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Climate forcing and desert malaria: the effect of irrigation

Andres Baeza1, Menno J Bouma2, Andy P Dobson3, Ramesh Dhiman4, Harish C Srivastava5 and Mercedes Pascual16*

Author Affiliations

1 Deparment of Ecology and Evolutionary Biology University of Michigan, Ann Arbor, MI, USA

2 London School of Hygiene and Tropical Medicine. University of London, London, UK

3 Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NY, USA

4 National Institute of Malaria Research (ICMR), Delhi, India

5 National Institute of Malaria Research, (ICMR), Field Unit, Civil Hospital, Nadiad, Gujarat, India

6 Howard Hughes Medical Institute, Chevy Chase, MD 20815-6789, USA

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Malaria Journal 2011, 10:190  doi:10.1186/1475-2875-10-190

Published: 14 July 2011

Abstract

Background

Rainfall variability and associated remote sensing indices for vegetation are central to the development of early warning systems for epidemic malaria in arid regions. The considerable change in land-use practices resulting from increasing irrigation in recent decades raises important questions on concomitant change in malaria dynamics and its coupling to climate forcing. Here, the consequences of irrigation level for malaria epidemics are addressed with extensive time series data for confirmed Plasmodium falciparum monthly cases, spanning over two decades for five districts in north-west India. The work specifically focuses on the response of malaria epidemics to rainfall forcing and how this response is affected by increasing irrigation.

Methods and Findings

Remote sensing data for the Normalized Difference Vegetation Index (NDVI) are used as an integrated measure of rainfall to examine correlation maps within the districts and at regional scales. The analyses specifically address whether irrigation has decreased the coupling between malaria incidence and climate variability, and whether this reflects (1) a breakdown of NDVI as a useful indicator of risk, (2) a weakening of rainfall forcing and a concomitant decrease in epidemic risk, or (3) an increase in the control of malaria transmission. The predictive power of NDVI is compared against that of rainfall, using simple linear models and wavelet analysis to study the association of NDVI and malaria variability in the time and in the frequency domain respectively.

Conclusions

The results show that irrigation dampens the influence of climate forcing on the magnitude and frequency of malaria epidemics and, therefore, reduces their predictability. At low irrigation levels, this decoupling reflects a breakdown of local but not regional NDVI as an indicator of rainfall forcing. At higher levels of irrigation, the weakened role of climate variability may be compounded by increased levels of control; nevertheless this leads to no significant decrease in the actual risk of disease. This implies that irrigation can lead to more endemic conditions for malaria, creating the potential for unexpectedly large epidemics in response to excess rainfall if these climatic events coincide with a relaxation of control over time. The implications of our findings for control policies of epidemic malaria in arid regions are discussed.