ArticleBMC public health2025
Flexible school attendance strategies for epidemic outbreaks: simulation-based decision support.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundEmerging infectious diseases require time before appropriate countermeasures can be established because of the uncertainty surrounding their infection characteristics. During the COVID-19 pandemic, this delay led to significant disruptions in both the education sector and society as a whole. However, it is challenging to impose uniformly strict infection control measures in educational settings because the importance of continuity of education and social stability must also be considered.
methodsCharacteristics of emerging infectious diseases, such as latent period, infectious period, transmission potential, and asymptomatic rate, gradually become clearer over time. This study therefore proposed a framework to evaluate effective infection control measures at different stages (early, middle, and late) of an emerging infectious disease, as more information becomes available. This framework enables decision-making about educational opportunities and social continuity to be adjusted to reflect the characteristics of the disease known at any given time. The value of this framework was verified through simulations. It was used to compare the effectiveness of four staggered school attendance strategies recommended by UNESCO, under various disease characteristics (latent period, infectious period, transmission potential, and asymptomatic rate).
resultsThe most effective intervention varies with the characteristics of the infectious disease (latent period, infectious period, transmission potential, and asymptomatic rate), demonstrating the importance of our framework. This framework makes it possible to select appropriate school strategies based on the known characteristics of the disease at different stages of an outbreak, when considering the school environment and economic conditions.
conclusionsThis study proposed a framework for the phased adjustment of infection control measures in schools with increasing knowledge of the characteristics of an emerging infectious disease. Simulations demonstrated the effectiveness of the framework. This framework enables the selection of effective staggered school attendance methods that balance infection suppression with educational and social considerations. The framework could be extended to other environments, such as workplaces and public facilities, providing a comprehensive infection control strategy that mitigates social and educational burdens. Future research should explore the framework's application to a broader range of infectious disease scenarios to enhance its feasibility for real-world policy implementation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.