Zurück zu den Ergebnissen
Bibliografischer Datensatz · Ansicht und Zugriff
Artículo

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

Zeye Liu et al · KeAi Communications Co., Ltd · 2020

Open Access verfügbar
Schnellübersicht. Prüfen Sie die grundlegenden Angaben und öffnen Sie den Inhalt über die Hauptschaltfläche. Die Seite zeigt nur die Informationen, die zum Identifizieren, Zitieren und Öffnen des Werks nötig sind.

Zugriff auf die Ressource

Öffnen Sie den Inhalt über die Hauptoption oder wählen Sie eine andere verfügbare Quelle.

DOAJ DOAJ Articles
Entrar por DOAJ
Hauptzugriff

Open Access verfügbar

Recurso identificado como acceso abierto, sin confirmar automáticamente si es texto completo directo.
Ressource öffnen

Übersicht

Descripción general del contenido del recurso.

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.

Zitieren

Elegí el formato que necesitás y copiá la referencia al portapapeles.

APA 7

al, Z. L. E. (2020). 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. https://doi.org/10.1186/s41256-020-00145-4

MLA

al, Zeye Liu et. "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." 2020. https://doi.org/10.1186/s41256-020-00145-4.

Chicago

al, Zeye Liu et. 2020. "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.". https://doi.org/10.1186/s41256-020-00145-4.

Harvard

al, Z. L. E. 2020, 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, KeAi Communications Co, Ltd, available at: https://doi.org/10.1186/s41256-020-00145-4 [Accessed 6 Aug. 2026].

Teilen und drucken

Speichern Sie den Datensatz, kopieren Sie den Permalink oder drucken Sie ihn als PDF.

Referenz exportieren

Exportieren Sie den Datensatz in gängigen Formaten für Literaturverwaltungsprogramme.

Ressourcendetails

Bibliografische Angaben zur Prüfung, ob es sich um das richtige Material handelt.

Titel
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
Autor / Mitwirkende
Zeye Liu et al
Verlag
KeAi Communications Co., Ltd
Erscheinungsjahr
2020
ISSN
2397-0642
ISSN
2397-0642
Sprache
Inglés
Kopiert