Commentary on Ferguson, et al., "Impact of Non-pharmaceutical Interventions (NPIs) to Reduce COVID-19 Mortality and Healthcare Demand".

Eubank, S; Eckstrand, I; Lewis, B; Venkatramanan, S; Marathe, M; Barrett, C L

Eubank, S; Eckstrand, I; Lewis, B; Venkatramanan, S; Marathe, M; Barrett, C L.

Eubank S; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, USA. eubank@virginia.edu.
Eckstrand I; Department of Public Health Sciences, University of Virginia, Charlottesville, USA. eubank@virginia.edu.
Lewis B; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, USA.
Venkatramanan S; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, USA.
Marathe M; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, USA.
Barrett CL; Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, USA.

Bull Math Biol ; 82(4): 52, 2020 04 08.

Article in English | MEDLINE | ID: covidwho-42142

ABSTRACT

ABSTRACT

A recent manuscript (Ferguson et al. in Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand, Imperial College COVID-19 Response Team, London, 2020. https//www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf) from Imperial College modelers examining ways to mitigate and control the spread of COVID-19 has attracted much attention. In this paper, we will discuss a coarse taxonomy of models and explore the context and significance of the Imperial College and other models in contributing to the analysis of COVID-19.

Subject(s)

Betacoronavirus; Coronavirus Infections; Health Services Needs and Demand; Infection Control; Models, Statistical; Pandemics/statistics & numerical data; Pneumonia, Viral; Basic Reproduction Number; COVID-19; COVID-19 Testing; Clinical Laboratory Techniques; Coronavirus Infections/diagnosis; Coronavirus Infections/mortality; Coronavirus Infections/prevention & control; Delivery of Health Care; Forecasting; Health Resources; Humans; Interprofessional Relations; Pandemics/prevention & control; Pneumonia, Viral/diagnosis; Pneumonia, Viral/mortality; Pneumonia, Viral/prevention & control; SARS-CoV-2; Time Factors

Keywords

COVID-19; Compartmental model; Epidemiology; Non-pharmaceutical intervention

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Models, Statistical / Infection Control / Coronavirus Infections / Pandemics / Betacoronavirus / Health Services Needs and Demand Type of study: Diagnostic study / Experimental Studies / Prognostic study Limits: Humans Language: English Journal: Bull Math Biol Year: 2020 Document Type: Article Affiliation country: S11538-020-00726-x

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