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A COVID-19 outbreak on board ship: Analysis of the sociotechnical system of epidemiological management in the French Navy
Copyright policy )A COVID-19 outbreak on board ship: Analysis of the sociotechnical system of epidemiological management in the French Navy
In late 2019, an epidemic of SARS-CoV-2 broke out in central China. Within a few months, this new virus had spread right across the globe, officially being classified as a pandemic on 11 March 2020. In France, which was also being affected by the virus, the government applied specific epidemiological management strategies and introduced unprecedented public health measures. This article describes the outbreak management system that was applied within the French military and, more specifically, analyzes an outbreak of COVID-19 that occurred on board a nuclear aircraft carrier. We applied the AcciMap systemic analysis approach to understand the course of events that led to the outbreak and identify the relevant human and organizational failures. Results highlight causal factors at several levels of the outbreak management system. They reveal problems with the benchmarks used for diagnosis and decision-making, and underscore the importance of good communication between different levels. We discuss ways of improving epidemiological management in military context.
- Université Paris Diderot France
- Aix-Marseille University France
Microsoft Academic Graph classification: Economic growth History Sociotechnical system Context (language use) Pandemic Government Risk management framework Outbreak Navy Management system
ACM Computing Classification System: ComputingMilieux_MISCELLANEOUS
Risk management framework, Incident analysis, Article, Outbreak management, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Complex socio-technical system, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, [SDV.MP.PAR]Life Sciences [q-bio]/Microbiology and Parasitology/Parasitology, Safety, Risk, Reliability and Quality, [SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases, Public Health, Environmental and Occupational Health, COVID-19, Building and Construction, [SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology, AcciMap, [SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology, Safety Research
Risk management framework, Incident analysis, Article, Outbreak management, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Complex socio-technical system, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, [SDV.MP.PAR]Life Sciences [q-bio]/Microbiology and Parasitology/Parasitology, Safety, Risk, Reliability and Quality, [SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases, Public Health, Environmental and Occupational Health, COVID-19, Building and Construction, [SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology, AcciMap, [SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology, Safety Research
Microsoft Academic Graph classification: Economic growth History Sociotechnical system Context (language use) Pandemic Government Risk management framework Outbreak Navy Management system
ACM Computing Classification System: ComputingMilieux_MISCELLANEOUS
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citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).7 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10% citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).7 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
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- Université Paris Diderot France
- Aix-Marseille University France
In late 2019, an epidemic of SARS-CoV-2 broke out in central China. Within a few months, this new virus had spread right across the globe, officially being classified as a pandemic on 11 March 2020. In France, which was also being affected by the virus, the government applied specific epidemiological management strategies and introduced unprecedented public health measures. This article describes the outbreak management system that was applied within the French military and, more specifically, analyzes an outbreak of COVID-19 that occurred on board a nuclear aircraft carrier. We applied the AcciMap systemic analysis approach to understand the course of events that led to the outbreak and identify the relevant human and organizational failures. Results highlight causal factors at several levels of the outbreak management system. They reveal problems with the benchmarks used for diagnosis and decision-making, and underscore the importance of good communication between different levels. We discuss ways of improving epidemiological management in military context.