Date of Award
2004
Degree Type
Dissertation
First Advisor
Thomas N. Mather
Abstract
We investigated potential risk factors for Lyme disease at the level of a southern Rhode Island community where vector ticks ( Ixodes scapularis Say) and human Lyme disease are endemic. We recruited homeowners with and without household histories of Lyme disease that would permit sampling of ticks and small mammals around the wooded edge of their properties. Entomologic factors including nymphal tick abundance, rates of tick infection with Lyme disease-causing bacteria (Borrelia burgdorferi ), and the density of infected nymphs were measured. We evaluated the relationship between these variables and the history of Lyme disease cases within households. The relationship between nymphal tick infection rates and the relative abundance of white-footed mice and their larval tick burdens also were assessed. In addition, high incidence regions of the community were determined using a census block level distribution of disease, and we measured the aforementioned entomologic risk factors, as well as various landscape factors, in census blocks of below- and above-average disease incidence. Residences reporting a history of Lyme disease had significantly higher nymphal tick densities, tick infection rates, and densities of infected ticks. There was no linear relationship between these factors or forest edge, and per capita Lyme disease incidence at the census block level; however, a significant linear relationship between amount of deciduous forest and Lyme disease incidence was detected. Census blocks of above-average disease had significantly higher mean forest area and mean forest edge density. In addition, we found no evidence of spatial autocorrelation of tick densities. Lastly, neither the relative abundance of mice, nor larval tick burdens on mice, was positively related to nymphal tick infection rates the following year. Although entomologic risk factors may be predictive of Lyme disease, the results demonstrate that predicting where ticks are distributed may be difficult--due to high variability of tick distributions. Furthermore, the results demonstrate that characteristics of deciduous forest within a community, including the amount of forest and the amount of forest edge, may be a potential predictive factor for Lyme disease risk, and may be useful for guiding prevention and control strategies at the level of an endemic community.
Recommended Citation
Pardanani, Neeta N., "Ecological determinants of Lyme disease in an endemic community" (2004). Open Access Dissertations. Paper 1997.
https://digitalcommons.uri.edu/oa_diss/1997
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