Optimal temperature for malaria transmission is dramatically lower than previously predicted

Erin A. Mordecai, Krijn Paaijmans, Leah R. Johnson, Christian Balzer, Tal Ben-Horin, Emily de Moor, Amy Mcnally, Samraat Pawar, Sadie J. Ryan, Thomas C. Smith, Kevin D. Lafferty

Research output: Contribution to journalArticle

205 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)22-30
Number of pages9
JournalEcology Letters
Volume16
Issue number1
DOIs
StatePublished - Jan 1 2013
Externally publishedYes

Fingerprint

malaria
temperature
mosquito
heat
Culicidae
parasite
insect physiology
parasites
disease transmission
life history trait
angle of incidence
physiology
life history
climate change
insect
ecology
prediction

Keywords

  • Anopheles
  • Climate change
  • Disease ecology
  • Malaria
  • Plasmodium falciparum
  • Temperature

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics

Cite this

Mordecai, E. A., Paaijmans, K., Johnson, L. R., Balzer, C., Ben-Horin, T., de Moor, E., ... Lafferty, K. D. (2013). Optimal temperature for malaria transmission is dramatically lower than previously predicted. Ecology Letters, 16(1), 22-30. https://doi.org/10.1111/ele.12015

Optimal temperature for malaria transmission is dramatically lower than previously predicted. / Mordecai, Erin A.; Paaijmans, Krijn; Johnson, Leah R.; Balzer, Christian; Ben-Horin, Tal; de Moor, Emily; Mcnally, Amy; Pawar, Samraat; Ryan, Sadie J.; Smith, Thomas C.; Lafferty, Kevin D.

In: Ecology Letters, Vol. 16, No. 1, 01.01.2013, p. 22-30.

Research output: Contribution to journalArticle

Mordecai, EA, Paaijmans, K, Johnson, LR, Balzer, C, Ben-Horin, T, de Moor, E, Mcnally, A, Pawar, S, Ryan, SJ, Smith, TC & Lafferty, KD 2013, 'Optimal temperature for malaria transmission is dramatically lower than previously predicted', Ecology Letters, vol. 16, no. 1, pp. 22-30. https://doi.org/10.1111/ele.12015
Mordecai, Erin A. ; Paaijmans, Krijn ; Johnson, Leah R. ; Balzer, Christian ; Ben-Horin, Tal ; de Moor, Emily ; Mcnally, Amy ; Pawar, Samraat ; Ryan, Sadie J. ; Smith, Thomas C. ; Lafferty, Kevin D. / Optimal temperature for malaria transmission is dramatically lower than previously predicted. In: Ecology Letters. 2013 ; Vol. 16, No. 1. pp. 22-30.
@article{ad93be1a16b1435aa2da0465e52d6c54,
title = "Optimal temperature for malaria transmission is dramatically lower than previously predicted",
abstract = "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.",
keywords = "Anopheles, Climate change, Disease ecology, Malaria, Plasmodium falciparum, Temperature",
author = "Mordecai, {Erin A.} and Krijn Paaijmans and Johnson, {Leah R.} and Christian Balzer and Tal Ben-Horin and {de Moor}, Emily and Amy Mcnally and Samraat Pawar and Ryan, {Sadie J.} and Smith, {Thomas C.} and Lafferty, {Kevin D.}",
year = "2013",
month = "1",
day = "1",
doi = "10.1111/ele.12015",
language = "English (US)",
volume = "16",
pages = "22--30",
journal = "Ecology Letters",
issn = "1461-023X",
publisher = "Wiley-Blackwell",
number = "1",

}

TY - JOUR

T1 - Optimal temperature for malaria transmission is dramatically lower than previously predicted

AU - Mordecai, Erin A.

AU - Paaijmans, Krijn

AU - Johnson, Leah R.

AU - Balzer, Christian

AU - Ben-Horin, Tal

AU - de Moor, Emily

AU - Mcnally, Amy

AU - Pawar, Samraat

AU - Ryan, Sadie J.

AU - Smith, Thomas C.

AU - Lafferty, Kevin D.

PY - 2013/1/1

Y1 - 2013/1/1

N2 - 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.

AB - 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.

KW - Anopheles

KW - Climate change

KW - Disease ecology

KW - Malaria

KW - Plasmodium falciparum

KW - Temperature

UR - http://www.scopus.com/inward/record.url?scp=84870941946&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84870941946&partnerID=8YFLogxK

U2 - 10.1111/ele.12015

DO - 10.1111/ele.12015

M3 - Article

C2 - 23050931

AN - SCOPUS:84870941946

VL - 16

SP - 22

EP - 30

JO - Ecology Letters

JF - Ecology Letters

SN - 1461-023X

IS - 1

ER -