In March of 2022, the Washington Post reported that the: “Deadliest war isn’t in Ukraine, it’s in Ethiopia.” Current death toll estimates are around 600,000: 50,000-100,000 (warfare); 150,000-200,000 (starvation), and 100,000 (lack of medical treatment). Due to increasing civil unrest, a mixed-methods study began at the University of Gondar Hospital in Gondar, Ethiopia. Between 2018-2022, the estimated (daily average) of patients was reported to have quadrupled, from 100 to 400. The global research team implemented 12 new systemic revisions in overcrowding, triage nursing praxes, and resuscitations. Patient data from 521 hospital records was evaluated, as well as resource allocation(s) in staffing, equipment, and training.

The study’s inclusion criteria for A&E data included all patients who sought emergency care at UoG Teaching Hospital’s Emergency Department between May 13, 2018, and June 29, 2018, primarily during the normal daytime working hours between 9am and 2pm, as nighttime security and road travel were deemed less secure for data collectors.

After the 12-benchmark implementation, there was an approximate 15%-25% decrease in direct-from-triage ‘Red’ patient admission; congestion dropped 50%-70%; and the occurrences of successful resuscitations increased. The study revealed that over 75% of patients presented with symptoms indicative of illness(es), and 24.4% presented with trauma (remaining psychiatric). Of the trauma cases, approximately 28.3% were ‘intentional’ injuries. The patients’ mean TEWS triage score was 3.294, with a standard deviation from the mean of 1.9938.

The overall prevalence of patients necessitating surgical evaluation, the elevated use of triage discriminators due to space, equipment, and staff concerns, and the predominant use of ‘Yellow Zone’ services–all pointed to the vital need for resource re-allocation(s), stricter ECCN adherences to TEWS triage indices, as well as future Mass Casualty Planning, Triage, and Response, and Mass Casualty Medical Operations training.

Due to the high number of road traffic accidents with acute injuries and fatalities–particularly in Mass Casualty Incidents (MCI) in low-resource urban sub-Saharan African cities–research was undertaken to create an evidence-based algorithm that could be used to assess and geospatially link EMS needs in Kumasi, Ghana, to trauma resources. Our examination showed that non-MCI fatalities was approximately 2.5%, however, MCI fatalities were found to be 1.8 times higher–at 4.3%, indicating significant opportunities in the planning, preparedness, care, and transport among MCI patient management.

Therefore, several studies (funded through Fulbright-Fogarty and Fulbright Specialist programs), supported the development of the A-E-M-S (Assess-EOP-Map-Simulate) Medical Mass Casualty Algorithm that began networking accident ‘hotspots’ to existing trauma-level capabilities and surge capacity competencies in eight specified Kumasi hospitals. This low-cost response model promises to be an innovative alternative to long-term infrastructure development and high-priced resource distributions. Use of GIS and UAV drones allowed response systems to geospatially locate, classify, shift, and/or augment resources as needed in conjunction with hotspots.

Sample sizes were averaged at 295 for all patients' ages, with only a sample size of 292 for adults at 95% confidence intervals, and a standard deviation of 0.5. A total of 300 road-traffic accident victims were collected at KATH A&E in February-May, 2017, utilizing handheld devices by four researchers 24/7 daily.

Our examination showed that non-MCI fatalities were approximately 2.5%, however, MCI fatalities were found to be 1.8 times higher–at 4.3%, indicating significant opportunities in the planning, preparedness, care, and transport among MCI patient management.

To date–and in partnership with Kwame Nkrumah University of Science and Technology, Komfo Anokye Teaching Hospital, Ghana Medical Council, Health Services, National Disaster Management Organization, and others–over 306 Ghanaian healthcare providers from 80 different facilities have been trained in the AEMS program.

Emergency medical services planners and providers consider the needs of many special populations (infants, elderly, disabled, etc.) during a disaster. However, the critical distinctions in gender-specific care, which are based not only on a woman's physiological makeup, but also within her psychosocial framework should be not overlooked. This research identifies key factors in female-specific care, including: (1) 12 risk factors that affect vulnerability, impact, and exposure; (2) post-traumatic stress disorder and pain; (3) triage and advocacy; and (4) supplies and services.

More than 110 surveys were conducted among post-disaster females in the US and South Africa to obtain critical gender-disaggregated data in health services, aid, resources, and evacuations.

The results support the contention that many gender-sensitive services and supplies were needed in post-disaster care settings, but were inadequate or non-existent.

Research indicates a pattern of gender differentiation in all areas of the disaster process—preparedness, response, impact, risk perception and exposure, recovery, and reconstruction. The research also issues and emphasizes interventions that could significantly reduce pain, suffering, and costs. These research conclusions indicate a dearth of gender-disaggregated data and the need for EMS planners and providers to take a more cognizant and proactive approach to gender-specific care in preparedness, triage, psychosocial needs assessment, aid, and advocacy.