SARS-CoV-2 and pediatric encephalopathy: Google analytics and predictive modeling

Authors

  • Hend Jaddoa Jasim Specialist Pediatrician, Department of Pediatrics, Diyala Health Directorate, Iraqi Ministry of Health, Fellow, Department of Pediatrics, The Iraqi Board for Medical Specialties, Iraq, Member, Department of Pediatrics, The Council of Arab Board of Health Specializations, Syria
  • Shaima Hussein Alwan Specialist Pediatrician, Department of Pediatrics, Diyala Health Directorate, Iraqi Ministry of Health, Fellow, Department of Pediatrics, The Iraqi Board for Medical Specialties, Iraq
  • Ahmed Al-Imam Senior Researcher, Department of Anatomy and Cellular Biology, College of Medicine, University of Baghdad, Iraq, Associate Researcher, Department of Computer Science and Statistics, PUMS Doctoral School, Poznan University of Medical Sciences, Poland https://orcid.org/0000-0003-1846-9424
  • Huda Adnan Hussein Resident Doctor, Department of Pediatrics, Diyala Health Directorate, Iraqi Ministry of Health
  • Ali Kamil Al-Shalchy Dean of the College of Medicine, University of Baghdad, Iraq, Consultant Neurosurgeon, Department of Surgery, Neurosurgical Unit, College of Medicine, University of Baghdad, Baghdad, Iraq, Fellow of the Royal Colleges of Surgeons, United Kingdom

DOI:

https://doi.org/10.3126/ajms.v12i11.39093

Keywords:

Covid-19, Internet, Peiatric encephalitis, pediatric encephalopathy, SARS-CoV-2, Surface web

Abstract

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is rare in children and possesses distinctive clinical features.

Aims and Objectives: The primary objective is to bring clinicians,’ researchers,’ and epidemiologists’ attention to pediatric encephalopathy as part of the clinical manifestations of SARS-CoV-2 in children.

Materials and Methods: Google analytics aimed to explore the spatial-temporal (geographic-chronological) mapping of SARS-CoV-2 in conjunction with pediatric encephalopathy and encephalitis. We retrieved longitudinal data from Google Trends, for one year starting from December 2019, by deploying five search topics; “SARS-CoV-2,” “Coronavirus disease 2019, COVID-19” “Pediatric Encephalopathy,” “Pediatric Encephalitis,” and “Encephalitis in Children.”

Results: Spatio-temporal mapping was most conclusive for “COVID-19” and “Severe acute respiratory syndrome coronavirus 2.” Internet users were least interested in topics related to pediatric encephalopathy and encephalitis in children; potentially, reflecting the rarity of these entities in SARS-CoV-2 infections in children. We are also reporting a case of atypical SARS-CoV-2 in an 8-year-old child, in which pediatric encephalopathy occurred in a PCR-confirmed COVID-19 case.

Conclusion: Google analytics reconciled with the case report. SARS-CoV-2 in children may present with neurological rather than respiratory manifestations, which is atypical and rare. We are conveying two key messages; (1) pediatricians can collaborate with data scientists to realize evidence-based pediatric medicine and (2) digital data are worthy of exploration to guide subsequent rigor research, including randomized controlled trials and meta-analytics.

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Published

2021-11-01

How to Cite

Jaddoa Jasim, H., Alwan, S. H. ., Al-Imam, A., Hussein , H. A., & Kamil Al-Shalchy, A. (2021). SARS-CoV-2 and pediatric encephalopathy: Google analytics and predictive modeling. Asian Journal of Medical Sciences, 12(11), 29–34. https://doi.org/10.3126/ajms.v12i11.39093

Issue

Vol. 12 No. 11 (2021)

Section

Original Articles

License

Copyright (c) 2021 Asian Journal of Medical Sciences

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