1. The Use of Molecular Epidemiology and
Statistical Software to Detect Transmission of Pathogens
in the Healthcare Setting
Michael Phillips, MD
APIC Greater NYC Annual Conference

2. Disclosures
None
APIC NYC 2017

3. Review of the current state of pathogen surveillance
Learning objectives
Review of the current state of pathogen surveillance
How can time-space analysis help?
Want is “whole genome sequencing” and “molecular epidemiology”
Understand how molecular epidemiology has been used
What is the future? What does this mean for the infection preventionist?
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4. The epidemiologic triangle
HOST
ENVIRONMENT
PATHOGEN
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5. Pathogen transmission
Contact
Water
Air
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6. Pathogen transmission
Contact
Water
Air
Methicillin-resistant Staph aureus "MRSA"
Enterococcus
Klebsiella, Enterobacter, E. coli
Serratia
Acinetobacter ??
Pseudomonas
Listeria
Clostridium difficile "C diff"
Legionella
Aspergillus
Respiratory virus
Tuberculosis
Measles
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7. Survival of organisms with contact transmission
Bacteria
Survival time
Clostridium difficile
5 months
MRSA
1 to 4 weeks
Enterococcus
1 weeks to months
 Magill, SS. et alN. Engl. J. Med.2014, 370 (13), 1198–1208; Kramer, A.; Schwebke, I.; Kampf, G. BMC Infect. Dis.2006, 6, 130.
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8. Current state
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9. Current state
Good Hospital?
Bad Hospital?
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10. Geography matters
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11. John Snow – 1854 Cholera outbreak
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12. John Snow – 1854 Cholera outbreak
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15. WHONET and SaTScan WHONET: Developed for the WHO in 1989 Free
Management of microbiology data
Works with BacLink, a program to convert data into WHONET format
SaTScan:
Free, developed in 1997
Takes input from WHONET
Identifies spatial, space-time disease clusters
Uses a Poisson-based model
Givens a measure of statistical significance

16. Prospective surveillance in the community
3 year surveillance period
32 clustered detected, 26 prior to identification by hospital
22 of 26 clusters were “closely related” by PFGE

17. Retrospective surveillance in the hospital
750 bed hospital
5 year period
Compared clusters identified by “rules” vs SaTScan
≥ 3 HA MRSA or VRE on a unit with 2 week period

18. MRSA and VRE clusters detected by rules based surveillance vs SaTScan.
Yes No
SaTScan 1 6 7 66 73
VRE
Rules based
Yes No
SaTScan 4 87
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19. Potential clusters detected by SaTScan
Mean cluster size: 6
Median cluster size: 4
21 Gram positive
31 Gram negative
7 Fungi

20. What about prospective use of SaTScan in Hospitals?
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21. What about prospective use of WHONET SaTScan in Hospitals?
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22. Classification of clusters: high vs low risk
Same unit
Shared room
Same HCW
Specimens obtained >72 hours after admission
Environmental pathogens
Same antibiotic susceptibilities
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23. Classification of clusters: high vs low risk
Same unit
Shared room
Same HCW
Specimens obtained >72 hours after admission
Environmental pathogens
Same antibiotic susceptibilities
High risk = 3 or more
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24. High vs low risk clusters, Jan-Sept 2016 (n-168)
Characteristic
High risk, transmission +
High risk, transmission -
Low risk
# clusters 6 39
123
Median # pts/cluster (range)
2 (2-8)
2 (1-11)
Shared room 4 16 27
Shared unit 31 75
Shared HCW 22 44
Culture >72hrs 5 32 72
Same susceptibility 2 25 26
Environmental 8
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25. Organisms by cluster type, Jan-Sept 2016 (n-168)
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26. SaTScan: surveillance system evaluation
Simplicity
Flexibility
Data quality and acceptability
Sensitivity and PPV
Timeliness and representativeness
Usefulness
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27. Pathogen transmission – food
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28. Pathogen transmission – food
BASF Innovent 2017

29. Pathogen transmission – food
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30. Goal is to identify clusters
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31. Routine typing methods won’t work
Clonal
Complex
5 (CC5)
Clonal
Complex
8 (CC8)
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32. DNA review
Khan Academy
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33. The Whole Genome Sequencing Process
Source: CDC
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34. Sequencing cost curve “next-generation” DNA sequencing
Wetterstrand KA. DNA Sequencing Costs: Data from the NHGRI Genome Sequencing Program (GSP)
Available at: Accessed Oct 2017.
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35. How do we know strains are related?
GTAC Biotech
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36. Example: MRSA outbreak in the NICU
Harris et al, Lancet Infect Dis Feb; 13(2):
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37. Example: WGS allows true measure of hospital transmission
Eyre et al. Clin Infect Dis. 2017;65(3):433-41
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38. Example: Geography and referral patterns matter
Williamsburg – cluster 2
Williamsburg – cluster 1

39. Multidrug resistant MRSA
Chlorhexidine resistance
Mupirocin resistance
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40. USA 300 SNP Tree
Others
Others

41. Other molecular methods: MALDI-TOF
Veenemans Eur J Clin Microbiol Infect Dis
2016; 35:
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42. Linking “molecular” to “epi”
Why the NICU? The patients don’t move and LOS is weeks
Requires advanced analytics
Prospective surveillance
Clear and careful messaging
Will become a part of our “toolkit”
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43. A few closing thoughts
Use of cluster detection methods and “molecular epi” will become routine
Sooner than you think!
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44. A few closing thoughts
Use of cluster detection methods and “molecular epi” will become routine
Sooner than you think!
Infection Prevention and Control needs to “own” this space
Only IPC can link data and epi to identify potential transmission routes
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45. A few closing thoughts
Use of cluster detection methods and “molecular epi” will become routine
Sooner than you think!
Infection Prevention and Control needs to “own” this space
Only IPC can link data and epi to identify potential transmission routes
New era of public reporting
A new paradigm for IPC and DOH
APIC NYC 2017

46. A few closing thoughts
Use of cluster detection methods and “molecular epi” will become routine
Sooner than you think!
Infection Prevention and Control needs to “own” this space
Only IPC can link data and epi to identify potential transmission routes
New era of public reporting
A new paradigm for IPC and DOH
Allow predictive analytics
Infection prevention, not just control
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48. Time Period: FY 2016 / Note: Includes Lutheran data