ArticleGlobal health research and policy2020
Modeling the trend of coronavirus disease 2019 and restoration of operational capability of metropolitan medical service in China: a machine learning and mathematical model-based analysis.
Article in Global health research and policy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.
- Data-driven strategies for model-informed decision-making during the COVID-19 pandemic: a systematic review.BMJ open · 2026Pooled it
- The application of the acoustic shadowing facilitates guidance in radial artery puncture and cannulation teaching in standardized training for residents: a randomized controlled trial.BMC medical education · 2022Trial
- Significance of supervision sampling in control of communicable respiratory disease simulated by a new model during different stages of the disease.Scientific reports · 2025Article
- Applications of Machine Learning (ML) and Mathematical Modeling (MM) in Healthcare with Special Focus on Cancer Prognosis and Anticancer Therapy: Current Status and Challenges.Pharmaceutics · 2024Review
- Role of miR-424 in the carcinogenesis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2024Review
- Noncontact remote sensing of abnormal blood pressure using a deep neural network: a novel approach for hypertension screening.Quantitative imaging in medicine and surgery · 2023Article
- A rapid review of machine learning approaches for telemedicine in the scope of COVID-19.Artificial intelligence in medicine · 2022Review
- Factors Influencing Post-traumatic Stress Symptoms in Chinese Adolescents During the COVID-19 Pandemic.Frontiers in psychiatry · 2022Article
- Activity-based epidemic propagation and contact network scaling in auto-dependent metropolitan areas.Scientific reports · 2021Article
- Application of machine learning in the prediction of COVID-19 daily new cases: A scoping review.Heliyon · 2021Article
- Impact of early Coronavirus Disease 2019 pandemic on pediatric cardiac surgery in China.The Journal of thoracic and cardiovascular surgery · 2021Observational
- Development of a machine learning algorithm to predict intubation among hospitalized patients with COVID-19.Journal of critical care · 2021Article
- Stay-at-home policy is a case of exception fallacy: an internet-based ecological study.Scientific reports · 2021Article
- Role of Machine Learning Techniques to Tackle the COVID-19 Crisis: Systematic Review.JMIR medical informatics · 2021Review
- How Do Machines Learn? Artificial Intelligence as a New Era in Medicine.Journal of personalized medicine · 2021Review
- Prediction of confirmed cases of and deaths caused by COVID-19 in Chile through time series techniques: A comparative study.PloS one · 2021Article
- Article
- COVID-ABS: An agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions.Chaos, solitons, and fractals · 2020Article
- Early survey with bibliometric analysis on machine learning approaches in controlling COVID-19 outbreaks.PeerJ. Computer science · 2020Article
Corrections and comments
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Authors and funding
7 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: To contain the outbreak of coronavirus disease 2019 (COVID-19) in China, many unprecedented intervention measures are adopted by the government. However, these measures may interfere in the normal medical service. We sought to model the trend of COVID-19 and estimate the restoration of operational capability of metropolitan medical service in China. Methods: Real-time data of COVID-19 and population mobility data were extracted from open sources. SEIR (Susceptible, Exposed, Infectious, Recovered) and neural network models (NNs) were built to model disease trends in Wuhan, Beijing, Shanghai and Guangzhou. Combined with public transportation data, Autoregressive Integrated Moving Average (ARIMA) model was used to estimate the accumulated demands for nonlocal hospitalization during the epidemic period in Beijing, Shanghai and Guangzhou. Results: The number of infected people and deaths would increase by 45% and 567% respectively, given that the government only has implemented traffic control in Wuhan without additional medical professionals. The epidemic of Wuhan (measured by cumulative confirmed cases) was predicted to reach turning point at the end of March and end in later April, 2020. The outbreak in Beijing, Shanghai and Guangzhou was predicted to end at the end of March and the medical service could be fully back to normal in middle of April. During the epidemic, the number of nonlocal inpatient hospitalizations decreased by 69.86%, 57.41% and 66.85% in Beijing, Shanghai and Guangzhou respectively. After the end of epidemic, medical centers located in these metropolises may face 58,799 (95% CI 48926-67,232) additional hospitalization needs in the first month. Conclusion: The COVID-19 epidemic in China has been effectively contained and medical service across the country is expected to return to normal in April. However, the huge unmet medical needs for other diseases could result in massive migration of patients and their families, bringing tremendous challenges for medical service in major metropolis and disease control for the potential asymptomatic virus carrier.
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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.