Cynthia Lord

Associate Professor

Population Modelling
clord@ufl.edu

The goal of my research program is to improve our understanding of disease transmission, particularly for vector-borne diseases. With an improved understanding of transmission, we are better able to predict outbreaks or the consequences of invasion of new pathogens or vectors, and are also better able to develop control strategies.

My laboratory uses mathematical and computer modeling to investigate questions about the ecology and epidemiology of pathogens. A major research project is the epidemiology of West Nile virus in Florida. In this project, we are trying to better understand the interaction of bird and mosquito species in transmission. Models are exploring the role of different bird and mosquito species in invasion of new areas and the transmission dynamics. Collaborative studies in the lab and field have investigated the biological and environmental factors that affect transmission

Ecological interactions such as competition can also play a role in disease transmission. Human activity like pesticide application may have effects on transmission beyond just changing mosquito numbers. We are modeling these interactions to explore how competition and pesticide use affects disease transmission. Associated collaborations are measuring parameters for the detailed relationships between aspects of transmission and competition or pesticide exposure. We are also using models and field studies to develop guidelines for methods of mosquito control that do not rely on pesticides, such as barriers of mosquito traps. Mosquito control districts need information about how to design these barriers for different species or environmental conditions. Other projects in my laboratory include the population dynamics of the black-legged tick in south Florida and modeling transmission dynamics of canine influenza in different dog populations.

A recent interest in my laboratory is how processes at one scale influence processes at other scales. We need to better understand these links to predict how differences in climate and ecology affect epidemiology. Are different pathways in the mosquito infection process critical to predicting outbreaks, or is estimating the average infection rate sufficient? Does the presence of a mosquito predator alter the population growth in a different way than changes in food availability, and does this affect the ability of the mosquitoes to transmit disease? Information is becoming available at different scales at an increasing rate, and we need to study how to integrate this to better predict or control disease. We are using models at different scales to investigate these types of questions.