114 Launching the First Molecular-Based Surveillance System for a Parasitic Disease — Cryptonet, 2016

Tuesday, June 6, 2017: 10:00 AM-10:30 AM
Eagle, Boise Centre
Michele C. Hlavsa , Centers for Disease Control and Prevention, Atlanta, GA
Dawn M. Roellig , Centers for Disease Control and Prevention, Atlanta, GA
Matthew H. Seabolt , Centers for Disease Control and Prevention, Atlanta, GA
CryptoNet State Partners , State Public Health Agencies, Everytown, DC
Kathleen E. Fullerton , Centers for Disease Control and Prevention, Atlanta, GA
Lihua Xiao , Centers for Disease Control and Prevention, Atlanta, GA

BACKGROUND: Molecular testing has rewritten Cryptosporidium taxonomy. What was once thought to be a single species is at least 30 species that infect vertebrates. Most Cryptosporidium species are morphologically indistinguishable by traditional diagnostic tests; only molecular methods can distinguish species and their subtypes. After 2004, U.S. annual incidence of cryptosporidiosis has risen >3-fold, calling for a better understanding of Cryptosporidium transmission, and thus, cryptosporidiosis epidemiology, to direct development of evidence-based prevention and control strategies. Thus, in 2015, CDC formally launched CryptoNet, the first U.S. molecular-based surveillance system for a parasitic disease.

METHODS:  CDC microbiologists and epidemiologists have been closely working with state partners in Alabama, Maine, Minnesota, Nebraska, New Hampshire, Tennessee, and Wisconsin since mid-2015. To date, the focus has been on increasing state public health laboratory capacity to perform Sanger-based amplicon typing and to collect corresponding diagnostic and epidemiologic data for each specimen submitted to CryptoNet for molecular typing. Ohio joined CryptoNet in mid-2016.

RESULTS: For 2016, CDC’s CryptoNet laboratory received 272 specimens for molecular typing, of which 227 (83.5%) were positive for Cryptosporidium by molecular methods. Among the 2016 Cryptosporidium specimens, 8 (2.9%) and 264 (97.1%) were identified in specimens of patients with outbreak-associated and sporadic cases, respectively. The following subtypes were identified in specimens of patients with outbreak-associated cases: C. hominis IdA19, C. hominis IfA12G1, C. parvum IIaA18G3R1, and C. parvum IIaA15G2R1. The following subtypes were most frequently identified in specimens of patients with sporadic cases: C. parvum IIaA15G2R1, C. hominis IfA12G1, and Cryptosporidium chipmunk genotype I. Identification of non-C. parvum and non-C. hominis species led to further patient interviews and identification of distinct risk factors (e.g., squirrel contact).

CONCLUSIONS: The formal launch of CryptoNet has facilitated progress towards the ultimate CryptoNet objective of integrating molecular typing and epidemiologic data for each nationally notified cryptosporidiosis case. The 2016 submission count and positive proportion represent substantial increases over 2014; in 2014, 24 specimens were submitted, of which 18 (75%) positive. In addition to further increasing submission and positivity, CryptoNet next steps include 1) transferring protocols for whole genome–based multi-locus sequence typing (with substantially increased discriminatory power), once they are established, to state public health laboratories, 2) increasing state epidemiology capacity to collect and transmit epidemiologic data to CDC, and 3) overcoming barriers to specimen recovery (e.g., diagnosing cryptosporidiosis with rapid cartridge kits, which have low positive predictive value, and fixing specimens in formalin, which precludes DNA sequencing).