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The Anatomy of an Epidemic: A Rational Approach to Understanding, Preventing and Combating Infectious Diseases

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The Anatomy of an Epidemic: A Rational Approach to Understanding, Preventing and Combating Infectious Diseases. Stephen Weber, MD, MS Assistant Professor Section of Infectious Diseases Hospital Epidemiologist Director, Infection Control Program University of Chicago Hospitals. Overview.

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slide1

The Anatomy of an Epidemic: A Rational Approach to Understanding, Preventing and Combating Infectious Diseases

Stephen Weber, MD, MS

Assistant Professor

Section of Infectious Diseases

Hospital Epidemiologist

Director, Infection Control Program

University of Chicago Hospitals

overview
Overview
  • Introduction
  • Modeling and the Anatomy of Epidemics
  • Preventing and Controlling Epidemics
  • Epidemics and Luck
slide4
Smallpox

SARS

Anthrax

Monkeypox

Mumps

Antibiotic-resistant Acinetobacter

Community-associated MRSA

Supertoxigenic Clostridium difficile

Avian influenza

Bordatella pertussis

Measles

West Nile Virus

Highly-resistant Pseudomonas aeruginosa

defining an epidemic
Defining an epidemic
  • An outbreak of a contagious disease that spreads rapidly and widely.
  • An increased frequency of infection above the normal or usual level
epidemic surveillance
Epidemic Surveillance

World Health Organization (WHO)

Centers for Disease Control and Prevention

Illinois Department of Public Health

Chicago Department of Public Health

UCH Infection Control Program

Individual Clinicians

modeling measles
Modeling Measles

Keeling, et al. Proc R Soc Lond. 2002

modeling malaria
Modeling Malaria

dX/dt = A B Y (N - X) - r X

dY/dt = A C X (M - Y) - m Y

McKenzie and Samba, et al. Am J Trop Med Hyg. 2004

progression of an epidemic

R0 = 1

R0 = 2

R0 = 3

Progression of an Epidemic
  • Basic reproductive number (R0)
    • Expected number of secondary cases on the introduction of one infected individual in a susceptible population

R0 > 1 Epidemic disease

R0 = 1 Endemic disease

R0 < 1 Disease dies out

slide13
Generation #

R0 1 2 3 …10

2 1 2 4 512

1 1 1 1 1

0.5 4 2 1 0

basic reproductive numbers
Basic Reproductive Numbers
  • SARS in general population: 0.49
  • SARS (hospital transmission): 2.6
  • Smallpox in a vulnerable population: 3.0-5.2
  • Measles (pre-vaccine): 10-15
  • Measles in Belgian schools (1996): 6.2-7.7
  • 1918 pandemic influenza: 1.8-2.0
  • Influenza on a commercial airliner: 10.4

Liao, et al. Risk Anal. 2005; Chowell, et al. Emerg Inf Dis. 2004; Mossong, et al. Epidemiol Infect. 2005; Meltzer, et al. Emerg Inf Dis. 2001.

r 0 p x k x d
R0 = p x k x d

p = transmissibility

k = contacts

d = duration of contagiousness

transmissibility p
Transmissibility (p)
  • Quantity of pathogen released
  • Mechanism of dissemination
  • Inherent infectiousness of the pathogen

R0 = p x k x d

quantity of pathogen released
Quantity of pathogen released
  • Varies with state of disease
    • Early chickenpox
    • Herpes simplex
    • Cattarhal phase of viral infections
  • Varies with activity
    • Coughing vs. sneezing vs. talking

R0 = p x k x d

mechanism of dissemination
Mechanism of dissemination
  • Respiratory
    • Influenza, tuberculosis
  • Contact
    • Seasonal viruses
    • Antibiotic-resistant bacteria
  • Fecal-oral
    • Salmonella, shigella, hepatitis A
  • Blood and body fluid
    • HIV, Hepatitis B and C

R0 = p x k x d

respiratory dissemination
Respiratory dissemination

Droplet Droplet nuclei

Pathogen BacteriaTB

Size ≥ 5µ < 5µ

Distance < 3 feet ?

Persistence < 10 min. > 1 hr.

Destination Upper airways Alveoli

R0 = p x k x d

inherent infectiousness
Inherent infectiousness
  • Biological differences between organisms
    • Adhesions, proteinases
  • Variation in host response
  • Expressed as the minimal infectious dose

E. coli infecting bladder epithelium

R0 = p x k x d

contacts
Contacts
  • Number of contacts
    • May be facilitated by environmental factors
  • Intensity of contacts

R0 = p x k x d

duration of contagiousness d
Duration of Contagiousness (d)
  • Assuming a constant frequency of contacts and an unchanging degree of transmissibility, the longer the period of time that a patient is contagious the more likely he/she is to transmit the pathogen.
  • For some infections, the period of contagiousness may not always be associated with symptoms of illness.

R0 = p x k x d

duration of contagiousness d24
Duration of Contagiousness (d)
  • The Ebola paradox
    • Rapid mortality reduces period of contagiousness

R0 = p x k x d

childbed fever vienna 1847
Childbed fever: Vienna, 1847

Robert A. Thom (1966)

slide28

Modeling and Infection Control

R0 = p x k x d

Interventions to prevent the spread of epidemics target transmissibility (p), contacts (k) or duration of contagiousness (d).

limiting transmissibility p
Limiting transmissibility (p)
  • Reduce the quantity of pathogen released
    • Symptom control
      • Anti-tussives
    • Barrier precautions
      • Masks for patients
limiting transmissibility
Limiting transmissibility

Blood pressure cuffs: 14%

  • Act on the mechanism of dissemination
    • Environmental controls
  • Reduce inherent infectiousness
    • Difficult to reduce, but possible to increase

Bedside Tables: 20%

Bed rails: 26%

Sheets: 40%

Overall, 63% of VRE (+) patient rooms are contaminated

quarantine and isolation
Quarantine and Isolation

“une quarantaine de jours (a period of forty days)”

Quarantine

S

M

T

W

R

F

S

Symptoms Begin

Exposed

Contagious

Isolation

social controls
Social Controls
  • Restriction on public events and gatherings
  • Travel limitations
  • Building quarantines
  • Import/Export controls
reducing duration of contagiousness
Reducing duration of contagiousness
  • Antimicrobial therapy
    • Influenza control
    • Anti-HIV therapy
  • Enhanced case recognition
    • Syndromic surveillance
    • Limit contacts
ebola revisited

Period of infectivity

Ebola revisited

Death

0

1

2

3

Days of illness

Ebola: Natural History

ebola revisited36

Period of infectivity

3

3

4

Traditional funeral practices

Ebola revisited

Death

0

1

2

3

Days of illness

Ebola: Current Practice

ebola revisited37

Period of infectivity

3

3

4

ICU Support

Ebola revisited

Death

0

1

2

3

Days of illness

Ebola: USA

epidemic misfortune
Epidemic Misfortune
  • Epidemics do not conform to the predictions of deterministic models. Stochastic phenomena prevail.
  • Monkeypox: Co-transport of Ghanan giant rat with prairie dogs
  • West Nile Virus: Survival of carrier mosquito through transatlantic flight
  • SARS: Co-mixing of viruses between humans, fowl and civets
  • HIV: Single African ancestral event
improving the odds
Improving the Odds
  • Understanding the role of chance in epidemics permits the deployment of manageable strategies to prevent spread.
  • Improved performance of day to day practices may be more important than an elaborate emergency response system.
conclusions
Conclusions
  • Epidemics are driven by a relatively understandable interplay of pathogens, infected and susceptible hosts.
  • Understanding the mathematical as well as the biological underpinnings of epidemics is critical to prevention and control.
  • Sometimes, it really is better to be lucky than to be good.