ReviewPhilosophical transactions. Series A, Mathematical, physical, and engineering sciences2022
Data science approaches to confronting the COVID-19 pandemic: a narrative review.
Review in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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
21 citing papers in PubMed.
- An integrated framework for modelling respiratory disease transmission and designing surveillance networks using a sentinel index.Royal Society open science · 2025Article
- COVID-19 health data prediction: a critical evaluation of CNN-based approaches.Scientific reports · 2025Article
- Integrating artificial intelligence with mechanistic epidemiological modeling: a scoping review of opportunities and challenges.Nature communications · 2025Article
- Using artificial intelligence and predictive modelling to enable learning healthcare systems (LHS) for pandemic preparedness.Computational and structural biotechnology journal · 2024Review
- Global Trends of Medical Misadventures Using International Classification of Diseases, Tenth Revision Cluster Y62-Y69 Comparing Pre-, Intra-, and Post-COVID-19 Pandemic Phases: Protocol for a Retrospective Analysis Using the TriNetX Platform.JMIR research protocols · 2024Article
- Identification of Early Warning Signals of Infectious Diseases in Hospitals by Integrating Clinical Treatment and Disease Prevention.Current medical science · 2024Article
- Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review.JMIR public health and surveillance · 2024Article
- Complex Interplay between Population Immunity and Viral Dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Determinants of COVID Vaccination Willingness among Health and Non-Health Studies Students: A Cross-Sectional Study.Vaccines · 2023Article
- Leveraging Responsible, Explainable, and Local Artificial Intelligence Solutions for Clinical Public Health in the Global South.Healthcare (Basel, Switzerland) · 2023Article
- COVID-19 resilience index in European Union countries based on their risk and readiness scale.PloS one · 2023Article
- Agenda-Setting for COVID-19: A Study of Large-Scale Economic News Coverage Using Natural Language Processing.International journal of data science and analytics · 2023Article
- A COVID-19 Search Engine (CO-SE) with Transformer-based architecture.Healthcare analytics (New York, N.Y.) · 2022Article
- A network analysis and support vector regression approaches for visualising and predicting the COVID-19 outbreak in Malaysia.Healthcare analytics (New York, N.Y.) · 2022Article
- A data-driven hybrid ensemble AI model for COVID-19 infection forecast using multiple neural networks and reinforced learning.Computers in biology and medicine · 2022Article
- Ending the tuberculosis syndemic: is COVID-19 the (in)convenient scapegoat for poor progress?The Lancet. Respiratory medicine · 2022Article
- Management of neurosurgical patients during coronavirus disease 2019 pandemics: The Ljubljana, Slovenia experience.World journal of clinical cases · 2022Review
- Data science approaches to infectious disease surveillance.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022Review
- Mobile Sensing in the COVID-19 Era: A Review.Health data science · 2022Review
- Benefits of COVID-19 non-pharmaceutical interventions on the prevention of other notifiable infectious diseases.The Lancet regional health. Western Pacific · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
During the COVID-19 pandemic, more than ever, data science has become a powerful weapon in combating an infectious disease epidemic and arguably any future infectious disease epidemic. Computer scientists, data scientists, physicists and mathematicians have joined public health professionals and virologists to confront the largest pandemic in the century by capitalizing on the large-scale 'big data' generated and harnessed for combating the COVID-19 pandemic. In this paper, we review the newly born data science approaches to confronting COVID-19, including the estimation of epidemiological parameters, digital contact tracing, diagnosis, policy-making, resource allocation, risk assessment, mental health surveillance, social media analytics, drug repurposing and drug development. We compare the new approaches with conventional epidemiological studies, discuss lessons we learned from the COVID-19 pandemic, and highlight opportunities and challenges of data science approaches to confronting future infectious disease epidemics. This article is part of the theme issue 'Data science approaches to infectious disease surveillance'.
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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.