• Preprint close
• English close
• Mémoires en Sciences de l'Information et de la Communication close
• COVID-19 close

International audience; Estimation of dynamical systems - in particular, identification of their parameters - is fundamental in computational biology, e.g., pharmacology, virology, or epidemiology, to reconcile model runs with available measurements. Unfortunately, the mean and variance priorities of the parameters must be chosen very appropriately to balance our distrust of the measurements when the data are sparse or corrupted by noise. Otherwise, the identification procedure fails. One option is to use repeated measurements collected in configurations with common priorities - for example, with multiple subjects in a clinical trial or clusters in an epidemiological investigation. This shared information is beneficial and is typically modeled in statistics using nonlinear mixed-effects models. In this paper, we present a data assimilation method that is compatible with such a mixed-effects strategy without being compromised by the potential curse of dimensionality. We define population-based estimators through maximum likelihood estimation. We then develop an equivalent robust sequential estimator for large populations based on filtering theory that sequentially integrates data. Finally, we limit the computational complexity by defining a reduced-order version of this population-based Kalman filter that clusters subpopulations with common observational backgrounds. The performance of the resulting algorithm is evaluated against classical pharmacokinetics benchmarks. Finally, the versatility of the proposed method is tested in an epidemiological study using real data on the hospitalisation of COVID-19 patients in the regions and departments of France.

This paper aims at reconstructing the evolution of all the available COVID-19 vaccines trials extracted from the COVID-NMA database by applying the phylomemy reconstruction process. We visualize the textual contents of 1,794 trials descriptions and explore their collective structure along with their semantic dynamics. We map the continuous progress of the main COVID-19 vaccine platforms from their early-stage trials in February 2020 to their most recent combinations driven by the rise of variants of concern, third dose issues and heterologous vaccinations. This paper brings insights for the global coordination between research teams especially in crisis situations such as the COVID-19 pandemic.

By using panel data of 15 Chinese manufacturing industries over the 2005-2014 period from OECD TiVA and WIOD databases, the impact of China's GVCs participation on labor productivity is estimated. We find that while the productivity elasticity of the share of sector's foreign value added relative to sector's exports known as sector backward linkages is negative, that relative to China's gross exports named structure backward linkage is positive. As the annual average growth rates of both backward linkages are negative, China's backward linkages have contributed to productivity growth of 6.41% per year on average. We find that the positive productivity elasticity of the share of domestic intermediate goods embodied in exports of third countries relative to sector's exports, named sector forward linages together with a positive annual average growth rate, and that relative to China's exports named structure forward linkages together with a negative annual average growth rate, have increased productivity of 1.97% per year on average. We find finally that GVCs position is improved from 0.3 in 2005 to 0.7 in 2014. China's GVCs participation exerted positive productivity effects via optimizing resource allocation inside sectors towards more efficiency ones, via moving up from low productivity backward linkages to higher productivity forward linkages and via improving its position. This diminished the risk to be entrenched in low-profitability low productivity growth GVCs activities in China. However, the productivity contribution of backward linkages 3 times higher than that of forward linkage suggests that the future positive productivity impact of GVCs moving up may be much more difficult in a less favorable context (trade war between China and USA, reindustrialization and trade protection related to Covid-19 for example).

The Covid-19 pandemic upset both the economies of most countries, but also the field of medical science. As never, public opinion has interfered in the choice of therapeutic trials as evidenced by the controversies surrounding protocols using hydroxychloroquine. The public's choice for these treatments is explained as the application of a kind of individual "Pascal's wager". This article analyses the formation of the belief system of individuals by applying ambiguity theory's insights and information entropy. It shows that the public's choices are the result of efficient communication strategies chosen by these treatments' promoters.

International audience; The disruption of supplies during the Covid-19 crisis has led to shortages but has also shown the adaptability of some companies, which have succeeded in adapting their production chains quickly to produce goods experiencing shortages: hydroalcoholic gel, masks, and medical gowns. These productive jumps from product A to product B are feasible because of the know-how proximity between the two classes of products. The proximities were computed from the analysis of co-exports and resulted in the construction of the product space. Based on the product space, as well as the customer-supplier relationships resulting from the input-output matrices, we propose a recommender system for companies. The goal is to promote distributed manufacturing by recommending a list of local suppliers to each company. As there is not always a local supplier for a desired product class, we consider the proximity between products to identify, in the absence of a supplier, a substitute supplier able to adapt its production tools to provide the required product. Our experiments are based on French data, from which we build a graph of synergies illustrating the potential productive links between companies. Finally, we show that our approach offers new perspectives to determine the level of territories' industrial resilience considering potential productive jumps.

AbstractThe definition of correlates of protection is critical for the development of next generation SARS-CoV-2 vaccine platforms. Here, we propose a new framework for identifying mechanistic correlates of protection based on mathematical modelling of viral dynamics and data mining of immunological markers. The application to three different studies in non-human primates evaluating SARS-CoV-2 vaccines based on CD40-targeting, two-component spike nanoparticle and mRNA 1273 identifies and quantifies two main mechanisms that are a decrease of rate of cell infection and an increase in clearance of infected cells. Inhibition of RBD binding to ACE2 appears to be a robust mechanistic correlate of protection across the three vaccine platforms although not capturing the whole biological vaccine effect. The model shows that RBD/ACE2 binding inhibition represents a strong mechanism of protection which required significant reduction in blocking potency to effectively compromise the control of viral replication.One Sentence SummaryA framework for modelling the immune control of viral dynamics is applied to quantify the effect of several SARS-CoV-2 vaccine platforms and to define mechanistic correlates of protection.

The author greatly acknowledges the generous support and assistance by FFJ/Michelin Foundation for the work.; This study searches for French urban mobility practices with the dilemma of planned versus lived spaces with a focus on the specific urban planning practice of pedestrianization. The contradictory interplay of residential, commercial and transport-led mobility is studied in Paris through direct observation, primary and secondary data collection. Moreover, the possible impacts of the on-going pandemic on this interplay of personal mobility, residential mobility and commercial mobility is recognized as a major factor –a game changer– in the Paris study. The Paris study findings are compared to Japanese pedestrianization practices from a perspective of municipally-led and gentrification-induced mobility practices as part of the urban neoliberal agenda.The Paris field study was made from February to June 2021. It composed mainly of an online survey with Paris (Île-de-France) residents and a corresponding paper survey with shopkeepers of three local shopping streets in Paris, including Rue Montorgueil-Rue des Petits Carreaux (in 2nd arrondissement), Rue Cler (in 7th arrondissement) and Rue Daguerre (in 14th arrondissement). Both surveys were translated into French and had multiple choice questions regarding the respondent’s personal situation, daily mobility habits and ideas on municipal pedestrianization efforts. The shop survey also had questions on the type of commerce, the effects of COVID-19 on one’s business and ideas on the effects of shopping street pedestrianization on one’s business in terms of number of customers, sales and shop value. The online resident survey was responded to by 119 people. The shop survey was done on Rue Montorgueil (31), Rue des Petits Carreaux (11), Rue Cler (25), Rue Daguerre (45), and the side streets of these shopping streets (9) on paper with the willing shopkeepers, who amounted to 121 altogether. Although the small size of the study surveys is a limitation of this study, the additional oral communication with the English-speaking shopkeepers about mobility and pedestrianization practices in Paris helped to mitigate this limitation. The online resident survey had been kept on purpose at Paris (Île-de-France) level with the intention of getting as much opinion as possible of Parisians on municipal pedestrianization efforts. The survey analysis that had been conducted at two different geographical levels—Paris (Île-de-France) and specific local shopping streets—on purpose indicated that Parisians can take a different stance against the on-going changes in the urban mobility regime of Paris, depending on their outlook as a resident or a local business. In that sense, their attitudes are not carved in stone, but they are quite flexible. Furthermore, the application of nonparametric tests of Chi-square test of independence and Fisher’s exact test indicated statistically significant relationships among the data variables, such as age and ideas on pedestrianization (resident survey); duration of residence in Paris (Île-de-France) and ideas on pedestrianization (resident survey); and place of residence and mode of transport to work (shop survey). Additional critical comments were made by some of the shopkeepers on Rue Cler and Rue Daguerre. Pedestrianization seems to create common problems for shops’ regular product deliveries, when their customers want to make large purchases at once, or if they have luggage (as mentioned by hoteliers) in particular. A couple of shopkeepers also heavily criticized a lack of municipal support for local independent businesses, and urban planners who did not ask about their opinions regarding their street’s pedestrianization as well as a wrong prioritization of pressing urban issues. Despite all these significant critiques, the study also found enormous support for the municipal pedestrianization efforts. This study also looked at the real estate values by taking a snapshot of Paris apartment and shop values on two online sites, including: paris-housing.com and thestorefront.com to search for a possible connection between higher than average real estate prices, used as a proxy for gentrification and pedestrianization. The study acknowledges that private agencies may modulate their database and housing offers in accordance with a specific group of customers, hence their online catalogues may not represent the actual price averages as a whole. Yet other potential databases were out of reach for the researcher because of language and economic barriers. Based on this simple real estate data analysis, although the m2 rental values for apartments and shops that are located near pedestrian streets seem to be higher than the Paris average in a few cases, this is not enough to conclude that there is a statistically significant relationship between pedestrianization and real estate values. It would require a consideration of the mediating factors, such as the assets’ own qualities, centrality, convenience, and availability of facilities and greenery nearby to cancel out their effects besides a more long-term data to compare the pre- and post-pedestrianization rental values. The paper concludes that despite the common tendency to prioritize active transport modes, such as walking and bicycling by the urban mobility regimes belonging to countries at different development levels, the mobility-based urban change policy and practices cause differing outcomes in different contexts. These can range from the more beneficial, such as resilience against environmental and health crises to the more controversial, including involuntary moves of people and shops (displacement) and more expensive, over-aestheticized cities of consumption (touristification and gentrification) with strengthened socio-economic demarcation lines between their citizens. The research underlines the possibility that popular urban policy discourses, in this case, a pedestrian-friendly city might create just the opposite ends depending on their way of implementation and contextual factors. At the same time, this paper argues that only by taking into account the opposite political stances of: the right to stay put, place-making, dwelling, anti-displacement, occupy and slow city movements in relation to the use of city space just as much as fluidity, liquidity, and mobility, more even forms of urban mobility can be achieved in the crisis-tested contemporary cities of the world.

The COVID-19 pandemic has prompted numerous fluid dynamical simulations of the propagation of potentially virus-laden respiratory droplets. While these studies have highlighted the apparent sensitivity of the numerical results to the sizes of the emitted droplet and the local humidity, many of them are still performed in stagnant air, i.e., without any external air flow. This very short note demonstrates, on the basis of coarse-grained fluid dynamical simulations in a simple generic setting, that even modest winds or air draughts strongly impact the risks of short-ranged transmission via droplets. The induced dispersion of droplets may contribute to explaining the lower risks of viral transmission experienced outdoors, even at short range.

Testing is a crucial control mechanism for an epidemic outbreak because it enables the health authority to detect and isolate the infected cases, thereby limiting the disease transmission to susceptible people, when no effective treatment or vaccine is available. In this paper, an epidemic model that incorporates the testing rate as a control input is presented. The proposed model distinguishes between the undetected infected and the detected infected cases with the latter assumed to be isolated from the disease spreading process in the population. Two testing policies, effective during the onset of an epidemic when no treatment or vaccine is available, are devised: (i) best-effort strategy for testing (BEST) and (ii) constant optimal strategy for testing (COST). The BEST is a suppression policy that provides a lower bound on the testing rate to stop the growth of the epidemic. The COST is a mitigation policy that minimizes the peak of the epidemic by providing a constant, optimal allocation of tests in a certain time interval when the total stockpile of tests is limited. Both testing policies are evaluated by their impact on the number of active intensive care unit (ICU) cases and the cumulative number of deaths due to COVID-19 in France. Comment: arXiv admin note: substantial text overlap with arXiv:2010.15438

International audience; In response to the ongoing COVID-19 pandemic caused by SARS-CoV-2, governments are taking a wide range of non-pharmaceutical interventions (NPI). These measures include interventions as stringent as strict lockdown but also school closure, bar and restaurant closure, curfews and barrier gestures i.e . social distancing. Disentangling the effectiveness of each NPI is crucial to inform response to future outbreaks. To this end, we first develop a multi-level estimation of the French COVID-19 epidemic over a period of one year. We rely on a global extended Susceptible-Infectious-Recovered (SIR) mechanistic model of the infection including a dynamical (over time) transmission rate containing a Wiener process accounting for modeling error. Random effects are integrated following an innovative population approach based on a Kalman-type filter where the log-likelihood functional couples data across French regions. We then fit the estimated time-varying transmission rate using a regression model depending on NPI, while accounting for vaccination coverage, apparition of variants of concern (VoC) and seasonal weather conditions. We show that all NPI considered have an independent significant effect on the transmission rate. We additionally demonstrate a strong effect from weather conditions which decrease transmission during the summer period, and also estimate increased transmissibility of VoCs.