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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
Optimal temperature for malaria transmission is dramatically lower than previously predicted
Ecology Letters, Volume 16, No. 1, Year 2013
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Description
The ecology of mosquito vectors and malaria parasites affect the incidence, seasonal transmission and geographical range of malaria. Most malaria models to date assume constant or linear responses of mosquito and parasite life-history traits to temperature, predicting optimal transmission at 31 °C. These models are at odds with field observations of transmission dating back nearly a century. We build a model with more realistic ecological assumptions about the thermal physiology of insects. Our model, which includes empirically derived nonlinear thermal responses, predicts optimal malaria transmission at 25 °C (6 °C lower than previous models). Moreover, the model predicts that transmission decreases dramatically at temperatures > 28 °C, altering predictions about how climate change will affect malaria. A large data set on malaria transmission risk in Africa validates both the 25 °C optimum and the decline above 28 °C. Using these more accurate nonlinear thermal-response models will aid in understanding the effects of current and future temperature regimes on disease transmission. © 2012 Blackwell Publishing Ltd/CNRS.
Authors & Co-Authors
Mordecai, Erin A.
United States, Santa Barbara
University of California, Santa Barbara
Paaijmans, Krijn Petrus
United States, University Park
Pennsylvania State University
Johnson, Leah R.
United States, Chicago
The University of Chicago
Ben-Horin, Tal
United States, Santa Barbara
University of California, Santa Barbara
de Moor, Emily
United States, Santa Barbara
University of California, Santa Barbara
McNally, Amy
United States, Santa Barbara
University of California, Santa Barbara
Pawar, Samraat S.
United States, Los Angeles
David Geffen School of Medicine at Ucla
Ryan, Sadie J.
United States, Albany
State University of new York System
Lafferty, Kevin D.
United States, Santa Barbara
University of California, Santa Barbara
United States, Reston
United States Geological Survey
Statistics
Citations: 353
Authors: 9
Affiliations: 6
Identifiers
Doi:
10.1111/ele.12015
ISSN:
14610248
Research Areas
Environmental
Infectious Diseases
Study Design
Cohort Study