Predicting aquatic development and mortality rates of Aedes aegypti

• Published in: PloS one 2019-05, Vol.14 (5), p.e0217199-e0217199
• Main Authors: Zapletal, Josef, Gupta, Himanshu, Erraguntla, Madhav, Adelman, Zach N, Myles, Kevin M, Lawley, Mark A
• Format: Article
• Language: English
• Subjects: Aedes - growth & development; Aedes - virology; Aedes aegypti; Animal development; Animals; Aquatic insects; Biological research; Biology and Life Sciences; Chikungunya Fever - transmission; Chikungunya Fever - virology; Chikungunya virus - isolation & purification; Climate change; Daily temperatures; Dengue; Dengue - transmission; Dengue - virology; Dengue fever; Dengue Virus - isolation & purification; Density; Diurnal; Diurnal temperature; Engineering; Entomology; Experiments; Human populations; Humans; Insect carriers of disease; Laboratories; Larva - growth & development; Larva - virology; Medicine and Health Sciences; Model testing; Mortality; Mosquito Vectors - growth & development; Mosquito Vectors - virology; Mosquitoes; Nutrition; Pathogenic microorganisms; Pathogens; Physical Sciences; Physiological aspects; Population; Prediction models; Pupation; Regression analysis; Regression models; Research and Analysis Methods; Temperature; Temperature effects; Temperature variations; Variation; Vector-borne diseases; Viral diseases; Viruses; Water - chemistry; Yellow fever mosquito; Zika virus; Zika Virus - isolation & purification; Zika Virus Infection - transmission; Zika Virus Infection - virology
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0217199

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.