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Detecting the impact of temperature on transmission of Zika, dengue, and chikungunya using mechanistic models

Author

Listed:
  • Erin A Mordecai
  • Jeremy M Cohen
  • Michelle V Evans
  • Prithvi Gudapati
  • Leah R Johnson
  • Catherine A Lippi
  • Kerri Miazgowicz
  • Courtney C Murdock
  • Jason R Rohr
  • Sadie J Ryan
  • Van Savage
  • Marta S Shocket
  • Anna Stewart Ibarra
  • Matthew B Thomas
  • Daniel P Weikel

Abstract

Recent epidemics of Zika, dengue, and chikungunya have heightened the need to understand the seasonal and geographic range of transmission by Aedes aegypti and Ae. albopictus mosquitoes. We use mechanistic transmission models to derive predictions for how the probability and magnitude of transmission for Zika, chikungunya, and dengue change with mean temperature, and we show that these predictions are well matched by human case data. Across all three viruses, models and human case data both show that transmission occurs between 18–34°C with maximal transmission occurring in a range from 26–29°C. Controlling for population size and two socioeconomic factors, temperature-dependent transmission based on our mechanistic model is an important predictor of human transmission occurrence and incidence. Risk maps indicate that tropical and subtropical regions are suitable for extended seasonal or year-round transmission, but transmission in temperate areas is limited to at most three months per year even if vectors are present. Such brief transmission windows limit the likelihood of major epidemics following disease introduction in temperate zones.Author summary: Understanding the drivers of recent Zika, dengue, and chikungunya epidemics is a major public health priority. Temperature may play an important role because it affects virus transmission by mosquitoes, through its effects on mosquito development, survival, reproduction, and biting rates as well as the rate at which mosquitoes acquire and transmit viruses. Here, we measure the impact of temperature on transmission by two of the most common mosquito vector species for these viruses, Aedes aegypti and Ae. albopictus. We integrate data from several laboratory experiments into a mathematical model of temperature-dependent transmission, and find that transmission peaks at 26–29°C and can occur between 18–34°C. Statistically comparing model predictions with recent observed human cases of dengue, chikungunya, and Zika across the Americas suggests an important role for temperature, and supports model predictions. Using the model, we predict that most of the tropics and subtropics are suitable for transmission in many or all months of the year, but that temperate areas like most of the United States are only suitable for transmission for a few months during the summer (even if the mosquito vector is present).

Suggested Citation

  • Erin A Mordecai & Jeremy M Cohen & Michelle V Evans & Prithvi Gudapati & Leah R Johnson & Catherine A Lippi & Kerri Miazgowicz & Courtney C Murdock & Jason R Rohr & Sadie J Ryan & Van Savage & Marta S, 2017. "Detecting the impact of temperature on transmission of Zika, dengue, and chikungunya using mechanistic models," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 11(4), pages 1-18, April.
  • Handle: RePEc:plo:pntd00:0005568
    DOI: 10.1371/journal.pntd.0005568
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    References listed on IDEAS

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    1. Cory W Morin & Andrew J Monaghan & Mary H Hayden & Roberto Barrera & Kacey Ernst, 2015. "Meteorologically Driven Simulations of Dengue Epidemics in San Juan, PR," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 9(8), pages 1-24, August.
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    Cited by:

    1. Eunho Suh & Isaac J. Stopard & Ben Lambert & Jessica L. Waite & Nina L. Dennington & Thomas S. Churcher & Matthew B. Thomas, 2024. "Estimating the effects of temperature on transmission of the human malaria parasite, Plasmodium falciparum," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    2. Yannick Drif & Benjamin Roche & Pierre Valade, 2020. "Conséquences du changement climatique pour les maladies à transmission vectorielle et impact en assurance de personnes," Working Papers hal-02998538, HAL.
    3. Tobias Brett & Marco Ajelli & Quan-Hui Liu & Mary G Krauland & John J Grefenstette & Willem G van Panhuis & Alessandro Vespignani & John M Drake & Pejman Rohani, 2020. "Detecting critical slowing down in high-dimensional epidemiological systems," PLOS Computational Biology, Public Library of Science, vol. 16(3), pages 1-19, March.
    4. Tobias S Brett & Pejman Rohani, 2020. "Dynamical footprints enable detection of disease emergence," PLOS Biology, Public Library of Science, vol. 18(5), pages 1-20, May.
    5. Abdalgader, Tarteel & Banerjee, Malay & Zhang, Lai, 2022. "Spatially weak syncronization of spreading pattern between Aedes Albopictus and dengue fever," Ecological Modelling, Elsevier, vol. 473(C).
    6. Flückiger, Matthias & Ludwig, Markus, 2020. "Malaria suitability, urbanization and subnational development in sub-Saharan Africa," Journal of Urban Economics, Elsevier, vol. 120(C).
    7. Yu-Chieh Cheng & Fang-Jing Lee & Ya-Ting Hsu & Eric V Slud & Chao A Hsiung & Chun-Hong Chen & Ching-Len Liao & Tzai-Hung Wen & Chiu-Wen Chang & Jui-Hun Chang & Hsiao-Yu Wu & Te-Pin Chang & Pei-Sheng L, 2020. "Real-time dengue forecast for outbreak alerts in Southern Taiwan," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 14(7), pages 1-18, July.
    8. Ana C Piovezan-Borges & Francisco Valente-Neto & Wanderli P Tadei & Neusa Hamada & Fabio O Roque, 2020. "Simulated climate change, but not predation risk, accelerates Aedes aegypti emergence in a microcosm experiment in western Amazonia," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-12, October.

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