Modeling Disease Transmission Among Malagasy Small Mammals: A Network Analysis

Loading...
Thumbnail Image

Date

2018

Journal Title

Journal ISSN

Volume Title

Repository Usage Stats

196
views
83
downloads

Abstract

Human disturbance of wildlife habitat leads to a change in wildlife community composition of an area, often decreasing species richness and favoring opportunistic or generalist species that thrive in a wide variety of environmental conditions. Such changes in a community have the potential to alter disease transmission dynamics and can affect human health. To make progress in linking ecosystem changes and disease risk, it is essential to develop new techniques to evaluate how wildlife communities interact, and how ecosystem stressors affect disease risk. The construction of social networks based on spatial data will provide information on community structure and disease transmission dynamics in relation to anthropogenic land use change. In the summer of 2017, small mammals were captured for 5 consecutive days at three sites in northeast Madagascar. Spatial data, Leptospira infection status, and morphometric data were collected from small mammals to identify host characteristics important to disease transmission. Data were input into R to construct a spatial network that aimed to model disease transmission. Through this study I found that a spatial network does not adequately model the environmental transmission of Leptospira, and highlights the importance of considering pathogen life cycle during the construction of disease transmission models. Additionally, Mus musculus were found to connect separate communities of small mammals, and thus inhabit an epidemiologically critical position in the spatial network.

Department

Description

Provenance

Citation

Citation

Wickenkamp, Natalie (2018). Modeling Disease Transmission Among Malagasy Small Mammals: A Network Analysis. Master's thesis, Duke University. Retrieved from https://hdl.handle.net/10161/17015.

Collections


Dukes student scholarship is made available to the public using a Creative Commons Attribution / Non-commercial / No derivative (CC-BY-NC-ND) license.