Microbial Risk Assessment Part 2: Dynamic Epidemiology Models of Microbial Risk

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Microbial Risk Assessment Part 2 Dynamic
Epidemiology Models of Microbial Risk

• Envr 133
• Mark D. Sobsey
• Spring, 2006

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Using Epidemiology for Microbial Risk Analysis

• Problem Formulation Whats 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

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Types of Epidemiological Studies that Have Been
Used in Risk Assessment for Waterborne Disease
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Epidemiology Intervention Study
POPULATION
randomly select from population
CASE GROUP (intervene to change level of exposure)
CONTROL GROUP
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Types of Epidemiological Studies that Have Been
Used in Risk Assessment for Waterborne Disease
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Epidemiology Cohort Study
POPULATION 2 (exposure 2)
POPULATION 1 (exposure 1)
randomly select from population
randomly select from population
COHORT 1
COHORT 2
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Types of Epidemiological Studies that Have Been
Used in Risk Assessment for Waterborne Disease
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Epidemiology Case-Control Study
POPULATION 2 (NO exposure)
POPULATION 1 (exposure 1)
randomly select from population
randomly select from population
CASE GROUP
CONTROL GROUP
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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

cases
Point Source
Time
cases
Common Source
Time
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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

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DEFINED Dynamic Compartment Epidemiology
Model of Microbial Risk

• DYNAMIC a force that stimulates change or
  progress within a system
• COMPARTMENT a small space or subdivision for
  storage
• EPIDEMIOLOGY the statistical study of the
  distribution and determinants of disease in
  populations
• MODEL a hypothetical description of a complex
  entity or process

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Infectious Disease Transmission (SIR) ModelHost
States in Relation to Pathogen Transmission
Pathogen Exposure
Susceptible
Infected
Resistant
?
?
?
? the rate or probability of movement from one
state to another
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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

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Dynamic State Epidemiological Model of
Microbial Risk - State VariablesSIR 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

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Simple SIR Model

• dynamic in that the numbers in each compartment
  fluctuate over time
• also dynamic in the sense that individuals are
  born susceptible, then may acquire the infection
  (move into the infectious compartment) and
  finally recover (move into the recovered
  compartment)
• each member of the population typically
  progresses from susceptible to infectious to
  recovered
• diseases tend to occur in cycles of outbreaks due
  to the variation in number of susceptibles (S(t))
  over time
• number of susceptibles falls rapidly as more of
  them are infected and thus enter the infectious
  and recovered compartments
• disease cannot break out again until the number
  of susceptibles has built back up as a result of
  babies being born into the compartment

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SEIR Model

• Similar to the simple SIR model with the
  following exception
• For many infections, there is a period of time
  during which the individual has been infected but
  is not yet infectious himself. During this latent
  period the individual is in compartment E (for
  exposed).

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MSIR Model

• Similar to the simple SIR model with the
  following exception
• For many infections, babies are not born into the
  susceptible compartment but are immune to the
  disease for the first few months of life due to
  protection from maternal antibodies.

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Simple SIR Model

• Similar to the simple SIR model with the
  following exception
• With certain infectious diseases, some people who
  have been infected never completely recover and
  continue to carry the infection, while not
  suffering the disease themselves. They may then
  move back into the infectious compartment and
  suffer symptoms (as in tuberculosis) or they may
  continue to infect others in their carrier state,
  while not suffering symptoms. (Ex. Typhoid
  Fever)

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Simple SIR Model

• Similar to the simple SIR model with the
  following exception
• Some infections, such as influenza, do not confer
  long lasting immunity. Such infections do not
  have a recovered state and individuals become
  susceptible again after infection.

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Infectious Disease Transmission Model at the
Population Level Dynamic Model

• Risk estimation depends on transmission dynamics
  and exposure pathways. Example Water

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Model Development Household-level Model of
Pathogen Transmission from Water
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Dynamic State Epidemiological Model of
Microbial Transmission and Disease Risk
Susceptible
Carrier I
Diseased I
Post-infection
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Dynamic State Epidemiological Model of
Microbial Transmission and Disease Risk
Susceptible
Carrier I
Diseased I
Post-infection
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Additional Analyses of Health EffectsHealth
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

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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

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Health Outcomes of Microbial Infection(previous
lecture)

• Acute Outcomes
• Diarrhea, vomiting, rash, fever, etc.
• Chronic Outcomes
• Paralysis, hemorrhagic uremia, reactive
  arthritis, etc.
• Hospitalizations
• Deaths

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Impacts of Household Water Quality on
Gastrointestinal Illness - Payment Study 1 (An
Intervention Study)
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Morbidity Ratios for Salmonella
(Non-typhi)(previous lecture)
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Acute and Chronic Outcomes Associated with
Microbial Infections(previous lecture)
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Outcomes of Infection Process to be
Quantified(previous lecture)
Infection
Asymptomatic Infection
Exposure
Advanced Illness, Chronic Infections and Sequelae
Disease
Acute Symptomatic Illness Severity and
Debilitation
Sensitive Populations
Hospitalization
Mortality
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Health Effects Outcomes E. coli O157H7
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Health Effects Outcomes Campylobacter
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Sensitive Populations(previous lecture)

• Infants and young children
• Elderly
• Immunocompromized
• Persons with AIDs
• Cancer patients
• Transplant patients
• Pregnant
• Malnourished

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Mortality Ratios for Enteric Pathogens in Nursing
Homes Versus General Population(previous lecture)
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Impact of Waterborne Outbreaks of
Cryptosporidiosis on AIDS Patients
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Mortality Ratios Among Specific Immunocompromised
Patient Groups with Adenovirus Infection(previous
lecture)
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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

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Waterborne Outbreak Attack Rates
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Waterborne Outbreak Hospitalizations
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Perz et al., 1998, Am. J. Epid., 147(3)289-301
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Elements That May Be Considered inRisk
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