, near-surface burst, a point light was created with a power of 96,725 gigawatts and a radius of 81 meters. Using the Cycles render engine, the resulting light/shadow was orthographically captured directly above the scene.Results:The rendered model demonstrated the attenuating effects of the built, urban environment. Nearly half (46.82%) of the pixels in the resulting raster were black, or regions that were not exposed to any thermal energy. Slightly less than a quarter (22.32%) of the pixels were white or light gray, or regions that received mostly direct thermal energy. The remaining regions (30.86% of the pixels) were dark gray, or regions that were initially in shadow from the thermal pulse but received thermal energy via reflection from nearby buildings.Conclusion:As the thermal pulse travels at the speed of light, it arrives at a location before the blast wave. As such, the built urban environment offers protection from the thermal energy released during a nuclear detonation. Future studies that incorporate this thermal model may more accurately determine the quantity and geospatial distribution of burn casualties in the aftermath of a nuclear detonation.