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The potential effects of climate change on
malaria in tropical Africa using regionalised
climate projections
European Geosciences Union (EGU)
General Assembly 2012
CL2.5 Climate and infectious disease
interactions
Volker Ermert, Andreas H. Fink, Heiko
Paeth, and Andrew P. Morse
Tuesday, 24 April 2012
Congress Center, Austria Center Vienna,
Bruno-Kreisky-Platz 1, Room 13
MALARIA - one of the world’s most serious health problems
©Sachs & Malaney (2002)
Central question: How does the spread of malaria
evolve in a warmer future climate?
©MARA
©AMMA
©mosquitomenace.com
Outline of the Study
Meteorological data &
malaria observations
Station time series &
malaria field studies
Malaria modelling
Present-day & projections
LMM
calibration
LMM2010
EIRa
S2005
validation
&
biascorrection
CRU
mosquito bites
Ermert et al.
2011a,b
EIR
a
Malaria Journal, 10:
35 & 62
malaria
season
parasite ratio
Present-day climate
ERA40
Malaria simulations
PR<15
malaria risk
cv (PR<15)
T
RR
Scenarios: A1B & B1
Ermert et al. 2012a
malaria
Env Health Persp, 120, 77-84
season
MSM
Ermert et al. 2012b, sub. to Climatic Change
Regionalised climate projections from the REgional MOdel (REMO)
Meteorological data &  including projected Land Use and land Cover (LUC) changes
malaria observations
Present-day climate
validation ERA40
&
biasCRU
correction
T
mixed forests
croplands
woody savannas
urban and built-up
Source: after Paeth et al. (2009), J Clim, 22, 114-132, their Fig.1
RR
Scenarios: A1B & B1
 strong influence on the hydrological cylce
 strong precipitation decline due to reduced water recycling
Further details: see Paeth et al. (2009), J Clim, 22, 114-132.
REMO: Precipitation (RR) and change of precipitation (RR)
corrected by
CRU data
statistical significant at the 5% level (Wilcoxon-Mann-Whitey rank-sum test)
Source: after Ermert et al. (2012), EHP, 120, 77-84
REMO: Temperature (T) and temperature change (T)
corrected by
ERA-40 data
Source: after Ermert et al. (2012), EHP, 120, 77-84
The integrated weather-malaria model(s)
MARA Seasonality Model (Tanser et al. 2003)
temperatures monthly
precipitation values
daily
values
LMM2010
dynamical
mathematicalbiological
Liverpool
Malaria Model
(Hoshen & Morse
2004; Ermert et al.
2011a,b)
MSM
malaria
season
malaria
season
EIRa
P. falciparum
infection model
from Smith et
al. 2005
annual Entomological
Inoculation Rate
(mosquito bites)
S2005 model
Parasite Ratio
of children
PR<15
cv (PR<15)
malaria risk
1960-2000
LMM2010: annual EIR (EIRa) and its change (EIRa)
Source:
Ermert et al. 2012
EHP, 120, 77-84
[infectious mosquito
bites per year]
LMM2010 & MSM: Changes of the malaria season
[month]
[month]
Source: after Ermert et al. 2012, EHP, 120, 77-84, their Fig. 1C
LMM2010 & MSM: Changes of the malaria season
2021-2030
2041-2050
-1.5
-1
-0.5
-0.1
0.1
0.5
1
2
4
[month]
8
Source: after Ermert et al. 2012, EHP, 120, 77-84, their Fig. 3C&D
Difference plot between the MSM and LMM2010 (MSM-LMM2010)
Source:
Ermert et al. 2012, EHP, 120, 77-84
-6
-4
-3
-2
-1
1
Source: after Ermert et al. 2012, submitted to Climate Change
2
3
4
6
[month]
S2005: Coefficent of variation (cv) of PR<15 (cv(PR<15))
1960-2000
= cv
→ malaria risk
Source: Ermert (2010), PhD dissertation, University of Cologne, Germany
S2005: Coefficent of variation (cv) of PR<15 (cv(PR<15))
= cv
Source: Ermert (2010), PhD dissertation, University of Cologne, Germany
1960-2000
S2005: Change of malaria risk
Source:
Ermert et al. 2012,
EHP, 120, 77-84
cv: coefficient
of variation
A1B
2021-2030
2041-2050
Projected future changes of malaria in Africa
Sahel
N
East African
Highlands
~2000 m
today
lower precipitation
higher temperatures
~2500 m
2050
stable malaria
malaria epidemics
malaria free
OUTLOOK
Liverpool Malaria Model
 Inclusion of some malaria control activities
 Estimation of the time window for expected changes of:
• altitude range of malaria
• latitudinal change of malaria in the Sahel region
 Information especially needed by decision-makers
QWeCI
 Seamless climate-disease projections in pilot countries (Senegal, Ghana & Malawi)
e.g. seasonal malaria forecasts  Health Early Warning System
See, for example, Morse et al. 2012 (Poster Z76 EGU2012-1559)
The QWeCI Project: seamlessly linking climate science to society
VECTRI (Vector borne disease model of Trieste)
 Development of a community malaria model
See Tompkins et al. 2012a (Poster Z85 EGU2012-12193)
VECTRI: A new dynamical disease model for malaria transmission
Tompkins et al. 2012b (Poster Z86 EGU2012-12228)
A simple pond parametrization for malaria transmission models
Thank you for your attention!
Peer-reviewed publications
• Ermert et al. 2011a. Malaria Journal, 10:35.
• Ermert et al. 2011b. Malaria Journal, 10:62.
• Ermert et al. 2012a. Environmental Health Perspectives, 120, 77-84.
PhD thesis
• Ermert V. 2010. Risk assessment with regard to the occurrence of malaria in Africa under the
influence of observed and projected climate change. University of Cologne.
http://kups.ub.uni-koeln.de/volltexte/2010/3109/
Contact
[email protected]