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Application of QMRA in waterborne...
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FIRST INTERNATIONAL SYMPOSIUM ON FOOD SAFETY
“Application of QMRA in waterborne pathogens”
Aiko Adell NakashimaSchool of Veterinary Medicine
Faculty of Ecology and Natural ResourcesUniversidad Andres Bello
E-mail: [email protected]
Quantitative Microbial Risk Assessment (QMRA)
Methodology used to:
- Estimate risk and consequences from an exposure of individuals or population to
infectious organisms.
Allowing resources and efforts to be focused in prioritized ways to reduce risks
- Identify situations that contribute to an increased risk of illness
QMRA OBJECTIVES
Aim of QMRA:
Management and comunication.
Help directors, managers, shareholders, public services, individuals, etc. to understand the risk and opportunities.
Evaluate the available options to control those risks
QMRA: 4 STEPS
1) Hazard Identification 2) Dose-Response Assessment
3) Exposure Assessment: 4) Risk Characterization
Step 1
Step 2
Step 3=
QMRA– TOOLS
1. SPREADSHEETS (EXCEL).
@RISK (Palisade)
Crystal Ball (Oracle)
ModelRisk (Vose)
FONDECYT INICIACION PROJECT:
The impact of land use on the fecal sources of contamination of rivers and on human and
animal health risks
(Project ID: 11160116)
1. Hazard Identification
1. Hazard Identification
• WHO 2015: 31 foodborne hazards have caused 600 million illness and 420,000 deaths. Diarrhea disease agents: 230,000 deaths.
• Chile
WHO 2015, http://apps.who.int/iris/bitstream/10665/199350/1/9789241565165_eng.pdf?ua=1Prado, VJ, et al. 2002. Rev. med. Chile. 130 (5): 495 -501Olea , A et al. 2012. Rev Chilena Infectol. 29(5):504-10Thomas MK, et al. 2011. Epidemiol. Infect. (2011): 139, 560–571
Year N° of Outbreaks Incidence rate Reference
1999 190 7.5 Prado et al., 2002
2000 260 8.2 Prado et al., 2002
2005-2010 5,689 Olea et al, 2012
0.98–2.3 episode per person-year
Thomas et al., 2011
1. Hazard Identification
• Gastrointestinal Illness (GI) caused by parasites in Chile:
• Giardia duodenalis: prevalence + 20-30% - principal cause of diarrhea in children (Tassara, 1999).
• 2008-2012: 1,392 children diarrhea = 183 (13,1%) positive samples = Blastocystus hominis , Giardia duodenalis and Cryptosporidium spp (ISP 2012).
• Water related Outbreaks:
US: >50 cryptosporidiosis outbreaksin humans
• No treatment for Cryptosporidium• Tassara R. 1999. Pediatria. 1999; 70 (5): 441 -445 / ISP. 2012. URL: http://www.ispch.cl/sites/default/files/boletin_diarreas.pdf
Infection/illness: small doses (10 oocysts)
Adapter for waterborne transmission:
Excreted in large quantities
Resistant to environmental conditions
Chloride resistant
Oocysts (Cry) and cysts are immediately infective after being excreted
Protozoa: Cryptosporidium, Giardia Public Health Importance
2. Exposure Assessment:
Cryptosporidium/ Giardia
Viable (oo/cysts) Not Viable (oo/cysts)
Exposure: Water Ingestion
Water Source: River
Dilution Factor
Human
Fecal Coliforms + E. coli
Bacteroidales
Estimate contamination
MST
Other studies
Estimation of oocysts / cysts ingested by humans:
2. Exposure Assessment:
Conversion from 10 L to 1 mL
Dilution Factor:• 1:1• 1:30
Bacteroidales (%)
Protozoa viability• 100%• 0.1%
Water ingestion (ml)
Protozoa Concentration in 10L*
Own data
Own data
*Adjusted for recovery % and detection limit
2) Dose-Response Assessment
Exposition routes: Ingestion, inhalation, contact
Final result: Infection or Illness
Dose response Studies:
Mild-virulent agents: healthy adult humans
Cryposporium parvum: Okhuysen et al. 1999; Okhuysen et al. 2002, Chappell et al, 2006; etc
Giardia: Rendtorff (1954), and Rendtorff and Holt (1954)
Animal models
2) Dose-Response Assessment
Independent action theory:
One organism is capable of initiating illness
But, as the probability of evading the host defenses and causing infection is low,
More than one microorganism is required to cause infection
QMRA supports this theory: to determine the probability that one microorganism cause disease:
Models: Beta Exponencial Log probit
http://qmrawiki.canr.msu.edu/index.php?title=Table_of_Recommended_Best-Fit_Parameters
d = oocysts and cysts dose given to an individual (it is not a median dose)
r = probability that only one protozoa is able to cause infection
The distribution of microorganism that survive (and cause infection) is binomial when each one of the ingested dose (d) has a probability of surviving (r) equal or identical (Haas, 2002)*
*Haas, C.N., 2002, Conditional dose-response relationships for microorganisms: Development and application. Risk Anal 22, 455-463.
2) Dose-Response Assessment
Binomial Model
1. Cryptosporidium (Teunis, 2009)
Okhuysen et al. 1999; Okhuysen et al. 2002, Chappell et al, 2006
ID50 = 35 oocysts
2) Dose-Response Assessment
II. Giardia (Rose and Gerba, 1991)
Rendtorff (1954) and Rendtorff and Holt (1954)
r = 0.01982
Dose response curve for humans:
4. Risk Characterization
¿What is acceptable?
EPA criteria for humans:
32 illness/1,000 individuals or 3.2%
Percent of infections resulting in illness: 50% for Cryptosporidium and 45% for Giardia (Soller et al. (2010)
Results:
Humans: Probability of illness
Soller, J.A., Schoen, M.E., Bartrand, T., Ravenscroft, J.E., Ashbolt, N.J., 2010. Water Res. 44, 4674e4691
Pathogens are randomly distributed in water
Oocysts and cysts do not multiply in the environment
Viability is not the same as infectivity
A single pathogen can survive the host's defenses and reach the site where the infection develops
The survival of a pathogen is independent of the presence of another pathogen
Humans are healthy and immunocompetent individuals
Human will be exposed once to the contaminated water
Secondary infection won´t occur
5. Risk Characterization
Assumptions
5. Risk Characterization
Statistical Methods
@ Risk
Stochastic models using MonteCarlos simulation
Sensitivity Analysis: what variables in the model have a higher impact on the result
5. Risk Characterization
6. Results
Sensitivity Analysis
More Important Less Important
Protozoa ConcentrationBacteroidales (%)
Water IngestedSwimming durationSea otter body weight
Search for a risk range when the exposition is known orassumed: X pathogen has been detected during thesampling of a specific finished food. What level of riskwould the consumers have?
Evaluation of HACCP systems
Evaluate mitigation measures in the processing of a food: temperature, etc.
Estimate the risk of a population that consumes a specific food containing X amount of the microorganismY
Some applications of QMRA in Food Safety
Many thanks to:
María Cristina MartínezISP
Woutrina SmithUniversity of California, Davis