Transcript The Anatomy of an Epidemic: A Rational Approach to

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
1. Introduction
2. Modeling and the Anatomy of
Epidemics
3. Preventing and Controlling Epidemics
4. Epidemics and Luck
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Smallpox
SARS
Anthrax
Monkeypox
Mumps
Antibiotic-resistant
Acinetobacter
Communityassociated MRSA
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Supertoxigenic
Clostridium difficile
Avian influenza
Bordatella
pertussis
Measles
West Nile Virus
Highly-resistant
Pseudomonas
aeruginosa
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
1.
2.
Smallpox
100
100
75
75
No. of cases
No. of cases
Seasonal viruses
50
25
50
25
0
0
2004
2005
2006
2007
2004
2005
2006
2007
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 and the Anatomy of
Epidemics
Modeling Measles
Keeling, et al. Proc R Soc Lond. 2002
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
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Basic reproductive number
(R0)
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R0 = 1
Expected number of secondary
cases on the introduction of one
infected individual in a
susceptible population
R0 = 2
R0 > 1 Epidemic disease
R0 = 1 Endemic disease
R0 < 1 Disease dies out
R0 = 3
R0
Generation #
1 2 3 …10
2
1
2
4 512
1
1
1
1
1
0.5
4
2
1
0
Basic Reproductive Numbers
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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.
R0 = p x k x d
p = transmissibility
k = contacts
d = duration of
contagiousness
Transmissibility (p)
1. Quantity of pathogen released
2. Mechanism of dissemination
3. Inherent infectiousness of the
pathogen
R0 = p x k x d
Quantity of pathogen released
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Varies with state of
disease
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Varies with activity
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R0 = p x k x d
Early chickenpox
Herpes simplex
Cattarhal phase of
viral infections
Coughing vs. sneezing
vs. talking
Mechanism of dissemination
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Respiratory
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Contact
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Seasonal viruses
Antibiotic-resistant bacteria
Fecal-oral
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Influenza, tuberculosis
Salmonella, shigella, hepatitis A
Blood and body fluid
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HIV, Hepatitis B and C
R0 = p x k x d
Respiratory dissemination
Pathogen
Size
Distance
Persistence
Droplet
Droplet nuclei
Bacteria
TB
≥ 5µ
< 5µ
< 3 feet
?
< 10 min.
> 1 hr.
Destination Upper airways
R0 = p x k x d
Alveoli
Inherent infectiousness
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Biological differences
between organisms
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Adhesions, proteinases
Variation in host
response
Expressed as the
minimal infectious dose
R0 = p x k x d
E. coli infecting bladder
epithelium
Contacts
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Number of contacts
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R0 = p x k x d
May be facilitated by
environmental factors
Intensity of contacts
R0 = p x k x d
Duration of Contagiousness (d)
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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 (d)
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The Ebola paradox
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Rapid mortality
reduces period of
contagiousness
R0 = p x k x d
Preventing and Controlling
Epidemics
Childbed fever: Vienna, 1847
Robert A. Thom (1966)
Cholera: London 1854
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)
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Reduce the quantity of
pathogen released
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Symptom control
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Anti-tussives
Barrier precautions
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Masks for patients
Limiting transmissibility
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Act on the
mechanism of
dissemination
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Environmental
controls
Reduce inherent
infectiousness
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Difficult to reduce,
but possible to
increase
Blood pressure
cuffs: 14%
Bedside Tables:
20%
Bed rails: 26%
Sheets: 40%
Overall, 63% of VRE (+) patient rooms are
contaminated
Preventing Contact
Quarantine and Isolation
“une quarantaine de
jours (a period of
forty days)”
Quarantine
S
Exposed
M
T
Contagious
W
R
F
Symptoms
Begin
Isolation
S
Social Controls
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Restriction on
public events and
gatherings
Travel limitations
Building
quarantines
Import/Export
controls
Reducing duration of
contagiousness
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Antimicrobial therapy
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Influenza control
Anti-HIV therapy
Enhanced case
recognition
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Syndromic surveillance
Limit contacts
Ebola revisited
Period of infectivity
0
1
2
Days of illness
Ebola: Natural History
Death
3
Ebola revisited
Period of infectivity
Death
0
1
2
Days of illness
Ebola: Current Practice
3
4
Traditional
funeral
practices
Ebola revisited
Period of infectivity
0
1
2
Days of illness
Ebola: USA
Death
3
4
ICU Support
Epidemics and Luck
Epidemic Misfortune
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Epidemics do not conform
to the predictions of
deterministic models.
Stochastic phenomena
prevail.
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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
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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
1. Epidemics are driven by a relatively
understandable interplay of pathogens,
infected and susceptible hosts.
2. Understanding the mathematical as well as
the biological underpinnings of epidemics is
critical to prevention and control.
3. Sometimes, it really is better to be lucky
than to be good.