Future Incidence Research Articles

The potential clinical impact and cost-effectiveness of the updated COVID-19 mRNA fall 2023 vaccines in the United States

Aims To assess the potential clinical impact and cost-effectiveness of COVID-19 mRNA vaccines updated for fall 2023 in adults aged ≥18 years over a 1-year analytic time horizon (September 2023-August 2024). Materials and methods A compartmental Susceptible-Exposed-Infected-Recovered model was updated to reflect COVID-19 cases in summer 2023. The numbers of symptomatic infections, COVID-19–related hospitalizations and deaths, and costs and quality-adjusted life-years (QALYs) gained were calculated using a decision tree model. The incremental cost-effectiveness ratio (ICER) of a Moderna updated mRNA fall 2023 vaccine (Moderna Fall Campaign) was compared to no additional vaccination. Potential differences between the Moderna and the Pfizer-BioNTech fall 2023 vaccines were also examined. Results Base case results suggest that the Moderna Fall Campaign would decrease the expected 64.2 million symptomatic infections by 7.2 million (11%) to 57.0 million. COVID-19–related hospitalizations and deaths are expected to decline by 343,000 (-29%) and 50,500 (-33%), respectively. The Moderna Fall Campaign would increase QALYs by 740,880 and healthcare costs by $5.7 billion relative to no vaccine, yielding an ICER of $7700 per QALY gained. Using a societal cost perspective, the ICER is $2100. Sensitivity analyses suggest that vaccine effectiveness, COVID-19 incidence, hospitalization rates, and costs drive cost-effectiveness. With a relative vaccine effectiveness of 5.1% for infection and 9.8% for hospitalization for the Moderna vaccine versus the Pfizer-BioNTech vaccine, use of the Moderna vaccine is expected to prevent 24,000 more hospitalizations and 3300 more deaths than the Pfizer-BioNTech vaccine. Limitations and conclusions As COVID-19 becomes endemic, future incidence, including patterns of infection, are highly uncertain. The effectiveness of fall 2023 vaccines is unknown, and it is unclear when a new variant that evades natural or vaccine immunity will emerge. Despite these limitations, our model predicts the Moderna Fall Campaign vaccine is highly cost-effective across all sensitivity analyses.

Abstract 16742: Deep-Learning-Derived Retinal Cardiovascular Risk Predictor (Reti-CVD) and 14 Cardiovascular Conditions in UK Biobank

Introduction: The advent of sophisticated deep learning algorithms has now made it possible to predict the risk of cardiovascular diseases (CVDs) using retinal images. We had previously developed a retina-based deep learning model, Reti-CVD, trained on coronary artery calcium (CAC) data, which successfully predicted future CVD incidents in a longitudinal study. Hypothesis: This study aims to investigate the cross-sectional association between Reti-CVD and 13 distinct CVDs, alongside arterial hypertension. Methods: Our cross-sectional analysis involved 45,980 participants from the UK Biobank at baseline. To discern the differential cardiovascular risk associated with Reti-CVD, we studied a wide array of CVDs. These included cerebrovascular diseases, aneurysms, thrombo-embolic diseases, other CVDs (coronary artery disease, aortic valve stenosis, atrial fibrillation, heart failure, and peripheral vascular disease), and arterial hypertension. We defined CVD outcomes based on the international classification of disease codes. We used logistic regression, adjusted for hypertension, diabetes, dyslipidemia, and smoking, to estimate the correlations between Reti-CVD and the defined CVD outcomes. Results: In the cross-sectional study, after adjusting for CVD risk factors, we found the highest tertile of Reti-CVD scores to be significantly associated with 11 outcomes in comparison to the first tertile (adjusted Odds Ratio [OR], 95% Confidence Interval [CI]). These include: Coronary artery disease (OR=10.37, 95% CI, 7.58-14.18), peripheral vascular disease (9.65, 2.94-31.64), atrial fibrillation (9.36, 6.51-13.45), aortic valve stenosis (8.13, 1.87-35.35), heart failure (7.33, 3.64-14.77), ischemic stroke (4.70, 2.30-9.59), transient ischemic attack (4.17, 2.07-8.40), arterial hypertension (3.17, 2.78-3.61), pulmonary embolism (3.00, 1.86-4.84), deep vein thrombosis (2.54, 1.70-3.80), and cerebrovascular diseases (2.36, 1.63-3.42). Notably, we found suggestive evidence of an inverse association of Reti-CVD tertiles with subarachnoid haemorrhage. Conclusions: This study demonstrates that higher Reti-CVD scores correlate with an elevated risk across a broad range of cardiovascular conditions.

Abstract 17498: Association Between 5-Year Change in Cardiovascular Risk and Atherosclerotic Cardiovascular Disease Incidence: A Multicohort Study

Introduction: Early measurement of atherosclerotic cardiovascular disease (ASCVD) risk factors contains valuable information about an individual's risk history. Hypothesis: Individuals with different historical cardiovascular risk statuses have varied risks of future ASCVD incidence. Methods: We analyzed pooled data from 7 community-based prospective cohort studies with up to 20-year follow-ups ( panel A ). White or Black participants aged 40-75 years without prevalent ASCVD were included. Cardiovascular risk was assessed using the pooled cohort equation and was categorized into non-high (<20%) or high risk (≥20%). Changes in CVD risk over a 5-year interval were considered. The main outcome is incident ASCVD. Results: Among 11026 participants (mean [SD] age,60.0 [8.1] years). 4272 (38.7%) were female and 3127 (28.4%) were Black. During a median follow-up of 9.9 years, 2560 (23.2%) ASCVD events occurred. Compared to individuals with consistently high risk, participants with non-high to high risk (HR 0.67; 95%CI 0.59-0.77), high to non-high risk (HR 0.57; 95%CI 0.41-0.80), and consistently non-high risk (HR 0.33; 95%CI 0.29-0.37) had a lower risk of incident ASCVD. Compared to individuals with consistently non-high risk, participants with high to non-high risk (HR 1.74; 95%CI 1.26-2.41), non-high to high risk (HR 2.04; 95%CI 1.84-2.27), and consistently high risk (HR 3.03; 95%CI 2.69-3.42) had an increased risk of incident ASCVD ( panel B ). Conclusions: Changes in the CVD risk status over time inform dissimilar ASCVD risk than a single risk assessment. Dynamic risk evaluation might enable more accurate cardiovascular risk stratification and decision on preventive interventions should take historical risk status into account.

The Prognostic Value of Arterial Stiffness According to Socioeconomic Status.

Individuals of low socioeconomic status (SES) often exhibit increased cardiovascular risk factors and a worse prognosis. We conducted this study to ascertain whether brachial-ankle pulse wave velocity (baPWV), a straightforward and reliable measure of arterial stiffness, can hold prognostic value for people with low SES. We retrospectively analyzed a total of 1266 subjects (mean age 64.6 ± 11.6 years; 47.2% female) without documented cardiovascular disease who had undergone baPWV measurement. The subjects included 633 National Health Insurance Beneficiaries (NHIB) and 633 Medical Aid Beneficiaries (MAB), matched for major clinical features through a 1:1 propensity score matching method. Major adverse cardiovascular events (MACE), such as death, non-fatal myocardial infarction, non-fatal ischemic stroke, coronary revascularization, and heart failure necessitating admission, were assessed during the clinical follow-up. During a median follow-up period of 4.2 years (interquartile range, 2.2-5.7 years), there were 77 MACE cases (6.1%). In multivariable Cox regression analyses, baPWV was identified as a significant predictor of MACE in both groups, regardless of the use of three different baPWV criteria (median value, Asian consensus recommendation, and cut-off value obtained by receiver operating characteristic [ROC] curve analysis). In both groups, the baPWV value obtained using ROC curve analysis emerged as the best predictor of MACE. This predictive value was stronger in the NHIB group (hazard ratio, 5.80; 95% confidence interval, 2.30-14.65; p < 0.001) than in the MAB group (hazard ratio, 3.30; 95% confidence interval, 1.57-6.92; p = 0.002). baPWV was associated with future MACE incidence in both NHIB and MAB groups. Since baPWV is simple and cost-effective to measure, it could be efficiently used as a risk stratification tool for individuals with low SES.

Epidemiology and etiology of diffuse large B-cell lymphoma

As the most common non-Hodgkin lymphoma subtype, diffuse large B-cell lymphoma (DLBCL) incidence patterns generally parallel that for NHL overall. Globally, DLBCL accounts for a third of all NHLs, ranging between 20% and 50% by country. Based on United States (U.S.) cancer registry data, age-standardized incidence rate for DLBCL was 7.2 per 100,000. DLBCL incidence rises with age and is generally higher in males than females; in the U.S., incidence is highest among non-Hispanic whites (9.2/100,000). Like NHL incidence, DLBCL incidence rose in the first half of the 20th century but has largely plateaued. However, there is some evidence that incidence rates are rising in areas of historically low rates, such as Asia; there are also estimates for rising DLBCL incidence in the near future due to the changing demographics in developed countries whose aging population is growing. Established risk factors for DLBCL include those that result in severe immune deficiency such as HIV/AIDS, inherited immunodeficiency syndromes, and organ transplant recipients. Factors that lead to chronic immune dysregulations are also established risk factors, and include a number of autoimmune conditions (eg, Sjögren syndrome, systemic lupus erythematosus, rheumatoid arthritis), viral infections (eg, HIV, KSHV/HHV8, HCV, EBV), and obesity. Family history of NHL/DLBCL, personal history of cancer, and multiple genetic susceptibility loci are also well-established risk factors for DLBCL. There is strong evidence for multiple environmental exposures in DLBCL etiology, including exposure to trichloroethylene, benzene, and pesticides and herbicides, with recent associations noted with glyphosate. There is also strong evidence for associations with other viruses, such as HBV. Recent estimates suggest that obesity accounts for nearly a quarter of DLBCLs that develop, but despite recent gains in the understanding of DLBCL etiology, the majority of disease remain unexplained. An understanding of the host and environmental contributions to disease etiology, and concerted efforts to expand our understanding to multiple race/ethnic groups, will be essential for constructing clinically relevant risk prediction models and develop effective strategies for disease prevention.

The effect of combination prevention strategies on HIV incidence among gay and bisexual men who have sex with men in the UK: a model-based analysis

In the UK, the number of new HIV diagnoses among gay and bisexual men who have sex with men (GBMSM) has decreased substantially. We aimed to understand the contribution of different interventions in reducing HIV incidence so far; to estimate future HIV incidence with continuation of current policies and with further scaling up of current interventions; and to estimate the maximum additional annual cost that should be spent towards these interventions for them to offer value for money. We calibrated a dynamic, individual-based, stochastic simulation model, the HIV Synthesis Model, to multiple sources of data on HIV among GBMSM aged 15 years or older in the UK. Primarily these were routine HIV surveillance data collected by the UK Health Security Agency. We compared HIV incidence in 2022 with the counterfactual incidence: if HIV testing rates stopped increasing in 2012 and the policy of antiretroviral therapy (ART) at diagnosis was not introduced in mid-2015; if pre-exposure prophylaxis (PrEP) was not introduced; if condom use was low from 2012 in all GBMSM, at levels similar to those observed in 1980; and in the first and second scenario combined. We also projected future outcomes under the assumption of continuation of current policies and considering increases in PrEP and HIV testing uptake and a decrease in condomless sex. Our model estimated a 77% (90% uncertainty interval [UI] 61-88) decline in HIV incidence since around 2014, with an estimated 597 infections ([90% UI 312-956]; 1·1 per 1000 person-years [90% UI 0·6-1·8]) in men aged 15-64 years in 2022. Both PrEP introduction and increased HIV testing with ART initiation at diagnosis each had a substantial effect on HIV incidence. Without PrEP introduction, we estimate there would have been 2·16 times the number of infections that actually occurred (90% UI 1·06-3·75) between 2012 and 2022; without increased HIV testing and ART initiation at diagnosis there would have been 2·18 times the number of infections that actually occurred (1·18-3·60), and if condomless sex was at the levels before the HIV epidemic, there would have been 2·27 times the number of infections that actually occurred (0·9-5·4). If rates of testing, ART use, and PrEP use remain as they are currently, there is a predicted decline in incidence to 388 HIV infections in 2025 (90% UI 226-650) and to 263 (137-433) in 2030. Increases in HIV testing and PrEP use were predicted to accelerate the decline in HIV incidence. Given the quality-adjusted life-year (QALY) benefit and a cost-effectiveness threshold of £30 000 per QALY gained, in order to be cost-effective an additional £1·62 million could be spent per year to increase testing levels by 34% (90% UI 25-46) and PrEP use by 55% (10-107). To achieve that, a 16% reduction in the cost of delivery of testing and PrEP would be required. Combination prevention, including a PrEP strategy, played a major role in the reduction in HIV incidence observed so far in the UK among GBMSM. Continuation of current activities should lead to a continued decline; however, it is unlikely to lead to reaching the target of fewer than 50 HIV infections per year among GBMSM by 2030. It will be important to reduce costs for testing and PrEP for their continued expansion to be cost-effective. National Institute for Health Research under its Programme Grants for Applied Research Programme and Medical Research Council-UK Research and Innovation.

Diagnosis of Chronic Kidney Disease Using Machine Learning Algorithm

A large percentage of people globally suffer from chronic kidney disease (CKD), a serious health concern. Effective diagnosis, treatment, and referral of CKD depend heavily on early identification and prediction of the disease. However, it is difficult to evaluate and derive significant insights from health data due to its vast and complicated nature. Engineers and medical researchers are using data mining techniques and machine learning algorithms to create predictive models for chronic kidney disease (CKD) in an effort to address this issue. The goal of this research is to create and validate predictive models for chronic kidney disease (CKD) based on a variety of clinical factors, including albuminuria, age, diet, eGFR, and pre-existing medical problems. The objective is to estimate the likelihood of renal failure, which may necessitate kidney dialysis or a transplant, and to evaluate the degree of kidney disease. With the use of this knowledge, patients and healthcare providers should be able to make well-informed decisions about diagnosis, treatment, and lifestyle changes. Patterns in the gathered data can be found, and future incidence of CKD or other related diseases can be predicted, by utilising MLT such as ANN and data mining techniques. Finding novel characteristics linked to the onset of renal disease and adding more trustworthy data from CKD patients. The best algorithm to categorise the data as CKD or NOT_CKD is chosen throughout the design process, and the data is then classified according to this differentiation. Estimated glomerular filtration rate (eGFR), which offers important details about the patient's current kidney function, is used to classify cases of chronic kidney disease. By combining complete patient data with machine learning algorithms, this research advances the diagnosis of chronic kidney disease (CKD) and improves patient outcomes.

Different outcomes between iso-osmolar and low-osmolar contrast media in acute myocardial infarction with renal impairment.

The selection of appropriate contrast media (CM) remains an important issue in terms of renal preservation in patients with acute myocardial infarction (AMI) and renal impairment scheduled for percutaneous coronary intervention (PCI). We compared the clinical outcomes of patients with AMI and renal impairment, depending on the CM type (iso-osmolar CM [IOCM] vs. low-osmolar CM [LOCM]) that was used during PCI. From the Convergent Registry of Catholic and Chonnam University for Acute Myocardial Infarction, 3174 post-PCI patients with AMI and renal impairment were subdivided into two groups (IOCM [n = 2101] and LOCM [n = 1073]). Regarding in-hospital clinical outcomes, the IOCM group had a higher peak creatinine (Cr) level and lower "Cr differential" than the LOCM group. A higher proportion of dialysis was noted in the IOCM group. In 30-day clinical outcomes, the IOCM group showed higher incidence of new-onset heart failure (HF) but lower incidence of revascularization than the LOCM group. The differences in in-hospital and 30-day clinical outcomes were attenuated after inverse probability of treatment weighting, except for new-onset HF. All other variables in 30-day clinical outcomes, including all-cause death, non-fatal myocardial infarction, cerebrovascular accidents, stent thrombosis, and any dialysis events, were similar between the two groups. IOCM use did not prevent future incidence of dialysis compared to LOCM use in AMI patients with renal impairment.

Historical Trends and Future Projections of Demand for Permanent Residential Aged Care for Older People in Australia, 2008–2052

ObjectivesTo examine the historical trends and predict the future rates and total volumes of permanent residential aged care (PRAC) service utilization in Australia. DesignA population-based repeated cross-sectional and projection study of non-indigenous older people (≥65 years) accessing PRAC in Australia was conducted. Setting and ParticipantsPublicly available aged care admissions from the Australian Institute of Health and Welfare and population estimates from the Australian Bureau of Statistics were used. MethodsHistorical incidence rates (per 1000 people), incidence rate ratios (IRRs) and 95% CIs of PRAC admission from 2008–2009 to 2020–2021 were estimated using negative binomial regression models. The future incidence and prediction intervals (PIs) of PRAC admission between 2021–2022 and 2051–2052 were projected using a generalized additive model-negative binomial regression. All estimates were adjusted or standardized by sex and age. ResultsBetween 2008–2009 and 2020–2021, the adjusted admission to PRAC decreased (from 23.6/1000 people to 15.7/1000 people with an IRR = 0.97/year, 95% CI 0.97–0.98). The projected PRAC admission rate will decrease to 12.1/1000 (95%PI 10.8–13.3) by 2037–2038 and 9.0/1000 (95%PI 7.6–10.4) by 2051–2052. The projected volume of PRAC admission will be 73,988 (95%PI 65,960–81,425) at its highest point in 2037–2038 and 64,579 (95%PI 54,258–74,543) in 2051–2052. Conclusions and ImplicationsThe utilization of PRAC has decreased in the past decade, and a predicted decrease in PRAC use in future years is estimated. However, the volume of PRAC utilization will still increase for the next 15 years (until 2037–2038) due to our increasingly older population. These findings can inform service planning of PRAC access in Australia.

Strategic planning for cancer control: Utilizing machine-learning models to predict future incidences

One of the top health issues in the world is the Cancer. The number of patients with various types of cancer registered in clinics, oncology centers and hospitals are annually increasing. Predicting the estimated number of future cancer incidences for subsequent years is an important topic and needs further study. In this paper, officially registered cases at the Ministry of Health, Iraq and Oncology Center at Kirkuk governorate are used to forecast three years ahead estimated number of incidences for different types of cancer using four machine-learning models. The considered models are; gaussian processes, multilayer perceptron (MLP), MLP regressor, and sequential minimal optimization regressor (SMOreg). The study reveals significant differences among different models based on performance metrics. Based on SMOreg analysis in 2023, most types of cancer are expected to see an increase in cases. For instance, bladder cancer is projected to rise from 13 cases in 2020 to around 33 cases in 2023, a 153.8% increase. Results show that, the prediction of incidence cases using SMOreg model is outperformed other algorithms with minimized error in most types of cancer. According to the results, there will be a rise in the number of incidences in the 2023 for most types of cancer except breast and non-hodgkin lymphoma cancer, which expected a decrease in the number of cases. By utilizing of three-year-ahead annual numbers of cancer cases predictions, governments will be able to hedge financial risks, provide patients care and plan for cancer control programs.

Analysis of applying a patient safety taxonomy to patient and clinician-reported incident reports during the COVID-19 pandemic: a mixed methods study

BackgroundThe COVID-19 pandemic resulted in major disruption to healthcare delivery worldwide causing medical services to adapt their standard practices. Learning how these adaptations result in unintended patient harm is essential to mitigate against future incidents. Incident reporting and learning system data can be used to identify areas to improve patient safety. A classification system is required to make sense of such data to identify learning and priorities for further in-depth investigation. The Patient Safety (PISA) classification system was created for this purpose, but it is not known if classification systems are sufficient to capture novel safety concepts arising from crises like the pandemic. We aimed to review the application of the PISA classification system during the COVID-19 pandemic to appraise whether modifications were required to maintain its meaningful use for the pandemic context.MethodsWe conducted a mixed-methods study integrating two phases in an exploratory, sequential design. This included a comparative secondary analysis of patient safety incident reports from two studies conducted during the first wave of the pandemic, where we coded patient-reported incidents from the UK and clinician-reported incidents from France. The findings were presented to a focus group of experts in classification systems and patient safety, and a thematic analysis was conducted on the resultant transcript.ResultsWe identified five key themes derived from the data analysis and expert group discussion. These included capitalising on the unique perspective of safety concerns from different groups, that existing frameworks do identify priority areas to investigate further, the objectives of a study shape the data interpretation, the pandemic spotlighted long-standing patient concerns, and the time period in which data are collected offers valuable context to aid explanation. The group consensus was that no COVID-19-specific codes were warranted, and the PISA classification system was fit for purpose.ConclusionsWe have scrutinised the meaningful use of the PISA classification system’s application during a period of systemic healthcare constraint, the COVID-19 pandemic. Despite these constraints, we found the framework can be successfully applied to incident reports to enable deductive analysis, identify areas for further enquiry and thus support organisational learning. No new or amended codes were warranted. Organisations and investigators can use our findings when reviewing their own classification systems.

Clinical characteristics of child and adolescent psychiatric outpatients engaging in fireplay or arson: a case–control study

BackgroundFireplay and arson incidents among children and adolescents have gained attention because of their potentially severe consequences and societal impacts. Understanding the underlying psychiatric characteristics of individuals engaging in fireplay or arson is crucial for early identification and targeted intervention. However, there is a lack of research conducted in clinical psychiatric populations in this context. This study compared the clinical characteristics of child and adolescent psychiatric outpatients who engaged in fireplay or arson with those without such behaviors.MethodsA retrospective case–control study was conducted using data collected from patients who visited the Department of Child and Adolescent Psychiatry at Kohnodai Hospital, National Center for Global Health and Medicine in Japan, between April 2014 and March 2022. Medical records were checked to see if the patient had practically committed behaviors that corresponded to fireplay or arson. The case group was identified using this process. After identifying the case and control groups, sex, diagnosis, antisocial behavior, abuse history, and children-to-parent violence were assessed and compared by careful review of medical records.ResultsThe study identified 64 patients who engaged in fireplay or arson, representing approximately 1.1% of the total 5,587 patients (case group). The median age of the patients’ first fire-related behavior was 13 years (range, 6–18 years). In the case group, 14.1% of the cases involved arson, resulting in substantial damage. Of the remaining 5523 patients, 2268 patients had datasets for the first consultation (control group). The most prevalent diagnosis in the case group was attention-deficit hyperactivity disorder (ADHD), present in 57.8% of the cases. The study revealed a significant association between fire-related behaviors and ADHD as well as antisocial behavior. Gender differences were observed, with boys being more likely to engage in fireplay or arson than girls.ConclusionsThis study suggests that clinicians and mental health professionals should closely consider male sex, ADHD, and antisocial behaviors as potential risk factors for fire-related behaviors. Monitoring the case group for the development of psychiatric disorders, including the use of illegal drugs, is recommended to prevent future arson incidents.

Analysis of the impact of Suez Canal blockage on the global shipping network

This study aims to quantitatively analyze the impact of the Suez Canal blockage on global maritime transportation networks. The Suez Canal, a critical global maritime transport route, experienced a significant disruption due to a ship grounding accident in March 2021, exposing the fragility of global logistics supply chains. We constructed a comprehensive shipping network, integrating real trajectory data from automatic identification system (AIS) devices on ships collected in 2018. The network comprises 2713 nodes and 137,830 links, with defined targeted (Suez Canal blockage) and random attack modes. Our analysis, based on multiple network topology metrics, reveals that the blockage had a considerable effect on the global shipping network, significantly more than random disruptions of comparable scale. The incident led to a decrease in network accessibility and connectivity, conforming to the law of distance attenuation. The effects varied across continents; Africa experienced the most significant impact, while Asia and Europe were less affected. Europe's developed transport system effectively mitigated the impact. Data on different ship types passing through the Suez Canal showed that container ships and petrochemical tankers were the most affected. This research underlines the Suez Canal's significance to global shipping and the necessity of robust supply chain management strategies to limit the fallout from similar future incidents.

An Ensemble Learning Approach for Fast Disaster Response using Social Media Analytics

Natural disaster happens, as a result of natural hazards that cause financial, environmental or human losses. Natural disasters strike unexpectedly, affecting the lives of tens of thousands of people. During the flood, social media sites were also heavily used to disseminate information about flooded areas, rescue agencies, food and relief centres. This work proposes an ensemble learning strategy for combining and analysing social media data in order to close the gap and progress in catastrophic situation. To enable scalability and broad accessibility of the dynamic streaming of multimodal data namely text, image, audio and video, this work is designed around social media data. A fusion technique was employed at the decision level, based on a database of 15 characteristics for more than 300 disasters around the world (Trained with MNIST dataset 60000 training images and 10000 testing images). This work allows the collected multimodal social media data to share a common semantic space, making individual variable prediction easier. Each merged numerical vector(tensors) of text and audio is sent into the K-CNN algorithm, which is an unsupervised learning algorithm (K-CNN), and the image and video data is given to a deep learning based Progressive Neural Artificial Search (PNAS). The trained data acts as a predictor for future incidents, allowing for the estimation of total deaths, total individuals impacted, and total damage, as well as specific suggestions for food, shelter and housing inspections. To make such a prediction, the trained model is presented a satellite image from before the accident as well as the geographic and demographic conditions, which is expected to result in a prediction accuracy of more than 85%.

The road to olympic failure is paved in poor risk management

In recent years there have been numerous high-profile incidents in professional cycling that have endangered the lives of cyclists, fellow competitors, and spectators in track and road disciplines. Yet, there has been little research conducted to ascertain why, and how things can be improved within the sport to improve safety. To illuminate this area, we apply safety culture theory to the now infamous Australian Cycling 2021 Olympic incident that saw their Olympians handlebar snap clean off during the competition. The results show that dimensions of safety culture are apparent in this incident, with distinct parallels between it and high-profile failures in other industries. The lack of adherence to rules, the existence of light-touch regulation, and management safety attitudes are concerning, and suggestive of a need for immediate improvement at a governing level. This research provides a conceptual basis for further research in the area to ensure interventions are effective at preventing future safety critical incidents within the sport.

Tactical leaders’ and collaborative organizations’ non-technical skills during major road tunnel incidents – An iterative focus group study

IntroductionLeadership during major incidents has been described as challenging and dependent on the non-technical skills of leaders. The complex tunnel environment contributes to an even more challenging incident response. Hence, this study aims to identify elements of non-technical skills when leading collaborative road-tunnel incident responses. MethodsThe study was conducted using four focus group discussions with tactical leaders from the rescue services, emergency medical services, police, and collaborative organizations from the emergency dispatch center and road-traffic control center. The data was analyzed using a non-technical skills taxonomy. ResultsTwelve non-technical skill elements emerged. Abilities to gather, sort, and proactively share relevant information and dispatch the correct resources were described. Additionally, abilities to prioritize actions and cooperate to establish a shared operational picture were found. Abilities to adjust leadership to the tunnel environment and conditions and assess the severity of the incident to make decisions were also described. ConclusionWhen managing a road-tunnel incident response, tactical leaders utilizes a range of non-technical skills. The elements of these skills were found to be specific both to the tunnel environment and the collaborative nature of the response. Further studies into and development of these skills are needed to facilitate a timely response and minimize potential risks to personnel or evacuees in future tunnel incident responses.

A-167 Repeatedly Positive Serum and Urine Beta-HCG Results in Non-Pregnant Patients—Application of Clinical Decision Support

Abstract Background In January of 2020, a 48-year-old woman, status post bilateral tubal ligation was postponed colonoscopy due to a positive urine and serum pregnancy point of care (POC) test. The quantitative serum HCG levels were normal at 4.9 mIU/mL (reference range 0–8 mIU/mL). Follow-up showed that over the prior year there were other 6 similar incidents when nonpregnant patients showed positive qualitative pregnancy results with quantitative HCG levels within “nonpregnancy” normal range being brought to the attention of the laboratory. Methods We assessed the possibility of a detection/measurement error including possible interfering antibodies. The likelihood of interfering substances/antibodies that would interact with 2 different types of POC detection systems (urine qualitative—Clinitest HCG Pregnancy test from Siemens Medical Solutions USA, serum qualitative—Pregnancy HCG Rapid Test from Cardinal Health) and serum quantitative—is very low, especially given that both serum and urine specimens were affected, and interfering antibodies are not normally excreted into urine. Testing of the diluted sample showed results like the neat specimen which further excludes interferences in the quantitative reaction as well as a possible hook effect. Based on this we concluded that the results were accurate.Chart review showed that 6 months prior, she had another quantitative HCG test performed using the same instrumentation obtaining a value of 6.6 mIU/mL. At this time a transvaginal ultrasound excluded the presence of any masses or abnormal findings. FSH (47.8 mIU/ml) and LH (49.8 mIU/ml) were found to be within the perimenopausal range. Qualitative serum and urine test were found to be repeatedly positive, while the quantitative tests were within nonpregnancy range, over several months. Retrospective chart review of the other 6 cases revealed similar pattern. Pregnancy, certain tumors (gestational trophoblastic neoplasia, ovarian germ cell tumor), kidney failure and menopause will manifest with increased HCG production. In (peri)menopausal women the pituitary produces HCG up to 14 mIU/mL in association with increased levels of FSH. The qualitative tests were repeatedly positive over several months while the quantitative results remained unchanged, excluding the diagnosis of pregnancy or tumors, and supporting the conclusion that these results are menopause related. Results To avoid similar future incidents we added the following comment to the POC test results: “If the result does not fit the clinical picture, please repeat testing on a new sample collected 48–72 h later or order serum HCG quantitative” We also added for the quantitative HCG result, the following comment: “Peri- and postmenopausal patients may have increased HCG of pituitary origin up to 14 mIU/mL. If the result does not fit the clinical picture, FSH measurement can be used for additional information.” During the 12 months preceding the implementation of the comments we had 6 incidents of positive qualitative HCG results in non-pregnant (peri)menopausal patients brought for investigation, and none during the 24 months after that. Conclusion The addition of the interpretative comment as clinical decision support increased the efficiency of the medical service, staff engagement and most importantly, patient satisfaction and safety.

Tobacco control policies implementation and future lung cancer incidence in Saudi Arabia. A population-based study

BackgroundDespite the implementation of the monitor tobacco products and prevention package (MPOWER) in Saudi Arabia since 2011, the impact of the policy implantation on smoking prevalence and lung cancer incidence have not been evaluated. ObjectivesWe aimed to estimate the potential reduction in future lung cancer incidence in Saudi Arabia that could be prevented if the highest level of tobacco control policies MPOWER score were implemented. MethodsPopulation-based lung cancer incidence data was used to predict lung cancer incidence in Saudi Arabia up to year 2039. We used hypothetical smoking prevalence that would be expected if countries had applied the highest-level implementation of MPOWER tobacco control policies score. We used potential impact fraction on the hypothetical smoking prevalence data to estimate the potentially preventable lung cancer cases taking into account latency periods between changes in smoking prevalence and development of cancer risks. After the hypothesized highest level of MPOWER tobacco policies implementation. Resultsthe national tobacco smoking prevalence has declined by 55% from 13.17% in 2020 to 5.91% in 2039. If the highest-level MPOWER is implanted, more than half the tobacco smoker rate will be reduced, and a total of 9783 lung cancer cases would be potentially prevented in 2039. ConclusionFurther implementation of effective messages is needed to reduce tobacco-related cancers. By doing so, we can gain valuable insights into the impact of these policies on public health outcomes in the broader context of the region and identify potential areas for further improvement and intervention.

Association of a lesser number of teeth with more risk of developing depressive symptoms among middle-aged and older adults in Japan: A 20-year population-based cohort study

ObjectivesThis 20-year prospective cohort study aimed to longitudinally explore the relationship between the number of teeth and the incidence of depressive symptoms among community-dwelling middle-aged and older adults. MethodsData were collected from the National Institute for Longevity Sciences-Longitudinal Study of Aging (NILS-LSA) database from 2002 to 2022 (3rd–9th waves). Data of adults aged ≥40 years were analyzed and those who had depressive symptoms at baseline (3rd wave), had missing data, or did not participate in follow-up, were excluded. We collected data on the number of teeth at baseline. Depressive symptoms were defined as a score of ≥16 on the Center for Epidemiologic Studies Depression Scale. The generalized estimating equation (GEE) model was used to examine the longitudinal relationships between the number of teeth at baseline and the subsequent incidence of depressive symptoms. ResultsThe final analysis included 1668 participants, with a mean (standard deviation) age of 58.8 (11.1) years and a mean follow-up time of 12.9 years. After GEE analysis with adjustment for multiple covariates, compared to participants with ≥20 teeth, participants with 10–19 teeth and < 10 teeth at baseline were associated with a higher risk of depressive symptoms. The subgroup analysis showed that the effect was stronger in men than in women. ConclusionsAmong middle-aged and older community dwellers, particularly men, a small number of teeth after the age of 40 was associated with the future incidence of depressive symptoms.

Mapping oil pollution in the Gulf of Suez in 2017–2021 using Synthetic Aperture Radar

The Gulf of Suez region accommodates diverse activities, including oil exploration and production, recreational activities, and export and import ports. The Gulf region is exposed to pollution risks due to these interactions, with few research studies documenting these pollution cases. This research aimed to use Synthetic Aperture Radar (SAR) satellite data to detect and map all the oil pollution incidents within the geographical extent of the Gulf of Suez that occurred from 2017 to 2021, locating the most affected regions and possible sources of pollution. It enabled the detection and mapping of nearly 150 oil spill incidents that occurred over 67 dates during the study period and covered 851 km2 of the sea surface. The year 2018 recorded the greatest pollution area over the study period, with 201 km2. Along the Gulf coast, Suez, Ain Sokhna, and Ras Ghareb cities recorded the highest number of marine pollution incidents. The research also located seven sources of pollution that frequently discharge into the Gulf water without regulations. This research recommends implementing a real-time monitoring system for oil pollution to robustly detect any future oil incidents in these high-risk areas as quickly as possible and minimize their environmental impact.