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Epidemiology of Infectious Diseases

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Title: Epidemiology of Infectious Diseases


1
Epidemiology of Infectious Diseases
  • Catherine Diamond MD MPH
  • UCI Infectious Diseases Epidemiology Divisions
  • (714) 456-7612
  • diamondc_at_uci.edu

2
Surveillance
  • Routine collection, analysis reporting of data
    monitoring morbidity mortality trends for
    public health purposes
  • Active agency actively contacts hospitals/MDs on
    a regular basis to find cases
  • Passive agency receives reports from
    hospitals/MDS
  • Sentinel systems certain MDs or hospitals report
    designated cases in order to catch trends early

3
Trends
  • Secular trend a change in the prevalence of
    infection over years, usually due to better
    living conditions, better hygiene vaccination,
    e.g. decrease in TB in US
  • Seasonal trend refers to changes in the
    prevalence of infection occurring over the year,
    e.g. influenza outbreaks. Changes of
    temperature, crowding, humidity may play a role

4
Endemic vs. Epidemic vs. Pandemic
  • Endemic infection-infection or disease that
    occurs regularly at low to moderate frequency
  • Epidemics occur when there are sudden increases
    in frequency in frequency above endemic levels
  • Pandemics are global epidemics, an epidemic
    occurring over a wide area usually affecting a
    large portion of the population. The size of
    outbreaks is dependent on factors such as the
    ratio of susceptible to immune subjects, period
    of infectivity, population density etc

5
What is an Outbreak?
  • The occurrence of cases of an illness clearly in
    excess of expectancy
  • Usually compare current number of cases with the
    number over a comparable period sometime in the
    past an increase in the number of cases over past
    experience for a given population, time place
  • Must take into account seasonal variations in
    disease incidence for diseases such as influenza

6
Three Common Conditions for the Occurrence of an
Epidemic or Outbreak
  • The introduction a new pathogen, or the increased
    amount of or change in virulence of a known
    pathogen from an infected human, animal, bird or
    arthropod vector or from air, water, food, soil,
    drug or other environmental source
  • An adequate number of exposed susceptible
    persons
  • An effective means of transmission between the
    source of the pathogen the susceptible persons

7
Why Should We Study Outbreak Investigations?
  • Outbreaks are important public health events
  • Outbreaks are experiments of nature allow the
    opportunity to learn more about the natural
    history of disease
  • Outbreaks represent breakdowns in public health
  • You might end up investigating an outbreak
    someday
  • Outbreaks are real life examples of practical
    applications of epidemiologic methods
  • Outbreaks are interesting

8
What Are the Steps in a Outbreak Investigation?
  • Verify the diagnosis
  • Confirm the existence of an outbreak
  • Identify count cases (establish case
    definition)
  • Orient data in terms of time, place person
  • Formulate test hypotheses
  • Identify implement control measures

9
Steps in an Outbreak Investigation
  • Different investigators may have slightly
    different lists of steps
  • The logistics of preparing for an outbreak
    investigation could be considered as one of the
    steps
  • The steps are not necessarily carried out exactly
    in the order listed

10
Step 1 Verify the Diagnosis
  • Is it an epidemic? Be certain it is real not a
    false alarm ( pseudoepidemic)
  • In hospital setting, pseudoepidemics may be due
    to false positive diagnosis resulting from
    contamination e.g. environmental contamination of
    specimens during laboratory processing
  • In contrast, there may also be artifactual
    clustering of real cases, e.g. change in
    reporting due to change in diagnostic methods,
    new physician/clinic in town, changes in
    local/national awareness. HIV/AIDS examples

11
Step 2 Confirm the Existence of an Outbreak
  • Compare the magnitude of the current problem with
    baseline
  • Problems with determining baselines
  • Lack of data
  • Varying or no case definition
  • Incomplete reporting, lack of surveillance

12
Step 3 Identify Count Cases
  • Case definition usually specifies a person with
  • Some set of symptoms or signs or laboratory
    diagnosis
  • Occurring in some time period
  • In some specific setting
  • Remember spectrum of disease (you may want to
    include asymptomatic/subclinical cases since
    information about them may be crucial to
    investigation)

13
Secondary Cases
  • Consider whether you want to include secondary
    cases.
  • Secondary cases are persons who were infected as
    a result of exposure to a primary case
  • E.g. in a food borne outbreak of E coli 0157 H7
    primary cases were infected by consumption of
    contaminated hamburger secondary cases would be
    infected through exposure to a primary case (e.g.
    in a day care)
  • These secondary cases were not exposed to the
    source of the outbreak their inclusion in the
    risk factor analysis would tend to bias toward
    the null
  • In many cases it is desirable to look for
    secondary cases collect information on them but
    not include them in the primary analysis

14
Evolving Case Definitions
  • Patients may not have laboratory tests because
    the tests are expensive, difficult to obtain or
    clinically not necessary
  • Early on, investigators use a loose case
    definition which includes confirmed, probable
    even possible cases
  • Later a tighter case definition may increase the
    ability to detect a true association
  • Ideally your case definition will include most if
    not all of the actual cases very few or no
    false positive cases

15
Definite vs. Probable vs. Possible Cases
  • Definite case laboratory confirmation
  • E.g. E coli 0157H7 isolated from stool culture
    in a resident of the county with onset of
    symptoms during a specified time period
  • Probable case typical clinical features without
    laboratory confirmation
  • Bloody diarrhea with same person, place time
    restrictions
  • Possible case fewer of the typical clinical
    features
  • Abdominal cramps diarrhea with the same person,
    place time restrictions

16
Identify Cases
  • 1. Conduct a systematic search
  • Cast a wide net regarding geography population
  • The original cases may or may not be
    representative of the true extent of the problem
  • 2. Use multiple sources which may include
  • Medical systems hospitals, laboratories,
    physician's office, clinics
  • Surveillance data
  • Media/press announcements
  • Special surveys e.g. if outbreak involved a
    defined population such as persons on a cruise
    ship you could survey that entire population

17
Step 4 Orient Data in Terms of Time, Place
Person
  • Characterize the cases in terms of time, place
    person
  • Time draw epidemic curves
  • Place construct spot maps
  • Person compare groups

18
Time Outbreaks The Epidemic Curve
  • An epidemic curve is a graph of the distribution
    of cases according to time of onset. From the
    curve you can tell
  • Where you are in the time course of an epidemic
    (e.g. beginning, middle, end)
  • From the pattern of the curve, you may be able to
    draw inferences about the mode of spread of the
    causative agent ( e.g. person-to-person, common
    source)

19
Common Source or Point Outbreaks
  • Common source or point outbreaks refer to the
    exposure of a susceptible population to a common
    source of a pathogen often at the same time, such
    as at a church picnic or neighborhood restaurant
  • These most frequently result in a short, sharp
    epidemic curve with cases clustered around single
    defined peak value. If the agent is
    transmissible to other by person to person
    contact then secondary peaks may occur

20
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22
Common Source or Point Outbreaks
  • For a common source exposure, if you have
    identified the disease know its usual
    incubation period (the time interval between
    exposure to an infectious agent the appearance
    of the first signs or symptoms of disease) , you
    can estimate a probable time period of exposure
    use that information to focus your investigation
  • The minimum incubation time should correspond to
    the interval between exposure the first case
  • The average incubation period should correspond
    to the interval between exposure the peak of
    the outbreak or the time occurrence of the median
    case

23
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24
Types of Epidemic Curves
  • The commercial distribution of food through many
    states or a chain of stores has created a new
    form of common source epidemic in which the time
    pattern of delivery, purchase consumption in
    a local area define the nature of the epidemic
  • If exposure occurs over different times, the
    epidemic curve can spread out continuously

25
Figure 1. Outbreak-Associated Confirmed Cases of
S. enteritidis Infection in Minnesota in
September and October 1994, According to the Date
of Onset. One hundred fifty cases were reported.
26
Propagative Epidemic Curves
  • Propagative or progressive epidemic curves result
    from epidemics involving the spread of a pathogen
    from one susceptible individual to another e.g.
    measles, influenza-frequently occur in
    propagative epidemics
  • Curve with some clusters of irregular peaks
    somewhat spread out is consistent with person to
    person spread
  • Mixed epidemics involve both a single, common
    exposure to an infectious agent secondary
    propagative spread to other individuals e.g. many
    food borne pathogens (Salmonella, Hepatitis A)
    airborne organisms (TB)
  • Mixed type of curves such as a single large peak
    followed by successive smaller peaks may be seen
    when a common source outbreak occurs followed by
    secondary person to person spread

27
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28
Place of Outbreak Spot Maps
  • Demonstrate geographic extent of the problem
  • Demonstrate cluster or pattern illustrating where
    cases live, work or may have been exposed
  • Most famous example of a spot map is John Snows
    spot map of the distribution of cholera cases
    around the Broad Street pump

29
Distribution of Cholera Deaths in Golden Square
Area of London August-September 1848
30
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31
Characterize Cases
  • Characterize the cases completely
    systematically by developing a questionnaire
    before the patients are contacted. Collect
  • Identifying information Name, address, telephone
    number
  • Demographic information Age, sex, race,
    occupation
  • Clinical information symptoms, date of onset,
    medical evaluation
  • Risk factor information depends on the disease
    being investigated

32
Personal Characteristics Outbreaks
  • The case group must be thoroughly described in
    terms of age, race, sex, occupation, diagnosis
    other factors
  • Rates are then calculated to identify high risk
    groups
  • E.g. age, sex (HIV), occupation (HCW)

33
Step 5 Formulate Test Hypotheses
  • Generate hypotheses to explain outbreak
  • Usually conduct a case control or cohort study
  • Consider evidence for causation

34
Cohort vs. Case Control Study Design
  • In cohort study, you have knowledge of entire
    population (e.g. can count how many individuals
    were exposed and how many were infected)
  • Can compare attack rate in the exposed and
    unexposed
  • Can calculate RR (incidence in exposed/incidence
    in unexposed)
  • But often only have information regarding some of
    the population and then need to use a case
    control design
  • Can compare proportion of cases and proportion of
    controls eating food item
  • Can calculate OR (AD/ BC)

35
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36
Coccidiodomycosis Outbreak Following Northridge
Earthquake
  • 39 of cases vs. 17 of controls reported
    physically being in a dust cloud OR 3.0 (95 CI
    1.6-54). Duration of time spent in dust cloud
    correlates with OR
  • 0 minutes OR 1.0
  • 1-15 minutes OR 1.7
  • 16-30 minutes OR 3.0
  • gt30 minutes OR 5.2

37
Causation
  • Strength of the association. The stronger the
    association, the more likely it is real
  • Consistency with other studies. A consistent
    finding is more plausible
  • Exposure precedes disease
  • Dose-response effect (not mandatory but adds
    credibility)
  • Biologic plausibility
  • Removal of agent decreases or eliminates disease

38
Attack Rate
  • Attack rate is an incidence rate
  • Used when occurrence of disease among a
    population at risk increases greatly over short
    period of time, often related to a specific
    exposure
  • The disease rapidly follows the exposure during a
    fixed time period
  • Often used for food borne illness
  • Attack rate ill X 100 during a time
    period
  • (ill well)

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40
Secondary Attack Rate
  • Secondary attack rate yields an index of the
    spread of disease within a household or similar
    circumscribed unit
  • The secondary attack rate is used to measure
    infectivity the capacity of the agent to enter
    multiply in a susceptible host thus produce
    infection or disease

41
Case Fatality Rate
  • Case fatality rate the number of deaths caused
    by a disease among people who have the disease
  • An index of the deadliness of a particular
    disease
  • CFR of deaths due to disease X X 100
  • of cases due to disease X

42
Step 6 Implementing Control Prevention Measures
  • Eliminating or treating the source-e.g. removing
    an infected foodhandler from work treating
    appropriately
  • Cohorting patients- a common approach in
    hospitals, childcare other institutional
    setting
  • Preventing further exposures-e.g. as in the
    HIV/AIDS epidemic through educational efforts to
    change knowledge behaviors
  • Protecting the population at risk- e.g. through
    vaccination
  • System changes. For example, changing the method
    by which meat inspection is conducted to decrease
    the risk of contamination with E coli 0157H7

43
Use of Molecular Subtyping in Infectious Disease
in Infectious Disease Outbreak
  • Molecular subtyping of patient source outbreaks
    has become an increasingly important part of
    outbreak investigations
  • Many methods of subtyping including pulsed field
    gel electrophoresis (PFGE) restriction fragment
    length polymorphism (RFLP)
  • Within a species of infectious agents, there are
    multiple strains with different genetic
    compositions. Subtyping techniques attempt to
    determine the degree of genetic relatedness of
    different isolates
  • Outbreaks are nearly always caused by a single
    strain of the causative organism thus termed
    clonal
  • Subtyping of isolates can be used to determine
    whether the isolated involved are closely related
    are therefore likely to be associated with a
    common source
  • The results of subtyping can be applied to the
    case definition
  • Subtyping is usually not immediately available
    thus is not used in the initial case definition
    but may be incorporated in later analysis

44
Case Scenario
  • You are the county epidemiologist in a county on
    the Pennsylvania/Ohio border
  • Between November 13 December 3, 26 cases of
    hepatitis are reported to your county health
    department
  • Although you just started working there, this
    seems like a lot to you! You decide to
    investigate

45
Step 1 Verify the Diagnosis
  • How would you verify the diagnosis of Hepatitis A?

46
Step 1 Verify the Diagnosis
  • Review clinical laboratory features of the
    cases to determine if they are consistent with
    the diagnosis of hepatitis A

47
  • HEPATITIS A CLINICAL FEATURES
  • Jaundice by lt6 yrs lt10
    age group 6-14 yrs
    40-50
    gt14 yrs 70-80
  • Rare complications Fulminant hepatitis
    Cholestatic hepatitis

    Relapsing hepatitis
  • Incubation period Average 30 days
    Range 15-50
    days
  • Chronic sequelae None

48
EVENTS IN HEPATITIS A VIRUS INFECTION
Clinical illness
Infection
ALT
IgM
IgG
Viremia
Response
HAV in stool
0
1
2
3
4
5
6
7
8
9
10
11
12
13
Week
49
Step 2 Confirm the Existence of an Outbreak
  • How would you confirm the existence of an
    outbreak?

50
Step 2 Confirm the Existence of an Outbreak
  • Compare the number of cases against historical
    numbers
  • Between November 13 December 3, 26 cases of
    Hepatitis A were reported to the county health
    department compared with 1 case in the previous 4
    months
  • FYI in Orange County in 2002, there were 91
    reported cases of hepatitis A (3.1 cases per
    100,000 population)

51
Step 3 Identify Count Cases
  • What would be your case definition?
  • How would you identify cases?
  • Would you include secondary cases?

52
ACUTE HEPATITIS A CASE DEFINITION FOR
SURVEILLANCE
  • Clinical criteriaAn acute illness with
  • discrete onset of symptoms (e.g. fatigue,
    abdominal pain, loss of appetite, intermittent
    nausea, vomiting),
  • jaundice or elevated serum aminotransferase
    levels
  • Laboratory criteria
  • IgM antibody to hepatitis A virus (anti-HAV)
    positive
  • Case Classification
  • Confirmed. A case that meets the clinical case
    definition is laboratory confirmed or a case
    that meets the clinical case definition occurs
    in a person who has an epidemiologic link with a
    person who has laboratory-confirmed hepatitis A
    (i.e., household or sexual contact with an
    infected person during the 15-50 days before the
    onset of symptoms)

53
Step 3 Identify Count Cases
  • Case definition defined as a person with
    discrete symptom onset between November 13
    December 4 in association with the presence of
    IgM antibody to HAV in your county

54
Step 3 Identify Count Cases
  • Identify cases
  • State health department requests counties to
    immediately report all HAV cases
  • The county contacts all county physicians,
    hospitals, laboratories neighboring county
    state health departments to rapidly report cases
  • Advertisements/media/signs
  • Secondary cases might bias toward the null could
    collect early on but might not include in analysis

55
Step 4 Orient Data in Terms of Time, Place
Person
  • What would the epidemic curve look like?
  • What would a spot map look like?
  • Are there specific demographic or other
    characteristics of the cases?

56
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57
Step 4 Orient Data in Terms of Time, Place
Person
  • A spot map would likely show more cases in the
    geographic area nearest the restaurant
  • Presumably cases would reflect the demographics
    of restaurant goers, patients with symptomatic
    hepatitis A residents of the county
  • 22 (51) were male
  • Median age 34 years (range 5-66)
  • All were white
  • 14 (33) hospitalized
  • No travel, injection drug use or male-male sex

58
Step 5 Formulate Test Hypotheses
  • What do you hypothesize is the cause of the
    outbreak?
  • How would you collect data to prove this
    hypothesis?
  • How would you analyze data to validate your
    hypothesis?

59
Step 5 Formulate Test Hypotheses
  • Infected food product vs. infected employee
  • The CDC Viral Hepatitis Surveillance Program
    Questionnaire
  • Case control study
  • Genetic relatedness of hepatitis A sequence.

60
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62
CONCENTRATION OF HEPATITIS A VIRUS IN VARIOUS
BODY FLUIDS
Feces
Serum
Body Fluids
Saliva
Urine
102
104
100
106
108
1010
Infectious Doses per mL
Source Viral Hepatitis and Liver Disease
19849-22 J Infect Dis 1989160887-890
63
HEPATITIS A VIRUS TRANSMISSION
  • Close personal contact(e.g., household contact,
    sex contact, child day-care centers)
  • Contaminated food, water(e.g., infected food
    handlers)
  • Blood exposure (rare)(e.g., injection drug use,
    rarely by transfusion)
  • No risk factor identified for 40-50 of cases

64
GLOBAL PATTERNS OF HEPATITIS A VIRUS TRANSMISSION
Disease Rate
Peak Age of Infection
Transmission Patterns
Endemicity
Low to high
High
Early childhood
Person to person
outbreaks uncommon
Late childhood/ young adults
High
Moderate
Person to person
food waterborne
outbreaks
Low
Young adults
Low
Person to person
food waterborne
outbreaks
Very low
Very low
Adults
65
RISK FACTORS ASSOCIATED WITH REPORTED HEPATITIS
A, 1990-2000, UNITED STATES
Source NNDSS/VHSP
66
Cause of the HAV Epidemic
  • Green onions grown processed in Mexico then
    shipped on ice to US restaurant where they are
    chopped and placed raw in giant vats of mild
    salsa
  • Possible contact with HAV-infected workers
    especially children working in the field during
    green onion harvesting/preparation
  • Possible contact with HAV-contaminated water
    during irrigation, rinsing, icing

67
Step 6 Implementing Control Prevention Measures
  • What control measures would you implement?
  • How would you prevent future cases?

68
Step 6 Implementing Control Prevention Measures
  • Control
  • Immunoglobulin
  • Close restaurant
  • Prevention
  • Vaccination
  • Public health announcements to avoid raw green
    onions
  • Agricultural quality control
  • Water quality for irrigation
  • Provide sanitary facilities for field workers
  • Child-care for field workers
  • Prevent HAV transmission

69
PREVENTING HEPATITIS A
  • Hygiene (e.g., hand washing)
  • Sanitation (e.g., clean water sources)
  • Hepatitis A vaccine (pre-exposure)
  • Immune globulin (pre- post-exposure)

70
HEPATITIS A PREVENTION IMMUNE GLOBULIN
  • Pre-exposure
  • travelers to intermediate high HAV-endemic
    regions
  • Post-exposure (within 14 days)
  • Routine
  • household other intimate contacts
  • Selected situations
  • institutions (e.g., day-care centers)
  • common source exposure (e.g.,
  • food prepared by infected food handler)

71
HEPATITIS A VACCINES
  • Highly immunogenic
  • 97-100 of children, adolescents, adults have
    protective levels of antibody within 1 month of
    receiving first dose essentially 100 have
    protective levels after second dose
  • Highly efficacious
  • In published studies, 94-100 of children
    protected against clinical hepatitis A after
    equivalent of one dose

72
Hepatitis A Incidence, United States, 1980-2002
2002 rate provisional
73
1987-97 average incidence
Hepatitis A Incidence
2002 incidence
74
Conclusion
  • Step 1 Verify the diagnosis
  • Step 2 Confirm the existence of an outbreak
  • Step 3 Identify count cases
  • Step 4 Orient data in terms of time, place
    person
  • Step 5 Formulate test hypothesis
  • Step 6 Implementing control prevention measures

75
Acknowledgements
  • Lisa Jackson, MD MPH University of Washington for
    lecture outline
  • HAV slides from CDC website www.cdc.gov
  • Dentinger et. al. An Outbreak of Hepatitis A
    Associated with Green Onions. J. Infect Dis 2001
    183 1273-6.
  • CDC. Hepatitis A Outbreak Associated with Green
    Onions at a Restaurant-Monaca, PA, 2003. MMWR
    2003 52 1155-1157.
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