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New Frontiers, Old Obstacles Pathogens, Genetics, Models, and Public Health J. Glenn Morris, Jr., MD, MPH&TM Emerging Pathogens Institute University of Florida
UF Emerging Pathogens Institute Created with $60 million appropriation from Florida state legislature, focusing on human, animal, and plant pathogens Over 200 faculty members, from 9 UF colleges (including medicine, public health, veterinary medicine, and agriculture) Strong global emphasis, reflecting Florida’s sub-tropical location
How do you guide optimal allocation of limited public health resources for prevention of diarrheal disease?
Why do kids in the developing world get symptomatic diarrhea? Driven by specific pathogens, but with occurrence of illness dependent on a complex set of interactions that include: Prior exposure to the pathogen /vaccination (immunity) Inoculum size Nutritional status Intestinal microenvironment, driven by local exposures
Lindsey et al, EID 2011;17:608-611 Sample of 2,748 patients with diarrheal disease in Kolkata; samples screened for 26 pathogens using standard microbiological techniques Approximately 1/3 had multiple pathogens Likelihood of infection with another specific pathogen among patients culture-positive for V. cholerae
Global Enterics Multi-Center Study (GEMS)(Levine et al, funded by Gates Foundation) 3609 samples from children with and without diarrhea, collected at 7 sites in Africa and Southern Asia Samples screened for pathogens using standard microbiological techniques Sub-Study: Comprehensive genetic analysis/ identification of all microorganisms in samples Data to date: analysis of 16S sequence data from samples from 1007 cases (514 children with diarrhea, 493 control children) Average of 3,900 sequences per sample
Bacterial Identification and Classification by 16S rRNA Permits screening of “total community DNA,” and identification of all “OTU” in sample Stool samples Environmental samples
Percentage of Case and Control Samples with Specific Pathogens, as Identified by Genetic vs. Microbiologic Techniques
Underlying intestinal flora did not differ by case/control status (although further analysis does suggest that risk can be influenced by flora composition) Patterns of intestinal flora (and pathogen distribution) did differ by country RedControl BlackCase Blue – Bangladesh Green -Kenya Black - Gambia
So does pathogen really matter? Yes: may be striking differences in public health impact, depending on pathogen Report released: April 28, 2011 Funded by: Robert Wood Johnson Foundation Available: epi.ufl.edu
U.S. Foodborne Pathogen Incidence* *Scallan et al, EID 2011;17:7-15
So does pathogen really matter? Yes: may be striking differences in public health impact, depending on pathogen Yes: transmission pathways (and optimal prevention strategies) may differ dramatically, depending on pathogen
Environmental Parameters V. cholerae in environment including plankton Cholera infections in humans Cholera Transmission Pathways “Slow” transmission: through fecal contamination of environment/water sources “Fast” transmission: driven by genetically-induced hyperinfectious state, occurring within a time window of a few hours after passage of stool. Transmission generally occurs within household or immediate environment of patient
Zimbabwe Spatial Models SIR model Calculation of R0 Average number of secondary infections that occur when one infective is introduced into a completely susceptible host population Estimation of relative contributions of: human/human transmission (short cycle, increased infectivity) vs. human/environment/human (long cycle, decreased infectivity) Use of these estimates to assess utility of intervention strategies such as vaccination
R0 by ProvinceZimbabwe Cholera Epidemic, 2008-9 Mukandavire et al, PNAS 2011;108:8767-72
Mapping ℛ0 values: Haiti Cholera Epidemic, 2010
Relative Contribution of “Slow” (Environmental) vs. “Fast” (Human) Sources to Cholera Transmission Zimbabwe RE (slow cycle) = 0.20 (17%) RH (fast cycle) = 0.95 (83% R0 = 1.15 Vaccine coverage to stop epidemic: 17% Haiti RE(slow cycle) = 0.84 (54%) RH (fast cycle) = 0.70 (46%) R0 = 1.54 Vaccination coverage to stop epidemic: 45%
How do you guide optimal allocation of limited public health resources for prevention of diarrheal disease? Systems are complex Mix of pathogens Mix of factors driving occurrence of symptomatic infection (disease) in individual patients Varying outcomes dependent on pathogen Mix of transmission routes, varying by pathogen, country, and region Variety of potential interventions, including water systems, sanitation, improved protection of water and food in households, vaccination…..
How do you guide optimal allocation of limited public health resources for prevention of diarrheal disease? Need for geographically-targeted, data-driven risk analysis, to define optimal approaches to disease prevention