unc water and health conference 2011: professor glenn morris, university of florida
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New Frontiers, Old ObstaclesPathogens, Genetics, Models, and Public Health
J. Glenn Morris, Jr., MD, MPH&TMEmerging Pathogens InstituteUniversity 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 Environmenta
l samples
Percentage of Case and Control Samples with Specific Pathogens, as Identified by Genetic vs. Microbiologic Techniques
Aerom
onas
Campy
lobact
er
C. diffi
cle
Salm
onell
a
Shige
lla0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
Case GeneticControl GeneticCase MicroControl Micro
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
Blue – Bangladesh
Green - Kenya
Black - Gambia
Red Control
Black Case
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*
PathogenIllness
es
Rank
(ill) HospsRank
(hosp)Death
s
Rank (death
)
Norovirus5,461,7
31 1 14,663 2 149 4
Salmonella1,027,5
61 2 19,336 1 378 1C. perfringens 965,958 3 438 10 26 8Campylobacter 845,024 4 8,463 3 76 5Shigella spp. 131,254 6 1,456 6 10 10E. coli STEC non-O157 112,752 7 271 12 0 20Yersinia enterocolitica 97,656 8 533 9 29 7Toxoplasma gondii 86,686 9 4,428 4 327 2E. coli 0157:H7 63,153 12 2,138 5 20 9Cryptosporidium spp. 57,616 13 210 14 4 15V. parahaemolyticus 34,664 14 100 16 4 16Vibrio spp., other 17,564 16 83 21 8 12Cyclo. cayetanensis 11,407 21 11 27 0 20Listeria mono. 1,591 24 1,455 7 255 3Vibrio vulnificus 96 28 93 18 36 6
*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
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
Cholera infections in
humans
V. cholerae in environment
including plankton
Environmental Parameters
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 95 % CI
Harare 1.52 (1.14-1.96)
Bulawayo 1.36 (1.12-1.61)
Mashonaland Central 1.38 (1.21-1.54)
Mashonaland East 1.11 (0.90-1.32)
Mashonaland West 1.87 (1.34-2.38)
Midlands 1.39 (1.23-1.56)
Manicaland 2.06 (1.78-2.34)
Matebeleland South 2.72 (1.19-4.24)
Matebeleland North 1.72 (1.44-1.99)
Masvingo 1.61 (1.20-2.03)
Zimbabwe 1.15 (1.08-1.23)
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