Utility of illness symptoms for predicting COVID-19 infections in children

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Abstract

Background: The Centers for Disease Control and Prevention and the American Academy of Pediatrics recommend that symptomatic children remain home and get tested to identify potential coronavirus disease 2019 (COVID-19) cases. As the pandemic moves into a new phase, approaches to differentiate symptoms of COVID-19 versus other childhood infections can inform exclusion policies and potentially prevent future unnecessary missed school days. Methods: Retrospective analysis of standardized symptom and exposure screens in symptomatic children 0–18 years tested for SARS-CoV-2 at three outpatient sites April to November 2020. Likelihood ratios (LR), number needed to screen to identify one COVID-19 case, and estimated missed school days were calculated. Results: Of children studied (N = 2,167), 88.9% tested negative. Self-reported exposure to COVID-19 was the only factor that statistically significantly increased the likelihood of a positive test for all ages (Positive LR, 5–18 year olds: 5.26, 95% confidence interval (CI): 4.37–6.33; 0–4 year olds: 5.87, 95% CI: 4.67–7.38). Across ages 0–18, nasal congestion/rhinorrhea, sore throat, abdominal pain, and nausea/vomiting/diarrhea were commonly reported, and were either not associated or had decreased association with testing positive for COVID-19. The number of school days missed to identify one case of COVID-19 ranged from 19 to 48 across those common symptoms. Conclusions: We present an approach for identifying symptoms that are non-specific to COVID-19, for which exclusion would likely lead to limited impact on school safety but contribute to school-days missed. As variants and symptoms evolve, students and schools could benefit from reconsideration of exclusion and testing policies for non-specific symptoms, while maintaining testing for those who were exposed.

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APA

Zhou, G. Y., Penwill, N. Y., Cheng, G., Singh, P., Cheung, A., Shin, M., … Perito, E. R. (2022). Utility of illness symptoms for predicting COVID-19 infections in children. BMC Pediatrics, 22(1). https://doi.org/10.1186/s12887-022-03729-w

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