Aiello, C.M., and Esque, T.C., 2017, Estimates of pathogen exposure predict varying transmission likelihood: Host contact and shedding patterns may clarify disease dynamics in desert tortoises Gopherus agassizii: U.S. Geological Survey data release, https://doi.org/10.5066/F78W3BC8.
Summary
These datasets (S2-S3) document the transmission of a bacterial pathogen (Mycoplasma agassizii) between desert tortoises (Gopherus agassizii) experimentally introduced in captivity and were used to create and compare models predicting transmission probability given data on the hosts and their interactions. Dataset S2 includes variables describing the individual tortoises interacting, e.g. id, sex; variables describing the length of their interaction, e.g., number of days cohabitating, hours of direct contact; and variables estimating the infection level (based on data in S3) of infected tortoises involved in the interaction with the focal host.Interaction time and the amount of bacteria present in an infected host were used to calculate [...]
Summary
These datasets (S2-S3) document the transmission of a bacterial pathogen (Mycoplasma agassizii) between desert tortoises (Gopherus agassizii) experimentally introduced in captivity and were used to create and compare models predicting transmission probability given data on the hosts and their interactions. Dataset S2 includes variables describing the individual tortoises interacting, e.g. id, sex; variables describing the length of their interaction, e.g., number of days cohabitating, hours of direct contact; and variables estimating the infection level (based on data in S3) of infected tortoises involved in the interaction with the focal host.Interaction time and the amount of bacteria present in an infected host were used to calculate “dose” variables that represent the intensity of exposure to the pathogen. These data were used to estimate model parameters for multiple generalized linear models (glm) with predictor variables related to exposure time to an infected host and host characteristics. The response variable or event of interest was the infection status of the exposed tortoise after a period of interaction. Infection status was defined in two ways (described in section 15) and determined using qPCR of tissue samples collected at intervals – the results of which are presented in the S3 dataset. The analyses allowed us to identify interactions that have high transmission likelihood, and so we explored the contact patterns of a wild tortoise population (25 individuals with overlapping or contiguous homeranges) to estimate how frequently high-risk contacts occur (Dataset S4). This dataset includes all interactions (tortoise ids of interacting pair, date & time interaction began, and interaction duration) documented between tortoises fitted with proximity logging devices. Each device detects other devices when tortoises are approximately 10 cm apart and ends an interaction when tortoises have remained further than 10 cm for 1 minute.
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Proximity logger contacts_S4_dataset.zip
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Purpose
Used to explore the contact pattern of wild desert tortoises and estimate the frequency of long-lasting interactions (which were determined to have high transmission likelihood based on analyses of S2).
Rights
The authors of these data require that data users contact them regarding intended use and to assist with understanding limitations and interpretation. Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government
