Analysis of the impact of the SARS-CoV-2 infection on the pediatric population hospitalized during the pandemic in the Greater Paris University Hospitals.

Background: The clinical characteristics, disease progression and outcome in children affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection appear significantly milder compared to older individuals. Nevertheless, the trends in hospitalization and clinical characteristics in the pediatric population seem to be different over time across the different epidemic waves. Objective: Our aim was to understand the impact of the different COVID-19 variants in the pediatric population hospitalized in the Pediatric Departments of the Public Hospital in the Greater Paris area by the analysis performed with the Assistance Publique-Hopitaux de Paris (AP-HP) Health Data Warehouse. Methods: This is a retrospective cohort study including 9,163 patients under 18 years of age, hospitalized from 1 March 2020 to 22 March 2022, in the Paris area, with confirmed infection by SARS-CoV-2. Three mutually exclusive groups with decreasing severity (Pediatric Inflammatory Multisystem Syndrome (PIMS), symptomatic infection, mild or asymptomatic infection) were defined and described regarding demography, medical history, complication of the SARS-CoV-2 infection, and treatment during admission. Temporal evolution was described by defining three successive waves (March-September 2020, October 2020-October 2021, and November 2021-March 2022) corresponding to the emergence of the successive variants. Results: In the study period, 9,163 pediatric patients with SARS-CoV-2 infection were hospitalized in 21 AP-HP hospitals. The number of patients with SARS-CoV-2 infection increased over time for each wave of the pandemic (the mean number of patients per month during the first wave was 332, 322 during the 2nd, and 595 during the third wave). In the medical history, the most associated concomitant disease was chronic respiratory disease. Patients hospitalized during the third wave presented a higher incidence of pulmonary involvement (10.2% compared to 7% and 6.5% during the first and second waves, respectively). The highest incidence of PIMS was observed during the first and second waves (4.2% in the first and second waves compared to 2.3% in the 3rd wave). Discussion: This analysis highlighted the high incidence of hospitalized children in the Greater Paris Area during the third wave of SARS-CoV-2 pandemic corresponding to the Omicron Covid-19 variant, which is probably an expression of a concomitant SARS-CoV-2, while a decreased incidence of PIMS complication was observed during the same period.

Evaluation of the prevalence of new-onset musculoskeletal symptoms in patients hospitalized for severe SARS-CoV-2 infection during the first two COVID waves in France: A descriptive analysis of the clinical data warehouse of 39 hospitals in France.

OBJECTIVE: To determine the prevalence of musculoskeletal (MSK) symptoms appearing after a SARS-CoV-2 infection. METHODS: This was an observational cohort based on data available at the Assistance publique-Hôpitaux de Paris (AP-HP) Clinical Data Warehouse (which includes data of more than 11 million patients treated in the 39 hospitals from AP-HP). The data collected included both ICD-10 codes in discharge summaries, and recurring wording expressions search on medical electronic documents. To be included in the analysis, patients had to have a positive RT-PCR for SARS-CoV-2 and be admitted in any department of AP-HP. Patients with previous history of any MSK condition were excluded. MSK conditions were considered if occurring up to 90days after the positive RT-PCR. Demographics and disease characteristics including treatment were compared in both groups (MSK yes/no) by t-test or Chi2 test, accordingly. RESULTS: In total, 17,771 patients had a positive SARS-CoV-2 RT-PCR at APHP and were admitted in any department of AP-HP. Among them, 15,601 had no previous history of MSK condition and among them, 1370 (8.8%) presented with MSK symptoms after the viral infection. The most prevalent MSK symptoms were back pain (32.9%), followed by arthralgia (29.9%), radicular pain (20.2%) and arthritis (22.8%). Patients with MSK symptoms (MSK+) were older (67 y vs. 64 y, P<0.01), more frequently obese (29% vs. 25%, P=0.03), hypertensive (34% vs. 30%, P<0.01) and with diabetes (21% vs. 18%, P<0.01). Treatment for SARS-CoV-2 was slightly different in both groups, with higher corticosteroids (40.7% vs. 29.0%, P<0.01), antivirals (21.5% vs. 15.3%, P<0.01) and immunosuppressors (8.5% vs. 4.5%, P<0.01) prescription rates in the MSK+ group. CONCLUSION: MSK symptoms occurred in almost 9% of patients admitted to the hospital after a SARS-CoV-2 infection, particularly in older and more comorbid patients. Further analysis evaluating whether these symptoms remain over time are needed.

Electric demand response and bounded rationality: mean-field control for large populations of heterogeneous bounded-rational agents.

The increased penetration of renewable energy sources into existing power systems induces challenges in supply-demand balancing. Demand-side flexibility is seen as an option to accommodate variability and limited predictability from renewable energy generation. Heat pumps at residential level, if well coordinated, can be one of those flexibility sources. The complexity involved is high though, since their coordinated operation combines control, population effects and the fact agents may actually not behave as rational decision-makers. We describe here a coordinated control framework that accounts for those aspects altogether. Decentralized model predictive control for large populations of heterogeneous agents is employed. As the cost to be minimized is affected by the population behaviour as a whole through the electricity price, the decentralized control is re-thought as a mean-field game. Existence and uniqueness of a Nash equilibrium are discussed while the Picard-Banach algorithm is used as a solution approach. It is extended to the case of bounded-rational agents. The impact on system dynamics of modelling agents as bounded rational is illustrated through numerical simulations. This article is part of the theme issue 'The mathematics of energy systems'.

Cortical recruitment determines learning dynamics and strategy.

Salience is a broad and widely used concept in neuroscience whose neuronal correlates, however, remain elusive. In behavioral conditioning, salience is used to explain various effects, such as stimulus overshadowing, and refers to how fast and strongly a stimulus can be associated with a conditioned event. Here, we identify sounds of equal intensity and perceptual detectability, which due to their spectro-temporal content recruit different levels of population activity in mouse auditory cortex. When using these sounds as cues in a Go/NoGo discrimination task, the degree of cortical recruitment matches the salience parameter of a reinforcement learning model used to analyze learning speed. We test an essential prediction of this model by training mice to discriminate light-sculpted optogenetic activity patterns in auditory cortex, and verify that cortical recruitment causally determines association or overshadowing of the stimulus components. This demonstrates that cortical recruitment underlies major aspects of stimulus salience during reinforcement learning.

RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system.

Future highly renewable energy systems will couple to complex weather and climate dynamics. This coupling is generally not captured in detail by the open models developed in the power and energy system communities, where such open models exist. To enable modeling such a future energy system, we describe a dedicated large-scale dataset for a renewable electric power system. The dataset combines a transmission network model, as well as information for generation and demand. Generation includes conventional generators with their technical and economic characteristics, as well as weather-driven forecasts and corresponding realizations for renewable energy generation for a period of 3 years. These may be scaled according to the envisioned degrees of renewable penetration in a future European energy system. The spatial coverage, completeness and resolution of this dataset, open the door to the evaluation, scaling analysis and replicability check of a wealth of proposals in, e.g., market design, network actor coordination and forecasting of renewable power generation.