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ISDS 2012 Conference Abstracts

CaseFinder: A Flexible Real-time Online Surveillance
Registry for Infectious Disease Physicians to Report
Cases of Carbapenem-resistant Enterobacteriaceae
(CRE)
Donald Curtis*1, Scott Weissman2, Dimitri Drekonja3, Susan Beekmann4, Benjamin
Buckmaster1, John Lynch5, April Abbott6, Ferric Fang6 and Philip Polgreen4

1Coe College, Cedar Rapids, IA, USA; 2Seattle Children’s Hospital, Seattle, WA, USA; 3Minneapolis Veterans Affairs Medical Center,
Minneapolis, MN, USA; 4University of Iowa, Iowa City, IA, USA; 5Harborview Medical Center, Seattle, WA, USA; 6University of
Washington, Seattle, WA, USA

Objective
To create a flexible online surveillance system for infectious dis-

ease experts to report cases of emerging infectious diseases.

Introduction
The Infectious Disease Society of America’s Emerging Infections

Network (EIN) is a sentinel network of over 1,200 practicing infec-
tious disease physicians, supported by the Centers for Disease Con-
trol and Prevention (CDC). In January 2012, the EIN listserv fielded
a member inquiry about treatment recommendations for a compli-
cated polymicrobial wound infection in a traveler returning to the
United States from India. The posting led to a member-to-member
communication that resulted in shipment of clinical microbiology iso-
lates from one member’s hospital to another’s research laboratory.
Molecular evaluation of the clinical isolates uncovered previously
undetected carriage of the emerging NDM-1 enzyme in 2 of the En-
terobacteriaceae species. Based on this interaction, we built a flexi-
ble online surveillance registry (CaseFinder) for infectious disease
physicians to report cases of CRE.

Methods
To ascertain the frequency and nature of CRE infections treated

by EIN members, a survey was sent to EIN members in July 2012
that elicited risk factors and clinical features associated with CRE.
Survey opt-out items also allowed respondents to specify that they
had not treated any CRE infections. Concurrently, we developed a
formal relational data model for CRE infection survey data, allowing
for analysis and visualization. The data model was implemented in
Python using the Object-Relational Mapping provided by the Django
web framework, which we used to implement the backend server
component to the online registry. An interactive front-end web ap-
plication, written in Javascript using the jQuery library, retrieves data
via the AJAX web protocol. Geolocated data is visualized using the
OpenLayers library to render map tiles and provide interactive con-
trols such as panning and zooming.

Results
The crowd-sourced online registry for infectious disease experts to

report CRE infections, called CaseFinder (http://casefinder.org/), was
developed, released, and seeded with data from the EIN survey. To
date, a total of 69 cases have been submitted, describing 53 infec-
tions with Klebsiella pneumoniae, 7 with Escherichia coli and 9 with
other Enterobacteriaceae, representing 7 of 9 US Census divisions.
Another 214 members have indicated that they have not seen any
cases to date. CaseFinder includes: an online data entry component
(to supplant the original EIN listserv survey); real-time filtering of
data; and interactive maps that geolocate survey responses using the

first 2 digits of the treating facility’s zip code. Users can filter data
based on species, clinical features (age, gender), resistance profile,
or 2-digit zip code. CaseFinder can also display clinical case data in
an exportable line-item format.

Conclusions
We have created a web-based data registry for CRE infections in

the US. Populated by EIN survey responses, the registry already has
a collection 283 data points—69 cases of CRE and 214 reports indi-
cating the absence of cases—and is open for ongoing submission of
data represented in real time. This system can serve as a de facto na-
tional surveillance system for CRE infections - an important but not
yet universally reportable condition. Our platform can be expanded
to map and track other emerging infections seen by infectious dis-
eases physicians. We are currently working to incorporate molecular
fingerprinting and typing information into the data model. The site
will also provide incentives for infectious disease experts to submit
cases in underrepresented geographic areas. In future efforts we will
incorporate “machine learning” techniques to leverage knowledge
from infectious disease experts on existing cases and provide features
such as an intelligent automated alert system.

Keywords
Surveillance; Carbapenemases; Antibiotic resistance; Enterobacteri-
aceae; Klebsiella pneumoniae

*Donald Curtis
E-mail: dcurtis@coe.edu

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 5(1):e28, 2013