Journal article
COVID-19 modeling and non-pharmaceutical interventions in an outpatient dialysis unit
PLoS computational biology, Vol.17(7), e1009177
07/08/2021
DOI: 10.1371/journal.pcbi.1009177
PMCID: PMC8291695
PMID: 34237062
Abstract
This paper describes a data-driven simulation study that explores the relative impact of several low-cost and practical non-pharmaceutical interventions on the spread of COVID-19 in an outpatient hospital dialysis unit. The interventions considered include: (i) voluntary self-isolation of healthcare personnel (HCPs) with symptoms; (ii) a program of active syndromic surveillance and compulsory isolation of HCPs; (iii) the use of masks or respirators by patients and HCPs; (iv) improved social distancing among HCPs; (v) increased physical separation of dialysis stations; and (vi) patient isolation combined with preemptive isolation of exposed HCPs. Our simulations show that under conditions that existed prior to the COVID-19 outbreak, extremely high rates of COVID-19 infection can result in a dialysis unit. In simulations under worst-case modeling assumptions, a combination of relatively inexpensive interventions such as requiring surgical masks for everyone, encouraging social distancing between healthcare professionals (HCPs), slightly increasing the physical distance between dialysis stations, and—once the first symptomatic patient is detected—isolating that patient, replacing the HCP having had the most exposure to that patient, and relatively short-term use of N95 respirators by other HCPs can lead to a substantial reduction in both the attack rate and the likelihood of any spread beyond patient zero. For example, in a scenario with R0 = 3.0, 60% presymptomatic viral shedding, and a dialysis patient being the infection source, the attack rate falls from 87.8% at baseline to 34.6% with this intervention bundle. Furthermore, the likelihood of having no additional infections increases from 6.2% at baseline to 32.4% with this intervention bundle.
Details
- Title: Subtitle
- COVID-19 modeling and non-pharmaceutical interventions in an outpatient dialysis unit
- Creators
- Hankyu Jang - University of IowaPhilip M Polgreen - University of Iowa, Internal MedicineAlberto M Segre - University of Iowa, Computer ScienceSriram V Pemmaraju - University of Iowa, Computer Science
- Resource Type
- Journal article
- Publication Details
- PLoS computational biology, Vol.17(7), e1009177
- DOI
- 10.1371/journal.pcbi.1009177
- PMID
- 34237062
- PMCID
- PMC8291695
- NLM abbreviation
- PLoS Comput Biol
- ISSN
- 1553-734X
- eISSN
- 1553-7358
- Grant note
- Funding for this research was provided as part of CDC the MInD Healthcare group under cooperative agreement U01CK000531 and associated Covid19 supplemental funding. Authors PMP, AMS, SVP were awarded the grant and all 4 authors were supported by the grant. URL: https://www.cdc.gov/hai/research/MIND-Healthcare.html The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
- Language
- English
- Date published
- 07/08/2021
- Academic Unit
- Infectious Diseases; Epidemiology; Nursing; Fraternal Order of Eagles Diabetes Research Center; Injury Prevention Research Center; Computer Science; Internal Medicine
- Record Identifier
- 9984228051302771
Metrics
18 Record Views