Algorithm shows that under the right conditions, mosquitoes can even
flourish in winter

Date:
December 9, 2021
Source:
Texas A&M University
Summary:
With an impressive capability of drinking up to three times their
body weight in a single blood meal, mosquitoes are formidable
parasites. But to reach adulthood, mosquitoes need to be raised in
environments where the temperatures are conducive to their breeding,
growth and development.



FULL STORY ==========================================================================
With an impressive capability of drinking up to three times their body
weight in a single blood meal, mosquitoes are formidable parasites. But
to reach adulthood, mosquitoes need to be raised in environments where
the temperatures are conducive to their breeding, growth and development.


==========================================================================
In a new study in the journal Scientific Reports, Texas A&M University researchers have developed a mathematical model based on machine
learning to precisely predict the local or microclimatic temperature
within the breeding grounds of theAedes albopictus mosquitoes, carriers
of the chikungunya and dengue viruses. Their algorithm also reveals that
even in winter, the temperature may be warm enough in certain breeding
grounds to allow mosquitoes to grow and thrive.

"Our goal is to develop accurate and automated mathematical models for estimating microclimatic temperature, which can greatly facilitate a
quick assessment of mosquito populations and consequently, vector-borne
disease transmission," said Dr. Madhav Erraguntla, associate professor
of practice in the Wm Michael Barnes '64 Department of Industrial and
Systems Engineering.

Responsible for around a million deaths globally, mosquitoes continue
to wreak havoc to public health in many parts of the world. In addition
to water, temperature plays a critical role at different stages in
mosquitoes' life cycle. Furthermore, The mosquitoes' development,
reproduction and survival can be mathematically modeled on the basis
of temperature.

Past studies have largely relied on ambient temperature, or general air temperature, to make predictions about mosquito populations. However,
these calculations have not been precise since ambient temperatures
can deviate from those within mosquito breeding grounds. Recognizing
this shortcoming, scientists rely on sensors, called data loggers, to continually keep track of the temperature, light intensity and humidity
within breeding grounds. Despite their advantages, these sensors are inconvenient due to their cost and long- term use.

"People have realized that the microclimatic conditions are important,
but right now data loggers are the only way to keep track of temperature,"
said Erraguntla. "We wanted to address this gap by automating the process
of estimating microclimatic temperatures so that we can model the life
cycle of mosquitoes accurately." For their experiments, the researchers
placed sensors in common mosquito breeding grounds around Houston,
Texas, including storm drains, shaded areas and inside water meters. In addition, they obtained information on ambient temperatures from the
National Oceanic and Atmospheric Administration repository. With this
data as training input to a machine learning algorithm, the computer
model could predict the microclimatic temperatures for a variety of
ambient temperatures and breeding grounds within 1.5 degrees centigrade.

Further, the model now could even forecast microclimatic temperatures
for any ambient temperature, precluding the need for sensors.

Next, they fed the values of the microclimatic temperatures to another mathematical model, called the population dynamic model, that tracks the
life cycle of the mosquitoes. Based on the microclimatic temperature
and other parameters, the population dynamic model could estimate the populations at different stages in the lifecycle including eggs, larvae,
pupae and adult Aedes albopictus mosquitoes.

The model also revealed that the insulated conditions of the storm
drains could result in the survival of 84% of juveniles and eggs and 96%
of adults during the winter months, a time of the year when mosquitoes
are assumed to be dormant.

Although their climatic temperature prediction model has a high degree
of accuracy, the researchers noted that additional research is needed
to affirm if their model is applicable to places outside of Texas.

"Our work automates the prediction of microclimatic conditions, bypassing
an otherwise expensive and time-consuming process of placing the sensors
in different breeding spots, collecting the sensor data and analyzing
it," said Erraguntla. "From a public health context, this work will
help epidemiologists better track mosquito-borne disease transmission
and surges in mosquito abundances." Other contributors to this research include Darpit Dave, Josef Zapletal and Mark Lawley from the industrial
and systems engineering department; and Kevin Myles, Zach Adelman and
Tyler Pohlenz from Department of Entomology at Texas A&M.

========================================================================== Story Source: Materials provided by Texas_A&M_University. Original
written by Vandana Suresh.

Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Madhav Erraguntla, Darpit Dave, Josef Zapletal, Kevin Myles, Zach N.

Adelman, Tyler D. Pohlenz, Mark Lawley. Predictive model for
microclimatic temperature and its use in mosquito population
modeling.

Scientific Reports, 2021; 11 (1) DOI: 10.1038/s41598-021-98316-x ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2021/12/211209124204.htm

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