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

1. Microbial Risk Assessment Part 2: Dynamic Epidemiology Models of Microbial Risk Envr 133 Mark D. Sobsey Spring, 2006

2. 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

4. Types of Epidemiological Studies that Have Been Used in Risk Assessment for Waterborne Disease

5. Epidemiology Intervention Study POPULATION randomly select from population CASE GROUP (intervene to change level of exposure) CONTROL GROUP

6. Types of Epidemiological Studies that Have Been Used in Risk Assessment for Waterborne Disease

7. Epidemiology Cohort Study POPULATION 2 (exposure 2) POPULATION 1 (exposure 1) randomly select from population randomly select from population COHORT 1 COHORT 2

8. Types of Epidemiological Studies that Have Been Used in Risk Assessment for Waterborne Disease

9. Epidemiology Case-Control Study POPULATION 2 (NO exposure) POPULATION 1 (exposure 1) randomly select from population randomly select from population CASE GROUP CONTROL GROUP

10. Some More Epidemiological Terms and Concepts # cases • 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 # cases Common Source Time

11. 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

12. DEFINED: “DynamicCompartmentEpidemiologyModel” 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

13. 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

14. “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

15. “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

16. 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

17. 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).

18. 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.

19. 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)

20. 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.

21. Infectious Disease Transmission Model at the Population Level: Dynamic Model • Risk estimation depends on transmission dynamics and exposure pathways. Example: Water

22. Model Development: Household-level Model of Pathogen Transmission from Water

23. “Dynamic State” Epidemiological Model of Microbial Transmission and Disease Risk Susceptible Carrier I Diseased I Post-infection

24. “Dynamic State” Epidemiological Model of Microbial Transmission and Disease Risk Susceptible Carrier I Diseased I Post-infection

26. 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

27. 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

28. Health Outcomes of Microbial Infection(previous lecture) • Acute Outcomes • Diarrhea, vomiting, rash, fever, etc. • Chronic Outcomes • Paralysis, hemorrhagic uremia, reactive arthritis, etc. • Hospitalizations • Deaths

29. Impacts of Household Water Quality on Gastrointestinal Illness - Payment Study #1 (An Intervention Study)

30. Morbidity Ratios for Salmonella (Non-typhi)(previous lecture)

31. Acute and Chronic Outcomes Associated with Microbial Infections(previous lecture)

32. Outcomes of Infection Process to be Quantified(previous lecture) Exposure Infection Asymptomatic Infection Advanced Illness, Chronic Infections and Sequelae Disease Acute Symptomatic Illness: Severity and Debilitation Sensitive Populations Mortality Hospitalization

33. Health Effects Outcomes:E. coli O157:H7

34. Health Effects Outcomes: Campylobacter

35. Sensitive Populations(previous lecture) • Infants and young children • Elderly • Immunocompromized • Persons with AIDs • Cancer patients • Transplant patients • Pregnant • Malnourished

36. Mortality Ratios for Enteric Pathogens in Nursing Homes Versus General Population(previous lecture)

37. Impact of Waterborne Outbreaks of Cryptosporidiosis on AIDS Patients

38. Mortality Ratios Among Specific Immunocompromised Patient Groups with Adenovirus Infection(previous lecture)

39. 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

40. Waterborne Outbreak Attack Rates

41. Waterborne Outbreak Hospitalizations

42. Perz et al., 1998, Am. J. Epid., 147(3):289-301

44. 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