Literature DB >> 33856876

A Spatiotemporal Tool to Project Hospital Critical Care Capacity and Mortality From COVID-19 in US Counties.

Alexis Zebrowski1, Andrew Rundle1, Sen Pei1, Tonguc Yaman1, Wan Yang1, Brendan G Carr1, Sarah Sims1, Ronan Doorley1, Neil Schluger1, James W Quinn1, Jeffrey Shaman1, Charles C Branas1.   

Abstract

Objectives. To create a tool to rapidly determine where pandemic demand for critical care overwhelms county-level surge capacity and to compare public health and medical responses.Methods. In March 2020, COVID-19 cases requiring critical care were estimated using an adaptive metapopulation SEIR (susceptible‒exposed‒infectious‒recovered) model for all 3142 US counties for future 21-day and 42-day periods from April 2, 2020, to May 13, 2020, in 4 reactive patterns of contact reduction-0%, 20%, 30%, and 40%-and 4 surge response scenarios-very low, low, medium, and high.Results. In areas with increased demand, surge response measures could avert 104 120 additional deaths-55% through high clearance of critical care beds and 45% through measures such as greater ventilator access. The percentages of lives saved from high levels of contact reduction were 1.9 to 4.2 times greater than high levels of hospital surge response. Differences in projected versus actual COVID-19 demands were reasonably small over time.Conclusions. Nonpharmaceutical public health interventions had greater impact in minimizing preventable deaths during the pandemic than did hospital critical care surge response. Ready-to-go spatiotemporal supply and demand data visualization and analytics tools should be advanced for future preparedness and all-hazards disaster response.

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Year:  2021        PMID: 33856876      PMCID: PMC8101594          DOI: 10.2105/AJPH.2021.306220

Source DB:  PubMed          Journal:  Am J Public Health        ISSN: 0090-0036            Impact factor:   9.308


  2 in total

1.  SPARSEMODr: Rapidly simulate spatially explicit and stochastic models of COVID-19 and other infectious diseases.

Authors:  Joseph R Mihaljevic; Seth Borkovec; Saikanth Ratnavale; Toby D Hocking; Kelsey E Banister; Joseph E Eppinger; Crystal Hepp; Eck Doerry
Journal:  Biol Methods Protoc       Date:  2022-09-01

2.  COVID-19 Prediction Models and Unexploited Data.

Authors:  K C Santosh
Journal:  J Med Syst       Date:  2020-08-13       Impact factor: 4.460

  2 in total

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