The confined environment of a ship promotes the transmission of the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) due to close contact among the population on board. The study aims to provide an overview of outbreaks of SARS-CoV-2 on board of cruise, navy or cargo ships, to identify relevant outbreak management techniques, related problems and to derive recommendations for prevention. Four databases were searched. The study selection included reports about seroprevalences or clinically/laboratory confirmed infections of SARS-CoV-2 on board ships between the first of January, 2020 and the end of July, 2020. A total of 37 studies were included of whom 33 reported outbreaks of SARS-CoV-2 on cruise ships (27 studies referred to the Diamond Princess). Two studies considered outbreaks on the Grand Princess, three studies informed about Nile River cruises and one study about the MS Westerdam (mention of multiple outbreaks possible in one study). Additionally, three studies reported outbreaks of SARS-CoV-2 on navy vessels and one study referred to a cargo ship. Problems in handling outbreaks resulted from a high number of asymptomatic infections, transportation issues, challenges in communication or limited access to health care. Responsible operators need to implement infection control measures which should be described in outbreak management plans for ships to prevent transmission risks, including, e.g., education, testing strategies, communication lines, social distancing and hygiene regulations.

Background The project “ARMIHN” (Adaptive Resiliency Management in Port) focuses on strengthening the capability to act in a mass casualty incident (MCI) due to an outbreak of infectious diseases (MCI-ID). In addition to the current threat from the COVID-19 pandemic and associated outbreaks on cruise ships, previous MCI-ID were especially caused by pathogens such as Influenza virus or Norovirus. The first step was, to get an overview of processes and resources using the example of the Port of Hamburg, and to show the associated interaction of involved parties. This will serve as a basis for developing an operational strategy and offers the opportunity to optimize current work processes. Methods A selective literature research using specified key words was performed and existing MCI concepts were received from local authorities. Identified structures and processes were analyzed in a multiple step process and also brought together through discussions in workshops with involved organizations and other experts. Additionally, the distances between the nearest rescue stations and selected hospitals from the Port of Hamburg were analyzed. Results The current available concepts are proven, but an adaptation to an MCI-ID shows opportunities for a further cross-organizational development. The organizational structure of an MCI-ID in the Port of Hamburg was described, including a large number of involved organizations (n = 18). There are 17 involved fire and rescue stations and the port can be reached from these locations within 6 to 35 min. Based on their specialist expertise, 14 of the 31 listed clinics were selected. Conclusion The purpose of the study was to provide an analysis of the current situation and show how involved parties would cope an MCI. A description of processes and resources at the Port of Hamburg will be used when designing a management plan for responding to an MCI-ID.

BACKGROUND The project “ARMIHN” (Adaptive Resiliency Management in Port) focuses on strengthening the capability to act in a mass casualty incident (MCI) due to an outbreak of infectious diseases (MCI-ID). In addition to the current threat from the COVID-19 pandemic and associated outbreaks on cruise ships, an MCI-ID can also be caused by pathogens such as Influenzavirus or Norovirus. The first step was, to get an overview of processes and resources using the example of the Port of Hamburg, and to show the relating interaction of involved parties. This will serve as a basis for developing an operational strategy and offers the opportunity to optimize current work processes. METHODS A selective literature research using specified key words was performed and existing MCI concepts were received from local authorities. Identified structures and processes were analyzed in a multiple step process and also brought together through discussions in workshops with involved organizations and other experts. Additionally, the distances between the nearest rescue stations and selected hospitals from the Port of Hamburg were analyzed. RESULTS The current available concepts are proven, but an adaptation to an MCI-ID shows opportunities for a further cross-organizational development. The organizational structure of an MCI-ID in the Port of Hamburg was described, including a large number of involved organizations (n = 18). There are 17 involved fire and rescue stations and the port can be reached from these locations within 6 to 35 minutes. Based on their specialist expertise, 14 of the 31 listed clinics were selected. CONCLUSION Based on identified existing structures and the determination of medical resources, an operational concept for an MCI-ID in the port can be adapted and can contribute to enhanced coping with this situation. Subsequently, the derived operational concept will be tested for practical suitability in several exercises within the present project.

This paper focuses on the advancement of a monocular sparse-SLAM algorithm via two techniques: Local feature maintenance and descriptor-based sensor fusion. We present two techniques that maintain the descriptor of a local feature: Pooling and bestfit. The maintenance procedure aims at defining more accurate descriptors, increasing matching performance and thereby tracking accuracy. Moreover, sensors besides the camera can be used to improve tracking robustness and accuracy via sensor fusion. State-of-the-art sensor fusion techniques can be divided into two categories. They either use a Kalman filter that includes sensor data in its state vector to conduct a posterior pose update, or they create world-aligned image descriptors with the help of the gyroscope. This paper is the first to compare and combine these two approaches. We release a new evaluation dataset which comprises 21 scenes that include a dense ground truth trajectory, IMU data, and camera data. The results indicate that descriptor pooling significantly improves pose accuracy. Furthermore, we show that descriptor-based sensor fusion outperforms Kalman filter-based approaches (EKF and UKF).