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Technical Information - Clostridium difficile Tracking


The Clostridium difficile infection (CDI) 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) activity. Data from the EIP CDI program can be 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, population targets for vaccine, and monitoring effectiveness of prevention strategies. The EIP CDI surveillance was launched in 2009 in 7 EIP sites. It currently operates in select counties in 10 EIP sites across the United States and has approximately 11.7 million people under surveillance.


Surveillance Objectives

  • Monitor the population-based incidence and disease burden of community– and healthcare–associated CDI
  • Characterize C. difficile strains causing disease in the population under surveillance with a focus on strains from community–associated cases, and describe changes in strain prevalence over time
  • Describe changes in the epidemiology of CDI with a focus on cases occurring outside of acute care settings

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  • Surveillance Population

    The table below illustrates the estimated population under surveillance for each EIP site as of December 2013.

    EIP CDI Sites and Estimated Population Under C. difficile Surveillance
    State Counties Under Surveillance 2011 2012 2013
    CA San Francisco County 812,826 825,863 837,442
    CO Adams, Arapahoe, Denver, Douglas and Jefferson Counties 2,488,410 2,532,982 2,583,519
    CT New Haven County 861,113 862,813 862,813
    GA Clayton, Cobb, DeKalb, Douglas, Fulton, Gwinnet, Newton and Rockdale Counties 3,753,452 3,821,534 3,864,091
    MD Caroline, Cecil, Dorchester, Frederick, Kent, Somerset, Talbot, Queen Anne’s, Washington, Wicomico and Worcester Counties 835,893 841,089 843,444
    MN Benton, Morrison, Olmsted*, Stearns and Todd Counties 248,079 395,098 397,786
    NM Bernalillo County 670,968 673,460 674,221
    NY Monroe County 745,625 747,813 749,606
    OR Klamath County 66,299 228,189 231,864
    TN Davidson County 635,475 648,295 658,602
    Total Population —————— 11,118,140 11,577,136 11,702,862

    *Olmsted County began CDI surveillance in July 2012.
    **Deschutes County began surveillance in January 2012.

  • Case Definition

    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 1 year of age or older. 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 eight consecutive weeks have elapsed since their last C. difficile-positive test.

    Recurrent episodes

    CDI cases with a positive C. difficile stool specimen between 2 to 8 weeks of the last positive specimen are considered recurrent episodes.

    Duplicate episodes

    CDI cases with a positive C. difficile stool specimen less than 2 weeks since the last positive specimen are considered duplicate episodes.

  • Case Ascertainment

    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 provides line listings of positive C. difficile test results to the local EIP site. The line listings 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 eight weeks after the last positive C. difficile specimen).

  • Data collection and epidemiologic classification

    Data collection is performed by trained surveillance epidemiologists at each EIP site. For each incident CDI case identified in 8 of the 10 EIP sites, a brief medical-record review is performed 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 catchment area. CDI cases are classified into three 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 healthcare exposure (i.e., history of hospitalization or long-term care facility residency in the 12 weeks before stool specimen collection); and community–associated (CA), if positive stool specimen was collected in an outpatient setting or within 3 calendar days in a person with no documented healthcare exposure 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.

  • Laboratory Characterization

    A convenience sample of stool specimens from incident CDI cases with complete clinical and epidemiologic information are sent to reference laboratories for C. difficile isolation. Isolates recovered are then sent to CDC for molecular characterization. Each isolate undergoes polymerase chain reaction (PCR)-screening for the tcdA, tcdB, cdtA and cdtB toxin genes, and deletions in tcdC are assessed by fragment analysis. Strain typing is performed using capillary-based PCR-ribotyping and results are analyzed against a library of standard profiles using BioNumerics.

  • Analysis

    Rates of CDI are calculated using population estimates 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 two EIP sites where sampling was performed (Colorado and Georgia).

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Annual Reports


  1. AS Chitnis, SM Holzbauer, RM Belflower, LG Winston, WM Bamberg, C Lyons, MM Farley, GK Dumyati, LE Wilson, ZG Beldavs, JR Dunn, LH Gould, DR MacCannell, DN Gerding, LC McDonald, FC Lessa. Epidemiology of community-associated Clostridium difficile infection, 2009–2011. JAMA Intern Med 2013;173:1359-67.
  2. Centers for Disease Control and Prevention (CDC). Vital Signs: Preventing Clostridium difficile infections. MMWR Morb Mortal Wkly Rep. 2012;61(9):157-62.
  3. 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;33(11):1107-12.
  4. Gould CV, Edwards JR, Cohen J, Bamberg WM, Clark LA, Farley MM, Johnston H, Nadle J, Winston L, Gerding DN, McDonald LC, Lessa FC. Effect of nucleic acid amplification testing on population-based incidence rates of Clostridium difficile infection. Clin Infect Dis 2013;57(9):1304-7.
  5. Cohen J, Limbago L, Dumyati G, Holzbauer S, Johnston H, Perlmutter R, Dunn J, Nadle J, Lyons C, Beldavs ZG, Clark LA, Lessa FC. 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;52(2):632-4.
  6. Wendt JM, Cohen JA, Mu Y, Dumyati GK, Dunn JR, Holzbauer SM, Winston LG, Johnston H, 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;133(4):651-8.
  7. See I, Mu Y, Cohen J, Beldavs ZG, Winston LG, Dumyati G, Holzbauer S, Dunn JR, Farley MM, Lyons C, Johnston H, Phipps E, Perlmutter R, Anderson L, Gerding DN, Lessa FC. NAP1 strain type is a predictor of outcomes from Clostridium difficile infection. Clin Infect Dis 2014;58(10):1394-400.
  8. Lessa FC, Mu Y, Winston L, Dumyati G, Farley MM, Beldavs Z, Kast K, Holzbauer SM, Meek JI, Cohen J, McDonald LC, Fridkin SK. Determinants of Clostridium difficile infection incidence across diverse U.S. geographic locations. Open Forum Infect Dis 2014;1(2):ofu048. doi: 10.1093/ofid/ofu048.
  9. Rhee SM, Tsay R, Nelson DS, Wijngaarden E, Dumyati G. Clostridium difficile in the Pediatric Population of Monroe County, NY. J Ped Infect Dis 2014;3:183-8.
  10. 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;372(24):2369-70.
  11. 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. doi: 10.1093/ofid/ofv113. First published online: August 11, 2015.

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