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Predicting aquatic development and mortality rates of Aedes aegypti

Author

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  • Josef Zapletal
  • Himanshu Gupta
  • Madhav Erraguntla
  • Zach N Adelman
  • Kevin M Myles
  • Mark A Lawley

Abstract

Mosquito-borne pathogens continue to be a significant burden within human populations, with Aedes aegypti continuing to spread dengue, chikungunya, and Zika virus throughout the world. Using data from a previously conducted study, a linear regression model was constructed to predict the aquatic development rates based on the average temperature, temperature fluctuation range, and larval density. Additional experiments were conducted with different parameters of average temperature and larval density to validate the model. Using a paired t-test, the model predictions were compared to experimental data and showed that the prediction models were not significantly different for average pupation rate, adult emergence rate, and juvenile mortality rate. The models developed will be useful for modeling and estimating the upper limit of the number of Aedes aegypti in the environment under different temperature, diurnal temperature variations, and larval densities.

Suggested Citation

  • Josef Zapletal & Himanshu Gupta & Madhav Erraguntla & Zach N Adelman & Kevin M Myles & Mark A Lawley, 2019. "Predicting aquatic development and mortality rates of Aedes aegypti," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-8, May.
    • Handle: RePEc:plo:pone00:0217199
    DOI: 10.1371/journal.pone.0217199
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    References listed on IDEAS

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    1. Josef Zapletal & Madhav Erraguntla & Zach N Adelman & Kevin M Myles & Mark A Lawley, 2018. "Impacts of diurnal temperature and larval density on aquatic development of Aedes aegypti," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-16, March.
    2. Erickson, Richard A. & Presley, Steven M. & Allen, Linda J.S. & Long, Kevin R. & Cox, Stephen B., 2010. "A stage-structured, Aedes albopictus population model," Ecological Modelling, Elsevier, vol. 221(9), pages 1273-1282.
    3. Erickson, Richard A. & Presley, Steven M. & Allen, Linda J.S. & Long, Kevin R. & Cox, Stephen B., 2010. "A dengue model with a dynamic Aedes albopictus vector population," Ecological Modelling, Elsevier, vol. 221(24), pages 2899-2908.
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    Cited by:

    1. Hasan T Abbas & Lejla Alic & Madhav Erraguntla & Jim X Ji & Muhammad Abdul-Ghani & Qammer H Abbasi & Marwa K Qaraqe, 2019. "Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-11, December.

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