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Predictive model for microclimatic temperature and its use in mosquito population modeling
by
Adelman, Zach N.
, Lawley, Mark
, Dave, Darpit
, Erraguntla, Madhav
, Pohlenz, Tyler D.
, Myles, Kevin
, Zapletal, Josef
in
631/114/1305
/ 631/114/2164
/ 631/114/2397
/ 639/705/1046
/ 692/699/255
/ Aedes albopictus
/ Aquatic insects
/ Breeding
/ Culicidae
/ Dormancy
/ Environmental conditions
/ Environmental factors
/ Generalized linear models
/ Humanities and Social Sciences
/ Infectious diseases
/ Microclimate
/ Mosquitoes
/ multidisciplinary
/ Population
/ Population dynamics
/ Prediction models
/ Science
/ Science (multidisciplinary)
/ Storm drains
/ Temperature
2021
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Predictive model for microclimatic temperature and its use in mosquito population modeling
by
Adelman, Zach N.
, Lawley, Mark
, Dave, Darpit
, Erraguntla, Madhav
, Pohlenz, Tyler D.
, Myles, Kevin
, Zapletal, Josef
in
631/114/1305
/ 631/114/2164
/ 631/114/2397
/ 639/705/1046
/ 692/699/255
/ Aedes albopictus
/ Aquatic insects
/ Breeding
/ Culicidae
/ Dormancy
/ Environmental conditions
/ Environmental factors
/ Generalized linear models
/ Humanities and Social Sciences
/ Infectious diseases
/ Microclimate
/ Mosquitoes
/ multidisciplinary
/ Population
/ Population dynamics
/ Prediction models
/ Science
/ Science (multidisciplinary)
/ Storm drains
/ Temperature
2021
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Predictive model for microclimatic temperature and its use in mosquito population modeling
by
Adelman, Zach N.
, Lawley, Mark
, Dave, Darpit
, Erraguntla, Madhav
, Pohlenz, Tyler D.
, Myles, Kevin
, Zapletal, Josef
in
631/114/1305
/ 631/114/2164
/ 631/114/2397
/ 639/705/1046
/ 692/699/255
/ Aedes albopictus
/ Aquatic insects
/ Breeding
/ Culicidae
/ Dormancy
/ Environmental conditions
/ Environmental factors
/ Generalized linear models
/ Humanities and Social Sciences
/ Infectious diseases
/ Microclimate
/ Mosquitoes
/ multidisciplinary
/ Population
/ Population dynamics
/ Prediction models
/ Science
/ Science (multidisciplinary)
/ Storm drains
/ Temperature
2021
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Predictive model for microclimatic temperature and its use in mosquito population modeling
Journal Article
Predictive model for microclimatic temperature and its use in mosquito population modeling
2021
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Overview
Mosquitoes transmit several infectious diseases that pose significant threat to human health. Temperature along with other environmental factors at breeding and resting locations play a role in the organismal development and abundance of mosquitoes. Accurate analysis of mosquito population dynamics requires information on microclimatic conditions at breeding and resting locations. In this study, we develop a regression model to characterize microclimatic temperature based on ambient environmental conditions. Data were collected by placing sensor loggers at resting and breeding locations such as storm drains across Houston, TX. Corresponding weather data was obtained from National Oceanic and Atmospheric Administration website. Features extracted from these data sources along with contextual information on location were used to develop a Generalized Linear Model for predicting microclimate temperatures. We also analyzed mosquito population dynamics for
Aedes albopictus
under ambient and microclimatic conditions using system dynamic (SD) modelling to demonstrate the need for accurate microclimatic temperatures in population models. The microclimate prediction model had an R
2
value of ~ 95% and average prediction error of ~ 1.5 °C indicating that microclimate temperatures can be reliably estimated from the ambient environmental conditions. SD model analysis indicates that some microclimates in Texas could result in larger populations of juvenile and adult
Aedes albopictus
mosquitoes surviving the winter without requiring dormancy.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
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