Global trend and epidemiological profiles of climate-related disasters from 2000 to 2021.

OBJECTIVE: The objective of this study is to analyse the epidemiological profile of global climate-related disasters in terms of morbidity and mortality, as well as to examine their temporal trends. METHOD: This cross-sectional study analysed climate-related global disasters from 2000 to 2021, utilising definitions and criteria from the United Nations Strategy for Disaster Reduction and the Centre for Research on the Epidemiology of Disasters. Data were sourced from the EM-DAT database. The study assessed trends over the entire period and compared them with previous years (1978-2000). RESULTS: A total of 7398 climate-related disasters were recorded, with hydrological disasters being the most frequent, followed by meteorological and climatological disasters. Statistically significant differences were noted in the average rates of affected individuals and injuries per million inhabitants. No significant trends were found in mortality rates, but the frequency trends for the entire period (1978-2021) and the subperiod (1978-2000) were increasing and statistically significant. However, the trend from 2000 onwards showed a non-significant decrease, potentially reflecting better disaster preparedness and response strategies under the Hyogo and Sendai Framework. CONCLUSION: The study highlights hydrological disasters as the most frequent and deadliest climate-related events, with climatological disasters affecting and injuring the most people. The lack of standardised criteria for disaster inclusion in databases presents a significant challenge in comparing results and analysing trends. Establishing uniform inclusion criteria is crucial for effective data analysis and disaster management.

The epidemiological profile of incidence and mortality from epidemics in complex humanitarian emergencies from 1990 to 2022 - A scoping review.

AIM: This study aimed to investigate the impact of communicable diseases with epidemic potential in complex emergency (CE) situations, focusing on the epidemiological profile of incidence and mortality and exploring underlying factors contributing to increased epidemic risks. METHODS: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Review (PRISMA-ScR) guidelines, we conducted a scoping review of articles published between 1990 and 2022. The search included terms related to complex emergencies, communicable diseases, outbreaks, and epidemics. We identified 92 epidemics related to CE occurring in 32 different countries. RESULTS: Communicable diseases like Shigellosis, Cholera, Measles, Meningococcal meningitis, Yellow Fever, and Malaria caused significant morbidity and mortality. Diarrhoeal diseases, particularly Cholera and Shigellosis, had the highest incidence rates. Shigella specifically had an incidence of 241.0 per 1000 (people at risk), with a mortality rate of 11.7 per 1000, while Cholera's incidence was 13.0 per 1000, with a mortality rate of 0.22 per 1000. Measles followed, with an incidence of 25.0 per 1000 and a mortality rate of 0.76 per 1000. Meningococcal Meningitis had an incidence rate of 1.3 per 1000 and a mortality rate of 0.13 per 1000. Despite their lower incidences, yellow fever at 0.8 per 1000 and malaria at 0.4 per 1000, their high case fatality rates of 20.1% and 0.4% remained concerning in CE. The qualitative synthesis reveals that factors such as water, sanitation, and hygiene, shelter and settlements, food and nutrition, and public health and healthcare in complex emergencies affect the risk of epidemics. CONCLUSION: Epidemics during complex emergencies could potentially lead to a public health crisis. Between 1990 and 2022, there have been no statistically significant changes in the trend of incidence, mortality, or fatality rates of epidemic diseases in CE. It is crucial to understand that all epidemics identified in CE are fundamentally preventable.

Performance of Google bard and ChatGPT in mass casualty incidents triage.

AIM: The objective of our research is to evaluate and compare the performance of ChatGPT, Google Bard, and medical students in performing START triage during mass casualty situations. METHOD: We conducted a cross-sectional analysis to compare ChatGPT, Google Bard, and medical students in mass casualty incident (MCI) triage using the Simple Triage And Rapid Treatment (START) method. A validated questionnaire with 15 diverse MCI scenarios was used to assess triage accuracy and content analysis in four categories: "Walking wounded," "Respiration," "Perfusion," and "Mental Status." Statistical analysis compared the results. RESULT: Google Bard demonstrated a notably higher accuracy of 60%, while ChatGPT achieved an accuracy of 26.67% (p = 0.002). Comparatively, medical students performed at an accuracy rate of 64.3% in a previous study. However, there was no significant difference observed between Google Bard and medical students (p = 0.211). Qualitative content analysis of 'walking-wounded', 'respiration', 'perfusion', and 'mental status' indicated that Google Bard outperformed ChatGPT. CONCLUSION: Google Bard was found to be superior to ChatGPT in correctly performing mass casualty incident triage. Google Bard achieved an accuracy of 60%, while chatGPT only achieved an accuracy of 26.67%. This difference was statistically significant (p = 0.002).

A Review of Mpox Outbreak and Public Health Response in Spain.

Objective: In May 2022, an unprecedented Mpox outbreak was reported in several non-endemic countries with unknown epidemiological links. Since May 2022, more than 20,000 cases have been reported in Europe. Spain has been the most affected country in Europe. We aim to describe the Mpox epidemiological profile in Spain, identify its outbreak risks, and describe public health interventions implemented by the Spanish authorities. Methods: A literature review was conducted, using specific selection criteria to obtain relevant publications describing Mpox clinical presentation and risk factors and the public health response in Spain to the ongoing outbreak. Results: 63.1% of the cases presented an anogenital rash, considered a specific and early symptom in this outbreak. Low case fatality rate is observed, mainly in risk groups, such as the immunocompromised population. Patients evolution was generally favorable, although 3-8% required hospitalization and two deaths occurred; 40% of patients were previously diagnosed with HIV infection. Most of the cases were seen among young population and concentrated in men who had sex with other men, mainly with multiple sexual partners, who did not practice safe sex such as using condoms, and those attending mass event parties. Conclusion: To date, the Mpox outbreak is not considered a public health emergency of international concern. The epidemiological trend of the virus in Spain shows that public health response interventions (health education, contact tracing, vaccination, etc.) have adequately controlled the epidemic curve in high-risk populations and avoided spreading the virus to other groups within the community.

Exploring Cascading Disaster Risk During Complex Emergencies: Chemical Industry Disaster Risk Assessment in the Aftermath of the Kakhovka Dam Bombing in Ukraine.

OBJECTIVE: This risk assessment aims to investigate the analysis of cascading disaster risks from the perspective of the chemical industry and public health subsequent to the Kakhovka dam bombing in Ukraine. METHOD: The study utilized a modified observational cross-sectional risk assessment method to assess disaster risk. The method involved identifying the location of chemical factories, determining flooded or at-risk factories, analyzing the type and frequency of chemical hazards, assessing population exposure, and plotting a disaster risk metric. Data on chemical industries and flood extent were collected from open-source secondary data. RESULTS: The destruction of the Kakhovka dam in June 2023 led to severe flooding, placing 42 000 individuals at risk. The analysis identified four chemical factories, with 1 affected by flooding and 3 at risk. The overall risk assessment indicated a high likelihood and severe consequences, including loss of life, environmental contamination, and property damage. CONCLUSION: The combination of complex emergencies and high-risk chemical facilities in Kherson Oblast poses a significant risk of a chemical industry disaster. The interplay between compound and cascading risks during complex emergencies amid the current war further exacerbates the situation, leading to the devastation and destruction of the environment to the detriment of life, and aligns with the characterization of ecocide.

Total worker health® based Helicobacter pylori public health prevention strategy.

Purpose of review: This review aims to explore the public health approach for Helicobacter pylori Infection Prevention within the Total Worker Health (TWH) framework strategy. Recent findings: The review identifies certain occupations considered high-risk groups for H. pylori infection. It underscores primary, secondary, and tertiary public health preventive measures align with the TWH approach. Within this framework, the role of raising awareness, emphasizing infection control, worker hygiene, risk assessment, and ensuring healthcare accessibility is emphasized. The importance of early detection, treatment, eradication, and a TWH approach emerges as a central theme. The TWH approach offers a holistic perspective, intertwining occupation-related health risks with overall health and well being. Summary: Adopting the TWH approach, coupled with household-based infection control and eradication strategies, can significantly reduce H. pylori prevalence, fostering a healthier workforce and diminishing long-term healthcare costs. The review underscores the importance of recognizing H. pylori as an occupational disease. It calls for further research into the "one-health" perspective on H. pylori transmission dynamics.

Development, validation, and accuracy of ORCHESTRA emotional exhaustion screening questionnaire among healthcare workers during COVID-19 Pandemic.

BACKGROUND: The COVID-19 pandemic has posed unprecedented challenges, particularly for healthcare workers (HCWs). The prolonged struggles exposed the HCWs to a variety of stressors, potentially leading to burnout. Emotional exhaustion is widely recognized as the core component of burnout. This research aims to conceptualize and develop an emotional exhaustion screening questionnaire through literature review, validation, and accuracy testing. METHOD: A literature review of questionnaires and extraction of items on emotional exhaustion were performed in June 2022. We proceed with the face validity of the items by experts. The items with good content validity ratio and index were selected and reworded to suit the context of HCWs working during the COVID-19 pandemic. A pilot test of the questionnaire was done in the Central University Hospital of Asturias (HUCA) from October to December 2022 with a sample of 148 HCWs from the ORCHESTRA cohort to determine its reliability, convergent validity, and accuracy. RESULTS: Our literature review identified 15 validated questionnaires. After exclusion, 32 items were sent for content validation by experts, yielding five final items that proceeded with the pilot test. Resulting in a Cronbach's alpha-coefficient of .83 for the scale and .78 for dichotomous responses, demonstrating good internal consistency and convergent validity. The result of our accuracy test yielded sensitivity (90.6%) and specificity (91.6%) for the OEEQ scale; and sensitivity (88.7%) and specificity (89.5%) for OEEQ dichotomous responses. CONCLUSION: This study developed and validated the ORCHESTRA Emotional Exhaustion Questionnaire, demonstrating the questionnaire's clarity, relevance, and comprehensibility in screening emotional exhaustion among HCWs.

Novel Google Maps and Google Earth application for chemical industry disaster risk assessment during complex emergencies in Eastern Ukraine.

The war in Ukraine has led to complex emergencies, humanitarian crises, and other severe consequences, such as chemical industry disasters. The chemical industry is one of the principal sectors of Ukraine's economy. In 2019, Ukraine had a total volume of hazardous chemical accumulation of more than a 5.1billion tons. Therefore, an attack on chemical industrial facilities will lead to catastrophic consequences such as chemical disasters. This paper aims to study the disaster risk of chemical industrial facilities and its effects on public health and the environment during complex emergencies in Eastern Ukraine. Observational cross-sectional risk assessment method was utilized to assess hazard, vulnerability, and exposure of the chemical industry in Eastern Ukraine in Donetsk Oblast and Luhansk Oblast. Data on chemical factories in Eastern Ukraine was collected on Google Maps and Google Earth on May 2022. Lastly, the semi-quantitative risk assessment method was utilized to describe the risk from the perspective of consequences for life and health, the environment, property, and speed of development. Our disaster risk assessment found more than 1 million people (1,187,240 people) in Donetsk Oblast and more than 350 thousand people (353,716 people) in Luhansk Oblast are exposed to potential hazards from the chemical facilities clusters. The aggregation risk of bombardment of chemical facilities cluster in Eastern Ukraine is also high due to ongoing war. Therefore, the chemical industry disaster risks for Eastern Ukraine during complex emergencies in Donetsk Oblast and Luhansk Oblast are high in terms of likelihood and consequences to life and health, environment, property, and speed of development.

ChatGPT's performance before and after teaching in mass casualty incident triage.

Since its initial launching, ChatGPT has gained significant attention from the media, with many claiming that ChatGPT's arrival is a transformative milestone in the advancement of the AI revolution. Our aim was to assess the performance of ChatGPT before and after teaching the triage of mass casualty incidents by utilizing a validated questionnaire specifically designed for such scenarios. In addition, we compared the triage performance between ChatGPT and medical students. Our cross-sectional study employed a mixed-methods analysis to assess the performance of ChatGPT in mass casualty incident triage, pre- and post-teaching of Simple Triage And Rapid Treatment (START) triage. After teaching the START triage algorithm, ChatGPT scored an overall triage accuracy of 80%, with only 20% of cases being over-triaged. The mean accuracy of medical students on the same questionnaire yielded 64.3%. Qualitative analysis on pre-determined themes on 'walking-wounded', 'respiration', 'perfusion', and 'mental status' on ChatGPT showed similar performance in pre- and post-teaching of START triage. Additional themes on 'disclaimer', 'prediction', 'management plan', and 'assumption' were identified during the thematic analysis. ChatGPT exhibited promising results in effectively responding to mass casualty incident questionnaires. Nevertheless, additional research is necessary to ensure its safety and efficacy before clinical implementation.

Point-of-care ultrasonography in diagnosing necrotizing fasciitis-a literature review.

INTRODUCTION: Necrotizing fasciitis (NF) is a rapidly progressive necrosis of the fascial layer with a high mortality rate. It is a life-threatening medical emergency that requires urgent treatment. Lack of skin finding in NF made diagnosis difficult and required a high clinical index of suspicion. The use of ultrasound may guide clinicians in improving diagnostic speed and accuracy, thus leading to improved management decisions and patient outcomes. This literature search aims to review the use of point-of-care ultrasonography in diagnosing necrotizing fasciitis. METHOD: We searched relevant electronic databases, including PUBMED, MEDLINE, and SCOPUS, and performed a systematic review. Keywords used were "necrotizing fasciitis" or "necrotising fasciitis" or "necrotizing soft tissue infections" and "point-of-care ultrasonography" "ultrasonography" or "ultrasound". No temporal limitation was set. An additional search was performed via google scholar, and the top 100 entry was screened. RESULTS: Among 540 papers screened, only 21 were related to diagnosing necrotizing fasciitis using ultrasonography. The outcome includes three observational studies, 16 case reports, and two case series, covering the period from 1976 to 2022. CONCLUSION: Although the use of ultrasonography in diagnosing NF was published in several papers with promising results, more studies are required to investigate its diagnostic accuracy and potential to reduce time delay before surgical intervention, morbidity, and mortality.

Sensitivity and Specificity of Spanish Prehospital Advanced Triage Method (META).

INTRODUCTION: Mass-casualty incident (MCI) triage systems aim to provide the best possible health care to the greatest number of affected people with the available resources in the context of a mass-casualty event. The Spanish Prehospital Advanced Triage Method (Modelo Extrahospitalario de Triaje Avanzado; META) was designed to improved patient sorting in MCIs. OBJECTIVE: The aim of this study was to estimate and compare sensitivity and specificity of META and the Manchester Triage System (MTS) in MCIs by retrospectively applying both triage algorithms to real MCI patients from the Emergency and Disaster Research Unit (Unidad de Investigación en Emergencia y Desastres; UIED) MCI database. METHOD: This was a comparative study of two triage methods using sensitivity and specificity with the Revised Trauma Score (RTS) as the gold standard. A total of 134 MCI patients from the UIED database were included. An MCI in Asturias is defined as an incident that involves four or more victims that require ambulance mobilization. RESULTS: Patients mean age was 39.85 years (95% CI, 35.9-43.8) with an age range from one to 88 years old. In total, 54.4% of the patients were female. The most common types of MCI involved were fires (51.0%), followed by road traffic accident (43.3%) and street fight (3.7%). For MTS, the overall sensitivity was 30.6% (95% CI, 22.9-39.1) and specificity was 66.0% (95% CI, 60.0-71.7). For META triage algorithm, the overall sensitivity was 79.9% (95% CI, 72.1-86.3) and specificity was 89.9% (95% CI, 85.7-93.3). CONCLUSION: The META triage algorithm is a reliable triage system; thus, it can be recommended to be used in an MCI.