posted on 2023-05-19, 16:06authored byEscobar, LE, Scott CarverScott Carver, Romero-Alvarez, D, VandeWoude, S, Crooks, KR, Lappin, MR, Craft, ME
Traditional epidemiological studies of disease in animal populations often focus on directly transmitted pathogens. One reason pathogens with complex lifecycles are understudied could be due to challenges associated with detection in vectors and the environment. Ecological niche modeling (ENM) is a methodological approach that overcomes some of the detection challenges often seen with vector or environmentally dependent pathogens. We test this approach using a unique dataset of two pathogens in wild felids across North America: Toxoplasma gondii and Bartonella spp. in bobcats (Lynx rufus) and puma (Puma concolor). We found three main patterns. First, T. gondii showed a broader use of environmental conditions than did Bartonella spp. Also, ecological niche models, and Normalized Difference Vegetation Index satellite imagery, were useful even when applied to wide-ranging hosts. Finally, ENM results from one region could be applied to other regions, thus transferring information across different landscapes. With this research, we detail the uncertainty of epidemiological risk models across novel environments, thereby advancing tools available for epidemiological decision-making. We propose that ENM could be a valuable tool for enabling understanding of transmission risk, contributing to more focused prevention and control options for infectious diseases.
Funding
National Science Foundation
History
Publication title
Frontiers in Veterinary Science
Volume
4
Article number
172
Number
172
Pagination
1-11
ISSN
2297-1769
Department/School
School of Natural Sciences
Publisher
Frontiers Research Foundation
Place of publication
Switzerland
Rights statement
Copyright 2017 The Authors Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/
Repository Status
Open
Socio-economic Objectives
Disease distribution and transmission (incl. surveillance and response)