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Forecasting mosquito populations in response to meteorological variables

Study level

PhD

Master of Philosophy

Honours

Faculty/Lead unit

Science and Engineering Faculty

School of Mathematical Sciences

Topic status

We're looking for students to study this topic.

Supervisors

Associate Professor Chris Drovandi
Position
Associate Professor
Division / Faculty
Science and Engineering Faculty

External supervisors

  • Dr Dan Pagendam, CSIRO

Overview

Being able to forecast changes in disease-carrying mosquito populations as a result of changes in rainfall and temperature would provide a powerful tool to public health bodies and also allow for more efficient application of biological control strategies.

The invasive mosquito, 'Aedes aegypti', predominantly inhabits urban landscapes and is responsible for the spread of diseases such as Dengue, Zika and Chikungunya.

It’s populations tend to decline during the cooler months and vary in the warmer months in response to rainfall events.

Recent biological control strategies applied in north Queensland relied upon the release of sterile male mosquitoes to reduce Aedes aegypti populations, but knowing when and to what extent mosquito populations are likely to rise following rainfall would allow for more targeted control strategies to be deployed.

Research activities

In this project, you will develop a state-space model that explains mosquito population dynamics in response to meteorological variables and also accounts for differences in the catch rates for mosquito traps placed in different parts of a study area.

You will use trapping data from mosquito monitoring studies in north Queensland and data available from the Bureau of Meteorology to find relationships between Aedes aegypti abundance and causal environmental variables.

This project will rely upon the use of Bayesian statistical methods for parameter estimation and inference from the available data.

Some of the activities involved in this project include:

  • stochastic modelling
  • developing Bayesian methods for parameter estimation
  • writing up results as journal articles.

Outcomes

You will use trapping data from mosquito monitoring studies in north Queensland and data available from the Bureau of Meteorology to find relationships between Aedes aegypti abundance and causal environmental variables.

The results of this research topic will be written up as journal articles.

Skills and experience

We expect you to have the following skills:

  • stochastic modelling
  • mathematical modelling
  • programming

A strong understanding of statistical inference is also desirable.

This project is most suitable for students who have an interest in applied statistical modelling, computational statistics and ecology.

Scholarships

You may be able to apply for a research scholarship in our annual scholarship round.

Annual scholarship round

Keywords

Contact

Contact the supervisor for more information.