Preparedness Strategies Research Articles

Predictors for vaccine hesitancy among nursing students in Namibia

Background: Healthcare workers (HCWs) are a priority group targeted for vaccination because they are greatly exposed to infectious agents.Aim: To determine the prevalence of coronavirus disease 2019 (COVID-19) vaccination and associated risk factors for vaccine hesitancy to recommend vaccine uptake strategies among student nurses.Setting: The study was carried out at the University of Namibia, main campus in Windhoek.Methods: A cross-sectional study was undertaken using a proportionate stratified sampling method. The total sample for the study was 509 students. Statistical Package for the Social Sciences (SPSS) 29 was used to analyse data. Frequencies and proportions were calculated. Bivariate analysis and multiple logistic regression were conducted to pronounce the predictors for vaccine hesitancy.Results: Only 31.40% students were vaccinated against COVID-19. Out of the vaccinated, 41.80% (p 0.001) were previously infected with COVID-19. Participants who were not HCWs before nursing school were most likely not to be vaccinated (p 0.001). Most unvaccinated students were hesitant because of a lack of information about the COVID-19 vaccine’s side effects (50.36%) and not knowing its effectiveness (38.13%). A total 60.80% of the participants believed a vaccine was needed to overcome the pandemic.Conclusion: We recommend the creation of targeted awareness campaigns that shed more light on the benefits of vaccination and vaccine side effects.Contribution: The study identifies key factors that can be targeted to change student nurses’ behaviour towards vaccination and offers valuable data that can inform preparedness and response strategies for future pandemics in Namibia and similar regions.

Embankment Breach Simulation and Inundation Mapping Leveraging High-Performance Computing for Enhanced Flood Risk Prediction and Assessment

Abstract. Embankment breaches represent significant hazards to communities and infrastructure, precipitating catastrophic flood occurrences. The precise prediction of floods and understanding the scope of inundation stemming from embankment failures are imperative for effective disaster preparedness and response. This research delves into a case study on simulating embankment breaches to evaluate the extent of flooding. Leveraging advanced hydrodynamic models validated through high-performance computing (HPC) systems, and integrating real-time data assimilation, we aim to improve accuracy in flood forecasting. The study endeavours to bolster flood risk management by furnishing detailed inundation maps and insights into embankment breach dynamics, thereby facilitating enhanced preparedness and response strategies. Our findings reveal that simulations conducted on multicore processors offer superior performance compared to single-core setups, yielding enhanced result accuracy and providing administrators with increased lead time. It unlocks high-resolution simulations for intricate basin details, explores a wider range of flood scenarios quickly, and allows for efficient ensemble modelling to assess model uncertainty. Through HPC utilization, we can harness high-resolution digital elevation models (DEMs) for 2D-hydrodynamic modelling, enabling rapid assessment of water spread resulting from embankment breaches within a mere 20-minute timeframe, a significant improvement from the previous 3–4 hours duration.

Genomic surveillance of Canadian airport wastewater samples allows early detection of emerging SARS-CoV-2 lineages

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has shown wastewater (WW) surveillance to be an effective means of tracking the emergence of viral lineages which arrive by many routes of transmission including via transportation hubs. In the Canadian province of Ontario, numerous municipal wastewater treatment plants (WWTPs) participate in WW surveillance of infectious disease targets such as SARS-CoV-2 by qPCR and whole genome sequencing (WGS). The Greater Toronto Airports Authority (GTAA), operator of Toronto Pearson International Airport (Toronto Pearson), has been participating in WW surveillance since January 2022. As a major international airport in Canada and the largest national hub, this airport is an ideal location for tracking globally emerging SARS-CoV-2 variants of concern (VOCs). In this study, WW collected from Toronto Pearson’s two terminals and pooled aircraft sewage was processed for WGS using a tiled-amplicon approach targeting the SARS-CoV-2 virus genome. Data generated was analyzed to monitor trends of SARS-CoV-2 lineage frequencies. Initial detections of emerging lineages were compared between Toronto Pearson WW samples, municipal WW samples collected from the surrounding regions, and Ontario clinical data as published by Public Health Ontario. Results enabled the early detection of VOCs and individual mutations emerging in Ontario. On average, the emergence of novel lineages at the airport preceded clinical detections by 1–4 weeks, and up to 16 weeks in one case. This project illustrates the efficacy of WW surveillance at transitory transportation hubs and sets an example that could be applied to other viruses as part of a pandemic preparedness strategy and to provide monitoring on a mass scale.

Enhancing Environmental Sensitivity and Vulnerability Assessments for Oil Spill Responses in the Caspian Sea

Oil spills pose significant threats to marine and coastal ecosystems, necessitating advanced methodologies for environmental sensitivity and vulnerability assessments. This study enhances existing frameworks to better manage oil spill risks in the Caspian Sea, a region characterized by its ecological sensitivity and economic dependence on oil extraction. Utilizing the Environmental Sensitivity Index (ESI), we adapted global standards to the unique conditions of the Caspian Sea and built a sensitivity map of the coastline, which later became one of the components of the integral sensitivity map for the entire Caspian Sea, which includes several biotic and abiotic components. We also developed a comprehensive geodatabase incorporating topographic, infrastructural, and hydrodynamic data. Through the sophisticated modeling of oil spill scenarios using the Oil Spill model of the MIKE 21 software (Release 2016) suite, we simulated spills of varying magnitudes to analyze their potential impacts on the marine and coastal environment. The results enabled the creation of vulnerability maps, pinpointing areas at highest risk and facilitating strategic response planning. Our study demonstrates the critical importance of integrating advanced geospatial analyses and dynamic modeling techniques to improve oil spill preparedness and response strategies. The findings of this study suggest that enhanced monitoring and adaptive management strategies are essential for protecting the Caspian Sea from environmental risks posed by its oil industry.

3.X.2. Integrating trust as a key component of pandemic preparedness and resilience

Abstract Trust is a key component of pandemic preparedness, which impacts the success of response measures during the public health emergency. Trust is built during preparedness, however the drivers and dimensions of trust are complex and context-specific. What is required is a collaborative, inclusive approach that provides a platform for communities to express their questions and concerns. The proposed workshop will begin with a presentation from a global expert on trust in the content of epidemics and pandemics and the current knowledge about how trust can be built during preparedness. This will be followed by interactive group-work, designed to encourage collaborative discussions and decision-making. Finally, introducing the WHO Hive digital platform that provides a safe space for public health communities to share information and ask questions. Attendees will then reconvene in plenary to discuss these approaches and interventions that can be implemented to build and maintain trust prior to and during an epidemic or pandemic. This workshop has the following objectives: 1. To demonstrate how trust is an important determinant of successful pandemic response; 2. To enable attendees to explore how the implementation of public health and social measures, infodemic management and digital community partnerships and engagement can build trust during pandemic preparedness for both online and offline communities; 3. To provide opportunity for attendees to workshop how the different features of the Hive digital space can enhance trust building, and to develop actionable strategies for health emergency preparedness, response and resilience. The workshop will deliver these objectives through an interactive simulation activity. Attendees will be placed into small groups to work through a scenario, having to decide on the actions that need to be taken, considering budget constraints, other health priorities, and the current local context. The teams will co-create actionable strategies for building and maintaining trust. While there is not a one size fits all approach to trust building, this workshop will aim to increase understanding of the drivers and determinants of trust to encourage participants to consider how they can be applied in their local context. It will be interactive and hands-on requiring active participation from participants. Key messages • Trust as a construct is an important component of pandemic preparedness and readiness that impacts on response. • A multidimensional approach to building and sustaining trust needs to considered across a range of drivers and determinants, where actionable strategies are vital.

4.C. Scientific session: Navigating through complex challenges of responding to outbreaks of multidrug-resistant organisms

Abstract Antimicrobial resistance is one of the top ten global public health threats according to the WHO, contributing to millions of deaths each year. While outbreaks of multidrug-resistant organisms (MDROs) are well studied in hospital and nursing home settings, knowledge gaps exist concerning the complex challenges of outbreaks of MDROs among vulnerable patient populations, such as patients with intellectual disabilities or elderly patients living longer at home with multiple comorbidities. The coordination of such outbreaks requires a multidisciplinary approach as these patients often receive care throughout different healthcare settings, including long-term care and home-based nursing care. We delve into the complexities of coordinating an MDRO outbreak response involving healthcare professionals from various healthcare settings. The challenges inherent to the coordination of multidisciplinary involvement and the use of innovative strategies for outbreak preparedness and surveillance, will be thoroughly examined based on scientific evidence and practice based experiences. Workshop objectives • To exchange experiences on managing cross-institutional outbreaks of MDROs • To foster deeper understanding of the complexities of multidisciplinary involvement during MDRO outbreaks among vulnerable patient populations The workshop structure: - A brief introduction will be provided on the generic challenges in providing long-term care to vulnerable patient populations carrying MDROs. We will subsequently illustrate potential challenges faced during a cross-institutional MDRO outbreak among these patients through a realistic scenario (5 min): A patient with severe intellectual and physical disabilities living in both a long-term care facility as well as with family at home, unexpectedly turns out to be carrying an MDRO after recent hospital admission. As the patient receives nursing care from both from family members and nursing staff in different healthcare settings, a cross-institutional MDRO outbreak has occurred requiring a coordinated response. - Hereafter, individual presenters will address evidence- and experience-based challenges faced in MDRO outbreak responses within the specific healthcare settings covered in the previously presented scenario. We will navigate through the scenario together with the participants, discussing practical and ethical dilemmas, and explore ways for containing the MDRO outbreak while maintaining effective and compassionate healthcare delivery. In addition, we will discuss the use of public health innovations, such as social network analysis as a basis for the development of a stress test exercise to improve preparedness for MDRO outbreaks, and the role of wastewater surveillance in MDRO outbreaks. Discussions will be facilitated by (online) voting tools to invite participants to exchange experiences (40 min). We conclude with an exciting quiz to summarize the key messages of this workshop (10 min). Key messages • Healthcare setting, knowledge, proportionality and well-being of vulnerable patients populations are important to acknowledge during cross-institutional MDRO outbreaks. • Novel stress test exercise and wastewater surveillance are potential methods to improve preparedness and surveillance, respectively, during cross-institutional MDRO outbreak responses.

Emergency Department admissions for Acute Respiratory Infections: a retrospective analysis

Abstract Background Acute Respiratory Infections (ARIs) have a relevant impact on public health in terms of prevalence and costs associated with the diseases. The COVID-19 pandemic highlighted the need to adopt accurate surveillance systems to respond to new emergencies and meet the demand for access to care. The aim of our work is to describe the accesses at the Emergency Departement (ED) of the Pisa University Hospital (AOUP), Italy, for ARIs, from 2017 to 2021. Methods A retrospective analysis of electronic medical records from the AOUP was conducted from January 2017 to December 2021. The analysis focused on ED admissions and positive lab test results, examining their correlation with ED visits caused by ARI. Multiple linear regression models were used to understand the influence of viral laboratory results on ARI-related ED admissions, adjusting the results for age. The study also assessed the contribution of each virus incausing ARI within different age groups. Results 33,101 (annual average 5,520) ARI admissions in ED were registered, resulting in 7,426 hospital admissions (22.8%, annual average 1,163) with a seasonal pattern between week 42 of each year and week 17 of the following year. The reduction in emergency room admissions in 2020 (weekly average of 78.2, compared to 144.3 in 2017-2019) may be due to the restrictions implemented for the COVID-19 pandemic. Nevertheless, the average weekly rate of ED admissions caused by ARI was 30.8% in 2020, as compared with 21.7% in 2017-2019. Analysis by age group showed a peak of accesses in the last weeks of 2021 for the <1 and 1-4 years old age groups. Conclusions Data on ARI-related admissions provide valuable insights into the dynamic patterns of seasonal air-borne infections and age-related vulnerabilities. This could be useful in directing health policies to identify indicators of future epidemic waves, contributing to the ongoing efforts to enhance preparedness and response strategies for respiratory infections. Key messages • It is important to create an integrated surveillance system to monitor and respond to ARIs. • Strategies should prioritise vaccination campaigns, particularly for RSV and influenza.

Lessons learned and new approaches to stockpiling for public health emergencies

Abstract Background The COVID-19 pandemic highlighted the need to improve preparedness for emerging health threats. This includes reserving assets for use in health emergencies, such as, shelters, energy supply items, and a stockpile of medical countermeasures (MCMs). Learnings from the recent pandemic are key to improving future strategies for preparedness in Ireland and across Europe. Methods Semi-structured interviews were conducted with key representatives in France, Latvia, Lithuania, the Netherlands, and Norway. These countries were chosen as they have a similar threat profile to Ireland. The interviews aimed to understand the national approach taken in each country to stockpiling of MCMs for public health emergencies. Interview summaries were developed and reviewed by key representatives for clarity. Thematic analysis was conducted. Results All of the key representatives interviewed were working within their associated Department of Health, or a government affiliated public health agency. Themes and key findings identified included scope and current stockpiling approaches; cost considerations and efficiency, and an understanding of how stockpiling approaches have evolved overtime. While some countries stockpiled items such as facemasks, gloves and ventilators during the COVID-19 pandemic, this is being reviewed, due to the high costs involved. Additionally, all countries reported that waste due to unused stock was a challenge, however, the use of stock rotation can reduce stock waste. Choice of supplier is also key for security of supply. Using indigenous suppliers can facilitate a scale up of supply in times of crises. Conclusions National MCMs stockpiles are a key resource that may be deployed as part of a response to health emergencies and disasters. Reducing waste was a key priority and challenge for all countries. Measures identified to reduce waste in future included active management of stockpiles, stock rotation and the use of indigenous suppliers. Key messages • As a result of the COVID-19 pandemic, many countries are reviewing their current approach to stockpiling. • Key issues for countries included preventing waste and ensuring security of MCM supply.

ERIMS assessment Tool Enhances Emergency Response in WHO Europe Region

Abstract Issue/problem The implementation of an Emergency Response Information Management System (ERIMS) assessment tool improves health emergency responses within the World Health Organization - European Region. The tool’s deployment aims to refine data management processes and bolster preparedness strategies. Managing health information systems (HIS) effectively during emergencies is a persistent challenge, as technologies keep innovating and potential challenges are constant. The ERIMS assessment tool addresses this by offering a structured approach, ensuring improved emergency responses and system resilience. Description of the problem Adopting a systems approach, the ERIMS tool was designed to be flexible, allowing adaptation to various HIS architectures and emergency coordination mechanisms. Its design and development process included consultations with digital health and emergency management experts and field testing across three WHO member states. Results Field applications of the ERIMS assessment tool demonstrated its capacity to evaluate, including, digital capability and knowledge management with focus on emergency scenarios. The tool identified systemic gaps, offered strategic guidance on enhancing data processes, and fortified decision-making protocols. These outcomes not only highlighted the tool’s utility in assessing HIS readiness but also its impact in improving emergency response mechanisms. Lessons The deployment of the ERIMS assessment tool enhanced HIS by providing an evaluation of emergency preparedness and response capabilities with a focus at the national perspective level. The tool’s application showcased its role in advancing public health emergency preparedness, illustrating how assessments can lead to substantial improvements in health information management and emergency response readiness. Key messages • ERIMS assessment implementation improves emergency data management. • Better preparedness relies on boosting digital capabilities and knowledge management.

Excess mortality during COVID-19 pandemic in Bangladesh - evidence from a rural survey.

The coronavirus disease 2019 (COVID-19) had a profound impact worldwide. In Bangladesh, the official number of deaths for COVID-19 was around 29 000. However, many countries including Bangladesh experienced substantial underreporting of COVID-19 deaths due to lack of complete national civil registration system. This study aims to estimate excess mortality in 2020, identify risk factors, and determine leading causes of death in Bangladesh. In February 2021, we conducted a cross-sectional household survey in Sitakunda, a subdistrict of Chattogram, identifying deaths from January 2018 to December 2020. Excess mortality was quantified using the p-score and incidence rate ratio (IRR) utilising Poisson segmented regression. We employed the InterVA-5 algorithm to attribute causes of death. Proportional distribution and cause-specific mortality rates (CSMR) per 100 000 individuals were compared between pre-pandemic and pandemic periods. Among 1748 deaths from 25 669 households, we found 1.4 (95% confidence interval (CI) = 1.2-1.4) times excess mortality in 2020 compared to 2018-2019. Leading causes of death in 2020 included cardiac disease (CSMR = 121.0, CI = 115.8-127.3), stroke (CSMR = 108.0, CI = 102.6-114.0), and acute respiratory infection (CSMR = 61.0, CI = 55.1-66.5), all displaying significantly higher mortality rates than in previous years. Older age (IRR = 1.6), less education (IRR = 1.8), and lower socio-economic groups (IRR = 2.1) had higher mortality rates in 2020 compared to pre-pandemic years. Our study suggests high rural excess mortality during COVID-19 including cardiac disease, stroke and acute respiratory infection as the leading causes of deaths. We require targeted strategies to identify high-risk patients with comorbidity and social vulnerabilities that contribute to mortality to guide the preparedness strategy for future pandemics.

Fire at Sea: A 70-year Review of Fire-Related Mass Casualty Events on U.S. Aircraft Carriers.

A major fire at sea is among the most devastating events that can occur while a U.S. Navy combatant vessel is underway. Since World War II, no attack on a large U.S. Navy capital ship has occurred during combat operations. However, increasing global tensions raise the threat of future peer adversary naval combat, and shipboard medical caregivers must be prepared for mass casualty events in the deployed maritime environment. To better prepare modern naval caregivers for this possibility, we reviewed mass casualty events from major fires aboard large U.S. Navy aircraft carriers from 1950 through 2020 to summarize available objective data and identify lessons learned. Underway fires from any cause aboard U.S. Navy aircraft carriers and large amphibious assault ships causing more than 10 casualties (injuries + deaths) were reviewed from 1950 through 2020 using available open access sources including literature review, the Naval Safety Command mishap database, and U.S. Navy Judge Advocate Manual reports. Of 246 fires identified, 27 met inclusion criteria resulting in 1,634 casualties with a combined crew mortality of 23% of those injured. In the 16 events with at least 1 death, 2.0% of the total crew was injured with a combined mortality of 28%. All mishaps occurred while underway during routine training or combat operations; none were caused by an enemy combatant attack. Those events affecting more than 5% of the crew were particularly devastating resulting in a mortality rate of 29% of 1,056 total casualties. Given that main medical spaces may be damaged or destroyed during major fires from any cause, identified lessons learned included the need for (1) distributed medical supplies, (2) flexible medical treatment locations throughout the ship, (3) specific training to prepare non-physician caregivers and non-medical first responders to provide burn and hemorrhagic shock resuscitation, airway management, and prolonged care at or near the point of injury, and (4) the prolonged holding capability of critically ill burned and injured patients if evacuation off the ships is unavailable. Shipboard fires underway pose a significant threat to crew safety with a mortality of nearly a quarter of those injured. These fire mass casualty events immediately overwhelm shipboard medical capabilities requiring a complex response from all hands beginning with non-medical first responders. Notably, all events occurred outside of direct enemy combat, potentially underestimating the impact and number of casualties of a shipboard fire during naval combat. Advances in peer weaponry and the threat of future conflict emphasize the need for pre-deployment burn care training for all shipboard medical caregivers as well as advanced airway and resuscitation training for non-physician caregivers. This review underscores the profound impact of shipboard fires on crew safety, highlighting the critical need for enhanced preparedness and response strategies to prepare for fire-related mishaps during routine operations and naval combat.

Evaluating the performances of SVR and XGBoost for short-range forecasting of heatwaves across different temperature zones of India

This research aims to forecast maximum temperatures and the frequency of heatwave days across four different temperature zones (Zone 1, 2, 3 and 4) in India. These four zones are categorized based on the 30-year average maximum temperatures (T30AMT) during the summer months of April, May, and June (AMJ). Two Machine Learning (ML) algorithms eXtreme Gradient Boosting (XGBoost) and Support Vector Regression (SVR) are employed to achieve this goal. The study utilizes nine key atmospheric variables namely air temperature, geopotential height, relative humidity, U-wind, V-wind, soil moisture, solar radiation, sea surface temperature, and mean sea level pressure at a daily scale spanning from 1991 to 2020 for the months of March, April, May, and June as predictors. The India Meteorological Department daily maximum temperature data spanning from 1991 to 2020 for the months of AMJ serves as the predictands. ML models are developed using spatially averaged atmospheric variables and daily maximum temperature across the grids falling within each temperature zone. Results indicate that for a 7-day lead time, SVR outperforms XGBoost in Zone-1 (T30AMT > 38 °C) and Zone-2 (T30AMT: 35.01 °C–38 °C) by more accurately capturing peak temperatures during training and testing. Conversely, for a 15-day lead time in Zone-1, XGBoost better predicts temperature peaks in both phases. In Zone-3 (T30AMT: 30 °C–35 °C) and Zone-4 (T30AMT < 30 °C) for both lead times, the performance of both models decline, indicating models and input variables are more effective in predicting higher temperatures typical of Zone-1 and 2 but less so in Zone-3 and 4. In a nutshell, the study attempts to highlight the capability of advanced ML techniques combined with spatial climate data to enhance the prediction of extreme heatwave events. These insights can aid in heatwave preparedness, climate management, and adaptation strategies for different Indian temperature zones.

Development of Potential Slip Surface Identification Model for Active Deep-Seated Landslide Sites: A Case Study in Taiwan

Identifying locations of landslide slip surfaces provides critical information for understanding the volume of landslides and the scale of disasters, both of which are essential for formulating disaster preparedness and mitigation strategies. Based on hydrogeological survey data from 24 deep-seated landslide-prone sites in Taiwan’s mountainous regions, this study developed the hydraulic conductivity potential index (HCPI) using principal component analysis to quantify the hydraulic properties of disturbed rock formations with six geological factors. Then, regression analysis was performed to construct a permeability estimation model for the geological environment of landslides. Finally, the established model was utilized to develop an identification method for potential slip depths in landslide-prone sites. Results indicated a strong relation between HCPI and hydraulic conductivity with a determination coefficient of 0.895. The relation equation confirmed that the data it generated concerning the depths of significant changes in hydraulic conductivity could be used to identify potential slip surfaces. Additionally, this study successfully established a rule for identifying potential slip zones by summarizing data concerning the generated hydraulic conductivity profiles, stratigraphic lithology, existing inclinometer slip depth records, and groundwater level of landslide sites. This identification method was then applied to predict potential slip depths for ten landslide sites where slip surfaces have not yet occurred. These findings offer a new alternative to having early information on potential sliding depths for timely disaster management and control implementation.

Resilience and preparedness of hospitals for pandemics: Lessons learned from COVID-19

Amidst the COVID-19 pandemic, health systems around the world took a lot of pressure, and the resilience of these systems has been addressed in thedisaster management and COVID-19 literature. However, little focus has been given to the resilience of hospitals in general. Therefore, the study assessed one hospital in the Free State province of South Africa as a preliminary study for a project that will look at all hospitals in the Free State province. The study assessed the following: (1) the preparedness and actionable strategies that were implemented across the waves of the COVID-19 pandemic; (2) the resilience plans of the hospitals and also determined (3) the resilience of the hospital amid the COVID-19 pandemic; (4) the vulnerabilities exposed by the COVID-19 pandemic in the hospital. Using the R statistical program and modelling, I found that the study hospital was not prepared holistically for the COVID-19 pandemic. The five generalised linear mixed models and the general linear models applied did not show significant differences for the most important variables used to measure resilience. The models showed the hospital to be less resilient to pandemics. Several vulnerabilities were recorded across the hospital.Contribution: This study’s findings suggest that the studied hospital is not resilient to pandemics and will be able to make recommendations to relevant government departments to work together to strengthen the resilience of the country’s healthcare system once the project is completed.

Child Preparedness for Infertility Disclosure: A Diagnostic Tool for Supporting Parent and Child Mental Health

Infertility, often perceived as an adult issue, can also manifest in childhood, presenting unique challenges. Improper handling of infertility disclosures can strain parent–child relationships and potentially lead to significant psychological distress, including depression, anxiety, and long-term impacts on self-image. Despite the critical nature of these conversations, parents often report receiving little or no guidance from professionals on how or when to disclose this information to their child. This article introduces the Child Readiness for Infertility Disclosure (CRID) Assessment Tool, designed to empirically guide parents and marriage and family counselors in assessing a child's readiness for receiving information about infertility. The CRID tool integrates the concepts of Tiered Priming and Cognitive Preparedness strategies, providing structured recommendations grounded in Erickson's Stages of Psychosocial Development for age-appropriate and developmentally suitable disclosure along with an applied case study.

Emergence of mpox in the Eastern Mediterranean Region: Data assessment and implications for a public health response

IntroductionMonkeypox (mpox) is an illness caused by the MPX virus and endemic to certain African countries. Historically, sporadic outbreaks have occurred in some non-endemic areas. In 2022, a new variant emerged, clade IIb, causing a global outbreak sustained within sexual networks among men who have sex with men (MSM). To our knowledge, this is the first multi-country study examining mpox epidemiology and clinical features of the 2022–2023 outbreak caused by clade IIb across the Eastern Mediterranean Region (EMR). MethodsWe analyzed datasets of anonymous mpox case-based reports submitted to the World Health Organization (WHO) from May 2022 to December 2023 in the EMR to describe the cumulative incidence, demographics, transmission routes, and clinical outcomes. ResultsBy the end of 2022, 95 case reports were submitted to the WHO. The first case of mpox was reported in the United Arab Emirates on May 24, 2022. The highest number of cases were reported from Lebanon (27 confirmed cases). Most cases in the EMR were adult males (92 %), 60 % identifying as MSM, and 10 % living with HIV. Most reported symptoms were rash (95.4 %) and fever (69.6 %). No intensive care unit admissions or deaths were reported. ConclusionIn this study we investigated the epidemiology, clinical presentation, and outcomes of the mpox outbreak related to clade IIb in the EMR. We raise concerns about the accuracy and completeness of the data, given that the number of cases reported to the WHO from EMR countries appears to be significantly lower than the number of cases documented within the region. This discrepancy could impact the reliability of the reported figures and the region's response strategies. Despite these challenges, collaborative efforts across EMR countries have laid the groundwork for effective outbreak response, underscoring the importance of ongoing regional cooperation to enhance future preparedness strategies.

Development of Vertical Radar Reflectivity Profiles Based on Lightning Density Using the Geostationary Lightning Mapper Dataset in the Subtropical Region of Brazil

The study aims to develop vertical radar reflectivity profiles based on lightning density data from the Geostationary Lightning Mapper (GLM) on the GOES-16 satellite in the subtropical region of Brazil. The primary objective is to improve the assimilation of lightning data in numerical weather prediction models. The methodology involves the analysis of polarimetric radar data from Chapecó-SC and Jaraguari-MS, spanning from January 2019 to December 2023, and their correlation with lightning data from the GLM. Radar reflectivity profiles were created for different lightning density classes, categorized into six classes based on geometric progression. Results show a significant relationship between lightning activity and radar reflectivity, with distinct profiles for convective and stratiform events. These findings demonstrate the potential of using GLM data to enhance short-term weather forecasting, particularly for severe weather events. The study concludes that the integration of GLM data into weather models can lead to more accurate predictions of intense precipitation events, contributing to better preparedness and response strategies.

Optimised prediction of tunnel fire heat release rate using the ResNet18_2CLSTM model with bagging for multimodal data

Accurate predictions of HRR will improve preparedness and response strategies, enhance safety, and minimise damage in tunnel fires. In this study, a deep learning prediction model for HRR under multimodal data fusion is proposed. A multimodal dataset is first established to obtain flame images and flue gas time series data through model-scale tunnel fire experiments. During the model training process, ResNet18 was used to extract features from the flame image, and 2CLSTM was employed to understand the time series of the flame image features and flue gas features to establish the correlation with the HRR. It was evaluated that the error analyses of the measured and predicted values of the validation set yielded R2 greater than 0.85, with errors and standard deviations less than 4 kW. And the model predicted better in the flame growth and decay phases. However, there is some deviation in the predictions near the peak HRR. To address this issue, the Bagging algorithm was introduced to optimise the model. The results show that the ResNet18_2CLSTM model with Bagging reduces the RMSE by 20.47 % and increases the R2 by 4.64 % compared to the original model, and the accuracy is greatly improved.

‘The coronavirus is a formidable foe’: children’s multimodal articulations of SARS-CoV-2 virus and COVID-19 pandemic experiences in China

Objective This study explored children’s post-pandemic articulations regarding the coronavirus along with their lived experiences during the COVID-19 pandemic. Design A qualitative survey featuring drawings, comments, questions and follow-up interviews was employed to gather data from 108 infected children aged 13 to 14 from two middle schools in China. This multimodal approach allowed for a rich capture of the children’s articulations of their pandemic experiences. Results Children’s multimodal articulations conveyed not only the biological features of, but also their emotional reactions to the coronavirus. The pandemic had disrupted children’s lives, making online learning, sleep and screen engagement dominant in their daily routines, while also compounding children’s unhappiness primarily due to restrictions on social interactions. Children associated the coronavirus with biological, medical, psychological and social aspects. Increased sanitisation and hygiene habits featured their pre‐to-post pandemic changes. Furthermore, children exhibited an awareness regarding preventive measures and transmission modes, albeit with certain biases or gaps. Their misunderstandings about recuperative strategies merit clarification. Conclusion The COVID-19 pandemic has had profound and multifaceted impacts on children’s emotional well-being, daily routines, social interactions, education, and health-related behaviors. Children’s multimodal articulations revealed a spectrum of adverse effects caused by the pandemic, calling for targeted health interventions to mitigate these negative effects while also equipping children with resilience and coping skills for navigating future health crises. Incorporating children’s perspectives and experiences into future pandemic preparedness and health promotion strategies is essential for addressing their vulnerabilities and ensuring their overall well-being during public health crises.

Thematic review on counseling crisis and intervention in school

Crisis counseling and intervention in schools play a crucial role in addressing students' psychological needs during crisis, yet there is limited comprehensive literature reviewing their application and effectiveness.This thematic review synthesizes research on crisis counseling and intervention in schools, descriptions, and evaluations. A systematic search was conducted using the Scopus and Web of Science databases to identify relevant studies published between 2019 and 2023. A total of 25 studies were selected based on predefined inclusion criteria and were analyzed to extract key themes related to crisis counseling and intervention in schools. Three primary themes emerged from the analysis: (1) the roles of school counselors, (2) crisis preparedness, and (3) crisis intervention strategies. These themes were explored in relation to various methodologies used in the studies, highlighting multiple approaches counselors use to integrate crisis counseling knowledge for prevention and intervention within school settings. The review underscores the importance of school counselors' roles in crisis preparedness and intervention. However, further empirical research is needed to support and expand upon current recommendations, ensuring more effective crisis counseling practices in schools.