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![Page 1: The potential effects of climate change on malaria in tropical Africa using regionalised climate projections European Geosciences Union (EGU) General Assembly.](https://reader035.fdocuments.in/reader035/viewer/2022062320/56649d025503460f949d5b07/html5/thumbnails/1.jpg)
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
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MALARIA - one of the world’s most serious health problems
©AMMA
©Sachs & Malaney (2002)
©MARA
©mosquitomenace.com
Central question: How does the spread of malaria
evolve in a warmer future climate?
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EIRa
S2005
parasite ratio
PR<15
cv (PR<15)malaria risk
Meteorological data &malaria observations
Malaria simulationsPresent-day & projections
Malaria modelling
Outline of the Study
LMM calibration
LMM2010
Station time series &malaria field studies
Present-day climate
Scenarios: A1B & B1
validation &
bias-correction
CRU RR
ERA40T
EIRa
mosquito bites
malaria season
MSMmalaria season
Ermert et al. 2011a,bMalaria Journal, 10: 35 & 62
Ermert et al. 2012aEnv Health Persp, 120, 77-84
Ermert et al. 2012b, sub. to Climatic Change
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Regionalised climate projections from the REgional MOdel (REMO)
Meteorological data &malaria observations
Present-day climate
Scenarios: A1B & B1
validation &
bias-correction
CRU RR
ERA40
including projected Land Use and land Cover (LUC) changes
T
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.
croplandsmixed forests
woody savannas urban and built-upSource: after Paeth et al. (2009), J Clim, 22, 114-132, their Fig.1
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statistical significant at the 5% level (Wilcoxon-Mann-Whitey rank-sum test)
REMO: Precipitation (RR) and change of precipitation (RR)
corrected byCRU data
Source: after Ermert et al. (2012), EHP, 120, 77-84
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REMO: Temperature (T) and temperature change (T)
corrected byERA-40 data
Source: after Ermert et al. (2012), EHP, 120, 77-84
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monthly
valuesMSM
malaria season
MARA Seasonality Model (Tanser et al. 2003)
S2005 model
PR<15
P. falciparum infection model
from Smith et al. 2005
Parasite Ratio of children
EIRa
annual Entomological Inoculation Rate(mosquito bites)
daily values
LMM2010dynamical
mathematical-biologicalLiverpool
Malaria Model(Hoshen & Morse 2004; Ermert et al.
2011a,b)
temperaturesprecipitation
The integrated weather-malaria model(s)
malaria season
cv (PR<15)malaria risk
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LMM2010: annual EIR (EIRa) and its change (EIRa)
[infectious mosquito bites per year]
196
0-2
000
Source:Ermert et al. 2012EHP, 120, 77-84
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LMM2010 & MSM: Changes of the malaria season
[month]
[month]
Source: after Ermert et al. 2012, EHP, 120, 77-84, their Fig. 1C
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2021-2030 2041-2050
-1.5 -1 -0.5 -0.1 0.1 0.5 1 2 4 8
LMM2010 & MSM: Changes of the malaria season
[month]
Source:Ermert et al. 2012, EHP, 120, 77-84
-6 -4 -3 -2 -1 1 2 3 4 6
Difference plot between the MSM and LMM2010 (MSM-LMM2010)
[month]
Source: after Ermert et al. 2012, EHP, 120, 77-84, their Fig. 3C&D
Source: after Ermert et al. 2012, submitted to Climate Change
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→ malaria risk
S2005: Coefficent of variation (cv) of PR<15 (cv(PR<15))
1960-2000
= cv
Source: Ermert (2010), PhD dissertation, University of Cologne, Germany
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S2005: Coefficent of variation (cv) of PR<15 (cv(PR<15))
= cv
Source: Ermert (2010), PhD dissertation, University of Cologne, Germany
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S2005: Change of malaria risk
cv: coefficient of variation
196
0-2
000
A1B 2021-2030 2041-2050
Source:Ermert et al. 2012,EHP, 120, 77-84
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Sahel
N
today
East AfricanHighlands
2050
higher temperatures
lower precipitation
stable malaria
malaria epidemics
malaria free
Projected future changes of malaria in Africa
~2000 m
~2500 m
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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
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Thank you for your attention!
Contact
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/