Back

Evaluation of kindergarten through grade 12 school absenteeism data as an indicator and predictor of respiratory disease

Oberholtzer, Z. W.; Jeon, S.; Fineman, L.; Hocevar Adkins, S. N.; Kang, G. J.; Imberi-Olivares, K.; Barrios, L. C.; Meltzer, M. I.

2024-12-13 public and global health
10.1101/2024.12.11.24318891 medRxiv
Show abstract

ObjectiveIncreases in school children absenteeism may precede increases in incidence of community-level respiratory diseases. This study assessed the correlations and predictive values between absenteeism in Kindergarten through Grade 12 students and community-level increases in influenza and COVID-19. MethodsAbsenteeism data from 4 districts between Fall 2018 and Spring 2022 was used to calculate correlations between school absenteeism and community-level cases of influenza, percent influenza-like-illnesses, and COVID-19. We estimated the positive predictive value (PPV) of a [≥]20% increase in school absences to predict a [≥]20% increase in community respiratory disease one or two weeks later. ResultsWe observed a median correlation of 0.4 between absenteeism and influenza cases across school years and districts, with a maximum of 0.8. COVID-19 cases had a median correlation of 0.1 with school absenteeism during the 2021-2022 school year. The median PPV for predicting increases in influenza 2 weeks ahead was 0.4 (maximum 0.6), and for COVID-19, the median PPV was 0.3. ConclusionsCorrelations and PPVs between school absenteeism and respiratory disease were variable, often below 0.5. School and public health officials may find absenteeism an inconsistent predictor of community-level respiratory diseases, limiting its utility for syndromic surveillance. Standardizing absence definitions and improving reporting timeliness may enhance its effectiveness. SUMMARY BOX1) What is the current understanding of this subject? Previous research has shown that K-12 student absenteeism may potentially anticipate surges in community influenza. 2) What does this report add to the literature? Correlations and predictive values between school absenteeism and community levels of respiratory diseases (influenza, influenza-like illnesses, COVID-19) were found to be variable and often below 0.5, suggesting limitations in using school absences as a form of syndromic surveillance. 3) What are the implications for public health practice? For school absenteeism to be a reliable syndromic surveillance tool, standardizing definitions of absences and improving reporting timeliness should be explored.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.