A Scenario-Based Evaluation of COVID-19-Related Essential Clinical Resource Demands in China.
Engineering (Beijing)
; 7(7): 948-957, 2021 Jul.
Article
in English
| MEDLINE | ID: covidwho-1240344
ABSTRACT
The coronavirus disease 2019 (COVID-19) pandemic is a global crisis, and medical systems in many countries are overwhelmed with supply shortages and increasing demands to treat patients due to the surge in cases and severe illnesses. This study aimed to assess COVID-19-related essential clinical resource demands in China, based on different scenarios involving COVID-19 spreads and interventions. We used a susceptible-exposed-infectious-hospitalized/isolated-removed (SEIHR) transmission dynamics model to estimate the number of COVID-19 infections and hospitalizations with corresponding essential healthcare resources needed. We found that, under strict non-pharmaceutical interventions (NPIs) or mass vaccination of the population, China would be able to contain community transmission and local outbreaks rapidly. However, under scenarios involving a low intensity of implemented NPIs and a small proportion of the population vaccinated, the use of a peacetime-wartime transition model would be needed for medical source stockpiles and preparations to ensure a normal functioning healthcare system. The implementation of COVID-19 vaccines and NPIs in different periods can influence the transmission of COVID-19 and subsequently affect the demand for clinical diagnosis and treatment. An increased proportion of asymptomatic infections in simulations will not reduce the demand for medical resources; however, attention must be paid to the increasing difficulty in containing COVID-19 transmission due to asymptomatic cases. This study provides evidence for emergency preparations and the adjustment of prevention and control strategies during the COVID-19 pandemic. It also provides guidance for essential healthcare investment and resource allocation.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Experimental Studies
/
Observational study
/
Prognostic study
Topics:
Vaccines
Language:
English
Journal:
Engineering (Beijing)
Year:
2021
Document Type:
Article
Affiliation country:
J.eng.2021.03.020
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