Assessing the impact of inland navigation on the faecal pollution status of large rivers: A novel integrated field approach.

The contribution of ships to the microbial faecal pollution status of water bodies is largely unknown but frequently of human health concern. No methodology for a comprehensive and target-orientated system analysis was available so far. We developed a novel approach for integrated and multistage impact evaluation. The approach includes, i) theoretical faecal pollution source profiling (PSP, i.e., size and pollution capacity estimation from municipal vs. ship sewage disposal) for impact scenario estimation and hypothesis generation, ii) high-resolution field assessment of faecal pollution levels and chemo-physical water quality at the selected river reaches, using standardized faecal indicators (cultivation-based) and genetic microbial source tracking markers (qPCR-based), and iii) integrated statistical analyses of the observed faecal pollution and the number of ships assessed by satellite-based automated ship tracking (i.e., automated identification system, AIS) at local and regional scales. The new approach was realised at a 230 km long Danube River reach in Austria, enabling detailed understanding of the complex pollution characteristics (i.e., longitudinal/cross-sectional river and upstream/downstream docking area analysis). Faecal impact of navigation was demonstrated to be remarkably low at regional and local scale (despite a high local contamination capacity), indicating predominantly correct disposal practices during the investigated period. Nonetheless, faecal emissions were sensitively traceable, attributable to the ship category (discriminated types: cruise, passenger and freight ships) and individual vessels (docking time analysis) at one docking area by the link with AIS data. The new innovative and sensitive approach is transferrable to any water body worldwide with available ship-tracking data, supporting target-orientated monitoring and evidence-based management practices.

Improving the Flexibility of Ship Propellers Additively Manufactured from High-Density Polyethylene/Long Carbon Fiber Composites by Prepreg Coating.

In efforts to achieve the goal of reducing ship emissions in the fight against climate change, reducing fuel consumption by making ships lighter is stated as one of the solutions. In this study, the possibilities of making composite equivalents of propellers, which are the most complex ship elements and traditionally produced from metal materials, are investigated with the advantages of additive manufacturing, which offers a rapid production opportunity for such forms. In this way, a lighter composite propeller and, therefore, a lighter ship will be achieved, and negative environmental impacts, especially harmful emissions, will be reduced. In the study, a 1/14-scale ship propeller was produced through the material extrusion method of additive manufacturing using an HDPE composite containing long carbon fiber with a 15% weight fraction. An attempt to reduce flexibility with an epoxy-carbon fabric prepreg coating was made, as the flexibility has negative effects on the performance of the produced propeller. The propeller tunnel test showed that the applied carbon fabric epoxy prepreg helped to improve the propeller's performance by decreasing the flexibility of the propeller and reducing the deformation at the tips. At the same time, the propeller weight was decreased by 60% compared to its metal counterparts.

Advanced Bayesian study on inland navigational risk of remotely controlled autonomous ship.

The arise of autonomous ships has necessitated the development of new risk assessment techniques and methods. This study proposes a new framework for navigational risk assessment of remotely controlled Maritime Autonomous Surface Ships (MASS). This framework establishes a set of risk influencing factors affecting safety of navigation of a remotely-controlled MASS. Next, model parameters are defined based on the risk factors, and the model structure is developed using Bayesian Networks. To this end, an extensive literature survey is conducted, enhanced with the domain knowledge elicited from the experts and improved by the experimental data obtained during representative MASS model trials carried out in an inland river. Conditional Probability Tables are generated using a new function employing expert feedback regarding Interval Type 2 Fuzzy Sets. The developed Bayesian model yields the expected utilities results representing an accident's probability and consequence, with the results visualized on a dedicated diagram. Finally, the developed risk assessment model is validated by conducting three axiom tests, extreme scenarios analysis, and sensitivity analysis. Navigational environment, natural environment, traffic complexity, and shore-ship collaboration performance are critical from the probability and consequence perspective for inland navigational accidents to a remotely controlled MASS. Lastly, important nodes to Shore-Ship collaboration performance include autonomy of target ships, cyber risk, and transition from other remote control centers.

Screening and early detection of communicable diseases on board cruise ships: An assessment of passengers' preferences on technical solutions.

BACKGROUND: Implementing technological solutions to screen for and detect early the most prevalent communicable diseases on cruise ships is contingent on, among others, willingness of passengers to accept use of such solutions. METHOD: We surveyed passenger preferences to record their willingness to accept technological solutions for screening and early detection of communicable diseases on cruise ships. Self-reported sociodemographic characteristics, use of technology and acceptance of solutions were recorded anonymously in paper format. Multiple logistic regression analyses investigated the association of demographic and other characteristics with willingness and barriers/concerns of passengers to endorse proposed solutions. RESULTS: Of a total of 1344 passengers on two successive cruises on board CELESTYAL OLYMPIA, 336 (1 every 4) participated in the survey. The vast majority of passengers (92.3 %, n = 310) agreed with at least one solution. Passengers showed lower levels of acceptance for more personalized solutions, such as use of wearable devices (45.5 %) and monitoring with cameras (64.0 %), whereas they were more receptive to less personally invasive solutions, such as integration of cabins with air purifiers (89.6 %) and air quality sensors (80.4 %). Age, self-employment status, educational level, and fear of contacting a communicable disease were significantly correlated with passengers' willingness to adopt proposed solutions. CONCLUSIONS: To successfully integrate screening and early detection technological solutions in cruise ships, it is imperative that targeted awareness and education interventions are implemented on passengers to strengthen understanding and acceptance of such solutions and assuage concerns around monitoring and handling of personal health data.

A bibliometric analysis of cellulose anti-fouling in marine environments.

Marine biofouling poses significant challenges to maritime industries worldwide, affecting vessel performance, fuel efficiency, and environmental sustainability. These challenges demand innovative and sustainable solutions. In this review, the evolving landscape of cellulose-based materials for anti-fouling applications in marine environments is explored. Through a comprehensive bibliometric analysis, the current state of research is examined, highlighting key trends, emerging technologies, and geographical distributions. Cellulose, derived from renewable resources, offers a promising avenue for sustainable anti-fouling strategies due to its biodegradability, low toxicity, and resistance to microbial attachment. Recent advancements in cellulose-based membranes, coatings, and composites are discussed, showcasing their efficacy in mitigating biofouling while minimizing environmental impact. Opportunities for interdisciplinary collaboration and innovation are identified to drive the development of next-generation anti-fouling solutions. By harnessing the power of cellulose, progress towards cleaner, more sustainable oceans can be facilitated, fostering marine ecosystems and supporting global maritime industries.

Historical evolution of the passenger ship's doctor.

The authors examine the evolution of the role of resident doctors on cruise ships dating back to the Roman and Byzantine empires, then in the Middle ages. In the past surgery was rarely performed by doctors, but by barber-surgeons, who, with their razor skills, did everything from haircuts to amputations. More recently, as in the last century, the first royal decrees were issued, pillar by pillar, forming the regulatory basis governing health care on board Italian or foreign ships travelling to and from national ports.

Impact of IoT System Imperfections and Passenger Errors on Cruise Ship Evacuation Delay.

Cruise ships and other naval vessels include automated Internet of Things (IoT)-based evacuation systems for the passengers and crew to assist them in case of emergencies and accidents. The technical challenges of assisting passengers and crew to safety during emergencies include various aspects such as sensor failures, imperfections in the sound or display systems that are used to direct evacuees, the timely selection of optimum evacuation routes for the evacuees, as well as computation and communication delays that may occur in the IoT infrastructure due to intense activities during an emergency. In addition, during an emergency, the evacuees may be confused or in a panic, and may make mistakes in following the directions offered by the evacuation system. Therefore, the purpose of this work is to analyze the effect of two important aspects that can have an adverse effect on the passengers' evacuation time, namely (a) the computer processing and communication delays, and (b) the errors that may be made by the evacuees in following instructions. The approach we take uses simulation with a representative existing cruise ship model, which dynamically computes the best exit paths for each passenger, with a deadline-driven Adaptive Navigation Strategy (ANS). Our simulation results reveal that delays in the evacuees' reception of instructions can significantly increase the total time needed for passenger evacuation. In contrast, we observe that passenger behavior errors also affect the evacuation duration, but with less effect on the total time needed to evacuate passengers. These findings demonstrate the importance of the design of passenger evacuation systems in a way that takes into account all realistic features of the ship's indoor evacuation environment, including the importance of having high-performance data processing and communication systems that will not result in congestion and communication delays.

Assessment of the performance of cruise ship waste management: Case study of the Rio de Janeiro port, Brazil.

The significant growth of the cruise ship industry has resulted in economic benefits, but there are also waste management-related challenges. The aim of this case study was to contribute to the research of cruise ship waste management at the Port of Rio de Janeiro. A3 methodology, applied for the first time in this context, was used to create questionnaires to assess the stakeholders involved, revealing that institutional bureaucracy has a negative effect on waste management. In addition, secondary data on unloaded waste, obtained from the transport manifests, showed that 56 % contained reliable information. The main wastes were plastics (57 %), glass (17 %), metal (9 %), and others. With respect to destinations, 41 % were sent to landfills, 55 % recycled and 4 % thermally treated. Only 5 % of cruise ship moorings removed waste at the Port of Rio de Janeiro, attributed to factors such as high costs.

Understanding the sources of marine litter in remote islands: The Galapagos islands as a case study.

Determining the sources of marine litter is necessary to mitigate this increasing global problem. Plastic bottles are useful tracers of marine litter and constitute the main item (24%) stranding on remote beaches in the Galapagos Islands. The aim of this study was to estimate the abundance of plastic bottles in remote beaches and inferred their sources. To do so, we collected plastic bottles at 60 remote Galapagos Island beaches from 2018 to 2022. 76% of beaches were qualified as badly polluted, with >34 bottles·100 m-1. Most identified bottles came from Peru (71%), followed by China (17%) and Ecuador (9%). Although most locally-sold products are made in Ecuador, they contribute little to beach litter loads. Polyethylene terephthalate bottles with lid (necessary for litter dispersal) represented 88% of all bottles, demonstrating that most of the litter reaching the Galapagos comes from distant sources, mainly from South America. However, bottle ages indicate that at least 10% of Peruvian, 26% of Ecuadorian, and all Chinese bottles likely were dumped from ships. Reducing marine litter reaching the Galapagos Islands requires tackling litter leakage from land-based sources in South America and better compliance with regulations banning the dumping of plastics and other persistent wastes from ships.

A lightweight CNN for multi-source infrared ship detection from unmanned marine vehicles.

Infrared ship detection is of great significance due to its broad applicability in maritime surveillance, traffic safety and security. Multiple infrared sensors with different spectral sensitivity provide enhanced sensing capabilities, facilitating ship detection in complex environments. Nevertheless, current researches lack discussion and exploration of infrared imagers in different spectral ranges for marine objects detection. Furthermore, for unmanned marine vehicles (UMVs), e.g., unmanned surface vehicles (USVs) and unmanned ship (USs), detection and perception are usually performed in embedded devices with limited memory and computation resource, which makes traditional convolutional neural network (CNN)-based detection methods struggle to leverage their advantages. Aimed at the task of sea surface object detection on USVs, this paper provides lightweight CNNs with high inference speed that can be deployed on embedded devices. It also discusses the advantages and disadvantages of using different sensors in marine object detection, providing a reference for the perception and decision-making modules of USVs. The proposed method can detect ships in short-wave infrared (SWIR), long-wave infrared (LWIR) and fused images with high-performance and high-inference speed on an embedded device. Specifically, the backbone is built from bottleneck depth-separable convolution with residuals. Generating redundant feature maps by using cheap linear operation in neck and head networks. The learning and representation capacities of the network are promoted by introducing the channel and spatial attention, redesigning the sizes of anchor boxes. Comparative experiments are conducted on the infrared ship dataset that we have released which contains SWIR, LWIR and the fused images. The results indicate that the proposed method can achieve high accuracy but with fewer parameters, and the inference speed is nearly 60 frames per second (FPS) on an embedded device.

Improving health literacy of passengers of cruise ships: readability of passenger-facing COVID-19 information provided by commercial cruise lines-an infodemiology study.

Readability of COVID-19 information from 35 cruise lines was examined. Mean Flesch Reading Ease and Flesch-Kincaid Grade Level scores (±standard error of mean) were 46.6 ± 1.3 (target ≥60) and 10.9 ± 0.3 (target ≤ 8.0), respectively. Two (6%) cruise lines met readability reference targets. Readability tools may aid in preparing more easily read passenger-facing health-related information on existing infections, including COVID-19, other respiratory infections, as well as gastroenteritis (e.g. norovirus), as well as providing a methodology for improving the readability of information prepared for newly emerging infectious diseases.

Emission factors of oxygenated polycyclic aromatic hydrocarbons from ships in China.

The rapid growth of maritime traffic, transportation, and fishery activities has increased shipping emissions and degraded the air quality in coastal areas. As a result, controlling ocean-based pollution sources have become increasingly important. This study investigated the real-world emission characteristics of oxygenated polycyclic aromatic hydrocarbons (OPAHs, a group of highly toxic semi-volatile organic compounds) from five types of offshore ships using diesel oil: small and medium fishing ships, tug boats, ferry, and engineering ships, under various driving mode. Both gaseous and particle emission factors (EF) of four specific OPAHs were determined in our study. Among the OPAHs species emitted from ships, 9-fluorenone (9FO; 72%) and anthrathrace-9,10-quinone (ATQ; 25%) were the most abundant. The arithmetic mean of the sum of gaseous OPAHs EFs for all ships in this study was 2.5 ± 4.4 mg/kg fuel burned, and the mean particulate OPAHs EF was 4.7 ± 7.9 mg/kg. Small fishing ships had the highest total OPAHs EFs (31.0 ± 17.0 mg/kg). Apart from small fishing ships, there was no significant difference in the total EF of OPAHs for the other four types of ships. The emissions of the four OPAHs are predominantly in the particulate phase. There were no significant differences in the emissions of the four OPAHs under different driving mode. According to estimates, the annual OPAH emissions from the four types of ships in Hainan in 2017 were approximately 4.2 (range: 2.7-7.0) tons, dwarfing the OPAH emissions from diesel-powered on-road vehicles in China (23.5 kg).

Estimation methods and reduction strategies of port carbon emissions - what literatures say?

Carbon emissions from port operational activities significantly contribute to climate change and have gained attention from researchers. However, there is a notable deficiency in systematically analyzing port carbon emissions' estimation methods and reduction strategies. This study reviewed 49 academic literatures to examine the port's carbon emissions estimation methodologies, quantitative research outcomes, and reduction techniques. The analysis results revealed: (1) Estimates of port carbon emissions frequently tend to underestimate actual emissions due to the omission of specific sources. (2) Inherent variances across ports present challenges in establishing a universally applicable estimation methodology. (3) Port carbon emissions reduction strategies involve operational optimization, dispatching, equipment transformation, and energy management. Future research directions were proposed, including comprehensive emissions source estimation, harmonization of estimation methodologies, equipment-integrated scheduling, port automation and electrification, and energy management. This study guides the development of the port's carbon emission estimation and reduction, aiding port operators in efficient production management.

iVision MRSSD: A comprehensive multi-resolution SAR ship detection dataset for state of the art satellite based maritime surveillance applications.

This article describes a comprehensive Synthetic Aperture Radar (SAR) satellite based ships dataset for use in state of the art object detection algorithms. The dataset comprises 11,590 image tiles containing 27,885 ships examples. Each image tile has spatial dimensions of 512 × 512 pixels and is exported in JPEG format. The dataset contains a wide variety of inshore and offshore scenes under varying background settings and sea conditions to generate an all-inclusive understanding of the ship detection task in SAR satellite images. The dataset is generated using images from six different satellite sensors covering a wide range of electromagnetic spectrum including C, L and X band radar imaging frequencies. All the sensors have different resolutions and imaging modes. The dataset is randomly distributed into training, validation and test sets in the ratio of 70:20:10, respectively, for ease of comparison and bench-marking. The dataset was conceptualized, processed, labeled and verified at the Artificial Intelligence and Computer Vision (iVision) Lab at the Institute of Space Technology, Pakistan. To the best of our knowledge, this is the most diverse satellite based SAR ships dataset available in the public domain in terms of satellite sensors, radar imaging frequencies and background settings. The dataset can be used to train and optimize deep learning based object detection algorithms to develop generic models with high detection performance for any SAR sensor and background condition.

Fire Detection and Notification Method in Ship Areas Using Deep Learning and Computer Vision Approaches.

Fire incidents occurring onboard ships cause significant consequences that result in substantial effects. Fires on ships can have extensive and severe wide-ranging impacts on matters such as the safety of the crew, cargo, the environment, finances, reputation, etc. Therefore, timely detection of fires is essential for quick responses and powerful mitigation. The study in this research paper presents a fire detection technique based on YOLOv7 (You Only Look Once version 7), incorporating improved deep learning algorithms. The YOLOv7 architecture, with an improved E-ELAN (extended efficient layer aggregation network) as its backbone, serves as the basis of our fire detection system. Its enhanced feature fusion technique makes it superior to all its predecessors. To train the model, we collected 4622 images of various ship scenarios and performed data augmentation techniques such as rotation, horizontal and vertical flips, and scaling. Our model, through rigorous evaluation, showcases enhanced capabilities of fire recognition to improve maritime safety. The proposed strategy successfully achieves an accuracy of 93% in detecting fires to minimize catastrophic incidents. Objects having visual similarities to fire may lead to false prediction and detection by the model, but this can be controlled by expanding the dataset. However, our model can be utilized as a real-time fire detector in challenging environments and for small-object detection. Advancements in deep learning models hold the potential to enhance safety measures, and our proposed model in this paper exhibits this potential. Experimental results proved that the proposed method can be used successfully for the protection of ships and in monitoring fires in ship port areas. Finally, we compared the performance of our method with those of recently reported fire-detection approaches employing widely used performance matrices to test the fire classification results achieved.

Biosafety of marine vessels: current trends and prospects.

BACKGROUND: The global aggravation of the political situation in the world against the background of catastrophic changes in the Earth's ecology is inexorably growing. Despite the fact that most ships are equipped with Waste Water Treatment Plants (WWTP), pollution of the World Ocean remains a serious problem. One of the main reasons contributing to the pollution of the sea by ships is the lack of the ship's environmental protection equipment necessary for the work. Thus, the adoption of measures to prevent the discharge of raw sewage from ships and improve the quality of their treatment is of paramount importance. MATERIALS AND METHODS: The data of comprehensive surveys of ship WWTP operation in the ports of Ukraine for 2009-2010 are analysed - the most intensive period of navigation in the last 20 years. To assess the quality of wastewater treatment, samples were taken for laboratory studies in accordance with the requirements of the "State Sanitary Rules and Norms for Discharge of Waste, Oily, Ballast Water and Garbage from Ships into Water Bodies", No. 199, 09/07/1997. RESULTS: The results of laboratory studies of wastewater after treatment on shipboard WWTP, conducted in the Black Sea ports of Ukraine in 2009-2010, show the unsatisfactory quality of their treatment according to the main regulated national and international indicators. CONCLUSIONS: Taking into account the results of surveys of foreign ships conducted in 2009-2010, the studied literature, we consider our study worthy of serious reflection in order to understand the current situation on ships equipped with WWTP installations, determine priority areas for ensuring their efficient operation and preventing pollution of water bodies by untreated waste carrying the threat of contamination of residents of coastal areas with pathogens of dangerous infectious diseases transmitted by water, toxic substances that are detrimental to the flora and fauna of the oceans.

Formulating Cybersecurity Requirements for Autonomous Ships Using the SQUARE Methodology.

Artificial intelligence (AI) technology is crucial for developing autonomous ships in the maritime industry. Autonomous ships, based on the collected information, recognize the environment without any human intervention and operate themselves using their own judgment. However, ship-to-land connectivity increased, owing to the real-time monitoring and remote control (for unexpected circumstances) from land; this poses a potential cyberthreat to various data collected inside and outside the ships and to the applied AI technology. For the safety of autonomous ships, cybersecurity around AI technology needs to be considered, in addition to the cybersecurity of the ship systems. By identifying various vulnerabilities and via research cases of the ship systems and AI technologies, this study presents possible cyberattack scenarios on the AI technologies applied to autonomous ships. Based on these attack scenarios, cyberthreats and cybersecurity requirements are formulated for autonomous ships by employing the security quality requirements engineering (SQUARE) methodology.

The Two Emergencies of Migrant-Related Policies in Italy During the First Wave of COVID-19: the Spread of the Virus and the Workforce Shortages.

Italy was the first European country touched by COVID-19 and one of the most severely affected, with a death toll that overtook China's by mid-March 2020. As a result, lockdown measures aiming to mitigate - and eventually interrupt - the spread of COVID-19 proliferated during the first wave of the pandemic. The vast majority of these concerned the resident population, regardless of their status or country of origin, and mainly involved the closure of public offices and proscription of private activities with the aim of reducing mobility and social and physical contacts. Only a few concerned the foreign population and arriving irregular migrants. This article analyses migrant-related policy measures taken by the Italian government during the first wave of the pandemic that aimed to prevent infection and reduce the impact of COVID-19 among the population. These measures addressed two emergencies: the spread of COVID-19 that hit the resident population hard, regardless of origin or nationality, and the workforce shortages in some key economic sectors with a high number of irregular migrant workers. The former aimed at containing the spread of the virus (sections 4 and 5) and targeted foreigners already residing in Italy as well as irregular migrants arriving along the Mediterranean route; the latter aimed at addressing workforce shortages (section 6) as a result of borders that were closed to external seasonal migration. This article is a contribution to the debate on changes to migration and migrant policy, and how these impacted on migration and foreign populations during the pandemic.

The Magnitude of Cardiovascular Disease Risk Factors in Seafarers from 1994 to 2021: A Systematic Review and Meta-Analysis.

OBJECTIVES: The incidence of acute cardiac events is one of the main reasons for medical consultation, disembarkation, repatriation, and death among seafarers at sea. Managing cardiovascular risk factors, particularly those that can be modified, is the key to preventing cardiovascular disease. Therefore, this review estimates the pooled prevalence of major CVD risk factors among seafarers. METHODS: We conducted a comprehensive search of studies published between 1994 and December 2021 in four international databases, namely PubMed/Medline, Scopus, Google Scholar, and Web of Science (WOS). Each study was evaluated for methodological quality using the Joanna Briggs Institute (JBI) critical appraisal tool for prevalence studies. The DerSimonian-Laird random-effects model with logit transformations was used to estimate the pooled prevalence of major CVD risk factors. The results were reported in accordance with the Preferred Items for Systematic Review and Meta-analysis (PRISMA) guidelines. RESULTS: Out of all 1484 studies reviewed, 21 studies with 145,913 study participants met the eligibility criteria and were included in the meta-analysis. In the pooled analysis, the prevalence of smoking was found to be 40.14% (95% CI: 34.29 to 46.29%) with heterogeneity between studies (I2 = 98%, p < 0.01). The prevalence of hypertension, overweight, obesity, diabetes mellitus, and alcohol consumption was 45.32%, 41.67%, 18.60%, 12.70%, and 38.58%, respectively. However, the sensitivity analysis after excluding studies showed a pooled prevalence of hypertension, overweight, obesity, and diabetes mellitus of 44.86%, 41.87%, 15.99%, and 16.84%, respectively. The subgroup analysis demonstrated that smoking prevalence among seafarers had decreased significantly after 2013. CONCLUSION: This study demonstrated that CVD risk factors, particularly hypertension, overweight, smoking, alcohol consumption, and obesity, are prevalent among seafarers. These findings may serve as a guide for shipping companies and other responsible bodies in order to prevent CVD risk factors among seafarers. PROSPERO Registration: CRD42022300993.

Accidents, diseases and health complaints among seafarers on German-flagged container ships.

BACKGROUND: For seafarers on the high seas health hazards are various and due to the setting also specific. The spectrum of job-related health impairments and accidents is mainly influenced by the maritime characteristics. The aim of this study is to assess the kind of accidents and the frequency of diseases and health complaints among seafarers on German container ships by evaluating medical log books. METHODS: A systematic analysis of 14,628 medical entries from 95 medical log books of 58 container ships under German flag from 1995 to 2015 was performed. This monocentric retrospective and descriptive study used information on accidents, diseases and health complaints among different occupational groups and medical treatment procedures for the analysis and evaluation. RESULTS: The analysis showed that more than one third of all consultations with the Health Officer on board are related to internal (33.7%) and surgical (31.3%) symptoms. Almost twenty percent of consultations were due to respiratory infections (19.6%) and accidents (17.9%). Accidents represented the most frequent reason for unfitness for sea service (31.2%). Based on occupational categories, most injuries occurred among deck crew (22.5%), followed by ratings working in the engine room (18.9%). In 106 cases, telemedical contact with a physician ashore was necessary. In total, 15 seafarers had to be evacuated from the ship for further medical treatment onshore. Medicine/drug application was the most common therapeutic measure on board, accounting for 77% of all consultations. CONCLUSIONS: The high proportion of health complaints and accidents among seafarers shows that there is a need to optimize medical care at sea and accident prevention, e.g. by standardized treatment algorithms or improving the medical training of Health Officers. The development and introduction of a digital patient file to record medical treatments on the vessels could also improve medical documentation on board.