global biogeography of human infectious diseases - agents
TRANSCRIPT
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Global biogeography of human infectious
diseases - agents of change
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0%
25%
50%
75%
100%
1990 1995 2000 2005 2010 2015
Year
% G
lob
al B
urd
en
of
Dis
ea
se
NCDs
other
Injuries
• Major
successes in
health in past
50-100yrs
• Particularly
burden from
infectious
diseases
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Funk et al. 2013
Emerging infectious diseases (EIDs)
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Wild
life
Emerging infectious diseases (EIDs)
• EIDs on the rise globally
• ~60% from animals ( “zoonotic”)
• Mostly wildlife
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Infectious diseases: the role of animals
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Climate change impacts - organisms to ecosystems
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From cold to mildly warm
From warm to extremely warm
Tra
it p
erf
orm
an
ce
Temperature
thanks - C. Caminade
Trait performance
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From cold to mildly warm
From warm to extremely warm
Tra
it p
erf
orm
an
ce
Temperature
Trait performance
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From cold to mildly warm
From warm to extremely warm
Tra
it p
erf
orm
an
ce
Temperature
Trait performance
Mordecai et al., 2017
+
Temperature
Rainfall
Humidity
….
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From cold to mildly warm
From warm to extremely warm
Tra
it p
erf
orm
an
ce
Temperature
Trait performance
Mordecai et al., 2017
+
Temperature
Rainfall
Humidity
….
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0
3
6
9
1950 1970 1990 2010 2030 2050
Year
Vecto
ria
l C
ap
acity
(%
ch
an
ge
re
l. 1
95
0)
RCP8.5
RCP2.6
Hist.
A. aegypti
0
5
10
15
20
1950 1970 1990 2010 2030 2050
Year
Vecto
ria
l C
apa
city
(%
ch
an
ge
re
l. 1
99
0)
RCP8.5
RCP2.6
Hist.
A. albopictus
0
3
6
9
1950 1970 1990 2010 2030 2050
Year
Vecto
ria
l C
ap
acity
(%
ch
an
ge
re
l. 1
95
0)
RCP8.5
RCP2.6
Hist.
A. aegypti
0
5
10
15
20
1950 1970 1990 2010 2030 2050
Year
Vecto
ria
l C
apa
city
(%
ch
an
ge
re
l. 1
99
0)
RCP8.5
RCP2.6
Hist.
A. albopictus
a = vector biting rate,
bh = vector to human transmission per bite
bm = human to vector infection per bite,
n = extrinsic incubation period – EIP,
μm = vector mortality rate,
m = female vector-to-human population ratio
Vectorial capacity
Watts et al., (2018) Lancet
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2107 pathogens in humans (Wardeh et al. 2015)
• 274 viruses
• 1003 bacteria
• 447 fungi
• 82 protozoa
• 301 helminths
Majority:
o Zoonotic
o Multiple zoonotic hosts
o If vector-borne, then multiple vectors
Pathodiversity
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Traitperform
ance
S1
S2…
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Traitperform
ance
S1
S2…
e.g. Richness patterns e.g. Bioregionalisat ion
Multi-disease biogeographic patterns
Disease (D)
Observat ion (O)
Management (M)
Humans (H)
Vector(s) (V/ Vn)
Reservoir(s) (R/ Rn)
Environment (E)
Geography (G)
Pathogen (P)
e.g. Chorotypes
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Traitperform
ance
S1
S2…
e.g. Richness patterns e.g. Bioregionalisat ion
Multi-disease biogeographic patterns
Disease (D)
Observat ion (O)
Management (M)
Humans (H)
Vector(s) (V/ Vn)
Reservoir(s) (R/ Rn)
Environment (E)
Geography (G)
Pathogen (P)
e.g. Chorotypes
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Traitperform
ance
S1
S2…
e.g. Richness patterns e.g. Bioregionalisat ion
Multi-disease biogeographic patterns
Disease (D)
Observat ion (O)
Management (M)
Humans (H)
Vector(s) (V/ Vn)
Reservoir(s) (R/ Rn)
Environment (E)
Geography (G)
Pathogen (P)
e.g. Chorotypes
Speciesxtraitsxenviron.covariates
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e.g. Richness patterns e.g. Bioregionalisat ion
Multi-disease biogeographic patterns
Disease (D)
Observat ion (O)
Management (M)
Humans (H)
Vector(s) (V/ Vn)
Reservoir(s) (R/ Rn)
Environment (E)
Geography (G)
Pathogen (P)
e.g. Chorotypes Pathogeography
Murray et al., (2018) Ecography
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Pathogeography
Disease identity (which diseases where?)
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Pathogeography
Regionalisation
Tiedt and Murray (in prep.) Murray et al., (2015) PNAS
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Pathogeography
Regionalisation
Murray et al., (2015) PNAS
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Distance
Pathogeography
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Biodiversity
Pathogeography
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Climate
Pathogeography
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Connectivity
Pathogeography
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Pathogeography
Murray et al., (2015) PNAS
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80
90
100
110
Disease richness
Pathogeography
Murray et al., (2018) Ecography
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Pathogeography
Start & Murray (submitted)
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Pathogeography
Start & Murray (submitted)
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Human influence
Little control
Human influence
Some control
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– 82% of 94 processes
– 1°C average
warming so far
– Conservative
estimates
– Processes are
connected!
Climate change impacts - organisms to ecosystems
Scheffers et al., (2016) Science
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• Most human infectious diseases are zoonotic
• Zoonoses are complicated - difficult to map, predict
• Zoonoses = biodiversity * habitats * land-use * dispersal * climate
...
• Increases AND decreases in risk due to climate change
• Host/pathogen traits global disease diversity
• Global scale disease diversity is controlled by factors that we affect
but don’t control
• Systems approaches required
• Public health + conservation policies = co-benefits
Conclusions
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Merci!