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Microbial Risk Assessment Envr 133 Mark D. Sobsey Spring, 2006 Definition of Quantitative Microbial Risk Assessment Applications of the principles of risk assessment to the estimation of the consequences from anticipated or actual exposure to infectious microorganisms Relationship Between Exposure, Level of Protection and Microbial Risk = Confidence Region or Interval Risk Exposure Level of Technological Control Some Differences Between Chemical and Microbial Risks • A single microbe (one unit) is infectious • Microbes multiply: – In a host – In environmental media (some) • Secondary spread – Microbe infects a host from an environmental route of exposure (water, food, etc.) can – Then, it spreads to other hosts by person-toperson transmission • Some microbes cause a wide range (spectrum) of adverse effects (Adapted from: National Academy of Sciences - National Research Council framework) RISK ASSESSMENT FOR ENVIRONMENTALLY TRANSMITTED MICROBIAL PATHOGENS: ILSI/EPA PARADIGM PROBLEM FORMULATION: HAZARD IDENTIFICATION CHARACTERIZATION OF EXPOSURE EFFECTS CHARACTERIZATION OF HUMAN HEALTH RISK CHARACTERIZATION Risk Management ILSI/EPA Risk Assessment Framework and Steps: Analysis Phase (Adapted from: National Academy of Sciences - National Research Council framework) Conducting Hazard Identification • Identify microbes as causative agent of disease • Develop/identify diagnostic tools to identify symptoms, infection and to isolate and identify causative microbe in host specimens • Understand the disease process from exposure to infection, illness (pathophysiology) and death • Identify transmission routes • Assess virulence factors and other properties of the microbe responsible for disease, including life cycle • Identify and apply diagnostic tools to determine incidence and prevalence in populations and investigate disease outbreaks • Develop models (usually animals to study disease process and approaches to treatment • Evaluate role of immunity in overcoming/preventing infection and disease and possible vaccine development • Study epidemiology associated with various exposures (Adapted from: National Academy of Sciences - National Research Council framework) Exposure Assessment • Purpose: determine the dose • Dose = number, quantity or amount of microorganisms corresponding to a single exposure (e.g., by ingestion) • Average or typical dose – a measure of central tendency • mean or median • Distribution of doses Described as a probability or frequency distribution; “probability density function” CHARACTERIZATION OF EXPOSURE ELEMENTS INCLUDED IN PATHOGEN CHARACTERIZATION: OCCURRENCE (previous lecture) • Temporal distribution, duration and frequency • Concentration in food or environmental media • Spatial distribution – clumping, aggregation, particle-association, clustering • Niche – ecology and non-human reservoirs – potential to multiply/survive in specific foods or media • • • • Survival, persistence, and amplification Seasonality Meteorological and climatic events Presence of control or treatment processes – including their reliability and variability • Indicators/surrogates for indirect evaluation – predictive of pathogen ELEMENTS CONSIDERED IN PATHOGEN CHARACTERIZATION (previous lecture) • • • • • • • • • Virulence and pathogenicity of the microorganism Pathologic characteristics and diseases caused Survival and multiplication of the microorganism Resistance to control or treatment processes Host specificity Infection mechanism and route; portal of entry Potential for secondary spread Taxonomy and strain variation Ecology and natural history Pathogen Characteristics or Properties Favoring Environmental Transmission (previous lecture) Multiple sources and high endemicity in humans, animals and environment – High concentrations released into or present in environmental media (water, food, air) – High carriage rate in human and animal hosts – Asymptomatic carriage in non-human hosts – Ability to proliferate in water and other media – Ability to adapt to and persist in different media or hosts – Seasonality and climatic effects – Natural and anthropogenic sources Pathogen Characteristics or Properties Favoring Environmental Transmission (previous lecture) • Ability to Persist or Proliferate in Environment and Survive or Penetrate Treatment Processes • Stable environmental forms – spores, cysts, oocysts, stable outer viral layer (protein coat), capsule, etc. • Resistance to biodegradation, heat, cold (freezing), drying, dessication, UV light, ionizing radiation, pH extremes, etc. • Resists proteases, amylases, lipases and nucleases – Posses DNA repair mechanisms and other injury repair processes • Colonization, biofilm formation, resting stages, protective stages, parasitism – Spatial distribution – Aggregation, particle association, etc. Virulence Properties of Pathogenic Bacteria Favoring Environmental Transmission (previous lecture) Virulence properties: structures or chemical constituents that contribute to pathophysiology: – Outer cell membrane of Gram negative bacteria: endotoxin (fever producer) – Exotoxins – Pili: for attachment and effacement to cells and tissues – Invasins: to facilitate cell invasion – Effacement factors Spores: – highly to physical and chemical agents and – very persistent in the environment Others: – plasmids, lysogenic bacteriophages, etc. Pathogen Characteristics or Properties Favoring Environmental Transmission (previous lecture) Genetic properties favoring survival and pathogenicity • Double-stranded DNA or RNA • DNA repair • Ability for genetic exchange, mutation and selection – recombination – plasmid exchange, transposition, conjugation, etc. – point mutation – reassortment – gene expression control • Virulence properties: expression, acquisition, exchange • Antibiotic resistance Role of Selection of New Microbial Strains in Susceptibility to Infection and Illness (previous lecture) • Antigenic changes in microbes overcome immunity, increasing risks of re-infection or illness – Antigenically different strains of microbes appear and are selected for over time and space – Constant selection of new strains (by antigenic shift and drift) – Partly driven by “herd” immunity and genetic recombination, reassortment , bacterial conjugation, bacteriophage infection and point mutations • Antigenic Shift: – Major change in virus genetic composition by gene substitution or replacement (e.g., reassortment) • Antigenic Drift: – Minor changes in virus genetic composition, often by mutation involving specific codons in existing genes (point mutations) • A single point mutation can greatly alter microbial virulence Pathogen Characteristics or Properties Favoring Environmental Transmission (previous lecture) Ability to Cause Infection and Illness • Low infectious dose • Infects by multiple routes – ingestion (GI) – inhalation (respiratory) – cutaneous (skin) – eye – etc. Microbe Levels in Environmental Media Vary Over Time Occurrence of Giardia Cysts in Water: Cumulative Frequency Distribution Previous lecture CHARACTERIZATION OF EXPOSURE ELEMENTS CONSIDERED IN EXPOSURE ANALYSIS (previous lecture) • Identification of water, food or other media/vehicles of exposure • Units of exposure • Routes of exposure and transmission potential • Size of exposed population • Demographics of exposed population • Spatial and temporal nature of exposure (single or multiple; intervals) • Behavior of exposed population • Treatment, processing, and recontamination (Adapted from: National Academy of Sciences - National Research Council framework) CHARACTERIZATION OF HUMAN HEALTH EFFECTS ELEMENTS CONSIDERED IN HOST CHARACTERIZATION (previous lecture) • • • • • • • Age Immune status Concurrent illness or infirmity Genetic background Pregnancy Nutritional status Demographics of the exposed population (density, etc.) • Social and behavioral traits CHARACTERIZATION OF HUMAN HEALTH EFFECTS ELEMENTS CONSIDERED IN HEALTH EFFECTS (previous lecture) • • • • • • Duration of illness Severity of illness Infectivity Morbidity, mortality, sequelae of illness Extent or amount of secondary spread Quality of life • Chronicity or recurrence Characteristics or Properties of Pathogens Interactions with Hosts (previous lecture) • Disease characteristics and spectrum • Persistence in hosts: – Chronicity – Persistence – Recrudescence – Sequelae and other post-infection health effects • cancer, heart disease, arthritis, neurological effects • Secondary spread Elements That May be Included in Dose-Response Analysis • Statistical model(s) to analyze of quantify doseresponse relationships • Human dose-response data • Animal dose-response data • Utilization of outbreak or intervention data • Route of exposure or administration • Source and preparation of challenge material or inoculum • Organism type and strain – including virulence factors or other measures of pathogenicity • Characteristics of the exposed population – age, immune status, etc. • Duration and multiplicity of exposure Dose-Response Data and Probability of Infection for Human Rotavirus Dose 90,000 9,000 900 90 9 0.9 0.09 # Dosed 3 7 8 7 7 7 5 # Infected 3 5 7 6 1 0 0 Dose-Response Models and Extrapolation to Low Dose Range • Most dose-response data for microbes are for high doses of microbes and few hosts – due practicalities and cost limits • Real world exposures to microbes from water, food and air are often to much lower microbial doses • It becomes necessary to extrapolate the doseresponse relationship to the low dose range where there are no experimental data points – a best-fit modelling approach is employed Models Typically Applied in Microbial Dose-Response Analyses • Exponential model: Pinfection = 1 - e-r where r = probability of infection and = mean concentration/dose – assumes organisms are distributed randomly (Poisson) and – probability of infection = r – approaches a linear model at low doses • Exponential (linear) model; two populations: – – one-hit kinetics, but two classes of human susceptibility to microbe • Beta-Poisson: a distributed threshold model – assumes Poisson distribution of microbes and a Betadistributed probability of infection • r is not a constant but a probability distribution (Beta-distribution) – two variables in the model Probabilities of Exposure and Infection • Pexp (j Dose) = Probability of having j pathogenic microbes in an ingested dose • Pinf (j Inf) = Conditional probability of infection from j pathogens ingested Probability of Exposure Exponential Dose-Response Model Beta-Poisson Dose-Response Model Rotavirus Dose-Response Relationships: Experimental Data, Exponential Model and Beta-Poisson Model Daily and Annual Risks of Various Outcomes from Exposure to Water Containing 4 Rotaviruses per 1000 Liters Volunteer Dose-Response Data for Norwalk Virus* Dose (ml) 4 1 0.01 0.0001 No. Dosed 16 21 4 4 No Ill 11 14 2 0 % Ill 69 67 50 0 *"1st passage NV": Dolin et al. 1972; Wyatt et al., 1974. Norwalk Virus Dose-Response Analysis Using Alternative Models 1 0.9 Measured P(D) Fraction withEffect 0.8 Linear (exp) 0.7 Lin(2pop) 0.6 b-Poisson 0.5 0.4 0.3 0.2 0.1 0 0 0.0001 0.01 Dose (ml) 1 4 Dose-Response Relationships for Various Waterborne Pathogens: Downward Extrapolation to Low-Dose Range Comparing Risks of Disease Agents • Comparing chemical to microbial risks as well as among agents of each type • Effects vary widely in severity, mortality rates and time scale of exposure • Need to protect both quality and quantity of life • Drinking water policy needs to be linked to overall public health policy • Decision making process needs to take social and economic factors into account Desirable attributes of an integrated measure of risk • Address probability, nature and magnitude of adverse health consequences • Incorporate age and health status of those affected DALYs as unit measures for health • Conceptually simple: – health loss = N x D x S • N = number of affected persons • D = duration of adverse health effect • S = measure for severity of the effect • Disability Adjusted Life Years – mortality: years of life lost (YLL) – morbidity: years lived with disability (YLD) – DALY = YLL + YLD Hypothetical example Disability weight 1 0.8 0.6 Acute (infectious) disease 0.4 0.2 Premature death 0 0 20 40 60 Age Residual disability 80 Key Question: define health? ‘a state of complete physical, mental and social well-being, and not merely the absence of disease or infirmity’ (WHO charter, 1946) ‘the ability to cope with the demands of daily life’ (the Dunning Committee on Medical Cure and Care, 1991) the absence of disease and other physical or psychological complaints (NSCGP, 1999) Deriving severity weights • Global Burden of Disease Project – Define 22 indicator conditions – Use Person Trade Off method to elicit severity weights – Panel of physicians and public health scientists – Use scale of indicator conditions to attribute severity weights to other conditions – Methodology also applied in other studies Using Epidemiology for Microbial Risk Analysis • Problem Formulation: What’s the problem? Determine what infectious disease is posing a risk, its clinical features, causative agent, routes of exposure/infection and health effects • Exposure Assessment: How, how much, when, where and why exposure occurs; vehicles, vectors, doses, loads, etc. • Health Effects Assessment: – Human clinical trials for dose-response – field studies of endemic and epidemic disease in populations • Risk characterization: Epidemiologic measurements and analyses of risk: relative risk, risk ratios, odds ratios; regression models of disease risk; dynamic model of disease risk – other disease burden characterizations: relative contribution to overall disease burdens; effects of prevention and control measures; economic considerations (monetary cost of the disease and cost effectiveness of prevention and control measures Types of Epidemiological Studies that Have Been Used in Risk Assessment for Waterborne Disease Some More Epidemiological Terms and Concepts • Outbreaks: two or more cases of disease associated with a specific agent, source, exposure and time period • Epidemic Curve (Epi-curve): Number of cases or other measure of the amount of illness in a population over time during an epidemic – Describes nature and time course of outbreak – Can estimate incubation time if exposure time is known – Can give clues to modes of transmission: point source, common source, and secondary transmission Point Source Time Common Source Time Databases for Quantification and Statistical Assessment of Disease • National Notifiable Disease Surveillance System • National Ambulatory Medical Care Survey • International Classification of Disease (ICD) Codes • Other Databases – Special surveys – Sentinel surveillance efforts Infectious Disease Transmission (SIR) Model: Host States in Relation to Pathogen Transmission Pathogen Exposure Susceptible Infected Resistant = the rate or probability of movement from one state to another “Dynamic State” Epidemiological Model of Microbial Risk - Modeling Infectious Disease Dynamics and Transmission in Populations • Members of population move between states – States describe status with respect to a pathogen • Movement from state-to-state is modeled with ordinary differential equations; – define rates of movement between states: rate terms • Each transmission process is assumed to be independent • Change in fraction of population in any state from one time period to another can be described and quantified • Different sources of pathogen exposure can be identified and included in the model “Dynamic State” Epidemiological Model of Microbial Risk - State Variables “SIR” Model of Infectious Disease State Variables: track no. people in each state at a point in time • S = susceptible = not infectious; not symptomatic • I = Infected – C = carrier = infectious; not symptomatic – D = disease = infectious; symptomatic • R = Resistant; same as P = post infection (or) not infectious; not symptomatic; short-term or partial immunity • In epidemiology these states are called SIR Host States in Relation to Pathogen Transmission Pathogen Exposure Susceptible Infected Resistant = the rate or probability of movement from one state to another Infectious Disease Transmission Model at the Population Level: Dynamic Model • Risk estimation depends on transmission dynamics and exposure pathways. Example: Water Model Development: Household-level Model of Pathogen Transmission from Water “Dynamic State” Epidemiological Model of Microbial Transmission and Disease Risk Susceptible Carrier I Diseased I Post-infection Impact of Waterborne Outbreaks of Cryptosporidiosis on AIDS Patients (previous lecture) Outbreak Oxford/ Swindon, UK, 1989 Attack Rate Mortal. Ratio (%) 36 Not reported Milwaukee, 45 WI, 1993 68 Las Vegas, Not known; 52.6 NV, 1994 incr. Crypto-pos. stools Comments 3 of 28 renal transplant pts. shedding oocysts asymptomatically 17% biliary disease; CD4 counts <50 assoc. with high risks CD4 counts <100 at high risk; bottled water case-controls protective (Previous Lecture) Predicted Waterborne Cryptosporidiosis in NYC in AIDS Patients Compared to the General Population Adults Adults Pediatric AIDS with AIDS 6,080,000 1,360,000 30,000 1,200 40 30 390 10 Total NYC population Reported cases (1995) Predicted tapwater2 (5%) related reported cases (% of total actually reported) Predicted annual risk 5,400 from tapwater unreported (0.03%) (% of those predicted to be reported) Children 3 (10%) 33 (8.5%) 1(10%) 940 (0.3%) 56 (59%) Perz et al., 1998, Am. J. Epid., 147(3):289-301 1 (100%) Impacts of Household Water Quality on Gastrointestinal Illness - Payment Study #1 (An Intervention Study) Percent of Study Subjects Reporting HCGI Symptoms and Mean Number of Episodes per Unit of Observation in Both Periods Combined Group Filtered Water (n=272) Tap Water (n=262) Unit of % with Mean Number % with Mean Number Observation Episodesa of Episodesb Episodes of Episodes Family 62.0 3.82 67.7 4.81 Informant 20.0 1.70 23.1 2.10 Youngest 42.3 1.83 46.3 2.37 child aDerived by logistic regression with covariables age, sex, geographic subregion. bMean number of episodes among those subjects who reported at least one episode. Additional Analyses of Health Effects: Health Effects Assessments (previous lecture) • Health Outcomes of Microbial Infection • Identification and diagnosis of disease caused by the microbe – – – – disease (symptom complex and signs) Acute and chronic disease outcomes mortality diagnostic tests • Sensitive populations and effects on them • Disease Databases and Epidemiological Data Methods to Diagnose Infectious Disease (previous lecture) • Symptoms (subjective: headache, pain) and Signs (objective: fever, rash, diarrhea) • Clinical diagnosis: lab tests – Detect causative organism in clinical specimens – Detect other specific factors associated with infection • Immune response – Detect and assay antibodies – Detect and assay other specific immune responses Health Outcomes of Microbial Infection (previous lecture) • Acute Outcomes – Diarrhea, vomiting, rash, fever, etc. • Chronic Outcomes – Paralysis, hemorrhagic uremia, reactive arthritis, etc. • Hospitalizations • Deaths Morbidity Ratios for Salmonella (Non-typhi) (previous lecture) Study 1 2 3 4 5 6 7 8 9 10 11 12 Avg. Population/Situation Children/food handlers Restaurant outbreak College residence outbreak Nursing home employees Hospital dietary personnel " Nosocomial outbreak Summer camp outbreak Nursing home outbreak Nosocomial outbreak Foodborne outbreak Foodborne outbreak Morb. (%) 50 55 69 7 8 6 27 80 23 43 54 66 41 Acute and Chronic Outcomes Associated with Microbial Infections (previous lecture) Microbe Campylobacter E. coli O157:H7 Helicobacter Sal., Shig., Yer. Coxsackie B3 Giardia Toxoplasma Acute Outcomes Diarrhea Diarrhea Gastritis Diarrhea Encephalitis, etc. Diarrhea Newborn Syndrome Chronic Outcomes Guillain-Barre Syndrome Hemolytic Uremic Syn. Ulcers & Stomach Cancer Reactive arthritis Myocarditis & diabetes Failure to thrive; joint pain Mental retardation, dementia, seizures Outcomes of Infection Process to be Quantified (previous lecture) Exposure Advanced Illness, Chronic Infections and Sequelae Infection Disease Asymptomatic Infection Acute Symptomatic Illness: Severity and Debilitation Sensitive Populations Mortality Hospitalization Health Effects Outcomes: E. coli O157:H7 Health Effects Outcomes: Campylobacter Sensitive Populations (previous lecture) • Infants and young children • Elderly • Immunocompromized – Persons with AIDs – Cancer patients – Transplant patients • Pregnant • Malnourished Mortality Ratios for Enteric Pathogens in Nursing Homes Versus General Population (previous lecture) Microbe Mortality Ratio (%) in: General Pop. Nursing Home Pop. Campylobacter jejuni E. coli O157:H7 0.1 1.1 0.2 11.8 Salmonella 0.01 3.8 Rotavirus 0.01 1.0 Snow Mtn. Agent 0.01 1.3 Impact of Waterborne Outbreaks of Cryptosporidiosis on AIDS Patients Outbreak Attack Rate Mortal. Comments Ratio (%) Oxford/ Swindon, UK, 1989 36 Milwaukee, 45 WI, 1993 Not reporTed 3 of 28 renal transplants pts. Shedding oocysts asymptomatically 68 17% biliary disease; CD4 counts <50 associated with high risks Las Vegas, Not known; 52.6 NV, 1994 incr. Crypto-+ stools CD4 counts <100 at high risk; bottled water casecontrols protective Mortality Ratios Among Specific Immunocompromised Patient Groups with Adenovirus Infection (previous lecture) Patient Group % Mortality (Case-Fatality Ratio) Overall Mean Age of Patient Group (Yrs.) Bone marow transplants Liver transplant recipients Renal transplant recipients Cancer patients 60 15.6 53 2.0 18 35.6 53 25 AIDS patients 45 31.1 Databases for Quantification and Statistical Assessment of Disease • National Notifiable Disease Surveillance System • National Ambulatory Medical Care Survey • International Classification of Disease (ICD) Codes • Other Databases – Special surveys – Sentinel surveillance efforts Waterborne Outbreak Attack Rates Waterborne Outbreak Hospitalizations Predictied Waterborne Cryptosporidiosis in NYC in AIDS Patients Compared to the General Population Adults Adults with AIDS 6,080,000 1,360,000 30,000 40 30 390 Total NYC population Reported cases (1995) Predicted tapwater-related reported 2 (5%) cases (% of total actually reported) Predicted annual risk from tapwater 5,400 unreported (% of those predicted to (0.03%) be reported) Children Pediatric AIDS 1,200 10 3 (10%) 33 (8.5%) 1(10%) 940 (0.3%) 56 (59%) 1 (100%) Perz et al., 1998, Am. J. Epid., 147(3):289-301 Elements That May Be Considered in Risk Characterization • Evaluate health consequences of exposure scenario – Risk description (event) – Risk estimation (magnitude, probability) • Characterize uncertainty/variability/confidence in estimates • Conduct sensitivity analysis – evaluate most important variables and information needs • Address items in problem formulation (reality check) • Evaluate various control measures and their effects on risk magnitude and profile • Conduct decision analysis – evaluate alternative risk management strategies