Transcript A25 Winn - InfectiousDiseaseEcology

The ecology of emerging infectious disease
From the New York Times, July 16, 2012
Woman dies from mad cow disease in
Spain
A Spaniard has died from the human form of mad cow disease, the fifth such death
in Spain since 2005, the Ministry of Health said in a statement late Friday.
March 2009
Eastern equine encephalitis kills 4 people
in Florida: Aug 18, 2010
Uganda Ebola outbreak confirmed
Health officials say mysterious illness that has killed 14 people in western Ugandan district
of Kibaale is Ebola virus (July 29, 2012)
Update to CDC's Sexually Transmitted Diseases Treatment
Guidelines, 2010: Oral Cephalosporins No Longer a
Recommended Treatment for Gonococcal Infections
Weekly
August 10, 2012 / 61(31);590-594
CDC: West Nile outbreak largest ever seen in U.S.
Posted on: 5:39 pm, August 26, 2012, by Alix Bryan
Infectious disease is a current important threat to human health
and well being and to the integrity of natural and managed
ecosystems
World Health Organization (1990)
37% human mortality attributable to infectious disease
1.7 billion tuberculosis infections
267 million cases of malaria
50 million reported cases of dengue fever
Institute of Medicine (1992)
54 new infectious diseases in US since1940
Nature 2008 (Jones et al.)
300 new human pathogens world-wide from 1940 – 2003
What is an emerging infectious disease (EID)?
One that has recently increased in occurrence
One that has recently expanded its geographic range
One that is caused by novel pathogen
Includes the emergence of novel pathogens and
reemergence of previously controlled infectious diseases
Examples of emerging infectious diseases
Increased incidence - Lyme disease
Increased impact - Tuberculosis
Increased geographic range - West Nile virus
Evolution of new strain - Influenza viruses (H1N1)
Pathogen entering humans - Nipah virus
Newly discovered pathogen - Hendra virus
Previously controlled but now re-emerging:
Dengue fever
The rate of emergence is increasing
Emerging infectious diseases (EID)
recent increase in occurrence
recent increase in geographic range, or effect
caused by a novel pathogen
What factors do you think
account for emergence of
new diseases and reemergence of old ones?
Drivers of emerging human pathogens*
Changes in land use and agricultural practices
Changes in human demography
Poor population health
Hospital and medical procedures
Pathogen evolution
Contamination of food or water supplies
International travel
Failure of public health programs
International trade
Climate change
*In order from most to least number of pathogens affected (2005)
What does ecology have to do with infectious disease?
Ecology
the study of the
distribution and
abundance of organisms
and of
parasitism
Infectious disease constitutes aPredation
classic form
species
interaction (predator-prey) studied by ecologists.
Competition
Mutualism
Predation
Facilitation
CONSUMER - RESOURCE INTERACTIONS
Lethality
Intimacy
HI
LOW
Host - Parasitoid Predator-prey
HI
Host - Parasite
LOW
Grazers
Two examples of how tools and concepts from
ecology can be used to help predict, prevent
and control outbreaks and emergence of
infectious disease
1. Use of a mathematical model of species
interactions to evaluate alternate means of
responding to outbreak of the novel disease
SARS.
2. The role of ecology in predicting the
occurrence of Lyme Disease
What is a model
and what can you
do with it?
A model is a simplified representation of something
Physical models
Conceptual model
Mathematical model
y = mx + b
Models can be used to describe, explain, or understand
more complex reality.
Some questions that might be answered with a
mathematical model of an infectious disease
1. What are the conditions under which an epidemic will
occur?
2. What fraction of the population will become infected?
3. How would vaccination change the speed or duration
of an epidemic?
4. How will treatment or other intervention affect the
course of an epidemic?
Ecologists use SIR models to study the interactions
between parasites and their hosts
N is the total number of individuals in the population of hosts
S is the number that are susceptible to a disease
I is the number of individuals that are infected with the disease
R is the number that are not susceptible or infected (removed)
S
#susceptible
I
#infected
S+I+R=N
R
#removed
Ecologists use SIR models to study the interactions
between parasites and their hosts
S

#susceptible
I
#infected
 is the rate at which
the disease is
transmitted
S+I+R=N
g
R
#removed
g is the rate of
recovery from the
disease
S

#susceptible
g
I
#infected
R
#removed
Equations describe how the numbers in each box change over
time.
dS
= -bSI
dt
dI
= bSI - gI
dt
dR
= gI
dt
The change in the number of
susceptible individuals through time
The change in the number of infected
individuals through time
The change in the number of removed
individuals through time
500
SIR Simulation of Outbreak in continuous time
300
200
100
0
Number of individuals
400
Susceptible
Infected
Removed
0
20
40
60
Time
80
100
S

#susceptible
dS
= -bSI
dt
dI
= bSI - gI
dt
dR
= gI
dt
g
I
#infected
R
#removed
is the rate at which the
disease is transmitted
g is the rate of recovery
from the disease
What information is in the sign of dI/dt?
Some questions that might be answered with a
mathematical model of an infectious disease
1. What are the conditions under which an epidemic will
occur?
2. What fraction of the population will become infected?
3. How would vaccination change the speed or duration
of an epidemic?
4. How will treatment or other intervention affect the
course of an epidemic?
SARS; Severe acute
respiratory syndrome.
Reservoir host
Will there be a pandemic?
Possible responses to an emerging novel viral epidemic?
Vaccination
Isolation of infected individuals
Quarantine of contacts
Culling (of the reservoir, not the victims)
How do we decide which responses will be most effective?
Mathematical models are used to explain, explore and predict
how biological systems work. We can conduct “experiments”
with models that would be impossible or too slow to be used in
an on-going epidemic.
Lipsitch et al. 2003 used a mathematical model to predict
the effects of different control measures on the initial
outbreak of SARS
Schematic diagram of a model of SARS
Indicates effect
of intervention
Latent Infection
designates individuals
who are infected but do
not have active disease
and so are not (yet)
infectious
The Model
The ODE
Schematic diagram of a model of SARS
S
Indicates effects
of intervention
Latent Infection designates
individuals who are infected
but do not have active disease
and so are not (yet) infectious
I
R
Use computer
simulation to ask how
isolation and/or
quarantine would affect
the course of an
epidemic
SARS Epilogue
Over 8000 cases world wide, over 750 deaths
Average mortality rate 9.6%, but variable among age
groups
Cases reported from >2 dozen countries on 4 continents.
Last reported case in 2004 (lab acquired infection)
Development of vaccine is on-going
Early intervention is critical, greater surveillance is
needed for prediction and early detection
About 40% of all human diseases are
caused by bacteria. Most cause disease via
the production of toxins. Exotoxins are
secreted or induced by live bacteria.
Endotoxins are released when bacteria die.
Agent of Lyme disease
Yersinea pestis
agent of plague
Lyme disease
From CDC report 2006
How many humans view Lyme disease
Ixodes scapularis
Borrelia burgdorferi
Host infection
How an ecologist sees the system in which Lyme disease is embedded
vector
reservoir
reservoir
reservoir
Tick vector life cycle and host associations
infected?
uninfected
How an ecologist sees the system in which Lyme disease is embedded
vector
reservoir
reservoir
reservoir
Predicting risk of exposure from ecological data
acorns
deer
weather
reservoirs
weather
Reservoir and “taxi”
Possible predictors
Affect populations
of rodents and
attract deer
Reservoir
Reservoir
mammals
Affect survival of
larval and
nymphal ticks off
hosts
The variables most closely associated with Lyme disease incidence
Chipmunk density a year earlier
Acorn abundance 2 years earlier
What determines spatial variation in risk of infection?
“Hot spots” on
North Atlantic
coast, upper
midwest, and
northern
California
Abundance of reservoir hosts, vectors, and humans must
coincide, but the mechanisms underlying the distribution of
each may vary.
How spatial variation in biodiversity of potential reservoir
species influence the risk of Lyme disease
Logic: As the most competent reservoir host becomes a
smaller fraction of the community, fewer tick nymphs will be
infectious and the number of cases of Lyme disease will
decline. This is called a dilution effect.
Ostfeld and Keesing 2000
Measured biodiversity of different components of the
reservoir community in 10 “states” along the US eastern
seaboard and looked for a relationship to cases of Lyme
disease.
Effects of biodiversity on the incidence of Lyme disease
r2 = 0.54
Suggests many birds may be
competent reservoirs
r2 = 0.47
Consistent with a dilution effect by
less competent reservoirs
r2 = 0.46
Consistent with known ability of
fence lizards to clear the bacteria
Keesing and Ostfeld 2000 Conservation Biology
Some contributions from ecological analyses
of Lyme disease
Nymphs cause more infections than adults
The abundance of chipmunks and acorns are better
predictors of the risk of Lyme disease than weather or
deer abundance
Greater biodiversity of the small mammal community
reduces the risk of Lyme disease
It’s not just Humans
Domestic animals: FMD in GB, Brucellosis in YNP
Wildlife: Chytrid fungus, white band disease
It’s not just animals
Dutch elm disease
Sudden oak death
Targets of agricultural biowarfare
Who should take
responsibility for
prevention of
disease emergence
and spread?
Roles in prediction, prevention, and control of
infectious disease
Medicine: diagnosis and treatment of individuals
Biomedical research: identification of pathogens,
development of treatment and defense of individuals
Epidemiology: Analysis of patterns of disease occurrence
and their relationship to potential causes
Ecology: incorporate biological mechanism into prediction,
prevention, and control of disease at the population,
species, community, and ecosystem levels
Public health: Devising and implementing policy and
practice to reduce the occurrence and spread of disease
Education:?
The study of infectious disease is inherently multidisciplinary
but has fallen through the cracks, and is not taught
systematically
Microbiology
Immunology
Public Health
Ecology
Mathematics
Summary
1. The emergence and reemergence of infectious
disease is a serious threat.
2. Humans are not separate from the environment.
Our actions and behaviors have consequences for
the structure and integrity of natural ecosystems.
3. Understanding ecology provides one set of tools to
address the problem of infectious disease
4. Current popular visibility provides an opportunity to
educate students