Trends in pediatric ambulatory community acquired infections before and during COVID-19 pandemic: A prospective multicentric surveillance study in France
Bibliographic record
Abstract
Background: The concept of immunity debt caused by non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic raised several concerns. We aimed to support this concept by analyzing the trends of community-acquired pediatric infectious diseases before and up to two years after the onset of the pandemic. Methods: We conducted a prospective surveillance study in France with 107 pediatricians. From January 2018 to April 2022, the electronic medical records of children with an infectious disease were automatically extracted. The annual number of infectious diseases in 2020 and 2021 was compared to 2018-2019 and their frequency was compared by logistic regression.Findings: From 2018 to 2021, 185,368 infectious diseases were recorded. Compared to 2018-2019, the number decreased in 2020 by about a third (from 98,783 to 35,432). Frequency of scarlet fever, tonsillopharyngitis, enteroviral infections, bronchiolitis, and gastroenteritis decreased with OR varying from 0·6 to 0·9, p<0·001. In 2021, among the 52,153 infectious diagnoses, an off-season rebound was observed with increased frequency of enteroviral infections, bronchiolitis, gastroenteritis and otitis with OR varying from 1·1 to 1·5, p<0·001. Children with chickenpox in 2021 were older by 1·9 months than in 2018-2019 (p<0·001).Interpretation: The unusual uptick of several infectious diseases after the partial relaxation of NPIs, at times with changed seasonality and age, underlines the interest of immunity debt, which could be attenuated through high vaccine coverage and an updated nationwide immunization schedule. These findings also highlight the need for continuous surveillance of infectious diseases, especially insofar as future epidemics are largely unpredictable.Trial Registration Details: The study was registered at ClinicalTrials.gov (NCT04471493).Funding Information: The study was supported by Association Clinique et Thérapeutique Infantile du Val de Marne (ACTIV), French Pediatrician Ambulatory Association (AFPA) and unrestricted grants of GSK, MSD, Pfizer and Sanofi.Declaration of Interests: RC reports grants to the institution ACTIV, personal fees, and nonfinancial support from GSK, Sanofi, Pfizer, and Merck, outside the submitted work. AR reports travel grants from Pfizer and AstraZeneca. FA reports receiving personal fees from MSD, AstraZeneca, Sanofi and Pfizer.NO reports travel grants from Pfizer, Sanofi, and GSK, outside the submitted work. BF is employed by CompuGroup Medical. CL reports grants to the institution ACTIV from GSK, Sanofi, Pfizer, and Merck, and personal fees and nonfinancial support from Pfizer and Merck, outside the conduct of the study. All other authors report no potential conflicts.Ethics Approval Statement: Parents and children were informed of the study before electronic data capture began and data were collected only in the event of non-refusal. The study was approved by the French National Commission on Informatics and Liberty (no. 1921226) and by an ethics committee (CHI Créteil Hospital, France).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".