Background: The COVID-19 pandemic has positioned fragile healthcare systems in low-income countries under pressure, leading to critical gaps in service delivery. The pandemic response demands the healthcare system to be resilient and continue provision of healthcare services. This review is aimed at describing the healthcare response challenges during the pandemic in Ethiopia. Methodology: Eligible studies dealing with challenges of the healthcare system in response to the COVID-19 pandemic in Ethiopia were included. The six World Health Organization (WHO) healthcare system building blocks were used to categorize healthcare challenges. PubMed ProQuest, databases were searched, and results were summarized using systematic review synthesis. Results: Financial constraints led to a shortage of mechanical ventilators. Furthermore, the pandemic hindered the capacity to avail full packages of personal protective equipment in health facilities and intensive care capacity. The pandemic also affected the delivery of maternal, child and new-born services, prevention, and treatment of childhood illness, including immunization services. Conclusions: The COVID-19 pandemic posed various challenges to the performance of the healthcare system in Ethiopia. It is recommended that policy makers and stakeholders enhance pandemic preparedness and strengthen response capacity by considering the six WHO healthcare system building blocks.

Heatwaves pose an important risk for population health and are associated with an increased demand for emergency care. To find factors causing such overload, an online Delphi study included 15 experts in emergency medicine, disaster medicine, or public health. One open-ended question was delivered in the first round. After content analysis, the obtained statements were sent to the experts in two rounds to be rated on a 7-point linear scale. Consensus was defined as a standard deviation ≤ 1.0. Thirty-one statements were obtained after content analysis. The experts agreed on 18 statements, mostly focusing on the input section of patient processing and identifying stakeholders, the population, and primary care as targets of potential interventions. Additional dedicated resources and bed capacity were deemed important as per throughput and output sections, respectively. These findings could be used in the future to implement and test solutions to increase emergency healthcare resilience during heatwaves and reduce disaster risk due to climatic change.

The application and provision of prehospital care in disasters and mass-casualty incident response in Europe is currently being explored for opportunities to improve practice. The objective of this translational science study was to align common principles of approach and action and to identify how technology can assist and enhance response. To achieve this objective, the application of a modified Delphi methodology study based on statements derived from key findings of a scoping review was undertaken. This resulted in 18 triage, eight life support and damage control interventions, and 23 process consensus statements. These findings will be utilized in the development of evidence-based prehospital mass-casualty incident response tools and guidelines.

Background: Assessing the current landscape of nurses’ knowledge and attitudes is a critical first step in facilitating a smooth and effective transition toward artificial intelligence (AI)–enhanced critical care. Objective: This study aimed to assess the levels of and factors affecting the knowledge of and general attitudes toward AI in critical care among nurses. Methods: A cross-sectional correlational design was used with 203 critical care nurses in Hail, Saudi Arabia, using the Nurses’ AI Knowledge Questionnaire and the 20-item General Attitudes Toward Artificial Intelligence Scale from May 2025 to July 2025. Data were analyzed using 2-tailed t tests, ANOVA, Pearson correlation, and multivariable linear regression. Statistical significance was set at P <.05. Results: Critical care nurses demonstrated moderate knowledge of (mean score 4.93, SD 1.78) and positive attitudes toward AI (mean score 64.39, SD 8.26). A moderate positive correlation was found between knowledge of and attitudes toward AI ( r =0.45; P <.001). In multivariable analyses, older age was associated with lower knowledge (≥40 years: β=−1.29, 95% CI −2.12 to −0.45; P =.003) and less positive attitudes (β=−8.97, 95% CI −12.49 to −5.44; P <.001). Female nurses reported lower knowledge (β=−0.69, 95% CI −1.20 to −0.19; P =.007) and less positive attitudes (β=−2.65, 95% CI −4.78 to −0.52; P =.02) than male nurses. Greater experience (>5 years) was positively associated with knowledge (β=1.20, 95% CI 0.65‐1.75; P <.001) and attitudes (β=8.08, 95% CI 5.76‐10.41; P <.001). Conclusions: Critical care nurses in Hail demonstrated moderate knowledge of and positive attitudes toward AI, which varied based on their demographic and professional characteristics. These findings highlight the need to strengthen AI literacy and provide targeted support to groups with lower scores, which may enhance readiness for AI integration in critical care settings.

The Hospital Safety Index is a tool developed by the World Health Organization and the Pan American Health Organization in 2008 and updated in 2015. Although it is the most widely used instrument of its kind to assess the level of hospital preparedness, scientific literature on its application in real life is scarce. This study aimed to investigate the use of the Hospital Safety Index to assess disaster preparedness in healthcare facilities. A retrospective, qualitative study employing semi-structured online interviews was conducted to gather the opinions and perspectives of professionals who have experience in applying the Hospital Safety Index. Authors of scientific publications using the Hospital Safety Index were recruited. A semi-structured interview guide was developed. It addressed different phases of data collection with the Hospital Safety Index, the challenges and facilitators of using it, and recommendations for future adaptations. Data were analysed using inductive thematic analysis. Nine participants who were from three countries (Serbia, Sri Lanka, and Indonesia) and had different professional backgrounds (medical doctors, engineers, spatial planners, etc.) participated in this study. A total of 5 themes and 15 subthemes emerged during data analysis. Most of the participants reported their reasons for choosing the Hospital Safety Index as being its comprehensiveness and the fact that it was issued by the World Health Organization. The tool appears to be very specific and allows investigators to spot details in hospitals; however, it is not easy to use, and training is highly encouraged to learn how to navigate the different components of the tool. Governmental support is a crucial facilitator for investigators to be able to enter hospitals and conduct their evaluations. Overall, the tool has a lot of potential, and it should be used to reach a broader audience, such as community members, and assess the preparedness of other facilities that can take part in the response to disasters (hotels, stadiums, schools, etc.). Nevertheless, it still needs more adaptations to be tailored to different contexts and settings.

Aim: The aim of this paper is to outline the steps taken to develop an operational checklist to assess primary healthcare (PHC) all-hazards disaster preparedness. It then describes a study testing the applicability of the checklist. Background: A PHC approach is an essential foundation for health emergency and disaster risk management (H-EDRM) because it can prevent and mitigate risks prior to disasters and support an effective response and recovery, thereby contributing to communities’ and countries’ resilience across the continuum of the disaster cycle. This approach is in line with the H-EDRM framework, published by the World Health Organization (WHO) in 2019, which emphasizes a whole-of-health system approach in disaster management and highlights the importance of integrating PHC into countries’ H-EDRM. Nevertheless, literature focusing on how to practically integrate PHC into disaster management, both at the facility and at the policy level, is in its infancy. As of yet, there is no standardized, validated way to assess the specific characteristics that render PHC prepared for disasters nor a method to evaluate its role in H-EDRM. Methods: The checklist was developed through an iterative process that leveraged academic literature and expert consultations at different stages of the elaboration process. It was then used to assess primary care facilities in a province in Italy. Findings: The checklist offers a practical instrument for assessing and enhancing PHC disaster preparedness and for improving planning, coordination, and funding allocation. The study identified three critical areas for improvement in the province’s PHC disaster preparedness. First, primary care teams should be more interdisciplinary. Second, primary care services should be more thoroughly integrated into the broader health system. Third, there is a notable lack of awareness of H-EDRM principles among PHC professionals. In the future, the checklist can be elaborated into a weighted tool to be more broadly applicable.