A decision-support tool for biological risk assessment of naval vessels: results interpretation and potential of application

Clara Inghels (), Audrey Duclos (), Clément Beghin (), Olivier Gorgé, Catherine da Cunha () and Emmanuelle Billon-Denis ()
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Clara Inghels: LS2N - Laboratoire des Sciences du Numérique de Nantes - Inria - Institut National de Recherche en Informatique et en Automatique - CNRS - Centre National de la Recherche Scientifique - IMT Atlantique - IMT Atlantique - IMT - Institut Mines-Télécom [Paris] - Nantes Univ - ECN - NANTES UNIVERSITÉ - École Centrale de Nantes - Nantes Univ - Nantes Université - Nantes univ - UFR ST - Nantes université - UFR des Sciences et des Techniques - Nantes Université - pôle Sciences et technologie - Nantes Univ - Nantes Université, Nantes Univ - ECN - NANTES UNIVERSITÉ - École Centrale de Nantes - Nantes Univ - Nantes Université, Naval Group, LS2N - équipe CPS3 - Conception, Pilotage, Surveillance et Supervision des systèmes - LS2N - Laboratoire des Sciences du Numérique de Nantes - Inria - Institut National de Recherche en Informatique et en Automatique - CNRS - Centre National de la Recherche Scientifique - IMT Atlantique - IMT Atlantique - IMT - Institut Mines-Télécom [Paris] - Nantes Univ - ECN - NANTES UNIVERSITÉ - École Centrale de Nantes - Nantes Univ - Nantes Université - Nantes univ - UFR ST - Nantes université - UFR des Sciences et des Techniques - Nantes Université - pôle Sciences et technologie - Nantes Univ - Nantes Université
Audrey Duclos: Naval Group
Clément Beghin: Naval Group
Olivier Gorgé: IRBA - Institut de Recherche Biomédicale des Armées [Brétigny-sur-Orge]
Catherine da Cunha: LS2N - équipe CPS3 - Conception, Pilotage, Surveillance et Supervision des systèmes - LS2N - Laboratoire des Sciences du Numérique de Nantes - Inria - Institut National de Recherche en Informatique et en Automatique - CNRS - Centre National de la Recherche Scientifique - IMT Atlantique - IMT Atlantique - IMT - Institut Mines-Télécom [Paris] - Nantes Univ - ECN - NANTES UNIVERSITÉ - École Centrale de Nantes - Nantes Univ - Nantes Université - Nantes univ - UFR ST - Nantes université - UFR des Sciences et des Techniques - Nantes Université - pôle Sciences et technologie - Nantes Univ - Nantes Université
Emmanuelle Billon-Denis: DGA Maîtrise NRBC, 91710 Vert-le-Petit

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Abstract: The spread of infectious diseases aboard naval vessels can have significant impacts on crew availability and operational continuity due to the closed and poorly ventilated environment of naval vessels. It is therefore essential to assess, analyze, and mitigate this risk, from the conception stage, using tools that model the spread of infectious diseases on board, their impacts on the mission carried by the vessel, and the effects of potential solutions implemented. To this end, a decision-support tool simulating the impact of selected biological risks [1][2] has been developed using a method that combines different types of modeling used in mathematical epidemiology [3]. Simulations show how the epidemic spreads according to the crew behaviors and the architecture of the vessels. The tool thus created was validated by comparing the tool's results with actual epidemiological data from a well-documented case study [4]. The tool's results describe performance indicators for the biological resilience of vessels. They are intended for operational staff, architects, and decision-makers to assess and mitigate biological risks on board naval vessels to ensure crew availability and mission continuity. Indicators provide information on: 1. The most at-risk rooms (through the count of new infections per room) to define priorities for the allocation of countermeasures; 2. The rate of air contamination per room by monitoring infectious particles in the air to assess ventilation systems; 3. The percentage of crew members infected simultaneously, by monitoring their health status, enabling the establishment of rules triggering the implementation of organizational countermeasures before transmission explodes and the crew is lost by infection. This poster focuses on the exploitation of these indicators and the potential applications of the tool. It reports on the potential of the decision-making tool for parties involved in the design and integration of solutions for vessels.

Keywords: Computational fluid dynamics; indoor; Agent-based modeling; Disease transmission (search for similar items in EconPapers)
Date: 2026-05-19
Note: View the original document on HAL open archive server: https://hal.science/hal-05646011v1
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Published in International conference CBRNE Research & Innovation, May 2026, Arcachon, France.

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