Journal article
Spatiotemporal clustering of in-hospital Clostridioides difficile infection
Infection control and hospital epidemiology, Vol.41(4), pp.418-424
04/2020
DOI: 10.1017/ice.2019.350
PMID: 32000873
Abstract
To determine whether Clostridioides difficile infection (CDI) exhibits spatiotemporal interaction and clustering.
Retrospective observational study.
The University of Iowa Hospitals and Clinics.
This study included 1,963 CDI cases, January 2005 through December 2011.
We extracted location and time information for each case and ran the Knox, Mantel, and mean and maximum component size tests for time thresholds (T = 7, 14, and 21 days) and distance thresholds (D = 2, 3, 4, and 5 units; 1 unit = 5-6 m). All tests were implemented using Monte Carlo simulations, and random CDI cases were constructed by randomly permuting times of CDI cases 20,000 times. As a counterfactual, we repeated all tests on 790 aspiration pneumonia cases because aspiration pneumonia is a complication without environmental factors.
Results from the Knox test and mean component size test rejected the null hypothesis of no spatiotemporal interaction (P < .0001), for all values of T and D. Results from the Mantel test also rejected the hypothesis of no spatiotemporal interaction (P < .0003). The same tests showed no such effects for aspiration pneumonia. Our results from the maximum component size tests showed similar trends, but they were not consistently significant, possibly because CDI outbreaks attributable to the environment were relatively small.
Our results clearly show spatiotemporal interaction and clustering among CDI cases and none whatsoever for aspiration pneumonia cases. These results strongly suggest that environmental factors play a role in the onset of some CDI cases. However, our results are not inconsistent with the possibility that many genetically unrelated CDI cases occurred during the study period.
Details
- Title: Subtitle
- Spatiotemporal clustering of in-hospital Clostridioides difficile infection
- Creators
- Shreyas Pai - Department of Computer Science, University of Iowa, Iowa City, IowaPhilip M Polgreen - Departments of Internal Medicine and Epidemiology, University of Iowa, Iowa City, IowaAlberto Maria Segre - Department of Computer Science, University of Iowa, Iowa City, IowaDaniel K Sewell - Department of Biostatistics, University of Iowa, Iowa City, IowaSriram V Pemmaraju - Department of Computer Science, University of Iowa, Iowa City, IowaCDC MInD-Healthcare group
- Resource Type
- Journal article
- Publication Details
- Infection control and hospital epidemiology, Vol.41(4), pp.418-424
- DOI
- 10.1017/ice.2019.350
- PMID
- 32000873
- NLM abbreviation
- Infect Control Hosp Epidemiol
- ISSN
- 0899-823X
- eISSN
- 1559-6834
- Grant note
- U01 CK000531 / NCEZID CDC HHS U01 CK000594 / NCEZID CDC HHS
- Language
- English
- Date published
- 04/2020
- Academic Unit
- Infectious Diseases; Epidemiology; Biostatistics; Nursing; Fraternal Order of Eagles Diabetes Research Center; Injury Prevention Research Center; Computer Science; Public Policy Center (Archive); Internal Medicine
- Record Identifier
- 9984214683602771
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