Syndromic surveillance as a predictive tool for health-related school absences in COVID-19 Sentinel Schools in Catalonia, Spain
preprint
OA: gold
CC-BY-NC-4.0
Abstract
ABSTRACT Monitoring influenza-like illness through syndromic surveillance could be an important strategy in the COVID-19 emergence scenario. The study aims to implement syndromic surveillance for children aged 6-11 years in COVID-19 sentinel schools in Catalonia. Data collection was made by self-applied survey to collect daily health status and symptoms. We proceed logistic mixed models and a Latent Class Analysis to investigate associations with syndromes and school absence. Were enrolled 135 students (2163 person-days) that filled 1536 surveys and 60 participants reported illness (29.52 by 100 person/day) and registered 189 absence events, 62 of them (32.8%) related to health reasons. Subgroups of influenza-like illness were founded such as a significantly and positively association with school absences. The findings of this study can be applied to the detection of health events, and association with school absences, offering an opportunity for quick action, or simply for monitoring and understanding the students’ health situation. ARTICLE SUMMARY LINE This study confirms the relevance of syndromic surveillance in students from 6 to 11 years of age as a strategy to timely detect events that can cause school absence, either to support public health actions by applying analytical models that improve their potential in providing systematized information, or to monitor and understand the health situation of students, thus offering an opportunity for rapid action.
My notes (saved in your browser only)
Citation neighborhood (no data yet)
We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.
Source provenance
- europepmc
- last seen: 2026-05-19T01:45:01.086888+00:00
- unpaywall
- last seen: 2026-05-21T05:10:58.409756+00:00
License: CC-BY-NC-4.0