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.

Decision-making during nonroutine outbreak management: Toward an exploration of experts' creative decisions.

Decision-making during critical outbreak management may require standard strategies, but also more creative ones. Our goal was to characterize the expert decision processes that take place during critical situations, where rule-based strategies and usual procedures cannot be satisfactorily applied. More specifically, we focused on the strategies experts use to deal with epidemiological problems, depending on the complexity of the situation. To this end, we carried out a simulated outbreak alert, to place two experts in a situation of epidemiological problem management, based on usual practice but also conducive to implementing creative solutions. To analyze the data, we considered not only the relevance of the solutions proposed by the experts, but also the four creativity criteria defined by Torrance (fluency, flexibility, elaboration and originality). Results allowed us to identify similarities but also differences between the solutions proposed by the experts, depending on their level of experience in this area.

Using decision fusion methods to improve outbreak detection in disease surveillance.

BACKGROUND: When outbreak detection algorithms (ODAs) are considered individually, the task of outbreak detection can be seen as a classification problem and the ODA as a sensor providing a binary decision (outbreak yes or no) for each day of surveillance. When they are considered jointly (in cases where several ODAs analyze the same surveillance signal), the outbreak detection problem should be treated as a decision fusion (DF) problem of multiple sensors. METHODS: This study evaluated the benefit for a decisions support system of using DF methods (fusing multiple ODA decisions) compared to using a single method of outbreak detection. For each day, we merged the decisions of six ODAs using 5 DF methods (two voting methods, logistic regression, CART and Bayesian network - BN). Classical metrics of accuracy, prediction and timelines were used during the evaluation steps. RESULTS: In our results, we observed the greatest gain (77%) in positive predictive value compared to the best ODA if we used DF methods with a learning step (BN, logistic regression, and CART). CONCLUSIONS: To identify disease outbreaks in systems using several ODAs to analyze surveillance data, we recommend using a DF method based on a Bayesian network. This method is at least equivalent to the best of the algorithms considered, regardless of the situation faced by the system. For those less familiar with this kind of technique, we propose that logistic regression be used when a training dataset is available.

Correction to: Using decision fusion methods to improve outbreak detection in disease surveillance.

Following publication of the original article [1], the authors reported that one of the authors' names is spelled incorrectly.

Dealing with uncertainty when using a surveillance system.

INTRODUCTION: Epidemiologists manage outbreak identification and confirmation by means of a "situation diagnosis", which involves validating (or invalidating) an alarm (signal identified as abnormal) as an alert (a real, characterized outbreak) and proposing the first countermeasures. This work investigates how uncertainty is materialized during this stage, and how experts develop strategies to address this uncertainty with the help of an early warning system. METHODS: We built an experiment using a simulation platform with a scenario involving both a natural and an intentional outbreak. Observations of expert activities were recorded and formalised using a specific task analysis method. These formatted data were then categorized by applying RAWFS (Reduction- Assumption - Weighing - Forestalling- Suppression) heuristics. RESULTS: We quantified uncertainty and the mechanisms involved. During the situation diagnosis, two sorts of uncertainty were characterized: practice-imposed uncertainty and situation-imposed uncertainty. We did not find either weighing pros and cons or suppression strategies in this area of expertise, but highlight the predominance of coping strategies that relied on reduction (66,4%) and assumption-based reasoning. We observed a predominance of the phone (89%) to cope with uncertainty and among electronic tools, the surveillance system plays a major role (69% of cases) and is mainly used in reduction strategies. We detail tools and systems used to support experts in their coping strategy. CONCLUSION: We confirmed that a surveillance system must include different features that provide relevant information to help users reduce uncertainty and thus support their decision making. In that perspective, the flow diagram and proposal presented in this study can help prioritize the necessary changes to surveillance system design.

Outbreak definition by change point analysis: a tool for public health decision?

BACKGROUND: Most studies of epidemic detection focus on their start and rarely on the whole signal or the end of the epidemic. In some cases, it may be necessary to retrospectively identify outbreak signals from surveillance data. Our study aims at evaluating the ability of change point analysis (CPA) methods to locate the whole disease outbreak signal. We will compare our approach with the results coming from experts' signal inspections, considered as the gold standard method. METHODS: We simulated 840 time series, each of which includes an epidemic-free baseline (7 options) and a type of epidemic (4 options). We tested the ability of 4 CPA methods (Max-likelihood, Kruskall-Wallis, Kernel, Bayesian) methods and expert inspection to identify the simulated outbreaks. We evaluated the performances using metrics including delay, accuracy, bias, sensitivity, specificity and Bayesian probability of correct classification (PCC). RESULTS: A minimum of 15 h was required for experts for analyzing the 840 curves and a maximum of 25 min for a CPA algorithm. The Kernel algorithm was the most effective overall in terms of accuracy, bias and global decision (PCC = 0.904), compared to PCC of 0.848 for human expert review. CONCLUSIONS: For the aim of retrospectively identifying the start and end of a disease outbreak, in the absence of human resources available to do this work, we recommend using the Kernel change point model. And in case of experts' availability, we also suggest to supplement the Human expertise with a CPA, especially when the signal noise difference is below 0.

Advantages and limits of real-time epidemiological surveillance during military deployments: the experience of the French Armed Forces.

To perform epidemiological surveillance during deployments, the French military health service has developed a real-time surveillance approach. The objective was to identify the benefits and problems of this approach. A prototype of real-time surveillance has been set up in French Guiana since 2004. Its permanent evaluation has allowed identifying strengths and weaknesses. The experience has permitted expansion of the concept to French forces in Djibouti and also development of a global approach for the whole French armed forces. Real-time surveillance has shown its usefulness for early warning during different real and simulated situations. Functional and architectural choices have permitted interoperability with allied nations. However, the information produced was only the first step of the diagnostic epidemiological situation followed by other investigations. This first step of development has highlighted the required complementarity with traditional epidemiological surveillance.

Intensive physical activity and alexithymia: results from swimmers' discourse analysis.

The aim of this study was to describe and understand the relationship of swimmers' practice intensity and alexithymia features in discourse. This study investigated psychological processes in two groups of male swimmers training at different intensities. The first group was composed of 10 Expert amateurs (M age = 19.5 yr., SD = 1.9), who were competing at the national or international level and trained 22 hours per week. The second group was composed of 10 Amateur swimmers (M age = 20.5 yr., SD = 1.4), who competed at the regional level and trained 6 hours per week. The discourse of swimmers was analysed using the ALCESTE (Analyse de Lexèmes Coocurents dans les Enoncés Simples d'un Texte) method of discourse analysis. Discourse analysis was performed on speech samples produced by swimmers. All the swimmers showed alexithymic verbal behaviour as regards both the means of expression used and the feelings and emotions expressed. This lack of articulateness was more pronounced in the Expert than in the Amateur group. The difference of alexithymic features in correlation with the intensity of sport practice raises the question of the health benefits of intense sports practice and the need for psychological assessment of athletes.

Web services based syndromic surveillance for early warning within French Forces.

OBJECTIVES: Syndromic surveillance for early warning in military context needs a robust, scalable, flexible, ubiquitous, and interoperable surveillance system. METHODS: We have designed our surveillance system as a collaborative network of web services on the basis of a skill oriented decomposition of the overall task and a formal model of epidemiological events. RESULTS: The services (integration devices, epidemiologic receivers, information processing devices, GUI clients) are distributed in several locations in France and French Guiana using a secured network. CONCLUSIONS: This system is in operation since several months. It has already early detected two outbreaks before conventional surveillance systems.

Distributed and Mobile Collaboration for Real Time Epidemiological Surveillance during Forces Deployments.

This paper presents a pilot project of a real time syndromic surveillance system in French armed forces for early warning of biological attack by mass destruction weapons. For simulating the situation of a theatre of operations and its organisation, an electronic syndromic surveillance system covering all branches of service in French Guiana (about 3,000 persons) has been deployed and connected to a surveillance centre in France. This system has been design taking in account a collaborative view of epidemiological surveillance and the mobility of forces in extreme conditions. Several kinds of hardware, from rugged personal digital assistant to desktop computer, and several telecommunication links, from PSTN to satellite data links, are used. This system allows a quick report of cases, which are georeferenced. In the first results, some problems associated with the human and the technical aspects have been reported, in association with some immediate advantages.

Evaluating the use of a comprehensive pretravel database by travel medicine experts and novices for advice building.

BACKGROUND: The practice of travel medicine is particularly dependent on knowledge that must be continuously updated, and that can be found in professional electronic documents (PEDs), as specialized websites or comprehensive off-line databases. In this study, we show to what extent the use of a comprehensive pretravel database can compensate for a lack of knowledge in travel medicine during advice building, despite inexperience in using such systems. METHODS: Sixteen physicians, novices and experts in travel medicine, were solicited for building adequate recommendations about real cases of international travel with the help of a specialized PED. The physician's verbalizations, browsing in the documentation and final recommendations have been analyzed for the purpose of identifying and counting the requests addressed to the system and the informative elements in the recommendations. RESULTS: Novices make 2.5 times as many requests for information as experts (p=.0009), and look for a greater variety of information, specifically connected to health precautions (p=.0012), immunizations (p=.0001), health care resources (p=.0037) and climate (p=.019), whereas experts focus their requests mainly on health risks (64.81% of requests, p5.0009). The recommendations from the two groups included equivalent quantities of about 12 pieces of information, but experts used 92.34% of the information found in the documentation, whereas novices used 72.37% (p=.00005). The most used informative elements, whatever the expertise level is, are related to immunizations and health precautions, but experts include more information about health risks (p=0.017), drug characteristics (p=0.014) and chemoprophylaxis (p=0.026). CONCLUSIONS: The PED actually increases the novices' travel medicine expertise, and is particularly efficient for immunizations and health precautions. The PED helps a novice to build advice that is, on the whole, equivalent to an expert's in terms of nature, if not of quality. Implications for the benefits of comprehensive PEDs in the practice of travel medicine are discussed.