Clostridioides difficile Infection (CDI) Tracking
Clostridioides difficile infection (CDI) is the leading cause of antibiotic-associated diarrhea and one of the most common healthcare-associated infections in the United States. The Clostridioides difficile infection surveillance program is an active population- and laboratory-based surveillance system conducted through CDC’s Emerging Infections Program (EIP) Healthcare-Associated Infections Community Interface (HAIC). Data from the EIP CDI program is used to measure the burden of CDI in the population, characterize C. difficile strains associated with disease, and to monitor trends in disease over time. The CDI surveillance program also provides an infrastructure for further public health research, including special studies aimed at identifying risk factors for C. difficile disease, populations to prioritize for vaccines, and monitoring effectiveness of prevention strategies. The EIP CDI surveillance was launched in 2009 in 7 EIP sites. Since 2011, EIP CDI surveillance has operated in selected counties in 10 EIP sites across the United States.
- Monitor population-based CDI incidence and disease burden of community- and healthcare-associated CDI over time to assess the impact of prevention strategies and inform public health practice.
- Describe the molecular and microbiologic characteristics of C. difficile strains causing disease in the population under surveillance and describe changes in strain prevalence over time.
- Monitor changes in the epidemiology of community- and healthcare-associated CDI, including disease severity, related complications and outcomes, and relevant risk factors to help guide prevention efforts.
The table below illustrates the estimated population under surveillance for each EIP site in 2019, the most recent year for which data are available.
|Areas Under Surveillance||Population|
|San Francisco County, CA||881,549|
|Adams, Arapahoe, Denver, Douglas and Jefferson Counties, CO||2,835,257|
|New Haven County, CT||854,757|
|Clayton, Cobb, DeKalb, Douglas, Fulton, Gwinnett, Newton and Rockdale Counties, GA||4,160,864|
|Caroline, Cecil, Dorchester, Frederick, Kent, Somerset, Talbot, Queen Anne’s, Washington, Wicomico and Worcester Counties, MD||867,271|
|Benton, Morrison, Olmsted*, Stearns and Todd Counties, MN||418,307|
|Bernalillo County, NM||679,121|
|Monroe County, NY||741,770|
|Klamath County, OR**||68,238|
|Davidson County, TN||694,144|
*Surveillance in Olmsted County began July 2012
**Deschutes County, OR participated in CDI surveillance during 2012-2013.
C. difficile infection Incident Case
A case of CDI is defined as a positive C. difficile toxin assay or a positive C. difficile molecular assay (e.g. PCR) of a stool specimen from a resident of the surveillance catchment area who is at least 1 year old. Cases with a C. difficile-positive stool specimen greater than 8 weeks after the last positive specimen are considered a new case with an incident stool specimen. Therefore, for surveillance purposes, an individual may be classified and captured as a new incident case if 8 consecutive weeks have elapsed since their last C. difficile-positive test.
CDI cases with a positive C. difficile stool specimen between 2 to 8 weeks of the last positive specimen are considered recurrent episodes.
CDI cases with a positive C. difficile stool specimen less than 2 weeks since the last positive specimen are considered duplicate episodes.
CDI cases are identified based on reports of positive C. difficile toxin assay or C. difficile nucleic acid amplification assay from all clinical, reference, and commercial laboratories that serve the population in the surveillance catchment areas. Each laboratory regularly reports positive C. difficile test results to the local EIP site. Accompanying data include the patient name and local laboratory identifier, date of specimen collection, as well as any additional available information (e.g. address, date of birth, age, sex, location of stool collection). Information on additional positive specimens from the same patient is recorded for the purpose of ascertaining and tracking recurrent or duplicate episodes, as well as new cases (i.e., greater than 8 weeks after the last positive C. difficile specimen).
Data Collection and Epidemiologic Classification
Data collection is performed by surveillance epidemiologists at each EIP site. In 8 of the 10 EIP sites, a brief medical-record review is performed for each incident CDI case to gather basic demographic characteristics, location of stool collection, and healthcare exposures. In the 2 remaining EIP sites with the largest surveillance populations (Colorado and Georgia), a brief medical record review is performed on a random sample of cases. Medical record reviews are not completed on recurrent or duplicate episodes or patients determined to reside outside the surveillance area.
CDI cases are classified into 3 epidemiologic categories:
- Healthcare facility-onset (HCFO), if the positive stool specimen was collected greater than 3 calendar days after hospital admission or in a resident of a long-term care facility
- Community-onset healthcare facility-associated (CO-HCFA), if the positive stool specimen was collected in an outpatient setting or within 3 days after hospital admission in a person with documented overnight stay in a healthcare facility (i.e., hospitalization or long-term care facility stay) in the 12 weeks before stool specimen collection
- Community–associated (CA), if positive stool specimen was collected in an outpatient setting or within 3 calendar days after hospital admission in a person with no documented overnight stay in a healthcare facility during the 12 weeks before the specimen was collected.
All CA and CO-HFCA cases and a random sample (10%) of HCFO cases subsequently undergo a comprehensive medical record review for clinical information and relevant risk factors.
A convenience sample of stool specimens from incident CDI cases with complete clinical and epidemiologic information is sent to reference laboratories for C. difficile isolation. Isolates recovered are then sent to CDC for molecular typing and characterization. Additional information can be found at Isolate Bank – C. difficile Infection Tracking.
Rates of CDI are calculated using population estimates (≥1 year of age) for the specified year. Cases with missing data (e.g., race) are multiply imputed using sequential regression imputation methods. A domain (subpopulation) analysis is performed to estimate the number of cases according to epidemiologic class and race in the 2 EIP sites where sampling was performed (Colorado and Georgia).
- 2019 Annual Report | Print Version [PDF – 10 Pages]
- 2018 Annual Report | Print Version [PDF – 2 pages]
- 2017 Annual Report | Print Version [PDF – 2 pages]
- 2016 Annual Report | Print Version [PDF – 2.41 MB]
- 2015 Annual Report | Print Version [PDF – 5.53 MB]
- 2014 Annual Report | Print Version [PDF – 5.52 MB]
- 2013 Annual Report [PDF – 1.07 MB]
- 2012 Annual Report [PDF – 1.04 MB]
For more information on the EIP surveillance data reported from Oregon in 2010, see the Federal Register: Findings of Research Misconduct (06/01/2015)
Adelman MW, Goodenough D, Sefton S, Mackey C, Thomas S, Fridkin SK, Woodworth MH. Changes in treatment of community-onset Clostridioides difficile infection after release of updated guidelines, Atlanta, Georgia, 2018. Anaerobe. 2021 Aug;70:102364. doi: 10.1016/j.anaerobe.2021.102364. Epub 2021 Apr 14.
Goodenough D, Sefton S, Overton E, Smith E, Kraft CS, Varkey JB, Fridkin SK. Reductions in positive Clostridioides difficile events reportable to National Healthcare Safety Network (NHSN) with adoption of reflex enzyme immunoassay (EIA) testing in 13 Atlanta hospitals. Infect Control Hosp Epidemiol. 2021 Jul 8:1-4. doi: 10.1017/ice.2021.145.
Pecora N, Holzbauer S, Wang X, Gu Y, Taffner S, Hatwar T, Hardy D, Dziejman M, D’Heilly P, Pung K, Guh A, Qiu X, Gill S, Dumyati G.
Genomic analysis of Clostridioides difficile in two regions of the United States reveals a diversity of strains and limited transmission. J Infect Dis. 2021 Jun 9:jiab294. doi: 10.1093/infdis/jiab294.
Paulick A, Adamczyk M, Anderson K, Vlachos N, Machado MJ, McAllister G, Korhonen L, Guh AY, Halpin AL, Rasheed JK, Karlsson M, Lutgring JD, Gargis AS; Emerging Infections Program Clostridioides difficile Pathogen Group. Characterization of Clostridioides difficile Isolates Available through the CDC & FDA Antibiotic Resistance Isolate Bank. Microbiol Resour Announc. 2021 Jan 7;10(1):e01011-20. doi: 10.1128/MRA.01011-20.
Korhonen L, Cohen J, Gregoricus N, Farley MM, Perlmutter R, Holzbauer SM, Dumyati G, Beldavs Z, Paulick A, Vinjé J, Limbago BM, Lessa FC, Guh AY. Evaluation of viral co-infections among patients with community-associated Clostridioides difficile infection. PLoS One. 2020 Oct 19;15(10):e0240549. doi: 10.1371/journal.pone.0240549. eCollection 2020.
Guh AY, Mu Y, Winston LG, Johnston H, Olson D, Farley MM, Wilson LE, Holzbauer SM, Phipps EC, Dumyati GK, Beldavs ZG, Kainer MA, Karlsson M, Gerding DN, McDonald LC. Trends in U.S. Burden of Clostridioides difficile Infection and Outcomes. N Engl J Med 2020 Apr;382(14):1320-1330. doi: 10.1056/NEJMoa1910215.
Novosad SA, Mu Y, Winston LG, Johnston H, Basiliere E, Olson DM, Farley MM, Revis A, Wilson L, Perlmutter R, Holzbauer SM, Whitten T, Phipps EC, Dumyati GK, Beldavs ZG, Ocampo VLS, Davis CM, Kainer M, Gerding DN, Guh AY. Treatment of Clostridioides difficile Infection and Non-compliance with Treatment Guidelines in Adults in 10 US Geographical Locations, 2013-2015. J Gen Intern Med. 2020 Feb;35(2):412-419. doi: 10.1007/s11606-019-05386-9. Epub 2019 Nov 25.
Guh AY, Hatfield KM, Winston LG, Martin B, Johnston H, Brousseau G, Farley MM, Wilson L, Perlmutter R, Phipps EC, Dumyati GK, Nelson D, Hatwar T, Kainer MA, Paulick AL, Karlsson M, Gerding DN, McDonald LC. Toxin Enzyme Immunoassays Detect Clostridioides difficile Infection With Greater Severity and Higher Recurrence Rates. Clin Infect Dis. 2019 Oct 30;69(10):1667-1674. doi: 10.1093/cid/ciz009.
Tsay S, Williams SR, Benedict K, Beldavs Z, Farley M, Harrison L, Schaffner W, Dumyati G, Blackstock A, Guh A, Vallabhaneni S. A Tale of Two Healthcare-associated Infections: Clostridium difficile Coinfection Among Patients With Candidemia. Clin Infect Dis. 2019 Feb 1;68(4):676-679. doi: 10.1093/cid/ciy607.
Weng MK, Adkins SH, Bamberg W, Farley MM, Espinosa CC, Wilson L, Perlmutter R, Holzbauer S, Whitten T, Phipps EC, Hancock EB, Dumyati G, Nelson DS, Beldavs ZG, Ocampo V, Davis CM, Rue B, Korhonen L, McDonald LC, Guh AY. Risk factors for community-associated Clostridioides difficile infection in young children. Epidemiol Infect. 2019 Jan;147:e172. doi: 10.1017/S0950268819000372.
Guh AY, Mu Y, Baggs J, Winston LG, Bamberg W, Lyons C, Farley MM, Wilson LE, Holzbauer SM, Phipps EC, Beldavs ZG, Kainer MA, Karlsson M, Gerding DN, Dumyati G. Trends in incidence of long-term-care facility onset Clostridium difficile infections in 10 US geographic locations during 2011-2015. Am J Infect Control. 2018 Jul;46(7):840-842. doi: 10.1016/j.ajic.2017.11.026.
Guh AY, Adkins SH, Li Q, Bulens SN, Farley MM, Smith Z, Holzbauer SM, Whitten T, Phipps EC, Hancock EB, Dumyati G, Concannon C, Kainer MA, Rue B, Lyons C, Olson DM, Wilson L, Perlmutter R, Winston LG, Parker E, Bamberg W, Beldavs ZG, Ocampo V, Karlsson M, Gerding DN, McDonald LC. Risk Factors for Community-Associated Clostridium difficile Infection in Adults: A Case-Control Study. Open Forum Infect Dis. 2017 Oct 26;4(4):ofx171. doi: 10.1093/ofid/ofx171.
Hunter JC, Mu Y, Dumyati GK, Farley MM, Winston LG, Johnston HL, Meek JI, Perlmutter R, Holzbauer SM, Beldavs ZG, Phipps EC, Dunn JR, Cohen JA, Avillan J, Stone ND, Gerding DN, McDonald LC, Lessa FC. Burden of Nursing Home-Onset Clostridium difficile Infection in the United States: Estimates of Incidence and Patient Outcomes. Open Forum Infect Dis. 2016 Jan 18;3(1):ofv196. doi: 10.1093/ofid/ofv196.
Baggs J, Yousey-Hindes K, Ashley ED, Meek J, Dumyati G, Cohen J, Wise ME, McDonald LC, Lessa FC. Identification of population at risk for future Clostridium difficile infection following hospital discharge to be targeted for vaccine trials. Vaccine. 2015 Nov 17;33(46):6241-9. doi: 10.1016/j.vaccine.2015.09.078. Epub 2015 Oct 9.
Dantes R, Mu Y, Hicks LA, Cohen J, Bamberg W, Beldavs ZG, Dumyati G, Farley MM, Holzbauer S, Meek J, Phipps E, Wilson L, Winston LG, McDonald LG, Less FC. Association Between Outpatient Antibiotic Prescribing Practices and Community-Associated Clostridium difficile Infection. Open Forum Infect Dis. 2015 Aug 11;2(3):ofv113. doi: 10.1093/ofid/ofv113. eCollection 2015 Sep.
Lessa FC, Winston LG, McDonald LC; Emerging Infections Program C. difficile Surveillance Team. Burden of Clostridium difficile infection in the United States. N Engl J Med. 2015 Jun 11;372(24):2369-70. doi: 10.1056/NEJMc1505190.
Rhee SM, Tsay R, Nelson DS, Wijngaarden E, Dumyati G. Clostridium difficile in the Pediatric Population of Monroe County, New York. J Pediatric Infect Dis Soc. 2014 Sep;3(3):183-8. doi: 10.1093/jpids/pit091. Epub 2014 Jan 15.
Lessa FC, Mu Y, Winston LG, Dumyati GK, Farley MM, Beldavs ZG, Kast K, Holzbauer SM, Meek JI, Cohen J, McDonald LC, Fridkin SK. Determinants of Clostridium difficile Infection Incidence Across Diverse United States Geographic Locations. Open Forum Infect Dis. 2014 Jul 28;1(2):ofu048. doi: 10.1093/ofid/ofu048. eCollection 2014 Sep.
See I, Mu Y, Cohen J, Beldavs ZG, Winston LG, Dumyati G, Holzbauer S, Dunn J, Farley MM, Lyons C, Johnston H, Phipps E, Perlmutter R, Anderson L, Gerding DN, Lessa FC. NAP1 strain type predicts outcomes from Clostridium difficile infection. Clin Infect Dis. 2014 May;58(10):1394-400. doi: 10.1093/cid/ciu125. Epub 2014 Mar 5.
Wendt JM, Cohen JA, Mu Y, Dumyati GK, Dunn JR, Holzbauer SM, Winston LG, Johnston HL, Meek JI, Farley MM, Wilson LE, Phipps EC, Beldavs ZG, Gerding DN, McDonald LC, Gould CV, Lessa FC. Clostridium difficile infection among children across diverse US geographic locations. Pediatrics. 2014 Apr;133(4):651-8. doi: 10.1542/peds.2013-3049. Epub 2014 Mar 3.
Cohen J, Limbago L, Dumyati G, Holzbauer S, Johnston H, Perlmutter R, Dunn J, Nadle J, Lyons C, Phipps E, Beldavs Z, Clark LA, Lessa FC, CDC’s Clostridium difficile Infection Surveillance Investigators. Impact of changes in Clostridium difficile testing practices on stool rejection policies and C. difficile positivity rates across multiple laboratories in the United States. J Clin Microbiol. 2014 Feb;52(2):632-4. doi: 10.1128/JCM.02177-13. Epub 2013 Nov 20.
Gould CV, Edwards JR, Cohen J, Bamberg WM, Clark LA, Farley MM, Johnston H, Nadle J, Winston L, Gerding DN, McDonald LC, Lessa FC, Clostridium difficile Infection Surveillance Investigators, Centers for Disease Control and Prevention. Effect of nucleic acid amplification testing on population-based incidence rates of Clostridium difficile infection. Clin Infect Dis. 2013 Nov;57(9):1304-7. doi: 10.1093/cid/cit492. Epub 2013 Jul 29.
Chitnis AS, Holzbauer SM, Belflower RM, Winston LG, Bamberg WM, Lyons C, Farley MM, Dumyati GK, Wilson LE, Beldavs ZG, Dunn JR, Gould LH, MacCannell DR, Gerding DN, McDonald LC, Lessa FC. Epidemiology of community-associated Clostridium difficile infection, 2009 through 2011. JAMA Intern Med. 2013 Jul 22;173(14):1359-67. doi: 10.1001/jamainternmed.2013.7056.
CDC. Vital Signs: Preventing Clostridium difficile Infections. Morb Mortal Wkly Rep. 2012 Mar 9;61(9):157-162.
Pawar D, Tsay R, Nelson DS, Elumalai MK, Lessa FC, Clifford McDonald L, Dumyati G. Burden of Clostridium difficile infection in long-term care facilities in Monroe County, New York. Infect Control Hosp Epidemiol. 2012 Nov;33(11):1107-12. doi: 10.1086/668031. Epub 2012 Sep 24.