Historical and Contemporary Variables Affecting the Range and Distribution of Aedes aegypti, The Yellow Fever Mosquito, in The United States

<p>Aedes aegypti, the primary mosquito vector of the yellow fever virus, threatens global health by passing on this virus, as well as chikungunya, dengue, and Zika viruses. Through its natural tendency to live in highly urban areas and bite human hosts; understanding the factors that affect the historical and current range of the pest is invaluable (Gubler, 1998). Although these viruses are not normally found in the United States, lack of vaccinations and wide-spread presence of the mosquito could lead to these diseases being reintroduced with potentially devastating effects (Monath, 2001). To determine a partial historical range of A. aegypti within the U.S. I examined the occurrence of yellow fever epidemics across time and space. Although many individual mosquitoes were not infected with yellow fever and therefore impossible to track, yellow fever incidence can provide some insights into the historical range. My hypothesis was that historically, A. aegypti was driven by human population density, like its contemporary range suggests (Kramer, 2015 & 2019). This was examined by compiling a list of all yellow fever occurrences in the U. S., human population density for that time period , location, and the number of people infected. This data was mapped using ArcGIS 10.6 (Esri, 2011) and was analyzed in R software (R Core Team) using linear regression models to determine the relationship between variables. The results showed there is a relationship between human population density and infected individuals for the whole dataset and by decade. To determine the current range of Aedes aegypti, species distribution models were used to include human variables and climate variables. My hypothesis was that climate (i.e., maximum temperature, minimum temperature, and average precipitation in the summer and winter) and anthropogenic factors (i.e., human population density, average household income, and percent of abandoned properties in neighborhoods) would explain the current range of Ae. aegypti within the continental U.S. These factors and mosquito occurrence data were incorporated into MaxEnt, a machine learning species distribution model, to predict habitat suitability for Ae. aegypti. Based on the results, I found support for my hypothesis, with human population density having the greatest effect on the range of Ae. aegypti. Thus, it appears that environmental factors are less important at explaining the rage of Ae. aegypti compared to anthropogenic factors.</p>

Name thesis:degree_name

Master of Science (MS)

Level thesis:degree_level

Masters Thesis

Year dc:date.available

2020

Author dc:creator

• Mackey, Nicole

Contributors dc:contributor

• Donald A. Yee
• Wei Wu
• Deanne Nuwer

• Modeling
• Ecology
• Entomology
• Aedes aegypti
• Species Distribution Model
• Biology

Repository record dc:identifier

https://aquila.usm.edu/masters_theses/725

OAI identifier oai:identifier

oai:aquila.usm.edu:masters_theses-1783