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

©AMMA

©Sachs & Malaney (2002)

©MARA

©mosquitomenace.com

Central question: How does the spread of malaria

evolve in a warmer future climate?

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

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

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

REMO: Temperature (T) and temperature change (T)

corrected byERA-40 data

Source: after Ermert et al. (2012), EHP, 120, 77-84

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

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

LMM2010 & MSM: Changes of the malaria season

[month]

[month]

Source: after Ermert et al. 2012, EHP, 120, 77-84, their Fig. 1C

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

→ 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

S2005: Coefficent of variation (cv) of PR<15 (cv(PR<15))

= cv

Source: Ermert (2010), PhD dissertation, University of Cologne, Germany

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

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

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!

Contact

vermert@meteo.uni-koeln.de

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/