Advancing the Management of Long COVID by Integrating into Health Informatics Domain: Current and Future Perspectives

The ongoing COVID-19 pandemic has profoundly affected millions of lives globally, with some individuals experiencing persistent symptoms even after recovering. Understanding and managing the long-term sequelae of COVID-19 is crucial for research, prevention, and control. To effectively monitor the h...

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Published inInternational journal of environmental research and public health Vol. 20; no. 19; p. 6836
Main Authors Ambalavanan, Radha, Snead, R Sterling, Marczika, Julia, Kozinsky, Karina, Aman, Edris
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 26.09.2023
MDPI
Subjects
Asymptomatic
COVID-19 vaccines
Epidemics
Health informatics
Illnesses
Infections
Literature reviews
Mortality
Pandemics
Pathophysiology
Public health
R&D
Research & development
Review
Severe acute respiratory syndrome coronavirus 2
Viral infections
China
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Summary:The ongoing COVID-19 pandemic has profoundly affected millions of lives globally, with some individuals experiencing persistent symptoms even after recovering. Understanding and managing the long-term sequelae of COVID-19 is crucial for research, prevention, and control. To effectively monitor the health of those affected, maintaining up-to-date health records is essential, and digital health informatics apps for surveillance play a pivotal role. In this review, we overview the existing literature on identifying and characterizing long COVID manifestations through hierarchical classification based on Human Phenotype Ontology (HPO). We outline the aspects of the National COVID Cohort Collaborative (N3C) and Researching COVID to Enhance Recovery (RECOVER) initiative in artificial intelligence (AI) to identify long COVID. Through knowledge exploration, we present a concept map of clinical pathways for long COVID, which offers insights into the data required and explores innovative frameworks for health informatics apps for tackling the long-term effects of COVID-19. This study achieves two main objectives by comprehensively reviewing long COVID identification and characterization techniques, making it the first paper to explore incorporating long COVID as a variable risk factor within a digital health informatics application. By achieving these objectives, it provides valuable insights on long COVID’s challenges and impact on public health.
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ISSN:1660-4601
1661-7827
1660-4601
DOI:10.3390/ijerph20196836