Perspectives on Preparedness for Chemical, Biological, Radiological, and Nuclear Threats in the Middle East and North Africa Region: Application of Artificial Intelligence Techniques.

Over the past 3 decades, the diversity of ethnic, religious, and political backgrounds worldwide, particularly in countries of the Middle East and North Africa (MENA), has led to an increase in the number of intercountry conflicts and terrorist attacks, sometimes involving chemical and biological agents. This warrants moving toward a collaborative approach to strengthening preparedness in the region. In disaster medicine, artificial intelligence techniques have been increasingly utilized to allow a thorough analysis by revealing unseen patterns. In this study, the authors used text mining and machine learning techniques to analyze open-ended feedback from multidisciplinary experts in disaster medicine regarding the MENA region's preparedness for chemical, biological, radiological, and nuclear (CBRN) risks. Open-ended feedback from 29 international experts in disaster medicine, selected based on their organizational roles and contributions to the academic field, was collected using a modified interview method between October and December 2022. Machine learning clustering algorithms, natural language processing, and sentiment analysis were used to analyze the data gathered using R language accessed through the RStudio environment. Findings revealed negative and fearful sentiments about a lack of accessibility to preparedness information, as well as positive sentiments toward CBRN preparedness concepts raised by the modified interview method. The artificial intelligence analysis techniques revealed a common consensus among experts about the importance of having accessible and effective plans and improved health sector preparedness in MENA, especially for potential chemical and biological incidents. Findings from this study can inform policymakers in the region to converge their efforts to build collaborative initiatives to strengthen CBRN preparedness capabilities in the healthcare sector.

[Clinical and epidemiological features of COVID-19-related deaths in Tunisia before the emergence of VOCs (March 2020-February 2021)]. / Caractéristiques cliniques et épidémiologiques des décès COVID-19 en Tunisie avant l'émergence des VOCs (mars 2020-février 2021).

Introduction: the purpose of this study was to describe the clinical and epidemiological features of COVID-19-related deaths in Tunisia notified at the ONMNE (National Observatory of New and emerging Diseases) between 2nd March 2020 and 28th February 2021 and to compare COVID-19-related deaths recorded in Tunisia with the international data. Methods: we conducted a national prospective longitudinal descriptive study of data collected from the National Surveillance System of SARS-CoV-2 infection of the ONMNE, Ministry of Health. All COVID-19-related deaths that occurred in Tunisia between March 2020 and February 2021 were included in this study. Data were collected from hospitals, municipalities and regional health departments. Death notifications were collected from multiple data sources (triangulation): The Regional Directorate of Basic Health Care, the ShocRoom (Strategic Health Operations Center), public and private health facilities, the Crisis Unit of the Presidency of the Government, the Directorate for Hygiene and Environmental Protection, the Ministry of Local Affairs and the Environment, as part of the follow-up of confirmed cases by the ONMNE team, positive RT-PCR / TDR post mortem results. Results: during this study, 8051 deaths were recorded, corresponding to a proportional mortality of 10.4%. The median age was 73 years, with an interquartile range of 17 years. Sex-ratio (M/F) was 1.8. The crude death rate was 69.1/100 000 inhabitants and fatality rate was 3.5%. The analysis of the epidemic curve showed 2 peaks of deaths on 29th October 2020 and 22nd January 2021, with 70 and 86 deaths notified respectively. The spatial distribution of mortality showed that the southern Tunisian region had the highest mortality rate. Patients aged 65 and over were most affected (73.7% of cases) with a crude mortality rate of 570.9/100,000 inhabitants and a fatality rate of 13.7%. Conclusion: prevention strategy based on public health measures must be reinforced by the rapid deployment of anti-COVID-19 vaccination, especially for people at risk of death.

Harnessing inter-disciplinary collaboration to improve emergency care in low- and middle-income countries (LMICs): results of research prioritisation setting exercise.

BACKGROUND: More than half of deaths in low- and middle-income countries (LMICs) result from conditions that could be treated with emergency care - an integral component of universal health coverage (UHC) - through timely access to lifesaving interventions. METHODS: The World Health Organization (WHO) aims to extend UHC to a further 1 billion people by 2023, yet evidence supporting improved emergency care coverage is lacking. In this article, we explore four phases of a research prioritisation setting (RPS) exercise conducted by researchers and stakeholders from South Africa, Egypt, Nepal, Jamaica, Tanzania, Trinidad and Tobago, Tunisia, Colombia, Ethiopia, Iran, Jordan, Malaysia, South Korea and Phillipines, USA and UK as a key step in gathering evidence required by policy makers and practitioners for the strengthening of emergency care systems in limited-resource settings. RESULTS: The RPS proposed seven priority research questions addressing: identification of context-relevant emergency care indicators, barriers to effective emergency care; accuracy and impact of triage tools; potential quality improvement via registries; characteristics of people seeking emergency care; best practices for staff training and retention; and cost effectiveness of critical care - all within LMICs. CONCLUSIONS: Convened by WHO and facilitated by the University of Sheffield, the Global Emergency Care Research Network project (GEM-CARN) brought together a coalition of 16 countries to identify research priorities for strengthening emergency care in LMICs. Our article further assesses the quality of the RPS exercise and reviews the current evidence supporting the identified priorities.

Psychological crisis intervention response to the COVID 19 pandemic: A Tunisian centralised Protocol.

In order to manage the urgent psychological need for support in response to the anticipated reaction of the population to the COVID-19 pandemic, we developed a new psychological crisis intervention model by implementing a centralised psychological support system for all of Tunisia. We set up a helpline which is accessible throughout the country, including those without access to Internet. This model integrates medical students, child and adolescent psychiatrists, psychiatrists, psychologists and social services to provide psychological intervention to the general population and medical staff. It will make a sound basis for developing a more effective psychological crisis intervention response system.