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Spatiotemporal clustering of in-hospital Clostridioides difficile infection

Published online by Cambridge University Press:  31 January 2020

Shreyas Pai ,
Philip M. Polgreen Open the ORCID record for Philip M. Polgreen [Opens in a new window] ,
Alberto Maria Segre ,
Daniel K. Sewell ,
Sriram V. Pemmaraju  and
for the CDC MInD-Healthcare group
Shreyas Pai
Affiliation:
Department of Computer Science, University of Iowa, Iowa City, Iowa
Philip M. Polgreen*
Affiliation:
Departments of Internal Medicine and Epidemiology, University of Iowa, Iowa City, Iowa
Alberto Maria Segre
Affiliation:
Department of Computer Science, University of Iowa, Iowa City, Iowa
Daniel K. Sewell
Affiliation:
Department of Biostatistics, University of Iowa, Iowa City, Iowa
Sriram V. Pemmaraju
Affiliation:
Department of Computer Science, University of Iowa, Iowa City, Iowa
*
Author for correspondence: Philip M. Polgreen, E-mail: [email protected]
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Abstract

Objective:

To determine whether Clostridioides difficile infection (CDI) exhibits spatiotemporal interaction and clustering.

Design:

Retrospective observational study.

Setting:

The University of Iowa Hospitals and Clinics.

Patients:

This study included 1,963 CDI cases, January 2005 through December 2011.

Methods:

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:

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.

Conclusion:

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.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 41 , Issue 4 , April 2020 , pp. 418 - 424
Copyright
© 2020 by The Society for Healthcare Epidemiology of America. All rights reserved

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Footnotes

PREVIOUS PRESENTATION: The work described in this manuscript was presented in part as poster #509, “Spatio-Temporal Clustering of CDI Cases at the University of Iowa Hospitals and Clinics,” at IDWeek 2018 on October 4, 2018, in San Francisco, California.

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